Estimating the Economic Impact of Air Cargo Operations at Airports, Part 1: User’s Guidebook and Part 2: Research Report (2014)

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Part 1: User’s Guidebook

Page CONTENTS Part 1: User’s Guidebook 1 SECTION I – INTRODUCTION AND PURPOSE .................................................... 1-1 1.1 Introduction .......................................................................................................... 1-1 1.2 Purpose of This Guidebook ................................................................................. 1-2 1.3 The Air Cargo Industry and Its Role in the Supply Chain ................................... 1-2 1.4 The Economic Impact of Air Cargo..................................................................... 1-8 1.5 Guidebook Organization ...................................................................................... 1-9 2 SECTION II – ASSESSING THE ECONOMIC IMPACT OF AIR CARGO ...... 1-11 2.1 Introduction ........................................................................................................ 1-11 2.2 Economic Impact Models .................................................................................. 1-11 2.3 Data Collection and Survey Techniques ............................................................ 1-15 2.4 Estimating Demand Elasticity – Security Screening and Fuel Cost Impacts .... 1-28 2.5 Simplified Economic Impact Analysis Model ................................................... 1-36 3 SECTION III – CASE STUDIES FOR FIVE SELECTED AIRPORTS ............... 1-39 3.1 Case Studies ....................................................................................................... 1-40 Case Study 1 – Kansas City International Airport, Kansas City, MO ........................... 1-40 Case Study 2 – Louisville International Airport, Louisville, KY .................................. 1-52 Case Study 3 – George Bush Intercontinental Airport, Houston, TX ........................... 1-68 Case Study 4 – John F. Kennedy International Airport, New York, NY ...................... 1-82 Case Study 5 – Reno-Tahoe International Airport, Reno, Nevada ................................ 1-96 References .................................................................................................................... 1-108 List of Tables Table 1. Characteristics of the CFS, T100, Import/Export, and FAF Datasets ........................ 1-18 Table 2. Estimated Impact of Increased Prices on Air Cargo Demand – Case Study Airports ................................................................................................................. 1-32 Table 3. Air Cargo Screening Inputs for I-O Models – Case Study Airports ........................... 1-33 Table 4. Summary of Stepwise Regression .............................................................................. 1-34 Table 5. Jet Fuel Price Elasticity Model – Analysis of Variance ............................................. 1-34 Table 6. Jet Fuel Price Elasticity Parameter Estimates ............................................................. 1-35 Table 7. Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) on Demand for Air Cargo .............................................................................................................. 1-35 Table 8. Simplified Economic Impact Estimation Model ........................................................ 1-38 Table 9. Characteristics of Airports Selected for Case Studies ................................................ 1-39 Table 10. Estimated Employment by Industry Group, MCI, 2010 ........................................... 1-44 Table 11. Using the Multipliers and an Estimate of the Number of Jobs the Final-demand Industry to Calculate Final-demand* ................................................................... 1-45 Table 12. Estimated Final Demand from Multipliers and Estimate of Jobs ............................. 1-46 Table 13. Estimated Economic Impact, Air Cargo Operations, MCI ....................................... 1-47 Table 14. Shipment Characteristics by Commodity for Air Transportation (including Truck and Air) for Kansas City Metropolitan Area of Origin: 2007 ................... 1-49 1-i

Table 15. Air Cargo Screening Inputs for I-O Models ............................................................. 1-50 Table 16. Air Cargo Screening Inputs for MCI I-O Modeling ................................................. 1-51 Table 17. Economic Impact Associated with Cargo Screening ................................................ 1-51 Table 18. Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) on Demand for Air Cargo .............................................................................................................. 1-52 Table 19. Economic Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) .................. 1-52 Table 20. Top Ten Industries, Ranked by Employment Louisville Region, 2009 ................... 1-55 Table 21. Top Ten Industries, Ranked by Output Louisville Region, 2009 ............................. 1-55 Table 22. Estimated Employment by Industry Group, SDF, 2010 ........................................... 1-57 Table 23. Estimated Economic Impact, Air Cargo Operations, SDF ....................................... 1-57 Table 24. Shipment Characteristics by Two-Digit Commodity and Mode of Transportation for Metropolitan Area of Origin: 2007 Louisville/Jefferson County-Elizabethtown-Scottsburg, KY-IN (KY part) ......................................... 1-59 Table 25. Location Quotients Calculated from Quarterly Census of Employment and Wages Data, 2010 ................................................................................................ 1-61 Table 26. Location Quotients Calculated from Quarterly Census of Employment and Wages Data, 2010 NAICS Codes 481 through 493 Only .................................... 1-62 Table 27. Estimation of Economic Activity Attributable to Presence of UPS’ Worldport Operations ............................................................................................................ 1-63 Table 28. Key Shippers Attributable to Presence of UPS’ Worldport Operations ................... 1-63 Table 29. Estimated Economic Impact, Enhanced Truck Transportation and Warehousing and Storage Industries .................................................................... 1-64 Table 30. Air Cargo Screening Inputs for I-O Models ............................................................. 1-65 Table 31. Air Cargo Screening Inputs for SDF I-O Modeling ................................................. 1-65 Table 32. Economic Impact Associated with Cargo Screening ................................................ 1-66 Table 33. Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) on Demand for Air Cargo .............................................................................................................. 1-66 Table 34. Economic Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) .................. 1-67 Table 35. Output impacts of Jet Fuel Price Increases (10, 20, and 30 percent) ........................ 1-68 Table 36. Top Ten Industries, Ranked by Employment Houston Region, 2009 ...................... 1-70 Table 37. Top Ten Industries, Ranked by Output Houston Region, 2009 ................................ 1-71 Table 38. Estimated Employment by Industry Group, IAH, 2010 ........................................... 1-72 Table 39. Estimated Economic Impact, Air Cargo Operations, IAH ....................................... 1-73 Table 40. Shipment Characteristics by Commodity for Air Transportation (including Truck and Air) for Houston Metropolitan Area of Origin: 2007 ......................... 1-74 Table 41. Employment, Output, and Employee Compensation of Industry Codes 234 through 249 .......................................................................................................... 1-76 Table 42. Per-worker Output and Employee Compensation of Industry Codes 234 through 249 .......................................................................................................... 1-77 Table 43. Top Exports by Weight and their Estimated Value, Houston ................................... 1-78 Table 44. Economic Impact of $3.1 Billion in Electronic Manufacturing ............................... 1-78 Table 45. Air Cargo Screening Inputs for I-O Models ............................................................. 1-79 Table 46. Air Cargo Screening Inputs for IAH I-O Modeling ................................................. 1-80 Table 47. Economic Impact Associated with Cargo Screening ................................................ 1-80 Table 48. Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) on Demand for Air Cargo .............................................................................................................. 1-81 1-ii

Table 49. Economic Impacts of Jet Fuel Price Inreases (10, 20, and 30 percent) on Airport Operations ........................................................................................... 1-81 Table 50. Economic Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) on Off- Airport Activities .................................................................................................. 1-82 Table 51. Sector Payroll Location Quotient, Employment, and Payroll for NY MSA (New York Portion), 2010 .................................................................................... 1-84 Table 52. Top Ten Industries by Three-Digit NAICS Code, 2010 ........................................... 1-85 Table 53. Top 20 Manufacturing Sectors in New York Portion of NYC MSA by Six- digit NAICS .......................................................................................................... 1-86 Table 54. Total Air Exports from NY Portion of NYC MSA, 2007 ........................................ 1-88 Table 55. Employment and Payroll of Commodity-producing Industries by Commodity, New York State Portion of NYC Metropolitan Area, 2007 ................................. 1-89 Table 56. Portion of Commodity-producing Industries Directly Related to Air Freight, New York Portion of NYC MSA ......................................................................... 1-90 Table 57. Total Economic Impacts of JFK Air Cargo Outflows on the New York Metropolitan Area ................................................................................................ 1-91 Table 58. Total Air Imports to NY Portion of NYC MSA ....................................................... 1-92 Table 59. Summary of Survey of JFK Airport Freight Operations and Related Activity ........ 1-93 Table 60. Total Economic Impacts of JFK Air Cargo Inflows on the New York Metropolitan Area ................................................................................................ 1-95 Table 61. Employment, Payroll, and Payroll Location Quotients (LQs) by Two-digit NAICS for the Reno-Sparks MSA (2010) ........................................................... 1-97 Table 62. Ten Highest Payroll LQ Industries among Three Digit NAICS for the Reno- Sparks MSA, 2010 ............................................................................................... 1-98 Table 63. The Ten Manufacturing Six-digit NAICS Sectors Most Highly Concentrated in the Reno-Sparks MSA, 2010 ............................................................................ 1-99 Table 64. Employment and Payroll by SCTG Category in the Reno-Sparks MSA, 2010 ..... 1-100 Table 65. Air Freight (including Truck-Air) for the Remainder of Nevada, Total Originating, 2007 ............................................................................................... 1-101 Table 66. Air Freight (including Truck-Air) for the Remainder of Nevada, Total Originating from Reno-Sparks MSA, 2007 ....................................................... 1-102 Table 67. Total Economic Impacts of RNO Air Cargo Outflows on the Reno-Sparks Metropolitan Area .............................................................................................. 1-104 Table 68. Air Freight (including Truck) to the “Remainder of Nevada,” 2007 ...................... 1-105 Table 69. Air Freight and Related Industries at RNO, 2011 .................................................. 1-106 Table 70. Total Economic Impacts of RNO Air Cargo Inflows on the Reno-Sparks Metropolitan Area .............................................................................................. 1-108 List of Figures Figure 1. TSA Estimated Total Costs of Complying with the 100 Percent Screening Rule .... 1-31 1-iii

1 SECTION I – INTRODUCTION AND PURPOSE 1.1 Introduction Air cargo services occupy a special place in modern supply chains, carrying the most valuable, most perishable, and most urgent shipments across the nation and the world. From necessities such as pharmaceuticals to luxuries such as exotic flowers, air cargo services shrink time and space to link customers to distance sources quickly, efficiently, and reliably. Air cargo keeps assembly lines rolling and remote communities connected. At the same time, air cargo service enables U.S. businesses large and small to communicate and compete in global markets. Air cargo facilities and operations likewise occupy a special niche in the communities they serve. International airports are large, costly facilities with a major presence in a metropolitan area. Even smaller regional airports are prominent fixtures in their markets. The air cargo niche reaches beyond airport boundaries to include integrated carriers, air freight forwarders, air freight truckers, ground handlers, and their customers. These stakeholders together constitute an industry that, unlike highway trucking or freight railroads, are largely behind the scenes. Despite its essential nature, air cargo service and the facilities it needs may be undervalued by the public sector. The general public is typically aware of integrated carriers such as FedEx and UPS, but lacks familiarity with the more complex interaction between air cargo carriers and the local economy. Airline passengers have little awareness of what goods are travelling beneath them as “belly cargo”, or of what round-the-clock activities are necessary to support those shipments. Airport authorities and air cargo stakeholders have periodic needs to demonstrate the public value of their activities and facilities. In this era of limited resources, public planners, elected officials, and legislators are forced to choose among competing transportation investment proposals, and need help in making good decisions. Complexity, specialization, and public unfamiliarity can place the air cargo industry at a disadvantage compared to more familiar transport modes. In one sense everyone who sends an overnight package is an air cargo shipper. Yet conventional approaches to air cargo data and analysis have underestimated the value of air cargo shipments and the economic importance of the air cargo industry. Regional planners and state transportation officials likewise have goods movement responsibilities that span air cargo service and facilities, but may have little experience in the field and no time to learn it in the face of looming deadlines. Approaches that work well when applied to passenger modes or other freight modes may yield misleading results when applied to air cargo. Logistics factors, including access to air cargo service, are increasingly prominent in industrial and commercial location decisions. As economic development agencies strive to attract and retain employers to their cities and regions, they have a concomitant need to understand the impact of air cargo service on regional competiveness. 1-1

This Guidebook and the companion project report were therefore commissioned by the Airport Cooperative Reproach Program to fill the need for economic impact estimation tools that public and private practitioners can apply to the air cargo industry. 1.2 Purpose of This Guidebook This Guidebook was developed to assist airport authorities, air cargo operators, and public sector planners in establishing the value of air cargo facilities and operations to their communities and regions. The primary metric of this value is economic impact: the direct, indirect, and induced income and employment generated by the industry. The primary tools are economic impact models that use available data to answer the questions posed by practitioners. The Guidebook addresses several dimensions of economic impact and value creation: • The structure of the air cargo industry and its role in the supply chain. • The size of air cargo facilities and operations relative to the region and market they serve. • The nature of air cargo services, and their linkage to local industry and economic activity. • Air cargo industry response to changing economic conditions, particularly the price of fuel and evolving security requirements. • The relative cost and service characteristics of alternate shipping modes (e.g. truck). Airports and air cargo services differ widely, so the tools and techniques presented in this Guidebook are flexible in their application. The basic tools offered include: • A discussion of economic impact models and their application to the air cargo industry. • A discussion of data collection and survey techniques to support the impact analysis. • Demand elasticity models for fuel cost impacts and security screening impacts • A simplified model for estimating economic impact. The Guidebook also presents selected case studies involving air cargo economic impact assessments for five airports. These case studies have been chosen to illustrate the application of analytic tools for airports that vary in size, air cargo volumes, and regional context. 1.3 The Air Cargo Industry and Its Role in the Supply Chain The air cargo industry has become an increasingly important sector in the transportation service industry. Indeed, it plays a key role in the globalization and evolution of supply chains and has enabled supply chain managers to shrink their firms’ “time-space continuum.” That is, geographically dispersed and distant markets are being served in ever-less time, overcoming such obstacles as perishability, inventory requirements, stringent order and replenishment lead times, and high inventory-carrying costs. Firms are thereby able to cover wider markets both nationally and internationally because air cargo makes it possible for them to quickly fulfill the needs of their customers in a cost-effective manner. 1-2

Part of the air cargo industry’s success can be attributed to the growth of internet and web applications, which have driven supply chains to new levels of efficiency. This is not only due to the speed of communication, but also to more efficient inventory management and lower net production and delivery costs. The use of air cargo also enables efficient supply-chain strategies—such as just-in-time (J-I-T) and postponement—by reducing carrying costs through lower inventory requirements. It further enables sellers to take advantage of both lower-cost labor markets and economies of scale in production, since they are now able to produce farther from their markets. Thus, air freight’s more responsive service justifies higher costs for many commodities. It has also enabled the growth of value-added services offered by third-party logistics (3PLs) providers and integrators. Visible examples illustrating contributions of the air cargo industry in the global supply chain include: • Helping to speed time-sensitive products to market • Improving the reliability of assembly lines by enabling rapid, JIT delivery of parts for processing machinery as well as production inputs. • Delivering quick-order, bio-medical products and equipment to hospital emergency wards and operating rooms • Deploying large project equipment to remote airfields • Enabling small businesses across America to compete in major foreign markets • Enabling remote communities and installations without surface transportation to timely access supplies and life safety products necessary for productive and healthy lives. Participants of the Air Cargo Industry Air cargo services are provided to customers in a highly complex and competitive environment to producers. Many parties are involved to ensure air cargo is shipped on time and safely from one place to another, either domestically or internationally. Parties such as freight forwarders, 3PLs, airlines, airports, ground handlers, and truckers are responsible for packing and transporting commodities to and from airports, or on and off aircraft. Below are brief descriptions of the services provided by each of the key industry participants: • Airports—offer infrastructure and services to air carriers for transporting and sorting commodities; such as runways/taxiways, aircraft parking, cargo handling land and facilities, roads and utilities, cargo security, aircraft maintenance, and other support. • Airlines—provide airport-to-airport freight services either via lower deck space on passenger aircraft or via all-cargo freighter space using both scheduled and supplemental or charter services; provide pickup and delivery services in airport regions or to more distant markets. • Air cargo terminals—process air cargo and mail that is transferred between air carriers, trucks, trains, and marine vessels. The terminals may be operated by airports, air carriers, surface transportation carriers, or third parties. 1-3

• Air freight forwarders and 3PLs—provide consignment, transportation handling, documentation services to shippers and consigners, as well as value-added logistics, transportation, and trade services. The largest are global companies that also offer truck, maritime steamship, barge, and rail services. • General sales agents—sell air freight capacity on behalf of airlines. • Integrators—offer direct selling of door-to-door services to businesses and individuals based on time-definite products handling shipment sizes from letters to heavy cargo that are comprised of a mix of air, truck and intermodal. Integrators typically own and operate aircraft or lease on a dedicated basis. • Consolidators—work with or may function as a freight forwarder providing assembly points for cargo prior to its delivery to a carrier on the airport. • Container freight stations—are typically located off-airport and handle the breakdown of inbound international freight. Their function is similar to a consolidator (see above) in that they provide space for short-term storage and redistribution to a number of clients. • Ground handlers—provide aircraft loading/unloading, short-term freight storage, fueling, technical maintenance, deicing, crew support, and liaison with support parties. • Air cargo truckers—specialize in road transportation services for air freight shipments, typically requiring specialized roller-bed equipment. • Brokers—buy capacity from airlines and sell it to small- and medium-sized forwarders. • Customs brokers—assist importers and exporters in meeting federal requirements governing imports and exports. Trends in the Air Cargo Industry The U.S. air cargo industry handles 32.7 percent of exports and 27.6 percent of imports by value, and 0.5 percent of exports and 0.7 percent by weight of the nation’s freight transportation, according to data reported by the Freight Analysis Framework (FAF). Comparatively, trucking represented the largest mode by both weight (61.6 percent) and by value (54.7 percent). The percentage of U.S. commodity value, including import and export, shipping by air freight grew from 6.5 percent in 2007 to 7.3 percent in 2011, and is forecast to reach 12.8 percent by 2040 (US DOT 2012). When benchmarking against other modes, a commodity’s value/weight ratio is clearly a key indicator of its propensity to be shipped by air. The higher relative value of air cargo supports the premise that air freight’s benefit of reliable, quick service justifies its higher cost. 1-4

This justification is especially poignant for overseas trade where the only alternative mode of freight shipment is water transportation, which is the most inexpensive and slowest freight transport mode. When compared to exports and domestic activities, exports represent the highest share of air cargo activity. Exports held a 32.7 percent share by value in 2011, which was a higher share relative to imports (27.6 percent) and domestic (1.2 percent) cargo shipping. While the domestic market is dominated by a few integrators, international traffic has many more airlines involved. The decision criteria for domestic and import traffic, which is discussed in a later section, are quite different. In terms of annual growth rates, U.S. air cargo grew 3.1 percent by value and 7.5 percent by weight from 2007 to 2011. The annual growth rates for air cargo are higher than the growth rates in the same period for total U.S. freight transported, which are 0.2 percent by value and -1.7 percent by weight. Also, the annual growth rates for air cargo are higher than the growth rates of freight transported by trucks, which declined in terms of both weight and value. During this period, an economic recession resulted in the slowing of economic forces that generate demand for shipping. A number of factors caused a more significant growth in air cargo relative to other modes. Whether that will be a short- or long-term phenomenon remains to be seen; however, Freight Analysis Framework (FAF) forecasts suggest the trends is expected to continue, though at a slower pace, through 2040. Air Cargo Success Factors As the industry undergoes major changes, the basic ingredients of an airport’s successful air cargo operation have remained essentially intact. These factors have played major roles in the success of gateways to date. However, as airports mature, regional growth and evolving goods movement dynamics may negatively impact the airport’s ability to meet the needs of the air cargo industry, and eventually force shifts in operations to alternate facilities. In looking at these factors, there are indications that growing challenges develop as airports mature. The challenges create opportunities to be explored regarding more efficient utilization of existing airport assets as well as development of new facilities and infrastructure. Substantial passenger market – both Origin & Destination and transfers: Despite their interest in air cargo, the gateways all stress that one of their top priorities is maintaining a preeminent position in passenger traffic. To grow this segment of the business will require an airport to accommodate substantial amounts of belly cargo and, in the instances of carriers that fly both passenger and freighter aircraft, provide adequate aircraft apron for the freighter component of the business. Given the existing high levels of passenger activity, and the projected growth for the industry, most of the national gateways are well positioned to achieve this goal and have the physical capacity to address physical constraints. Large regional consuming and producing marketplace: The large and growing population of a gateway city and the surrounding region, along with the city’s interest in the promotion of logistics and the related jobs generates substantial volumes of both inbound and outbound freight. Trade flows to Europe and to Asia typically favor exports and imports 1-5

respectively as a result of international monetary standards. This creates shortfalls in outbound shipments to Asia and inbound product from Europe. A balance is critical to the financial success of a cargo operation. The flow of cargo to and from certain global regions will vary based on economic trends. In the event the economics substantially decrease in either direction, there is a strong probability that cargo in general and freighter traffic in particular will be reduced accordingly. The challenge for a region is to create an operating environment with sufficient financial benefits to attract products from the surrounding region. Air cargo business reacts to economies of scale; large volumes enable all parties to reduce costs and potentially pass on savings to customers. Substantial lift to a large number of markets: A substantial number of operations to global markets and sufficient volumes of cargo to each destination enables shippers to consolidate shipments thus reducing overall shipping rates. Gateways have a large and diverse user universe that enables efficient interlining between passenger and freighter aircraft with a resultant global outreach. Forwarders are attracted to larger facilities because of the ability to backstop flights with other options in the event the targeted flight is missed. The other major element of this factor is that the amount of lifts and the competition helps control costs. Supporting business infrastructure of freight forwarders, customs brokers, and trucking: While integrated carriers control the vast majority of domestic cargo shipments, freight forwarders and customs brokers control the majority of the international market. Although this split has remained fairly consistent, the role of forwarders in domestic shipping continues to shrink and the integrators are pursuing a larger share of the international business as well. Typically, these segments of the industry cluster on or near the transportation facility they wish to utilize. The result is the existence in the areas immediately surrounding the airport of substantial square footage of logistics facilities. Many gateways also have expanded supporting business infrastructure reflecting related ocean-borne shipping that is served by regional customs brokers and freight forwarders. In an ideal environment many of these supporting businesses would prefer to locate on-airport (space permitting) to help reduce operating costs. Historically, the biggest issues are the inability of an airport to sell property and the comparative high leasing costs of on- versus off-airport property. Roadway infrastructure providing ready access to the airport and to an effective highway distribution system: One of the side effects of air cargo growth is a corresponding increase in trucking traffic and its impact on regional traffic patterns and flows. An original determinant of air cargo success at the larger airports was the regional roadway infrastructure and the links it provided between the airport and a highway distribution system. The growth in passengers and cargo, as well as overall regional growth, can cause congestion making effective access and efficient rates of travel increasingly problematic. The resultant shipping inefficiencies and higher costs can place the more mature regions at a disadvantage. The traffic is an issue at the larger airports. Nevertheless, the other advantages of the major gateways continue to offset most traffic concerns. Physical capacity to accommodate growth: The most obvious criterion for the future success of an air cargo program is the physical capacity to accommodate the airside and landside requirements of both tenants and users. This includes aeronautical infrastructure, physical 1-6

facilities, landside parking and queuing, and roadway geometry. The latter two elements are important to ensure that the airport functions efficiently as an intermodal facility. While the cargo operations continue to experience solid growth, there are some very real constraints facing airports as buildings age and carrier requirements change. Geographic positioning to serve effectively as a major cargo center with clear advantages over potential competitors: Historically, the gateways were coastal airports best- positioned for international cargo growth. Inland airports such as Dallas, Houston and Chicago are in a sense better positioned for overall growth because of the greater catchment areas (the areas around the airport to and from which cargo is typically shipped, which is typically considered the market that can be reached within a day’s drive). Bilateral and Open Skies Agreements: The use of U.S. airports by foreign flag carriers is based on international trade agreements which formally grant nations and carriers access and are discussed at greater length later in this section. The gateways are usually the first markets to which international carriers seek, and are granted access. Critical Cargo Variables The goods movement industry continues to experience dramatic changes. Factors such as consolidations, rising fuel costs, changing distribution patterns, increased reliance on speed, e- commerce, and high-speed logistics will require that individual airports re-examine their business goals, market priorities, physical capacity, and the compatibility of these three criteria in meeting the challenges of accelerating growth. The remainder of this section outlines several critical variables driving goods movement by air. All of these variables impact air cargo operations to some degree. Although some of the variables are not air cargo specific, they reflect changes that will eventually affect air cargo volumes at the airports and their long-term compatibility with industry needs. One of the most difficult variables to evaluate in air cargo is the truck substitution component. Many air cargo facilities are operating to a great extent as truck terminals, yet requirements to report truck-to-truck traffic are scarce. Airports cannot realistically evaluate comprehensive space demands, effectively plan for and phase new development, or fully capture business opportunities without careful consideration of the truck substitution component. Additionally, as truck substitution continues to play a greater role, airports must address the fact that an air cargo facility is an inter-modal facility, and must be designed to accommodate trucks as well as aircraft. Critical elements include roadway access and truck parking, as well as queuing, maneuvering, and docking challenges. Truck substitution has been accelerated by the new security screening requirements which, because of the associated increases on air shipping costs, have pushed modal diversion. When combined with passenger growth, the constraints of the land envelope warrant business strategies, lease management practices, and physical planning that will optimize airport property and its ability to serve customers. 1-7

1.4 The Economic Impact of Air Cargo The economies involved with air cargo operations, not unlike any facility, industry, or event can affect the local economy in many ways. The most common measures of “economic impact” are the jobs created, the total revenues brought to local businesses, and contributions to the gross domestic product (“GDP”) of an area. So in turn, the economic effect of an airport’s cargo operations, whatever their form, can reach the community through four principal channels. 1. There are the effects of the activities taking place at the airport. These could include the loading and unloading of cargo, work related to leasing and security, and cargo handling in the warehouse. 2. The activities that occur off - airport. These activities can include a wide range of functions including the work of freight forwarders and customs brokers, trucking, and a number of other diverse supporting firms. 3. The effects that arise from the expenditures by the recipients of direct and indirect wages and salaries. Wage earners spend a portion of their income on goods and services, thereby creating employment for additional persons. 4. The catalytic affects resulting from the structural changes a facility such as an airport makes in the business environment of a region. An airport may lower the cost of doing business in a region, or increase the quality of life sufficiently to attract new firms. A firm that establishes a warehouse near an airport to capitalize on the air cargo services would also generate such an effect. Economic impact models measure changes in the regional economy resulting from a change in activity relative to a baseline representation of the economy. The sources of the activity being measured vary, but typically involve changes in production or consumption activities, government policies, infrastructure, or changes in costs or technology. For any change in economic activity, the impacts on the economy can be reported on one of three levels: • Direct impacts represent the initial change in final demand for the industry sector(s) in question. • Indirect impacts represent the response as supplying industries increase output to accommodate the initial change in final demand. These indirect beneficiaries spend money for supplies and services, which results in another round of indirect spending, and so on. Indirect impacts are often referred to as “supply-chain” impacts. • Induced impacts are generated by the spending of households who benefit from the additional wages and income they earn through direct and indirect economic activity. The increase in income, in effect, increases the purchasing power of households. Induced impacts are also described as “consumption-driven” effects. 1-8

This cycle of direct, indirect, and induced spending does not go on forever. It continues until the spending eventually leaks out of the economy as a result of taxes, savings, or purchases of non-locally produced goods and services or “imports”. While the modeling tools are well known, the approaches used to evaluate the economic impact of air cargo operations has historically varied significantly between studies. Some studies use gross measures of economic output of the air cargo industry to determine total cargo revenue. Input-output models are then employed to determine overall regional economic impacts, including indirect and induced effects. For example, the 2013 economic impact analysis of Detroit Metropolitan County Airport estimated cargo yields of 36 cents per ton-mile for international shipments and 74.9 cents per ton-mile for domestic shipments to estimate a direct economic impact of $92 million per year (Detroit Metro Willow Run Wayne County Airport Authority and the University of Michigan-Dearborn School of Business 2014). In a study conducted for the Memphis International Airport, the product of the total pounds of air cargo enplaned (4.4 billion in fiscal year 2007) in Memphis and the average revenue per pound ($2.92 taken from the FedEx Express Corporation’s Financial Highlights for 2007) were used to estimate total cargo revenue ($12.8 billion annually). The multiplier effects were, in turn, determined through input-output models and total economic output resulting from air cargo operations was estimated at $27.1 billion annually (University of Memphis 2009). Other studies evaluating the economic impacts of air cargo operations employ more complex approaches similar to those used in the case studies (Section III, below). These studies attempt to characterize the regional air cargo industry or air cargo operations at the regional airport. Typical types of air cargo oriented businesses targeted in these studies include: airlines, freight forwarders, cargo handlers, integrated couriers, customs brokers, trucking firms, and warehousers. These assessments are, in turn, used to determine the number of direct jobs tied to the region’s aviation industry and direct wages. For example, the Port Authority of New York and New Jersey (PANYNJ) estimated that air cargo operations serving the region’s three major airports accounted for 40,280 jobs and $2.4 billion in direct wages. When indirect and induced effects were included, the number of jobs rose to 79,650 and total wages exceeded $4 billion. 1.5 Guidebook Organization Section II of this Guidebook begins with an overview of the estimation and modeling approach, and of economic impact concepts as applied to air cargo. The main body of Section II is devoted to coverage of: • Economic Impact Models • Survey Techniques • Demand Elasticity of Fuel Cost Impacts • Demand Elasticity of Security Screening Impacts • The Simplified Estimation Model The final component of the Guidebook, Section III presents case studies for five selected airports: Kansas City International Airport (MCI), Louisville International Airport (SDF), 1-9

George Bush Intercontinental Airport (IAH), JFK International Airport (JFK), and Reno-Tahoe International Airport (RNO). 1-10

2 SECTION II – ASSESSING THE ECONOMIC IMPACT OF AIR CARGO 2.1 Introduction The key participants in the air cargo industry include air carriers, airports, and freight forwarders or third-party logistics providers (3PLs). The three types of air carriers involved in air cargo shipment are: passenger airlines carrying cargo in the “belly” of aircraft, all-cargo carriers, and integrators – combining all-cargo air service with ground transportation. Passenger and all-cargo airlines may only provide airport-to-airport shipment, while integrators such as FedEx and UPS offer door-to-door delivery services. Despite high shipping costs relative to other modes, air cargo is frequently selected for delivering commodities with high value with tight time-definite delivery windows. Additionally, air freighters often handle perishable goods and emergency deliveries for unexpected shortages. Growing openness in international trade has stretched the “just-in-time” business model, and air freight has played a key role by enabling quick, regular access to an increasing array of geographic areas on different continents. It also has expanded the types of commodities shipped and types of supply chains served by air cargo. Similar to other industries, the air cargo industry is sensitive to the conditions of the U.S. and world economies. The global economic recession experienced in recent years has added negative pressure on the air cargo industry. The International Air Transport Association (IATA) reported that “in just one year international air cargo traffic fell 23 percent.” International air cargo has stabilized in recent years, but the impact of the recession was significant. In addition to economic conditions, the air cargo industry is sensitive to other factors such as changes in fuel prices, aircraft design, regulation, security regulations, and shifts between air and other transportation modes logistical dynamics. To examine the economic impact of air cargo, it is necessary to articulate the magnitude and nature of the air cargo business itself and to describe its potential effects on the complicated economic systems that it generates. The analysis of the air cargo industry, involves all the linkages in the supply chain as it pertains to air cargo economic impact. This section addresses the models, tools and information required to evaluate the economic impacts of air cargo, along with the related impacts of demand elasticity with fuel costs and security screening. Finally, this section provides a simplified estimation model to help airport authorities, planners and public officials to more effectively gauge the impacts of this industry for their respective airports. 2.2 Economic Impact Models In the United States, most airports are owned and operated by local government or quasi- government agencies, which need to provide convincing evidence of the economic significance of airports. These impacts are provided to the public and stakeholders for the purpose of competing for public funding. Economic impact studies utilizing models to support data findings commonly help achieve that purpose. Model studies report the number of jobs and economic activities (state and/or local) generated by airports and civil aviation. Although the economic 1-11

impact study differs from a financial feasibility study, which focuses on return of public investment, some results of economic impact studies feed readily into such financial feasibility analyses and typically are more readily understood and communicated to the public. One of the examples of the economic impact study is the contribution of civil aviation made to the U.S. economy. As estimated by FAA, civil aviation contributed 11 million jobs and $1.2 trillion in economic activities in 2006 (FAA 2008). To effectively communicate with the public and stakeholders, it is important to understand what an economic impact study covers. The coverage of an economic impact study typically includes two fundamental elements: types of activities and the depth of economic activities. Types of activities can also be referred to as the parties to be included in the study. An FAA guideline report indicates that types of activities in an economic impact study for airports should include airport employees, employees of an aviation manufacturing plant if the plant locates on or near the airport site, and visitor spending. Based on the guideline report, numerous airport economic studies have been conducted to demonstrate the significant economic value that an airport contributes to its local and regional economies. Economic Impact Model Preparation The preparation of economic tools/models includes defining regions to be covered by the models, as well as renting/purchasing the models selected for use. The I-O models can be built for any regions composed of counties, and requires users to specify the regions of analysis before renting/purchasing. So, the first action is to define the regions, which can be a single county or a combination of counties to be covered by the models. Once the regions are defined, the model vendors need to be contacted for renting/purchasing the models. Before using with economic impact analysis, economic tools and models must be tested for several reasons. First, bugs can turn up in the models. They tend to be produced in low- volume with somewhat frequent updates. Testing it will ensure the selected model has the capabilities promised. Second, users can make sure they fully understand how to use the model and interpret its results when they are not under the pressure of project deadlines. Third, the data related to the direct impact such as the opportunity costs need to feed in and run through the models to test the validity of the models. Fourth, tests can reveal whether additional data are needed for a complete economic impact analysis. Economic Tools for Economic Impact Analysis I-O Model. The most popular tool for evaluating an airport’s economic impact is the regional input-output model. Input-output (I-O) models are built around a matrix that describes how sectors of an economy interact with one another. That is, for a given industry, it shows the “production recipe” for the goods and/or services that it sells as well as the shares of its revenues that are consumed by other industries in the economy. Such models provide multiplier effects (indirect and induced impacts) that attenuate to a specific geography and are typically calibrated using economic data for a local economy. 1-12

The advantages of using an input-output model are: (1) Its structure is relatively straightforward (2) Provides extraordinary sectoral detail (400-500 industries), which enables refined estimates of multiplier effects (3) It can measure the results of economic changes in terms of jobs, labor compensation, GDP, industry receipts (often the value of shipments), and even local, state, and federal tax revenues (4) Compared to other economic models its cost of use is low. Although popular, the input-output model has some shortcomings. Primarily those weaknesses are: (1) It lacks an ability to measure an economy’s response to price changes (2) It also lacks the ability to show how an economy’s response is likely to be changed over time As a result of these weaknesses there will then be certain cases where the needs of modeling exercises do not match up well against I-O’s capabilities. Of course, other economic models can be used to measure multiplier effects at the regional or national level. SETS Model. One of the most established tools is structural econometric time-series (SETS) models. For states, the model is composed of a system of as many as 300 equations, each of which is based on historical data for that state and the nation. Further, such models are tailor-made for an economy. Typically established national forecasts of employment, wages, GDP, and prices drive the model's state or local forecasts. The key focus of SETS models is employment since these data are generally the most current. Equations in SETS models must be updated on a monthly, quarterly, or annual basis to keep them current. Major strengths of SETS models are: (1) They produce results that are dynamic (laid out in time schedule) (2) They can simulate the effects of price changes (3) They have great sensitivity to historical trends in the local economy. Of course, this strength of their entrenchment in historical trends is also a prime weakness. That is, the past cannot always inform us about how major economic events or activities will affect an economy in the future. Other limitations with the SETS model include (1) Full historical data by industrial sectors for employment and gross product are available at the three-digit NAICS level or less, depending on the sector. That is, they lack the articulation of multiplier effects that is available in I-O models. (2) Perhaps the most significant limitation is the extreme cost in terms of time and labor required to construct and maintain SETS models. 1-13

CGE Model. Computable General Equilibrium (CGE) models are another set of models frequently used in a variety of economic impact analyses. CGE models assume optimal decisions by consumers and producers in response to markets and prices subject to labor, resource, and capital constraints. CGE models, in essence, have blocks of equations that represent key actors in the economy (e.g., consumers, producers, government) and equations that make sure that the different blocks are consistent. The heart of the model is usually a modified I-O model—a so-called “social accounts matrix” (SAM). The models can be built to explicitly consider sectoral resilience and substitution across industries in the equation structure. In short, the factors of economic elasticity, which are simply the measure of how responsive one economic variable is to a change in other – if the price goes up, how will it affect sales? This element of the CGE Model offers a major advantage, if, the elasticities in the models realistically reflect resilience, commodity substitution, and other built-in changes. A chief criticism leveled at CGE models is their reliance on external sources for some of the elasticity values required during their calibration. This is especially the case for region- specific models where studies that derive the elasticities are scant. As a result, regional CGE models tend to rely upon elasticities from national or international studies, which are likely not to be comparable. In some cases this may not be a serious fault if the analyst can perform sensitivity analyses on various values of certain key elasticities. But in some cases, particularly for dynamic CGE models the data are lacking to econometrically estimate some key components equations. Additionally, the costs in terms of time and labor required to produce such a model are likely not much less than those of a SETS model. Other economic models exist and have been or could be used to model the economic impacts of airports. One option is a model that conjoins I-O and SETS models, which maintains the best of both models but is greater in cost than a SETS model alone for obvious reasons. Other proprietary models implemented for airport economic impact analysis utilize a structure which offers a cross between an input-output model and a SETS model. These are predicated on a panel of data across U.S. states, although as in the case of I-O models its relationships are extrapolated for use for any aggregates of counties. Although, like SETS models, this type of modeling overcomes most shortcomings of the I-O models. The costs of such proprietary models prohibits many users from selecting them for their studies (Lynch 2000). Still, they can prove to be a less costly alternative than building either the CGE or SETS models. Another disadvantage compared to I-O models is the degree of sophistication that is required of the model user and would often require extensive training prior to application. Economic Tools for Supply Chain Analysis A supply chain is defined as an integrated process involving various organizations, people, technology, activities, information, and resources for transforming raw materials to a product and transporting from suppliers to end users or customers. Obviously, the air cargo industry is a major supply chain component for a numerous industries with shipping demands fulfilled by these services. The complicated structure of most supply chains calls for a powerful and easy-to-understand economic tool for analyzing its component activities. On-going research focuses on the use of input-output models to describe and examine effects of supply chain on specific industries or regional economies because these models are ideal for supply chain 1-14

analysis. This results since the I-O models reveal average direct and indirect relationships among industrial sectors. The model begins with an account of economic transactions—a matrix with purchases of materials made by each sector from all other sectors involved in their production processes. By normalizing on the columns of the transactions matrix, one can depict the intensity of the dependency between any pair of industries, for example, the auto-producing industry and the primary metals sector. Beyond the direct production relationship, the model can also capture additional indirect relationships existing in supply chain. For instance, in responding to the demand from the auto- producing industry, the primary metals sector will call suppliers from its supply chain. Production by the auto-producing industry is labeled by the model as a “first round” response, while actions taken by the primary metals sector is a “second round” response. The effects from one round to other rounds of responses decline since demand shares diminish as the production extends to other “rounds” or pushing output further and further backward. The I-O model captures the round-by-round effects that inevitably occur in supply chains of an economic system. Indeed, this analytical approach has been implemented in analyzing supply chain for numerous industries, to include transportation sectors and the performance and sustainability of their supply chains. 2.3 Data Collection and Survey Techniques The first and most obvious source of airport-related economic impacts is the employees who work there. Those associated with air cargo include airlines handling cargo, third-party cargo-handling companies, customs agents, TSA, customs brokers, container freight stations, freight forwarders, trucking companies, and other cargo-related services. Airports’ employment data can be obtained through the airport authority based on the number of employees with security badges. Additional data are then supplemented through the project surveys of air carriers and third-party cargo-handling companies. These combined data yield cargo-related employment estimates. More difficult to quantify is the contribution of air cargo to the regional economy. However, it is generally agreed that industries are concentrated within regions with direct access to air cargo operations. In the absence of this access, companies that rely on these services would likely re-locate to other regions with such access. Several publicly available freight datasets provide freight shipment data by transportation mode, weight, value of commodities, commodity, or region. Some of these datasets provide estimates of air cargo data, which are valuable for the economic impact analysis of air cargo at airports. A recently compiled dataset, the Freight Analysis Framework (FAF) from the Federal Highway Administration (FHWA), has overcome some shortcomings in older datasets which have attained a relatively long history of data collection. There are still data gaps so this Guidebook offers other data sources that could be used to partially address these data gaps, along with the use of surveys to a attain a relatively more accurate data representation of air cargo related activities. 1-15

Given the lack of data, one approach is to utilize the linkage of interdependence between businesses, industries and clusters. One tool common with cluster analysis is to study the Location Quotient (LQ), which measures industry concentration in a regional economy. It does so by comparing the ratio of employment in a certain sector of a local economy to the same ratio in a comparison economy, identifying specializations in the local economy. An LQ value of 1.0 indicates that employment in an industry in the regional economy is exactly the same proportion as the national average, while an LQ value greater than 1.0 indicates that employment in that industry has a higher concentration than that of the reference economy. 2.3.1 Air Cargo Data In working economic impact analysis the air cargo data for an airport reveals the amount of commodities, express packages, and mail shipped by air. In and outbound air shipment data are useful for analyzing industrial activities near and around airports that have an impact on the overall cargo operations. In and outbound domestic and international air shipment data are useful information for directing specific analysis to examine related economic impacts, such as assessing opportunity costs under a scenario of closing an airport. At a national or regional level, air cargo data measured by weight and by value of shipment can be used for comparative analysis between air transportation and other modes. Through continuous efforts, federal government agencies collect and compile aviation- related cargo flow data. Four major publicly available data sources related to air cargo are as follows: • The Commodity Flow Survey (CFS) from the Bureau of Transportation Statistics (BTS), an establishment-based survey, is conducted every five years as part of the Economic Census. Conducted in 1993, 1997, 2002, 2007 and most recently in 2012, the CFS provides a modal picture of national freight flows. • The T100 and T100f airline data from the BTS, Office of Airline Information (OAI) contains Air Carrier Traffic and Capacity data. This data collection includes two data reports: the Non-Stop Flight Segment; and On-Flight Market data. The T100 covers all U.S.-certified air carriers and commuter air carriers; the T100f contains information for all foreign air carriers operating in the United States. • The Import/Export data on Merchandise Trade from the U.S. Census Bureau contains data collected by the U.S. Customs and Border Protection for all goods that pass through U.S. Customs other than low-value items and some intergovernmental shipments. The data are broken out by foreign country, U.S. customs district, commodity, value, and mode of transportation. • The FAF, which covers freight transportation from all modes to include air freight. This analysis estimates commodity flows and related freight transportation by mode and between regions, and flow through major international gateways in the United States. The FAF integrates data from several sources, to include the CFS, T100, and Import/Export data described above. 1-16

2.3.2 Air Cargo Data Bases This section focuses on the data coverage and recognized data gaps of four publicly available air cargo datasets, including the CFS, T100, Merchandise Imports/Exports, and FAF. It further provides a description of the coverage and gaps for these datasets that may impact and assessment. Additionally, it provides how the FAF combines these and other sources to close some, but not all, of the data gaps. Table 1 (below) presents the coverage and key characteristics for each of these datasets. All of the four datasets would be useful to minimize gaps that exist in air cargo data in structuring an economic impact model. The CFS Dataset The CFS is the first major dataset that laid the foundation for air cargo data. Major advantages of the CFS include its basis in formal survey techniques, multimodality, capture of “door-to-door” shipments, and coverage of weights and values by commodity shipped. However, gaps in the coverage of the CFS must be recognized and those include: • Imports are not covered since the CFS surveys U.S. establishments. • There is evidence that exports in the CFS are underrepresented. • A limited number of geographic regions are covered by the CFS, which has 114 domestic regions. • Intermodal connections may be underrepresented because shippers do not know modal changes in shipping routes. • The commodities reported by the CFS at a region-to-region level are limited to commodities classified at 2-digit of the Standard Classification of Traded Goods (SCTG). • Industries outside of CFS’s survey scope may account for as much as 25 percent of U.S. freight In addition to those commonly mentioned gaps in the CFS, some issues with respect to air express are particularly relevant to air cargo: • Parcels or packages shipped by the U.S. Postal Service (USPS) or other couriers by air are either missing or lumped into the much smaller other data category such as “other multi-modal.” • Air express packages classified under the category of administrative/mail/business documents are explicitly excluded from statistics. This final shortfall is significant since the integrators’ rapid expansion in the shipping business has raised the importance of air express. According to T100 data, the top five integrated carriers account for over 51 percent of U.S. air freight enplaned. Federal Express (FedEx) and United Parcel Service (UPS) alone account for almost 47 percent of U.S. air cargo. 1-17

Table 1. Characteristics of the CFS, T100, Import/Export, and FAF Datasets Main Category Detailed Category CFS T100 Import/Export FAF Air cargo data Weight Yes Yes Yes Yes Value Yes No Yes Yes Detailed commodity 2 digit No 10-digit harmonized system Same as CFS Low-value/ weight goods <100 lbs. included in the box- type of parcels Yes Imports <$2,000 and exports <$2,500 are excluded Same as CFS Box-type of parcels shipped by air Yes, but lumped with other intermodal Yes No Same as CFS Letter-type of packages shipped by air No, excluded from surveys Yes No Same as CFS Industry coverage Surveyed by CFS Manufacturing, mining, wholesale, selected retails, and publishing (except 2002) Yes Yes Same as CFS Not surveyed by CFS Most services, publishing (2002), petroleum, government, and households Yes Yes, except intra-governmental Expanded coverage from CFS for trucks, but little expansion for domestic air and parcel shipments International trade Imports No Yes Yes Yes, expanded by combining the T100 and Import data to account for inbound shipments Exports Yes, but underrepresented Yes Yes Yes; expanded by combining the T100 and Export data to account for outbound shipments 1-18

The Merchandise Import/Export Dataset Census Bureau’s Merchandise Import/Export dataset contains information that can be used to fill the first two gaps in the CFS related to international trade. The air cargo data available from the Import/Export dataset include values and weights of the international shipments at the detailed 10-digit commodity level. However, there are at least two shortcomings in the Import/Export dataset: • Data are reported on customs districts for entry/routes rather than on the actual entry and origin-destination points. • Low-value shipments, parcel, and mail for all modes are excluded, but those shipments could be significant for air cargo. The T100 Dataset The T100 (and T100f) dataset is collected from air carriers according to regulatory requirements. The T100 dataset contains monthly air cargo weight data summarized by carrier- origin-destination airports for all U.S. and foreign carriers operating a flight with at least one takeoff/ landing in the United States. The T100 dataset includes two reports, the Non-Stop Segment and On-Flight Market data. In short, the segment data covers air cargo transported between nonstop segments, while the market data contain information of air cargo between airports where it is enplaned and where it is “deplaned.” A caveat to the Market data is that in addition to actual unloading, cargo is also counted as deplaned when there is a change in flight number. From a technical point of view, the T100 data should provide a breakout of shipments between mail and commodities. However, in reality, integrators such as FedEx are less willing to break out mail due to concerns that it would reveal proprietary information regarding its contract with the USPS. The T100 dataset’s shortcomings include a lack of information on detailed commodities shipped, first origin/ultimate destination routes, and value. However, the T100 dataset provides a valuable contribution with its complete coverage of inter-airport cargo weight data. The FAF Dataset Using the CFS as a base and supplemented by the Import/Export and T100 datasets, the FAF is able to close or reduce the gaps with respect to international air shipments, and with air shipments missed by the surveys in the CFS. The estimated results of international air freight in the FAF include international shipments in terms of the CFS’s O-D as well as weights and values at the 2-digit commodity level. The use of the T100 and Import/Export data also eliminates the data gap existing in the CFS for those industries not covered in the survey for international shipments. Since neither the T100 nor Import/Export data are subject to the same restrictions of data collection as CFS, including the results is an approximately 50 percent increase in the coverage of air freight. Furthermore, the T100 dataset provides actual entry/exit points as opposed to customs districts. 1-19

The FAF dataset has made significant improvement in data coverage for air cargo and overcomes shortcomings reported in the other three datasets. Nevertheless, data gaps still exist in the FAF as part of inheritance from the CFS, and some of the data gaps—especially in the coverage of air express data—have impacts on air cargo. The major data gaps related to air cargo in the FAF are listed below: • Box-type of packages – These are parcels or packages weighing less than 100 lbs. They are often shipped by integrators, USPS, or other couriers and are lumped together with other modes such as “other intermodal.” As a result, the air express of these shipments is combined with shipments that were ground only or used other modes in the FAF. • Letter-type packages – Similar to the CFS, any letter-type of air express packages that fall into the category of Administrative/Mail/Business documents are excluded in the FAF. Although the coverage of air cargo was increased by 50 percent with the FAF over the CFS with the inclusion of Import/Export information, the domestic shipments by industrial establishments not covered in the CFS are still missing. Similar to the CFS, the FAF has limited coverage for commodities and geographic areas. The number of commodities covered by the FAF is limited at the 2-digit commodity level, while the total number of geographic regions covered is still limited to 114 regions and 17 gateways in the United States. Other Air Cargo Data Sources Beyond these four publically available datasets there are other data sources for air cargo provided either by a government agency or private entities. A new data source, the Freight Assessment System has been compiled by the Transportation Security Administration (TSA) as a result of implementing the regulation of screening cargo on passenger aircraft. Other data sources compiled by private entities that include air cargo-related data include: IHS Global Insight’s Transearch database; Colography, and the Official Airline Guide (OAG). The TSA Dataset. The TSA collects information on all air cargo shipments within the United States as part of its aviation risk analysis system. The resultant database is being developed as the Freight Assessment System (FAS), which is described as follows: The FAS will screen all air cargo to identify elevated-risk shipments for aircraft operator inspection prior to flight. Data on shippers, agents, IACs, air carriers, consignees, contents of the shipment, and threat information will be incorporated into the risk assessment at a transactional level for domestic and international shipments. As a virtual census of all commodities shipped by air, the FAS might be a valuable source of information on air cargo flows. In particular, the FAS data may be supplemental to shipments missed in the CFS surveys. However, the TSA has treated the FAS data as sensitive security information. At present, little information is available on how the data are collected, the coverage of data, and whether it will be released for public use. 1-20

The Transearch Dataset. The Transearch dataset is a database that provides Origin- Destination flows for truck, rail, water and air. This is based on a combination of a shipper’s survey conducted by Global Insight and publicly available data such as the CFS. Shipment data in the Transearch dataset are available by commodity and value at the county/state level. The major advantage of the Transearch data is the use of private information from the Motor Carrier Data Exchange, which may be of limited advantage for the analysis of air cargo. The Transearch data has a relatively high purchasing cost as well as a methodology for estimating shipment data that is proprietary. The Official Airline Guide (OAG) Dataset. The OAG is a leading publisher of worldwide airline flight schedules and also provides data on air freight rates. The schedule information could be used to validate routes obtained for air cargo shipments under the estimation procedure above, as well as provide useful information on time of day/day of the week. This dataset also has a relatively high purchasing cost of this product relative to its targeted use is its primary shortcoming. Colography Group’s Dataset. The Colography Group conducts annual shipper surveys and compiles transportation databases based on the data collected. The products do not include specific information on air cargo, Origin-Destination information, or inbound shipment data. Therefore, the Colography’s dataset would not add significant value to what is available from public sources. In sum, each of the above data sources cannot be used as the only data source on air cargo flows and related air cargo studies. The TSA dataset is restricted and at this time cannot be released to the public, and the other three datasets provided by private entities either lack specific data required for the economic impact analysis, lack an available explanation for their methodologies, or bear relatively high purchasing costs. 2.3.3 Survey Techniques It is recommended that any air cargo research involving the use of surveys use the principles provided in the ACRP Report 26 Guidebook for Conducing Airport User Surveys to gather the information for economic analyses of air cargo.(This Guidebook can be found at: http://onlinepubs.trb.org/onlinepubs/acrp/acrp_rpt_026.pdf ) Of importance for applied surveys the following points are drawn from Report 26: • “Surveys of air cargo activities and operations at an airport represent a particularly challenging type of survey, because information on shipment characteristics and detailed cargo flows is typically regarded as highly proprietary.” • “Surveys of air cargo carriers, freight forwarders, or selected shippers will typically take the form of an in-person interview. Respondents may be able to provide useful information in general terms, even if they are not willing to provide detailed data on individual shipments.” 1-21

• “There is little experience to draw upon, and therefore virtually no standard practices that can be applied, or modified, for a particular airport. Any survey designed to capture air cargo data is likely breaking new ground.” • “To date, the most common survey method for air cargo is similar to stakeholder interviews. Although shippers and forwarders may be reluctant to release detailed information on air cargo shipments or cargo activity at their facility, it is possible to construct a survey in the form of an interview. Using the survey purpose as a base, a series of questions can be constructed to form a structured interview to be conducted with all, or selected, air cargo operators at the airport” (Biggs et al. 2009). A recommended representation of airport and air cargo personnel to be considered for a survey would include: • Airport representative • Air carriers • Freight forwarders and air transportation service providers • Shippers – Single stand-alone businesses; warehouses; distribution centers In general, the surveys should request information on the air cargo volumes (dollar value and/or weight) by type (or commodity code) as well as numbers of employees. Follow-up interviews may also prove helpful in answering any questions the respondent might have on specific survey questions. If you chose to complete surveys in-person, ensure you have plenty of time to complete the survey. Due to varied amount of information being requested the commitment of time is usually longer than expected. Given the breadth of the information which needs to be covered, most individuals would need to conduct some research in order to complete the surveys. In many situations, various data points may be kept in a variety of locations such as, the Office of Public Relations having landing data, while the Air Operations Office may have data on actual cargo movements on the air field. Recognize that data from each source may not match exactly, but can be cross- referenced and reconciled to determine which data is most robust and accurate. Due to the proprietary nature of the cargo market, individual companies will need assurance that their individual data will be kept confidential. Be prepared to discuss issues such as how business/competition sensitive corporate data will be used, stored, protected, presented, and published (or not) in a private or public forum. Some airports with large numbers of carriers and large volumes of cargo have local air cargo associations and annual (or more frequent) cargo conferences. Requesting the assistance of the local industry groups or associations may help identify professionals in the field that can assist with survey efforts. However, keep in mind many organizations keep their membership lists private. To gain the support of the members, it may be most effective to write a formal request for assistance to be introduced at a regular business meeting and/or request a speaking role at one of their meetings. These associations and events provide excellent opportunities to 1-22

introduce the purpose of an impact analysis, the importance of the survey information, along with networking to meet individuals who will assist in providing the necessary data. Small incentives, such as coffee shop gift cards or airport club passes, may encourage survey responses from private industry participants. However, air cargo revenues provide small margins to freight forwarders, and even incentives for survey completion may not easily offset the time spent completing a survey, to working on their standard business items or selling a cargo shipment. It is recommended to identify one or more key individuals at each airport who are knowledgeable about the local air cargo industry; their contacts assist with gathering necessary information and they often can provide estimates if actual detailed information cannot be obtained. Finally, surveys assessing economic impact may be more effective if they include questions related to elasticity of the market (e.g., How the market would reduce cargo shipments if the price increases and/or air cargo was not available at the specific airport). Of course, these types of questions greatly increased the survey length and likely the time required to complete the survey. In addition, many individuals are uncomfortable answering such subjective questions and may not want their responses perceived as responses from their whole organization. If elasticity questions hinder the number of desired responses, then these questions may have to be removed to increase overall participation and survey response. In summary, only build into the survey the necessary pieces of information to gain the data required in the most succinct manner to enhance participation. Considering the four suggested representatives, examples of the types of information to request and the people to engage with for a survey are provided by position with the following information. Airport Representative An airport focused survey primarily requests information the authorities have readily available, including: • Total numbers of airport employees • Number of employees performing air cargo-related operations (airport employees and tenants) by industry sector • Annual cargo volume by: o Inbound/outbound o Domestic/international o Weight and/or monetary value o Airline • Commodity code • Passenger, express and all-cargo airlines serving the airport • Forecasted air cargo growth rates While the airport likely has the information readily available, it may reside with different offices or departments. Employment for tenants may be estimated from security badging counts, 1-23

which can be obtained from the airport security manager. Access control records may provide estimates of cargo vehicle movements. In general, airport staff are able to provide all the information requested and may even assist in identifying others to survey. A further action may be to have the airport manager or cargo manager can send introductory email to air carriers, third-party ground handlers, and freight forwarders to facilitate their understanding of the overall project and encourage their participation. Suggested survey reach out list: • Airport Manager • Staff person responsible for Air Cargo at that airport • Security officer (badging or access control office) can help with on-airport employment estimates • Public Relations (usually has the basic, distilled information) • FAA Airports All Cargo data: http://www.faa.gov/airports/planning_capacity/passenger_allcargo_stats/passenger/. Air Carriers Both commercial passenger airlines (accepting cargo as belly freight) and commercial cargo airlines need to be included in the survey. The airports have information on cargo volume by carrier, so some of the survey questions may be redundant, but the surveys can also serve to gather more detailed information from the specific airlines. The air carrier surveys may also include requesting information on the costs for accommodating the Transportation Security Administration (TSA) requirements to screen 100 percent of all air cargo. Specifically, the air carrier survey should primarily requests information on the following: • Total numbers of employees on-airport and off-airport, full-time and part-time • Annual cargo volume by weight and/or monetary value • Top ten commodity codes • Forecasted air cargo growth rates • Estimates of customer reactions (change in volume) to price increases • Cost implications of TSA screening requirements. In cases where the airport provides information about cargo volume by carrier, then focusing questions with the group of the providers who process the largest amounts of cargo will maximize the overall percentage of cargo volume represented by completed surveys. Recognize also local station managers or sales managers may have authorization to provide only basic information on volumes and employment, but not any speculative information (e.g., forecasts, how the cargo might be transported if this airport could not accommodate the volumes, or how the cargo volumes might change due to price increases). The carriers’ corporate headquarters often must be consulted to request the data and/or grant permission to discuss the information with their local personnel on-site at the airports. Each business has their own procedures regarding participation in surveys and/or releasing company data. Most carriers will consider all 1-24

information provided as Business Sensitive and/or Confidential. Be prepared to discuss how you will use and protect the data, especially from their competitors. At airports where individual carriers have small numbers of flights and/or cargo volume, the airlines often contract with third-party ground handlers to process the cargo. It is important to capture their employment numbers, since in many cases the third parties will have many more employees than the individual carriers. The airport will have a list of third-party ground handlers and cargo terminal operators since they operate on the airfield. Suggested survey reach out list: • Commercial passenger &/or cargo airline station managers • Cargo Airline Sales Managers • Third-party ground handlers • Air Cargo Associations: o Regional: http://www.raccaonline.org/ o International: http://www.tiaca.org Freight Forwarders Freight forwarders are an important element in the air cargo system. Freight forwarders are third-party logistics providers who contract with originators of shipments (manufacturers, etc.) and with the carriers to deliver items from the shipper’s site to the final destination. Most airports have a list of known freight forwarders who work with cargo at their airport, but there may still be additional forwarders in the area that should be surveyed. The initial survey questions for forwarders should include the following: • Total numbers of employees in the specific economic region, on-airport and off- airport, full-time and part-time • Annual air cargo volume handled in area, by: o Weight and/or monetary value o Cargo-only airlines vs passenger belly cargo o Inbound/outbound o Domestic/international • Air cargo value as percent of total cargo value handled in area • Top ten commodity codes • Estimates of customer reactions (change in volume) to price increases for: o Cargo-only air cargo o Belly air cargo o Other modes • Estimates of customer reactions (change in volume) to reduction of belly cargo capacity • Estimates of how air cargo would move to other modes if air cargo services were discontinued • Cost implications of TSA screening requirements. 1-25

The freight forwarders could also be asked to rank why their customers choose air transportation rather than other modes to ship cargo. This may include survey decision parameters such as time to market, frequency of service, reliability of service, value of time relative to other modes, security, ability to track/trace air shipments. The freight forwarder surveys may be quite extensive, asking several more items than the air carrier survey. Due to the length potential length of the survey and time required to answer all the questions for this group it may be more difficult to gain responses from freight forwarders. Again, freight forwarders’ profit margins are thin, so requesting their time for an economic survey simply takes away more time from their business than they may be willing to spend. If information is limited, relying on employment estimates based on information from the Airforwarders Association, local brokers/freight forwarders organizations, and/or local chambers of commerce may help in filling this information gap. Suggested Survey reach out list with information sites: • Freight forwarders: http://airforwarders.org/ • Third Party Logistics (3PL) association: http://www.iwla.com/why/members.aspx • National Customs Brokers and Forwarders Association of America: http://www.ncbfaa.org Shippers Shippers may be any type of business/organization, including manufacturers, office/professional businesses, warehouses, distribution centers, or consolidation centers. Requesting the assistance of the local industry groups, chambers of commerce, economic development councils or associations may help identify appropriate businesses to survey. Recognize, however, these only represent cargo shipments that originate locally, not inbound shipments or connecting cargo at each airport. ACRP Report 26 states, “surveys of area businesses and other organizations are perhaps the most difficult of all airport user surveys to perform in a way that gives results that accurately reflect the characteristics and views of the targeted population” and “non-response can be a significant problem with surveys of area businesses.” 1-26

The initial survey questions for shippers should include the following: • Total numbers of employees within the specific economic region • Company/industry NAICS code • Annual air cargo handled in area, by: o Weight and/or monetary value o Cargo-only airlines vs. passenger belly cargo o Inbound/outbound o Domestic/international • Air cargo value as percent of total cargo value handled in area • Top five commodity codes shipped by their business • Estimates of company shipping reactions (change in volume) to price increases for: o Cargo-only air cargo o Belly air cargo o Other modes • Estimates of company shipping reactions (change in volume) to reduction of belly cargo capacity • Estimates of how air cargo would move to other modes if air cargo services were discontinued • Annual spending by company on all air transport services, and proportion to air cargo vs air passenger transport • Value assigned to a one-hour delay in shipment The survey could also include asking shippers to rank why they choose air transportation rather than other modes to ship cargo. This should include decision parameters such as: time to market; frequency of service; reliability of service; value of time relative to other modes; security; and the ability to track/trace air shipments. Similar to the questions asked of freight forwarders, shippers should also be asked how their air cargo volumes would respond to changes in market prices, capacity, and overall availability of air cargo at this specific airport. Again gathering the requested data and gaining the level of responses desired will be difficult, so overall employment numbers may be the most relevant data for local businesses/shippers. Suggested survey reach out list: • Local/regional chambers of commerce • Local economic development agencies or city/county departments for economic development 1-27

2.4 Estimating Demand Elasticity – Security Screening and Fuel Cost Impacts The role of air cargo in the nation’s supply chain has continued to expand in recent years, with system revenue freight ton miles expanding from 7.0 billion in 1996 to nearly 29 billion in 2011 (BTS 2011). The nation’s growing reliance on air cargo, however, does not come without some uncertainty. Two issues that have raised concern within the industry in recent years are the implementation of the Transportation Security Administration’s 100 percent air cargo screening rule (TSA 100) and jet fuel price volatility. 2.4.1 Demand Elasticity Models for Security Screening Impacts In estimating the economic impact of the TSA 100 percent screening rule – requiring security screening of all cargo transported in the belly of passenger aircraft, the following five- step approach will guide the assessment. The five-step approach is outlined in the step descriptions below and supported by the graphic to the right. As each step is addressed, the corresponding step in the graphic will be shown in black with white text. The five-step approach is as follows: Step 1. Develop a statistical price elasticity model relating the quantity of air cargo services demanded to certain economic variables, including shipping prices, to model the potential impacts of the TSA 100 percent screening rule, as well as those associated with other future regulations. Step 2. Develop an approach for estimating the costs associated with the 100 percent screening rule. Step 3. Translate these costs into price impacts. Step 4. Using the price elasticity model, estimate the impact of the upward price pressure on the demand for air cargo. Step 5. Model the economic impacts of the reduced demand for air cargo, increased shipping prices, and increased use of air transportation support industries using the input-output (I-O) models The I-O models will aid determining the direct, indirect, and induced economic effects of the 100 percent screening rule as these associated costs ripple through the local economies. This approach is supported by examples from five airport test cases. An additional model, also used in these test cases, provides airport staffs the means to better understand the demand and economic impacts associated with fuel price volatility. Step 1: Develop Price Elasticity Model Step 2: Estimate Regulatory Compliance Costs Step 3: Translate Costs into Price Impacts Step 4: Estimate Impact of Increased Prices on Demand Step 5: Model Economic Impacts 1-28

Air Cargo Price Elasticity of Demand Model Data collected in support of the air cargo price elasticity of demand model will capture numerous variables, utilizing data obtained from a number of sources. Leading data sources which should be used include: the Bureau of Economic Analysis (BEA); Energy Information Administration (EIA); Bureau of Transportation Statistics (BTS); Bureau of Labor Statistics (BLS); and Association of American Railroads (AAR). Broadly described common variables will fall into the following categories: • Economic indicators including gross domestic product (GDP) and national income • Price data including jet fuel prices, consumer price index (CPI), and price/revenue per ton-mile of air freight • Price data from competing modes including the general freight trucking producer price index (PPI) • Quality of service variables including flight stage length. The dependent variable used in the model is the sum of international and domestic freight enplaned as measured in pounds. A thorough exploration of the data would be of great help estimating the price elasticity to find any data anomalies with determined variables. This will uncover changes in reporting, changes in data requirements or inaccurate data reporting that must be accounted. Even with the rich data available, some derivations of simple data transformations may be necessary. Many candidate models can be tested that utilize variable permutations or incorporate different statistical techniques. With all models or approaches some exploratory data analysis should be performed to tease out variables which accomplish two primary objectives: 1) Finding variables that have practical and reasonable interpretability 2) Identifying variables contributing to the best-fitting model possible given the data. A suggested model would use the real air cargo operating revenue per ton-mile (essentially real air cargo price) as an independent variable. This real air cargo operating revenue per ton-mile variable is of significance because its coefficient will determine, at the national level, the elasticity (or relationship) between the price and demand of air cargo. Step 1: Develop Price Elasticity Model Step 2: Estimate Regulatory Compliance Costs Step 3: Translate Costs into Price Impacts Step 4: Estimate Impact of Increased Prices on Demand Step 5: Model Economic Impacts 1-29

Estimating the Compliance Costs Associated with the TSA 100 Percent Screening Rule To determine the economic impacts of reduced air cargo operations on local regions, it is necessary to determine the screening costs associated with the 100 percent screening rule. Two sources of information are useful in assessing these costs: the regulatory evaluation of the 100 screening rule carried out by the Transportation Security Administration (TSA); and data collected from third-party entities. The Air Cargo Screening Initial Regulatory Evaluation carried out by the TSA presents a methodology for assigning costs to the 100 percent air cargo screening rule. These costs include those associated with the: • certification of shippers • indirect air carriers (IACs) • logistics companies and other companies with Certified Cargo Screening Facilities (CCSFs) for screening air cargo off-airport Additional costs included in the evaluation involve expenses to support: training requirements; the adoption and assessment of security programs; labor costs associated with screening air cargo; equipment costs; and the costs associated with delays (TSA 2009). The cost framework developed by TSA in its regulatory evaluation was subsequently used to estimate the costs of the 100 percent screening rule on the operations of commercial airline facilities at a small number of airports across the country. The estimated screening cost per pound varied significantly from as low as 1 cent per pound to as high as 57 cents per pound. The results demonstrated that due to the significant fixed costs associated with the upfront purchase of equipment and associated facility design and construction, costs per pound declined significantly as the number of parcels passing through the facility grew. This point is demonstrated in Figure 1, which compares the screening price per pound to the annual number of parcels expected to be screened at each facility. When the results for each facility are weighted based on the expected number of parcels screened annually, the estimated weighted average cost per pound is 4.8 cents. Step 1: Develop Price Elasticity Model Step 2: Estimate Regulatory Compliance Costs Step 3: Translate Costs into Price Impacts Step 4: Estimate Impact of Increased Prices on Demand Step 5: Model Economic Impacts 1-30

Figure 1. TSA Estimated Total Costs of Complying with the 100 Percent Screening Rule The results of this graph suggest strong incentives for airlines with small cargo operations to seek third-party screeners who can take advantage of economies of scale to reduce the screening price. Translate Costs into Price Impacts/ Estimate Impact of Increased Prices on Demand To determine the economic impact of the 100 percent screening rule, the costs presented in the previous section must be translated into price impacts in percentage terms. Using the outlined approach, price impacts are translated into demand impacts, which are then fed into the input-output models (e.g., IMPLAN, RIMS II) to determine regional economic impacts. To determine the price effects of the screening costs, the BEA’s input-output (I-O) accounts were used to apply an industry overhead charge to the screening costs. This overhead charge was set equal to the gross operating surplus for the air transportation industry. Between 2008 and 2012, gross operating surplus added an average of 8.4 percent to total output in the air transportation industry. Applying this 1.084 industry markup to the screening costs resulted in a final screening price impact of 5.7-7.4 cents per pound (Bureau of Economic Analysis 2011). y = 11.972x-0.844 R² = 0.7427 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0 500 1000 1500 2000 2500 To ta l D ire ct C os t p er P ou nd Number of Parcels Screened Annually (000s) Step 1: Develop Price Elasticity Model Step 2: Estimate Regulatory Compliance Costs Step 3: Translate Costs into Price Impacts Step 4: Estimate Impact of Increased Prices on Demand Step 5: Model Economic Impacts 1-31

To determine the percentage increase in air cargo prices resulting from the added screening costs, the average revenue per pound of air freight in the US was calculated using financial data and traffic statistics published by the BTS. Using freight weight and revenue data the average revenue per pound of air cargo transported by U.S. carriers was estimated at 86.2 cents. To calculate this value, freight data for specific carriers were obtained from the T-100 Market (US Carriers) BTS data file and compared with revenues from the P-1.2 data file. The price impacts associated with the 100 percent screening rule must be translated into percentage terms to apply the price elasticity model. The TSA100 percent screening rule was estimated to increase the overall price of air cargo transported on-board passenger aircraft by 6.0-8.6 percent. Table 2 provides examples of impact analysis using the outlined approach applied to the five case study airports. The table presents the estimated reduction in freight on-board aircraft using the suggested approach and then translates those reductions into overall reductions in freight. For each airport, BTS data were used to determine the share of total freight comprised of air cargo transported on-board passenger aircraft. At airports with the largest share of freight comprised of cargo transported on-board passenger aircraft (e.g., JFK), impacts were the most significant. At airports dominated by air cargo operations (e.g., SDF), demand reductions were estimated to be relatively less significant. Table 2. Estimated Impact of Increased Prices on Air Cargo Demand – Case Study Airports Airport Reduction in Freight On- board Passenger Aircraft Air Cargo On-board Passenger Aircraft as Share of Total Freight Reductions in Total Freight TSA Analysis Industry Estimates TSA Analysis Industry Estimates IAH -1.4% -2.0% 47.1% -0.6% -0.9% JFK -5.7% -8.2% 46.1% -2.7% -3.8% MCI -6.1% -8.7% 6.8% -0.4% -0.6% RNO* -3.0% -4.3% 3.3% -0.1% -0.1% SDF -6.9% -9.8% 0.1% 0.0% 0.0% *The national model was used as a default for estimating the price elasticity of air cargo demand in Reno due to the inadequate results generated using local data. 1-32

Estimate Regional Economic Impacts From an economic perspective, there are three effects that will be captured in the I-O models applied to airport studies: • The reduced demand for air cargo reveals a contraction in the industries engaged in air cargo operations • Increased output by air transportation operations engaged in air cargo screening activities • Increased output for air transportation companies due to overhead expenses applied to air cargo screening costs (this third impact may serve to counterbalance the first effect) Table 3, presents the air cargo inputs required for the I-O models to effectively assess impacts. The reduction in freight presented in this table represents the percentage reduction in total (cargo-only and cargo transported on-board passenger airplanes) cargo. The impacts vary depending on the price elasticity modeled at each airport and the scale of air cargo transported on-board passenger aircraft. Of course, the screening rule does not affect cargo-only aircraft. So economic impacts are isolated to only cargo transported on-board passenger aircraft. The negative economic effects reduce the economic output of the industry. Since the impact of the TSA 100 percent screening rule applies to all air cargo transported on-board passenger aircraft, it is expected to impact both enplaned and deplaned cargo volumes. Since it does not impact cargo-only aircraft, the overall reductions in freight are less than the impacts on cargo on-board passenger aircraft. The cargo screening costs and industry markup attached to those costs reflect the price increase that is passed on to the customer. These values reflect increased revenue/output to the air transportation and supporting industries. Table 3. Air Cargo Screening Inputs for I-O Models – Case Study Airports Airport Reductions in Freight Cargo Screening Costs Gross Industry Surplus on Cargo Screening Costs TSA Analysis Industry Estimates TSA Analysis Industry Estimate TSA Analysis Industry Estimate IAH -0.6% -0.9% $8,944,118 $12,775,705 $751,501 $1,073,438 JFK -2.7% -3.8% $25,241,205 $36,054,330 $2,120,813 $3,029,352 MCI -0.4% -0.6% $247,949 $354,169 $20,833 $29,758 RNO* -0.1% -0.1% $71,619 $102,300 $6,018 $8,595 SDF 0.0% 0.0% $101,236 $144,605 $8,506 $12,150 Step 1: Develop Price Elasticity Model Step 2: Estimate Regulatory Compliance Costs Step 3: Translate Costs into Price Impacts Step 4: Estimate Impact of Increased Prices on Demand Step 5: Model Economic Impacts 1-33

2.4.2 Demand Elasticity Models for Fuel Cost Impacts To model the price elasticity of air cargo demand with respect to jet fuel prices a stepwise regression approach should be used to target variables that had a statistically significant impact on air cargo demand. The use of this approach is effective since you have a choice of predictive variables (e.g. cost to demand) which can be carried out by a selective procedure. So for example, one variable, log-GDP, can be manually entered into the model. An example of the variable selection process used with this approach is reviewed in Table 4, where besides the five flag variables there are three other selected inputs: log-GDP (real); log-Jet Fuel Price (real), and domestic passengers enplaned. Table 4. Summary of Stepwise Regression Step Variable Entered Variable Removed Partial R- Square Model R- Square F Value Pr>F 1 post_flag 0.0472 0.9322 56.44 <.0001 2 anom_flag 0.0210 0.9533 36.01 <.0001 3 pasenplanedd 0.0091 0.9624 19.16 <.0001 4 Lrailrev 0.0025 0.9649 5.65 0.0199 5 q3_flag 0.0016 0.9666 3.80 0.0550 6 q2_flag 0.0036 0.9701 9.03 0.0036 7 Lrailrev 0.0009 0.9693 2.21 0.1412 8 Lrealjetfuel 0.0014 0.9706 3.59 0.0619 9 q1_flag 0.0012 0.9719 3.30 0.0733 Results of a jet fuel price elasticity model are summarized in Table 5. The model fits the data well with an R-Squared and an adjusted R-Squared of approximately 0.97. The overall model is highly significant with a p-value less than 0.001. Table 5. Jet Fuel Price Elasticity Model – Analysis of Variance Source Degrees of Freedom (DF) Sum of Squares Mean Square F Value Pr > F Model 8 20.00432 2.50054 324.07 <.0001 Error 75 0.570 0.00772 Corrected Total 83 20.58302 Root MSE 0.08784 R-Square 0.9719 Dependent Mean 22.44098 Adj R-Square 0.9689 Coeff Var 0.39143 An inspection of the parameter estimates table in Table 6 reveals much about the observed relationship between air cargo demand and the selected explanatory variables. As important as the magnitude of the parameter estimates is the arithmetic sign. Of the eight inputs (not counting the intercept), four are positive and four are negative in sign indicating a positive 1-34

or negative correlation, respectively, with air cargo demand. Of the three non-flag variables, only the jet fuel variable was negative in sign as expected. Two of the flag variables helped the model better fit the aforementioned data anomaly, and the other three were quarterly flags. These latter variables were all negative in sign – indicating a steady quarterly decrease in Air Cargo shipments culminating in an offsetting increase in the 4th quarter. The parameter estimate for the real jet fuel price variable is -.07537 indicating that for every 10 percent increase in jet fuel prices, air cargo demand would be expected to drop by 0.75 percent. Table 6. Jet Fuel Price Elasticity Parameter Estimates Variable Parameter Estimate T Value Pr > |t| Intercept 2.50542 0.49 0.6286 lgdp05 0.62514 3.54 0.0007 q1_flag -0.04974 -1.82 0.0733 q2_flag -0.12919 -4.22 <.0001 q3_flag -0.13259 -4.24 <.0001 anom_flag 0.45435 8.84 <.0001 post_flag 0.56740 12.18 <.0001 lrealjetfuel -0.07539 -2.06 0.0433 pasenplanedd 7.313436E-9 6.32 <.0001 Table 7 presents the impacts of a 10, 20, and 30 percent increase in jet fuel prices on demand for air cargo at each of the five case study airports. As shown, the impacts range from less than 1 million pounds for RNO under the 10 percent jet fuel price increase scenario to over 100 million pounds for SDF under the 30 percent price increase scenario. For every 10 percent increase in jet fuel prices, air cargo demand is estimated to decline by 0.7 percent. Table 7. Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) on Demand for Air Cargo Impacts of Jet Fuel Prices Increases on Demand for Air Cargo Airport 10% 20% 30% IAH (6,368,857) (12,737,715) (19,106,572) JFK (21,150,552) (42,301,105) (63,451,657) MCI (1,354,130) (2,708,260) (4,062,390) RNO (781,291) (1,562,582) (2,343,873) SDF (33,956,926) (67,913,853) (101,870,779) Reduction in Air Cargo -0.7% -1.5% -2.2% The five-step approach outlined previously for the TSA 100 percent air cargo screening can be applied to jet fuel costs. (Note that Steps 2 and 3 – in estimating regulatory compliance costs and translate cost into price impacts are not required for this analysis because there are no overhead costs associated with constant price fluctuations in jet fuel). Thus, the output of the model can be applied directly to freight totals to estimate reductions in air cargo demand. In terms of applying these results at the local level, reduced demand for air cargo would be modeled as a contraction in the industries engaged in air cargo operations. For every 10 percent increase in price, air cargo operations would be expected to contract by 0.7 percent. 1-35

2.5 Simplified Economic Impact Analysis Model To determine the contribution of additional air cargo freight activity at a given airport on the total economic output in the market area influenced by that airport, there are several decisions must be make in structuring a model. Decisions will involve several characteristics of the air cargo’s potential economic impact on final demand. Final demand is an economic term defining the total amount of economic activity for a defined region. Final demand would include the direct impacts of expanding air cargo freight capacity at the airport, plus the additional economic activity generated by these direct changes. These indirect and induced effects are why the additional impacts are often called multipliers. 2.5.1 Instructions for a Simple Estimation Model To determine the relationship between freight and economic output key questions about changes to the status quo must be addressed. The following provides those questions supported by specific guidance for finding the answers to support inputs for a simplified model. 1. How much additional economic activity would be generated? • The following are the key data items that are needed to evaluate additional economic activity: a. Jobs and wage related to air cargo services from the participants of the air cargo industry such as freight forwarders/3PLs, airports, airlines, and others at the selected airport b. Air cargo shipments in tons handled by the industry participants such as freight `forwarders/3PLs c. Commodities shipped by air and other modes d. Revenue related to air cargo business from the industry participants such as airports and freight forwarders/3PLs e. Industry concentrations within the defined study region. (See page 72 of the main report) 2. What industries would be most affected by such changes? a. Inspection of the BEA RIMS II 471 industry types would suggest which detailed industries would best match to the main industries needing the support of air cargo operations b. Stakeholders and their respective survey response would also provide extra data and information in answering this question 3. What area (economic region) would the changes effect? a. In determining a study region, most cases should begin with the counties within the Metropolitan Statistical Area (MSA) where each airport is located. b. The study region is defined at the county level because the datasets underlying each of the I-O models reside at that level Simple Step Process to Construct a Simple Economic Estimating Model: • After considering the three key questions above, the first action is to define the regions, which can be a single county or a combination of counties that that will be 1-36

covered by the impacts generated by air cargo freight capacity changes within an airport market area. • Once the regions are defined, the Bureau of Economic Analysis (BEA) should be contacted for renting/purchasing the needed models. • Select our construct the simple model • Fill in the data and factor your estimated outcomes Supporting Information The BEA has developed input-output (I-O) models for any United States regions composed of counties, and requires users to specify the regions of analysis before renting/purchasing. This I-O model from BEA is called RIMS II. • The URL to purchase RIMS II multipliers is: https://bea.gov/regional/rims/rimsii/ • Multipliers may be ordered for any region that consists of one or more contiguous counties at a cost of $275 per region. • For each region ordered includes Type I and Type II (detailed below) final-demand and direct-effect multipliers for all the RIMS II industries in the region. o Note: Multipliers for each county or state within the region will not be provided. o Type II multipliers should be used as it includes both inter-industry and household spending of a final demand changes. Type I multipliers only account for the inter-industry effect, which is not the full impact being sought with a regional air cargo estimate. In addition, BEA has published two useful reference documents. The first is a RIMS II user guide, which can be found at the URL: http://www.bea.gov/regional/pdf/rims/RIMSII_User_Guide.pdf • While the BEA guide is useful material, the streamlined model offered here is intended to further simplify a description of the use of RIM II multipliers. The second suggested resource is entitled, Regional Multipliers: A User Handbook for the Regional Input-Output Modeling System (Third Edition, 1997), found at the URL: http://www.bea.gov/scb/pdf/regional/perinc/meth/rims2.pdf. • This document provides appendices which will guide you to choose the appropriate industries whose multipliers would be most affected by air cargo freight expansion. In estimating economic impact this simplified approach uses economic output measures combined with basic input-output account data to formulate direct, indirect, and induced effects. This can be accomplished by first executing the various data collection and survey techniques discussed in this Guidebook. Information can be generated on basic economic measures such as employment (number of jobs and earnings) value and value-added output (expressed in dollars). This gives the analyst the basic information on changes in economic activity to which economic multipliers will be applied. 1-37

Reviewing the Regional Multipliers: A User Handbook for the Regional Input-Output Modeling System (RIMS II), will reveal massive tables of multipliers. Additionally, for 38 industry aggregations, and 471 detailed industries, four tables of multipliers exist. Rather than discuss in detail each of these options, we recommend using a table of total final-demand multipliers for output, earnings, employment (Labeled Table 1.4). Since the air cargo industry is limited in the types of industries that use its services, it would be best to select from the more detailed 471 industry multipliers rather than the 38 industry aggregation. As offered with Table 8, a simple table can be developed to total these full impacts. In the first column, list all the detailed industries that would be impacted by the expansion of air cargo capacity. In the second column, list the direct impact to the column 1 industry either as dollars for most items or the number of jobs for the additional employment provided. There would then be up to three columns (3, 4, and 5, below) listing the final demand multipliers. These multipliers would be provided by BEA in accordance with what the analyst ordered from them for the modeled region. The final set of columns (6, 7, and 8) would then be the final demand multiplier columns (3, 4, and 5) times the second column displaying the resulting full impact on the defined region. The last three columns would be added up for all the industries listed to determine the estimated final full impact. Table 8. Simplified Economic Impact Estimation Model Column 1 Column 2 Column 3 Column 4 Column 5 Column 6 Column 7 Column 8 Final Demand Multiplier Full Impact Industry 1 Direct impact ($ or employ) Output ($) Earnings ($) Employment (jobs) Output ($) Earnings ($) Employmen t (jobs) Col. 2X3 Col. 2x4 Col. 2x5 Industry 2 Industry 3, etc. Total Total Total 1-38

3 SECTION III – CASE STUDIES FOR FIVE SELECTED AIRPORTS In 2012, U.S. airports served 807.1 million passengers and handled 57.3 billion pounds of freight (Bureau of Transportation Statistics 2012). Most of the air service (83.2 percent of passengers and 88.5 percent of the cargo) was provided by the nation’s top 50 airports (ACI 2012). Although the air services supplied by airports were highly concentrated in the nation’s largest airports, small and medium airports also were involved and generated substantial economic effects for their local economies. In selecting a sample of five airports for the case studies, it is certainly critical to understand that air freight and passenger services are dominated by a small number of large airports. Still, it is important to capture the perspective of airports with differing characteristics, since the models presented with this Guidebook must be useful for various types of airports. The selection criteria for sample airports included: • Geographic dispersion • Airport characteristics o Major passenger and air freight hub o Specialized airport o Major regional airport. Based on the criteria set up for selecting sample airports for case studies, the following five airports were selected: • JFK in New York, NY • SDF in Louisville, KY • RNO in Reno, NV • MCI in Kansas City, MO • IAH in Houston, TX These airports represent a sample of major hubs, special types of large airports, and major regional airports in diversified regions. Each airport has its characteristics and specialties, which are summarized in Table 9. Table 9. Characteristics of Airports Selected for Case Studies Airport Code City, State Selection Criterion Region Freight Shipment (million lbs.) # of Passengers Enplaned (thousands) % of Outbound JFK New York, NY Hub NE 2,824.2 23,663.0 44.3 SDF Louisville, KY Integrator S 4,640.0 1,647.5 51.6 MCI Kansas City, MO Regional MW 182.7 5,007.3 50.2 IAH Houston, TX Regional S 919.2 19,303.1 50.4 RNO Reno, NV Regional W 109.3 1,8178.0 59.3 Source: Bureau of Transportation Statistics (2012). 1-39

3.1 Case Studies Case Study 1 – Kansas City International Airport, Kansas City, MO MCI has served the needs of travelers to the Midwest for over 25 years. Opening in 1972, the airport is owned and operated by the city of Kansas City, Missouri. The airport is located approximately 15 miles from the center of the city. Its 10,000-plus acres of airfield make it physically one of the largest airports in the U.S., and its three runways can accommodate up to 139 aircraft operations per hour. There are currently ten major airlines that operate out of the three passenger terminals at MCI, which saw an increase in passenger traffic in 2010 of 1.3 percent from the previous year, despite a decrease in total aircraft movements of 2.5 percent over 2009 (Kansas City Aviation Department 2012). The airport is well positioned in the United States for air cargo and distribution development. It must, however, compete with larger gateways where the ability to consolidate freight is a substantial advantage. In 2010, total cargo handling saw a decrease of 1.8 percent from the previous year due to a shift in domestic freight to trucking and total airmail operations. However, international freight saw a substantial 41.3 percent increase from the previous year (from a relatively small base) due mainly to increased charter activity (Kansas City Aviation Department 2012). The airport has a surplus of existing cargo capacity and enough land to expand if needed. The cargo area is comprised of four commercial cargo terminals with airside access. The cargo facilities contain an expansive cargo-handling infrastructure, on-site Foreign Trade Zone, and Enhanced Enterprise Zone tax initiatives. The city is also known for having the nation’s second largest rail center, which contributes to the efficiency of the region’s overall logistics system. More than 95 percent of the cargo moving through MCI is processed by the integrators (Kansas City Aviation Department 2012). FedEx and United Parcel Service (UPS) control 73 percent and 25 percent of the cargo moving through the airport, respectively (Kansas City Aviation Department 2012). Since the early 1990’s, much of the international origin-and- destination cargo from the Kansas City area has been trucked to international hubs such as Chicago and Dallas/Ft. Worth due to the lack of wide-body passenger aircraft at MCI. In 2011, passenger carriers accounted for less than 6.2 percent of the total freight carried at the airport and this percentage has diminished (Bureau of Transportation Statistics 2012). Trans-Pacific and trans-Atlantic air cargo markets may have some future potential if congestion builds at other established gateways. Domestic growth in the cargo industry is expected to increase in the future for integrated carriers, which could potentially have an impact on future cargo operations at MCI. It is likely that growth in the air cargo industry will also require leading carriers such as FedEx and UPS to adjust and update aircraft to accommodate the growing market, potentially affecting cargo operations at MCI. This case study describes the structure of the Kansas City regional economy, and the method for estimating the economic impact of air cargo through MCI airport. These estimates are presented at the scale of the 15-county Kansas City, MO-KS Metropolitan Statistical Area, consistent with the 2009 Office of Management and Budget (OMB) regional definition and comprised of the following counties: 1-40

• Franklin County, KS • Johnson County, KS • Leavenworth County, KS • Linn County, KS • Miami County, KS • Wyandotte County, KS • Bates County, MO • Caldwell County, MO • Cass County, MO • Clay County, MO • Clinton County, MO • Jackson County, MO • Lafayette County, MO • Platte County, MO • Ray County, MO Airports play an essential role in supporting the growth of a metropolitan economy like the Kansas City region. They directly employ hundreds of workers and provide millions of dollars in direct economy activity and taxes and other revenues to local government. They also support the growth of the regional economy by moving people, goods, and services that originate in, or are transported through the region, in response to its market opportunities. Airports and related aviation facilities become structurally integrated into a region’s economy and provide it with competitive advantages. Airports enable industries that either depend on, or learn to take advantage of, efficient air transportation to access domestic and international markets. In the Kansas City region, MCI plays this vital role. The airport accommodated over 10 million passengers and nearly 86,000 metric tons of cargo in 2011, making it the 36th busiest passenger airport and 45th busiest cargo airport in North America according to ACI’s 2011 report. The primary objective of this case study was to estimate the current economic impacts associated with the air cargo movement, estimating the economic output, employment, personal income, of that activity, and to document the analysis so as to make it easily replicable for other airports in other regions. The analysis is based on RIMS-II multipliers. The RIMS-II multipliers are regional input-output multipliers developed and provided by the Bureau of Economic Analysis (BEA). These multipliers allow the user to estimate the economic impact of a change in final demand,1 in earnings, or in employment on a region’s economy. The multipliers are used to estimate changes in the regional economy that result from a change in activity relative to a baseline representation of the economy. The sources of the activity being measured vary, but typically involve changes in production or consumption 1 Also referred to as “change in output delivered to final users.” 1-41

activities, government policies, infrastructure, or changes in costs or technology. For any change in economic activity, the impacts on the economy are typically reported on one of three levels: • Direct impacts represent the initial change in final demand for the industry sector(s) in question. For this analysis, we are estimating the economic activity associated with air cargo in Kansas City. • Indirect impacts represent the response as supplying industries increase output to accommodate the initial change in final demand. These indirect beneficiaries spend money for supplies and services, which results in another round of indirect spending, and so on. Indirect impacts are often referred to as “supply-chain” impacts. • Induced impacts are generated by the spending of households that benefit from the additional wages and income earned through direct and indirect economic activity. The increase in income, in effect, increases the purchasing power of households. Induced impacts are also described as “consumption-driven” effects. This cycle of direct, indirect, and induced spending does not go on forever. It continues until the spending eventually leaks out of the economy as a result of taxes, savings, or purchases of non-locally produced goods and services or “imports.” The RIMS-II multipliers are provided for Type I and Type II impacts. Type I multipliers account for the direct and indirect impacts based on the supply of goods and services in the region. Type II multipliers account for these same direct and indirect impacts, and for induced impacts, associated with the purchases made by employees. Both types of multipliers include the initial change. Kansas City Regional Economy Kansas City is one of 422 Metropolitan Statistical Areas (MSA) in the United States. Based on its 2009 population estimate of 2,067,585, it is ranked 29th in size in the United States. Its per-capita personal income is about 102 percent of the national average. The scale of economic activity occurring in the Kansas City region would not have been possible without development of the water, rail, highway, and airport infrastructure that enables businesses to take maximum advantage of the region’s location. The economic multiplier effect generated by air cargo activities depends on the geographic boundary or defined “region of analysis.” A dollar spent in the City of Kansas City has a smaller impact on the city alone than it would have on the 15-county region. When selecting the region of analysis, the goal is to balance selecting an area that is large enough to capture a substantial portion of the economic multiplier effect and an area that is small enough to be relevant for the regional analysis. 1-42

Estimating MCI’s Air Cargo Contribution to the Regional Economy This section summarizes the methods used to estimate MCI’s current contribution to the regional economy. This effort quantifies the impact the air cargo through the airport has on the economy at a particular moment in time, using input-output modeling and analysis recommended by the FAA. Measuring the economic impact of the cargo activity at the airport involves tracing the linkages between the airport’s cargo activity level, expressed in terms of airport operations and air cargo volumes, and the sectors of the economy that interact with them. These linkages produce the “direct,” or initial round of economic impact. Direct impacts, in turn, stimulate “indirect” impacts, from the supply of goods and services to businesses at the airport or production of goods for shipment by air. A third round of economic impacts, called “induced” impacts, results from the spending of income earned by direct and indirect employees. The sum of indirect and induced impacts is often referred to as the “multiplier effect” on direct impacts. Total economic impact is the sum of the direct, indirect, and induced impacts. The first and perhaps most obvious source of MCI-related economic impact is the employees who work there. Though many are present to support the air passengers (such as passenger and visitor service providers), many are associated with airport operations and air cargo, including cargo-handling companies, customs agents, TSA, customs brokers, container freight stations, freight forwarders, trucking companies, and other cargo-related services. A second important impact related to airport economic activity is the passenger impact, including expenditures for lodging, food, retail purchases, entertainment, transportation services and parking, among others. Again, the scope of this effort is focused on air cargo, rather than on passengers. The final category of impact is the contribution of air cargo to the regional economy. The analysis of economic impacts of air cargo shipments is part of a developing area of economic research that is still limited by two key factors: 1) the lack of a complete and workable theory of the role of air cargo in economic development; and 2) the lack of data describing the quantity and value of exported goods at any level of specificity. We will explore these limitations and some analytic approaches to them in the next section. Airport Operations As noted earlier, the first and most obvious source of MCI-related economic impact is the employees who work there. Those associated with air cargo include airlines handling cargo, other cargo-handling companies, customs agents, TSA, customs brokers, container freight stations, freight forwarders, trucking companies, and other cargo-related services. Employment data were provided by the airport authority and supplemented by the project surveys of air carriers. These combined data yielded the cargo-related employment estimates presented in the remainder of this section. 1-43

Cargo-related employment for airlines and forwarders were estimated from survey responses, employment data from the airport, and analyses of other similar airports. Despite repeated attempts to gather employment data for several of the cargo-related categories listed above (customs agents, customs brokers, TSA, etc.), we were unable to secure such data. Therefore, it is likely that some of the categories are underrepresented in this analysis. Information received on Kansas City airport cargo operations includes limited employment information from the airport and information from the survey of airlines. Given the information available, the figures for employment and employment categories were estimated from the information provided by the airport, and are shown in Table 10. Table 10. Estimated Employment by Industry Group, MCI, 2010 Number of Jobs (a) Air Transport 27 Transportation Support Activities 380 Couriers and Messengers 55 Total 462 Source: Employer surveys and MCI Airport Authority. Resulting output was estimated from these employment figures and the RIMS-II multipliers. Using the RIMS-II multipliers, we can determine the average number of direct jobs per million dollars change in final demand, as shown in Table 11. 1-44

Table 11. Using the Multipliers and an Estimate of the Number of Jobs the Final-demand Industry to Calculate Final-demand* Industry Final-demand Multiplier Direct-effect Multiplier Direct jobs per $1m change in final-demand (col. c ÷ col. f) Output (total industry output per $1 change in final- demand) Earnings (total household earnings per $1 in final- demand) Employment (total jobs per $1m change in final- demand) Value-added (total value- added per $1 change in final- demand) Earnings (total household earnings per $1 change of household earnings in the final-demand industry) Employment (total jobs per 1 job change in the final- demand industry) (a) (b) (c) (d) (e) (f) (g) Air transportation 2.20 0.71 17.82 1.15 2.02 2.68 6.66 Support activities for transportation 2.44 0.87 22.41 1.42 2.07 2.79 8.04 Couriers and messengers 2.09 0.63 22.27 1.24 2.15 1.91 11.65 *Multipliers for the final-demand industry are used to calculate the final-demand change. The change in earnings in the final-demand industry is often referred to as the direct or initial earnings. Similarly, the change in jobs in the final-demand industry is often referred to as the direct or initial jobs. Source: BEA 2011. 1-45

From there, the number of direct jobs is divided by the direct jobs per $1 million in final demand to arrive at an estimated final demand, as shown in Table 12. Table 12. Estimated Final Demand from Multipliers and Estimate of Jobs Direct Employment Direct jobs per $1m change in final-demand (col. H from Table 2) Estimated final-demand based on RIMS II assumptions and estimated new jobs in the final-demand industry (millions of dollars) (col. a / col. b) (a) (b) (c) Air transportation 27 6.66 4.06 Support activities for transportation 380 8.04 47.25 Couriers and messengers 55 11.65 4.72 Source: BEA 2011. For most types of goods-producing industries, the resulting estimated output would be adjusted for regional purchases in purchasers’ prices, adjusting for transport costs and wholesale and retail margins. However, according to the I-O commodity composition of NIPA (BEA’s National Income and Product Accounts) final use by exports of goods and services, the purchaser value is equivalent to the producer value for these industry categories, therefore, margining for producer prices does not apply. These 462 direct jobs have an estimated output value of over $56 million as shown in Table 13. In addition to the direct impacts, they would have an additional total impact estimated of over $134 million in output, over $47 million in aggregated earnings, and over 1,230 total jobs, as shown in Table 13. 1-46

Table 13. Estimated Economic Impact, Air Cargo Operations, MCI Regional Purchases (millions of dollars) Final Demand Multiplier Impact Output (millions of dollars) Earnings (millions of dollars) Employment (number of jobs) Output (millions of dollars) (col a * col b) Earnings (dollars) (col a * col c) Employment (number of jobs) (col a* col d) (a) (b) (c) (d) (e) (f) (g) Air transportation $4.06 $2.20 $0.71 17.82 $8.92 $2.87 72 Support activities for transportation $47.25 $2.44 $0.87 22.41 $115.48 $41.31 1,059 Couriers and messengers $4.72 $2.09 $0.63 22.27 $9.85 $2.99 105 Total $56.02 $134.25 $47.18 1,236 Source: BEA 2011. 1-47

Air Cargo Impacts to Regional Economy More difficult to quantify is the contribution of air cargo to the regional economy. However, it is generally agreed industries are concentrated within regions with direct access to air cargo operations. In the absence of this access, companies that rely on these services would likely re-locate to other regions with such access. As noted earlier, the analysis of economic impacts of air cargo shipments is part of a developing area of economic research that is still limited by two key factors: 1) the lack of a complete and workable theory of the role of air cargo in economic development; and 2) the lack of data describing the quantity and value of exported goods at any level of specificity. In the first category, one important issue that remains unanswered is the potential for shippers to utilize other airports in the region to export goods in the presence of air cargo supply constraints. For example, there are other airports within the trade area of MCI. This factor is important for modeling MCI’s contribution to the regional economy. It would be unreasonable, for example, to simply subtract the entire value of goods exported by air, because this subtraction would grossly overstate the economic impacts of air cargo (i.e., the value of the goods shipped by air). In the second category are severe air cargo limitations. There are few systematic sources of air cargo data. One is the US Department of Commerce import and export trade statistics and a second is the Commodity Flow Survey (CFS) undertaken every five years by a partnership between the Bureau of Transportation Statistics and the Census Bureau. Data are available for 89 National Transportation Analysis Regions (NTARs). The challenge is that these NTARs are generally larger in geographic area than the metropolitan regions being analyzed. (There are only 89 NTARs in the United States, compared to 422 Metropolitan Statistical Areas. As such, the NTARs are generally much larger than the metropolitan areas, making the cargo volumes for NTARs generally higher than those for the metropolitan areas.) The Freight Analysis Framework (FAF) integrates data from a variety of sources to create a comprehensive picture of freight movement among states and major metropolitan areas by all modes of transportation. With data from the 2007 Commodity Flow Survey and additional sources FAF version 3 (FAF3) provides estimates for tonnage and value by origin, destination, commodity, and mode for 2007, the most recent year, and forecasts through 2040. According to the FAF, over 8 million tons of goods were shipped from the Kansas City Metropolitan area. Of that, nearly 1,040 tons were shipped via air (including truck and air).2 The largest proportion of goods shipped by air is machinery by weight, comprising just under 15 percent of the weight of commodities shipped by air. In terms of value, transportation equipment is higher in value terms, nearly 47 percent of the value of goods shipped by air but just over 7 percent of the weight of goods shipped by air in 2007. Other major commodities shipped via air include electronics and precision equipment, as shown in Table 14. 2 The modes tracked by the Commodity Flow Survey are: For-hire truck, Private truck, Rail, Air, Shallow draft vessel, Deep draft vessel, Pipeline, Parcel/U.S. Postal Service/courier, Other, and Unknown. 1-48

Table 14. Shipment Characteristics by Commodity for Air Transportation (including Truck and Air) for Kansas City Metropolitan Area of Origin: 2007 Commodity Value Weight Million $ in 2007 Percent of Total Value KTons in 2007 Percent of Total Weight Animal feed 0.0062 0.0% 0.0065 0.6% Articles-base metal 1.3462 1.4% 0.0895 8.6% Base metals 0.4849 0.5% 0.0524 5.1% Basic chemicals 1.1997 1.2% 0.0697 6.7% Cereal grains 0.005 0.0% 0.0038 0.4% Chemical prods. 1.3744 1.4% 0.0421 4.1% Coal-n.e.c. 0.0203 0.0% 0.0056 0.5% Electronics 15.668 16.0% 0.1081 10.4% Furniture 0.3874 0.4% 0.0122 1.2% Live animals/fish 0.0372 0.0% 0.0005 0.0% Machinery 12.9457 13.2% 0.1498 14.5% Meat/seafood 0.0118 0.0% 0.0037 0.4% Metallic ores 0.0025 0.0% 0.0075 0.7% Milled grain prods. 0.0043 0.0% 0.0189 1.8% Misc. mfg. prods. 0.3542 0.4% 0.0084 0.8% Mixed freight 0.6968 0.7% 0.0116 1.1% Motorized vehicles 0.2932 0.3% 0.0235 2.3% Nonmetal min. prods. 0.6282 0.6% 0.0753 7.3% Nonmetallic minerals 0 0.0% 0 0.0% Other ag prods. 0.0054 0.0% 0.0005 0.0% Other foodstuffs 0.1913 0.2% 0.0608 5.9% Paper articles 0.1672 0.2% 0.0198 1.9% Pharmaceuticals 3.2331 3.3% 0.0475 4.6% Plastics/rubber 0.8406 0.9% 0.0478 4.6% Precision instruments 11.0804 11.3% 0.0281 2.7% Printed prods. 1.0938 1.1% 0.0349 3.4% Textiles/leather 0.2452 0.2% 0.0117 1.1% Transport equip. 45.8372 46.7% 0.0756 7.3% Wood prods. 0.0088 0.0% 0.0206 2.0% Grand Total 98.169 100.0% 1.0364 100.0% Source: BTS 2009. 1-49

Cargo Screening and Jet Fuel Elasticity Modeling The effects of the 100-percent cargo screening rule and volatility in jet-fuel prices were analyzed and described in a separate chapter, with price models developed to estimate the elasticity of demand upon price changes from the increased costs of the additional cargo screening and the increase in the price of air cargo due to increases in jet-fuel prices. Cargo Screening Impacts The elasticity analysis noted that the cargo screening includes three effects to be captured in the I-O models applied at the case-study airports: • The reduced demand for air cargo modeled as a contraction in the industries engaged in air cargo operations • Increased output by air transportation engaged in air cargo screening activities • Increased output for air transportation companies due to overhead applied to air cargo screening costs (this third impact serves to counterbalance the first effect) Table 15 presents the air cargo the inputs required for the I-O models. The reduction in freight presented in this table represents the percentage reduction in total (cargo-only and cargo transported on-board passenger airplanes) cargo. The impacts vary depending on the price elasticity modeled at each airport and the scale of air cargo transported on-board passenger aircraft. The screening rule does not affect cargo-only aircraft. The negative economic effects reduce the economic output of the industry. The cargo screening costs and industry markup attached to those costs reflect the price increase that is passed on to the customer. These values reflect increased revenue/output to the air transportation and supporting industries. Table 15. Air Cargo Screening Inputs for I-O Models Airport Reductions in Freight Cargo Screening Costs Gross Industry Surplus on Cargo Screening Costs TSA Analysis Industry Estimates TSA Analysis Industry Estimate TSA Analysis Industry Estimate IAH -0.6% -0.9% $8,944,118 $12,775,705 $751,501 $1,073,438 JFK -2.7% -3.8% $25,241,205 $36,054,330 $2,120,813 $3,029,352 MCI -0.4% -0.6% $247,949 $354,169 $20,833 $29,758 RNO* -0.1% -0.1% $71,619 $102,300 $6,018 $8,595 SDF 0.0% 0.0% $101,236 $144,605 $8,506 $12,150 1-50

For Kansas City, the reductions in freight and counterbalancing increases in cargo screening impacts results in the following direct impacts: Table 16. Air Cargo Screening Inputs for MCI I-O Modeling Grand Total Changes Lower Estimate Upper Estimate Air Transport ($15,854) ($24,390) Transportation Support Activities ($182,264) ($280,645) Couriers/messengers ($28,320) ($42,480) Total Changes ($226,438) ($347,515) According to the RIMS-II multipliers, these direct impacts of between $226,400 and $348,000 would result in between $539,400 and $828,600 in total impact, as shown in Table 17 below. Table 17. Economic Impact Associated with Cargo Screening Regional Purchases (dollars) Output (dollars) Earnings (dollars) Employment (number of jobs) Value-added (dollars) Cargo Screening- lower estimate Transport by air ($15,854) ($34,865) ($11,234) (0.28) ($18,181) Sup’t activities/ air transport ($182,264) ($445,490) ($159,372) (4.08) ($258,742) Couriers/messengers ($28,320) ($59,078) ($17,963) (0.63) ($35,049) Total Impact ($226,438) ($539,433) ($188,569) (5.00) ($311,972) Cargo Screening- upper estimate Transport by air ($24,390) ($53,636) ($17,283) (0.43) ($27,970) Sup’t activities/ air transport ($280,645) ($685,953) ($245,396) (6.29) ($398,404) Couriers/messengers ($42,480) ($88,618) ($26,945) (0.95) ($52,573) Total Impact ($347,515) ($828,206) ($289,624) (7.67) ($478,947) Impacts of Jet Fuel Price Fluctuations The second elasticity model developed examines the impacts of jet-fuel price increases on air cargo demand. It examined the impacts associated with 10 to 30 percent increases in jet- fuel prices, using a stepwise regression approach. Table 18 presents the impacts of a 10, 20, and 30 percent increase in jet fuel prices on demand for air cargo at each of the five case study airports. For every 10 percent increase in jet- fuel prices, air cargo demand is estimated to decline by 0.7 percent. 1-51

Table 18. Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) on Demand for Air Cargo Impacts of Jet Fuel Prices Increases on Demand for Air Cargo Airport 10% 20% 30% IAH (6,368,857) (12,737,715) (19,106,572) JFK (21,150,552) (42,301,105) (63,451,657) MCI (1,354,130) (2,708,260) (4,062,390) RNO (781,291) (1,562,582) (2,343,873) SDF (33,956,926) (67,913,853) (101,870,779) Reduction in Air Cargo -0.7% -1.5% -2.2% Applying these values to the on-airport operations yields the following results for the 10, 20, and 30-percent increases in jet-fuel prices. As shown in Table 19, the reduction in output ranges from $939.7 thousand to $2.8 million for 10 percent and 30 percent increases in jet fuel prices, respectively. Table 19. Economic Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) Regional Purchases (dollars) Output (dollars) Earnings (dollars) Employment (number of jobs) Value-added (dollars) 10% increase in fuel price .7% decrease in cargo volume Transport by air ($28,399) ($62,453) ($20,124) (0.5) ($32,568) Sup’t activities/ air transport ($330,721) ($808,348) ($289,182) (7.4) ($469,492) Couriers/messengers ($33,035) ($68,915) ($20,954) (0.7) ($40,885) Total Impact ($392,156) ($939,717) ($330,261) (8.7) ($542,945) 20% increase in fuel price 1.5% decrease in cargo volume Transport by air ($60,856) ($133,828) ($43,122) (1.1) ($69,789) Sup’t activities/ air transport ($708,688) ($1,732,175) ($619,677) (15.9) ($1,006,053) Couriers/messengers ($70,790) ($147,675) ($44,902) (1.6) ($87,610) Total Impact ($840,334) ($2,013,678) ($707,701) (18.5) ($1,163,453) 20% increase in fuel price 1.5% decrease in cargo volume Transport by air ($85,198) ($187,359) ($60,371) (1.5) ($97,705) Sup’t activities/ air transport ($992,163) ($2,425,045) ($867,547) (22.2) ($1,408,475) Couriers/messengers ($99,106) ($206,746) ($62,863) (2.2) ($122,654) Total Impact ($1,176,467) ($2,819,150) ($990,782) (26.0) ($1,628,834) Case Study 2 – Louisville International Airport, Louisville, KY Louisville International Airport (SDF), located just 10 minutes from downtown Louisville, Kentucky was originally established by the U.S. Army Corp of Engineers in 1941. The airport efficiently operates with two parallel runways and one crosswind runway and more than 62,000 linear feet of Taxiways. In 2011, the Airport recorded 152,998 operations (take offs and landings). Situated on 1,200 acres, the airport contains a centralized terminal facility with 23 1-52

passenger gates. In 2010, the airport served more than 3.3 million passengers. This represented an increase of 2.6 percent over 2009 traffic volumes (Louisville Regional Airport Authority 2012). Currently, 8 major commercial passenger airlines operate out of SDF. These carriers mainly serve the Midwest and east coast, however, there are a few western destinations including Las Vegas, Nevada and Denver, Colorado. Most of the operations are with narrow-body aircraft or regional jets that provide very limited belly capacity for cargo. SDF is also home to the 123rd Wing of the Kentucky Air National Guard, as well as one of the top air cargo facilities in the world. SDF is ranked 10th among the top air cargo airports in the world and ranks 3rd domestically behind Memphis, Tennessee and Anchorage, Alaska (which is essentially a transfer facility and fuel stop for transpacific traffic). SDF processed over 2.3 million tons of total cargo in 2010 - up 11.2 percent from the previous year (Louisville Regional Airport Authority 2012). In 2011, the Airport’s cargo volumes were flat due to recent economic stagnation. Cargo is the fortress hub of United Parcel Service (UPS) and its massive Worldport facility. This substantial operation connects Louisville to 220 countries and territories and process 416,000 packages per hour. In addition to their Worldport facility, UPS added a heavy airfreight hub in 2005 that provides an additional 686,000 square feet of space for operations (United Parcel Service 2011). The Worldport facility occupies approximately 5.2 million square feet of space. The second UPS Worldport expansion was completed in 2010 increasing the facilities sorting capacity by 37 percent. The operation, which is dominated by an extremely sophisticated material handling system, is nevertheless extremely labor intensive. This section describes the structure of the Louisville regional economy, and the method for estimating the economic impact of air cargo through SDF airport. These estimates are presented at the scale of the eight-county region, comprised of Bullitt, Jefferson, Oldham, and Shelby counties in Kentucky, and Clark, Floyd, Harrison, and Scott counties in Indiana. Airports play an essential role in supporting the growth of a metropolitan economy like the Louisville region. They directly employ hundreds of workers and provide millions of dollars in direct economic activity and taxes and other revenues to local government. They also support the growth of the regional economy by moving people, goods, and services that originate in, or are transported through, the region. Airports and related aviation facilities become structurally integrated into a region’s economy and provide it with competitive advantages. Airports enable industries that either depend on, or learn to take advantage of, efficient air transportation to access domestic and international markets. In the Louisville region, SDF plays this vital role. Because the purpose of this project is to develop a Guidebook for quantifying the economic impacts of air cargo, this analysis focuses on the cargo volumes through SDF, with limited analysis of passengers and airline operations. The primary objective of this analysis is to estimate the current economic impacts associated with the air cargo movement, estimating the economic output, employment, personal income, of that activity, and to document the analysis so as to make it easily replicable for other airports in other regions. 1-53

This memo first describes the structure of the Louisville metropolitan economy in 2009, using a Louisville region-specific version of the IMPLAN impact analysis software.3 It then presents the methods used to estimate the air cargo contribution to the economy, and finally presents estimates of economic impact of that air cargo movement. The model is used to measure changes in the regional economy that result from a change in activity relative to a baseline representation of the economy. The sources of the activity being measured vary, but typically involve changes in production or consumption activities, government policies, infrastructure, or changes in costs or technology. For any change in economic activity, the impacts on the economy can be reported on one of three levels: • Direct impacts represent the initial change in final demand for the industry sector(s) in question. For this analysis, we are estimating the economic activity associated with air cargo in Louisville. • Indirect impacts represent the response as supplying industries increase output to accommodate the initial change in final demand. These indirect beneficiaries spend money for supplies and services, which results in another round of indirect spending, and so on. Indirect impacts are often referred to as “supply-chain” impacts. • Induced impacts are generated by the spending of households who benefit from the additional wages and income they earn through direct and indirect economic activity. The increase in income, in effect, increases the purchasing power of households. Induced impacts are also described as “consumption-driven” effects. This cycle of direct, indirect, and induced spending does not go on forever. It continues until the spending eventually leaks out of the economy as a result of taxes, savings, or purchases of non-locally produced goods and services or “imports”. Louisville Regional Economy This section summarizes the Louisville economy, and presents an economic portrait of the region’s economy in terms of employment and output by industry for the base year of 2009. Louisville is one of 422 MSAs in the United States. Based on its 2009 population estimate of 1.14 million, it is ranked 42nd in size in the United States. Its per-capita personal income is about 95 percent of the national average. There are an estimated 726,742 jobs across 356 industries in the region. The top industries by employment are presented in Table 20. 3 The IMPLAN model is based on an input-output modeling framework, and uses secondary source data and proprietary analytic methods to estimate empirical input-output relationships from a combination of national technological relationships and county-level measures of economic activity. 1-54

Table 20. Top Ten Industries, Ranked by Employment Louisville Region, 2009 Code Description Employment Labor Income Output 413 Food services and drinking places 49,539 $1,022,839,000 $2,829,005,000 438 State & local govt, education 44,401 $2,489,589,000 $2,828,209,000 360 Real estate establishments 30,527 $285,869,900 $2,811,924,000 319 Wholesale trade businesses 27,909 $2,034,809,000 $5,337,690,000 394 Offices of physicians, dentists, and other health practitioners 22,438 $1,658,313,000 $2,806,253,000 397 Private hospitals 21,994 $1,353,499,000 $2,895,250,000 382 Employment services 20,393 $410,902,500 $599,624,600 339 Couriers and messengers 17,650 $1,341,379,000 $3,645,585,000 357 Insurance carriers 17,154 $1,308,918,000 $5,289,567,000 437 State & local govt, non-education 14,988 $776,938,200 $882,612,900 Source: MIG 2011a. The top industries ranked by output are presented in Table 21. Table 21. Top Ten Industries, Ranked by Output Louisville Region, 2009 Code Description Employment Labor Income Output 277 Light truck and utility vehicle manufacturing 3,314 $349,197,500 $5,516,958,000 319 Wholesale trade businesses 27,909 $2,034,809,000 $5,337,690,000 357 Insurance carriers 17,154 $1,308,918,000 $5,289,567,000 361 Imputed rental activity for owner-occupied dwellings 0 $0 $4,360,240,000 339 Couriers and messengers 17,650 $1,341,379,000 $3,645,585,000 397 Private hospitals 21,994 $1,353,499,000 $2,895,250,000 413 Food services and drinking places 49,539 $1,022,839,000 $2,829,005,000 438 State & local govt, education 44,401 $2,489,589,000 $2,828,209,000 360 Real estate establishments 30,527 $285,869,900 $2,811,924,000 394 Offices of physicians, dentists, and other health practitioners 22,438 $1,658,313,000 $2,806,253,000 Source: MIG 2011a. The scale of economic activity occurring in the Louisville region would not have been possible without development of the water, rail, highway, and airport infrastructure that enables businesses to take maximum advantage of the region’s strategic location at the midpoint of key North American trade routes. Today, the region is a major hub of express freight, with over 20,000 UPS employees based in the Louisville region. Though UPS had a hub in Louisville since 1980, it was in 2002 that the company made its first $1 billion expansion, establishing Louisville as “Worldport”, the company’s worldwide air hub. A second $1 billion expansion was completed in April 2010, bringing its facility to 5,200,000 square feet, with capacity to handle 416,000 packages per hour (United Parcel Service 2011). 1-55

The regional economic impacts of air cargo through SDF are directly related to the scale and composition of the air cargo forecasts (i.e., international versus domestic, and belly cargo versus all-cargo freighters). Estimating SDF’s Air Cargo Contribution to the Regional Economy This section summarizes the methods used to estimate SDF’s current contribution to the regional economy. This effort quantifies the impact the air cargo through the airport has on the economy at a particular moment in time, using input-output modeling and analysis recommended by the FAA (Butler and Kiernan 1992). Measuring the economic impact of the cargo activity at the airport involves tracing the linkages between the airport’s cargo activity level, expressed in terms of airport operations and air cargo volumes, and the sectors of the economy that interact with them. These linkages produce the “direct,” or initial round of economic impact. Direct impacts, in turn, stimulate “indirect” impacts, from the supply of goods and services to businesses at the airport or production of goods for shipment by air. A third round of economic impacts, called “induced” impacts, results from the spending of income earned by direct and indirect employees. The sum of indirect and induced impacts is often referred to as the “multiplier effect” on direct impacts. Total economic impact is the sum of the direct, indirect, and induced impacts. The first and perhaps most obvious source of SDF-related economic impact is the employees who work there. Though many are present to support the air passengers (such as passenger and visitor service providers), many are associated with airport operations and air cargo, including cargo-handling companies, customs agents, TSA, customs brokers, container freight stations, freight forwarders, trucking companies, and other cargo-related services. A second important impact related to airport economic activity is the passenger impact, including expenditures for lodging, food, retail purchases, entertainment, transportation services and parking, among others. Again, the scope of this effort is focused on air cargo rather than on passengers. The final category of impact is the contribution of air cargo to the regional economy. The analysis of economic impacts of air cargo shipments is part of a developing area of economic research that is still limited by two key factors: 1) the lack of a complete and workable theory of the role of air cargo in economic development; and 2) the lack of data describing the quantity and value of exported goods at any level of specificity. We will explore these limitations and some analytic approaches to them in the next section. Airport Operations As noted earlier, the first and most obvious source of SDF-related economic impact is the employees who work there. Those associated with air cargo include airlines handling cargo, other cargo-handling companies, customs agents, TSA, customs brokers, container freight stations, freight forwarders, trucking companies, and other cargo-related services. 1-56

Employment data were provided by the airport authority and supplemented by the project surveys of air carriers. These combined data yielded the cargo-related employment estimates presented in the remainder of this section. Cargo-related employment for airlines and forwarders were estimated from survey responses, employment data from the airport, and analyses of other similar airports. Despite repeated attempts to gather employment data for several of the cargo-related categories listed above (customs agents, customs brokers, TSA, etc.), we were unable to secure such data. Therefore, it is likely that some of the categories are underrepresented in this analysis. Employment with other air freight companies was extrapolated using cargo volumes reported by the airport and UPS’ employment in their air business unit. Of UPS’ 20,288 Louisville employees, 13,934 work in the air business unit. Using the employment in the air business unit and the airport-reported air cargo volume for UPS of 2.396 billion enplaned pounds and 2.280 billion deplaned pounds yields an average of about 167.8 tons of air cargo volume per employee. There are shortcomings to this approach given UPS’ atypical operations. However, other freight-handling companies operating in this area need to do so in a way which effectively competes with UPS, supporting the application of UPS’ business model to ratios of other freight-handling companies. Applying that UPS average to the volume of air cargo reported by other air freight carriers to the airport suggests air cargo related employment in the Louisville region of 243 employees with other air freight employers (Table 22). Table 22. Estimated Employment by Industry Group, SDF, 2010 Industry Estimated Employment Airlines 40 Freight forwarders 45 Other express package companies 243 UPS 20,288 Total 20,616 Source: Employer surveys, Louisville Regional Airport Authority. These 20,616 direct jobs have an estimated aggregated labor income of $1.6 billion, and estimated output value of nearly $4.6 billion. In addition to these direct impacts, they would have an additional indirect impact of an estimate 9,200 indirect with nearly $413 million in labor in come and over $1 billion in output, and an additional 16,200 induced jobs with nearly $624 million in labor in come and over $1.8 billion in output, as shown in Table 23. Table 23. Estimated Economic Impact, Air Cargo Operations, SDF Impact Type Employment Labor Income Value Added Output Direct Effect 20,616.0 $1,628,987,781 $3,003,199,929 $4,582,713,114 Indirect Effect 9,241.3 $412,823,692 $630,001,968 $1,035,052,465 Induced Effect 16,227.4 $623,604,815 $1,114,000,105 $1,853,075,695 Total Effect 46,084.7 $2,665,416,288 $4,747,202,002 $7,470,841,275 Source: MIG 2011a. 1-57

Air Cargo Impacts to Regional Economy More difficult to quantify is the contribution of air cargo to the regional economy. However, it is generally agreed that industries are concentrated within regions with direct access to air cargo operations. In the absence of this access, companies that rely on these services would likely re-locate to other regions with such access. As noted earlier, the analysis of economic impacts of air cargo shipments is part of a developing area of economic research that is still limited by two key factors: 1) the lack of a complete and workable theory of the role of air cargo in economic development; and 2) the lack of data describing the quantity and value of exported goods at any level of specificity. In the first category, one important issue that remains unanswered is the potential for shippers to utilize other airports in the region to export goods in the presence of air cargo supply constraints. For example, there are other airports within the trade area of SDF. This factor is important for modeling SDF’s contribution to the regional economy. It would be unreasonable, for example, to simply subtract the entire value of goods exported by air, because this subtraction would grossly overstate the economic impacts of air cargo (i.e., the value of the goods shipped by air). In the second category are severe air cargo data limitations. There are few systematic sources of air cargo data. One is the US Department of Commerce import and export trade statistics and a second is the CFS undertaken every five years by a partnership between the BTS and the Census Bureau. Data are available for 89 NTARs. The challenge is that these NTARs are generally larger in geographic area than the metropolitan regions being analyzed. (There are only 89 NTARs in the United States, compared to 422 MSAs. As such, the NTARs are generally much larger than the metropolitan areas, making the cargo volumes for NTARs generally higher than those for the metropolitan areas.) According to the CFS, over 52 million tons of goods were shipped from the Kentucky part of the Louisville/Jefferson County-Elizabethtown-Scottsburg Metropolitan area. Of that, 11,000 tons were shipped via air (including truck and air).4 The largest proportion of goods shipped by air is machinery by both weight and value terms, comprising 40 percent of the value of goods shipped by air and over 36 percent of the weight of goods shipped by air in 2007. Other major commodities shipped via air include electronics, printed products, pharmaceutical products, miscellaneous manufactured products, and articles of base metal. Unfortunately, the data for many of the commodities are suppressed for confidentiality, as shown in Table 24. 4 The modes tracked by the Commodity Flow Survey are: For-hire truck, Private truck, Rail, Air, Shallow draft vessel, Deep draft vessel, Pipeline, Parcel/U.S. Postal Service/courier, Other, and Unknown. 1-58

Table 24. Shipment Characteristics by Two-Digit Commodity and Mode of Transportation for Metropolitan Area of Origin: 2007 Louisville/Jefferson County-Elizabethtown-Scottsburg, KY-IN (KY part) Value Tons SCTG (2) Code Commodity Description 2007 (million $) 2007 (thousands) 07 Other prepared foodstuffs and fats and oils S S 08 Alcoholic beverages S S 20 Basic chemicals S S 21 Pharmaceutical products 3 - 23 Chemical products and preparations, nec S S 24 Plastics and rubber S S 28 Paper or paperboard articles S S 29 Printed products 2 1 30 Textiles, leather, and articles of textiles or leather S S 31 Nonmetallic mineral products - - 32 Base metal in prim. or semifin. forms & in finished basic shapes S S 33 Articles of base metal 4 - 34 Machinery 176 4 35 Electronic & other electrical equip & components & office equip 45 S 36 Motorized and other vehicles (including parts) S S 38 Precision instruments and apparatus S S 40 Miscellaneous manufactured products 4 S 43 Mixed freight S S 00 All Commodities (5) 440 11 S = Estimate does not meet publication standards because of high sampling variability or poor response quality. - = Zero or Less than half the unit shown; thus, it has been rounded to zero. Notes: (1) Commodity Flow Survey (CFS) geographic areas were drawn from a subset of Combined Statistical Areas (CSAs) and Metropolitan Statistical Areas (MeSAs) as defined by the Office of Management and Budget (OMB). However, CFS metropolitan areas are divided into their state parts when they include more than one state. In addition, the CFS also utilizes a unique geography referred to as, “remainder of state,” to represent those areas of a state not contained within a separately published metropolitan area for the CFS (as opposed to not part of any Core-Based Statistical Area (CBSA) as defined by OMB). Because of the differences in the CFS geography, as compared to OMB defined geography, caution should be exercised when comparing CFS estimates to other estimates of similar geography. (2) Standard Classification of Transported Goods. (6) "Truck" as a single mode includes any shipment that was made by private truck only, by for-hire truck only, or by a combination of private and for-hire truck. Source: BTS 2009. 1-59

Given the lack of data, one approach is to utilize the linkage or interdependence between businesses, industries and clusters. One tool common with cluster analysis is to study the Location Quotient (LQ)5, which measures industry concentration in a regional economy. It does so by comparing the ratio of employment in a certain sector of a local economy to the same ratio in a comparison economy, identifying specializations in the local economy. An LQ value of 1.0 indicates that employment in an industry in the regional economy is in exactly the same proportion as the national average, an LQ value greater than 1.0 indicates that employment in the industry has a higher concentration that of the reference economy, and—similarly—an LQ value lower than 1.0 indicates a lower employment concentration in the industry than that of the reference economy. This analysis uses the BLS’ Location Quotient Calculator of the 2010 Quarterly Census of Employment and Wages (QCEW) data (Bureau of Labor Statistics 2011). It uses the Louisville MSA as the analysis area and the U.S. total as the reference area. Concentrations or specialties in the regional economy emerge at the two-digit NAICS level, as shown in Table 25. 5 Location Quotient: Ratio of analysis-industry employment in the analysis area to base-industry employment in the analysis area divided by the ratio of analysis-industry employment in the base area to base-industry employment in the base area. 1-60

Table 25. Location Quotients Calculated from Quarterly Census of Employment and Wages Data, 2010 Industry Louisville, KY-IN MSA Base Industry: Total, all industries 1 NAICS 11 Agriculture, forestry, fishing and hunting 0.14 NAICS 21 Mining, quarrying, and oil and gas extraction ND NAICS 22 Utilities 0.68 NAICS 23 Construction 0.99 NAICS 31-33 Manufacturing ND NAICS 42 Wholesale trade 1.02 NAICS 44-45 Retail trade 0.91 NAICS 48-49 Transportation and warehousing 2.06 NAICS 51 Information 0.74 NAICS 61 Educational services ND NAICS 62 Health care and social assistance 0.98 NAICS 71 Arts, entertainment, and recreation 0.95 NAICS 52 Finance and insurance 1.31 NAICS 53 Real estate and rental and leasing 0.79 NAICS 54 Professional and technical services 0.79 NAICS 55 Management of companies and enterprises ND NAICS 56 Administrative and waste services ND NAICS 72 Accommodation and food services 0.98 NAICS 81 Other services, except public administration ND NAICS 99 Unclassified 0.1 Footnotes: (ND) Not Disclosable Source: BLS 2011. Compared to the U.S. average, the Louisville region has relatively lower concentrations of most industry groupings (or LQs) for most industry groups, with exceptions in Wholesale Trade, and Transportation and Warehousing, most likely due to the role of UPS’ regional operations and related industries. The relatively high LQ in the Finance and Insurance industry group is likely due to the presence of key Bank of America and Citicorp operations in the Louisville region. Though some of the data are suppressed for confidentiality reasons, we can explore the employment concentrations at the three-digit level for some codes, including NAICS codes 481 through 493, as shown in Table 26. 1-61

Table 26. Location Quotients Calculated from Quarterly Census of Employment and Wages Data, 2010 NAICS Codes 481 through 493 Only Industry Louisville, KY-IN MSA Base Industry: Total, all industries 1 NAICS 481 Air transportation 0.25 NAICS 482 Rail transportation ND NAICS 483 Water transportation ND NAICS 484 Truck transportation 1.47 NAICS 485 Transit and ground passenger transportation 0.46 NAICS 486 Pipeline transportation ND NAICS 487 Scenic and sightseeing transportation ND NAICS 488 Support activities for transportation 0.9 NAICS 491 Postal service 1.08 NAICS 492 Couriers and messengers 7.29 NAICS 493 Warehousing and storage 2.25 (ND) Not Disclosable Source: BLS 2011. At the three-digit level, it is evident that the higher LQs in the transportation and warehousing are related to the very high LQ of NAICS code 492 (couriers and messengers)— most likely attributable to the presence of UPS. At 7.29, the courier and messenger industry is over seven times as concentrated in the Louisville region than in the U.S. national average overall. Warehousing and storage is also very concentrated—more than twice as concentrated as the U.S. national average, likely made possible by the concentration of courier and messenger services. It is interesting to note that these concentrations are present in spite of the fact that truck transportation is just slightly higher than the national average and air transportation actually has a very low LQ—one-quarter the concentration of the U.S. national average. One way to approach the LQ to estimate the impact of air cargo in the region is to quantify the economic impact of the air cargo on the regional economy is model the portion of the high LQ industries. For example, with the truck transportation LQ at 1.47 and warehousing and storage at 2.25, it is likely that 32 percent of truck transportation (the “extra 0.47”) and 55.6 percent of warehousing and storage (the “extra 1.25”) are due to the presence of UPS’ Worldport operations (Table 27). 1-62

Table 27. Estimation of Economic Activity Attributable to Presence of UPS’ Worldport Operations LQ Percentage over Base Total Industry Employment "Extra" Employment due to presence of UPS’ Worldport NAICS 484 Truck transportation 1.47 32.0% 10,741 3,434 NAICS 493 Warehousing and storage 2.25 55.6% 6,022 3,346 Source: Bureau of Labor Statistics 2011and MIG 2011a. Using total industry employment in each of those industries, we are able to calculate the additional employment in the industry due to the presence of UPS’ Worldport operations and to estimate the economic impacts associated with those activities. As one indicator, the warehousing and storage industry in the Louisville metropolitan region has over 6,000 employees in aggregate. According to the shippers’ survey, many of the shippers in this region fall into this warehousing and storage category, and many of them state explicitly that they chose to locate in this region largely due to the presence of UPS’ Worldport operations. For example, some of the key shippers engaged in this activity include the employers outlined in Table 28. Table 28. Key Shippers Attributable to Presence of UPS’ Worldport Operations Employer Number of Employees Alliance Entertainment LLC 300 Best Buy Co Inc DC #1376 100 Gilt Group 180 GSI Commerce Solutions Inc 325 JOM Pharmaceutical Services Inc 43 Medline Industries Inc 47 Zappos Fulfillment Centers Inc 971 Total 1,966 Source: Kentucky Cabinet for Economic Development 2011. Industries with high LQs built into our estimates (e.g., trucking and warehousing operations) are included because Worldport offers such a strong competitive advantage that it can be argued to be the dominant attractor to those industries. The economic impacts of the companies highlighted in our analysis (and listed in Table 28) were characterized as warehousing operations and are thus included in the trucking/warehousing employment estimates. These 1,966 direct jobs have an estimated aggregated labor income of $86.4 million, and estimated output value of over $180 million. 1-63

Using the increased employment of 6,780 for the truck transportation and warehousing and storage industries from the LQ analysis, the impact of these economic activities includes a total impact of 13,345 jobs, with a total of over $595 million in labor income and total output of over $1.5 billion (Table 29). Table 29. Estimated Economic Impact, Enhanced Truck Transportation and Warehousing and Storage Industries Impact Type Employment Labor Income Value Added Output Direct Effect 6,780.0 $327,398,501 $420,554,676 $806,524,806 Indirect Effect 2,918.2 $127,869,435 $201,068,011 $326,858,325 Induced Effect 3,646.5 $139,986,987 $250,213,553 $416,130,791 Total Effect 13,344.7 $595,254,923 $871,836,241 $1,549,513,922 Source: MIG 2011a. The competitive advantage offered by Worldport could be argued to extend to other industries with a heavy reliance on air cargo (such as machinery or electronics); however, because of a lack of data to link these industries empirically to air cargo, any attempt to include them would be speculative and unsupportable. Thus, the economic activity associated with these industries was not included in our estimates. Cargo Screening and Jet Fuel Elasticity Modeling The effects of the 100-percent cargo screening rule and volatility in jet-fuel prices were analyzed and described in a separate chapter, with price models developed to estimate the elasticity of demand upon price changes from the increased costs of the additional cargo screening and the increase in the price of air cargo due to increases in jet-fuel prices. Cargo Screening Impacts The elasticity analysis noted that the cargo screening includes three effects to be captured in the I-O models applied at the case-study airports: • The reduced demand for air cargo modeled as a contraction in the industries engaged in air cargo operations • Increased output by air transportation support industries engaged in air cargo screening activities • Increased output for air transportation companies due to overhead applied to air cargo screening costs (this third impact serves to counterbalance the first effect) Table 30 presents the air cargo inputs required for the I-O models. The reduction in freight presented in this table represents the percentage reduction in total (cargo-only and cargo transported on-board passenger airplanes) cargo. The impacts vary depending on the price elasticity modeled at each airport and the scale of air cargo transported on-board passenger aircraft. As noted previously in this report, the screening rule does not affect cargo-only aircraft. 1-64

The negative economic effects reduce the economic output of the industry. The cargo screening costs and industry markup attached to those costs reflect the price increase that is passed on to the customer. These values reflect increased revenue/output to the air transportation and supporting industries. Table 30. Air Cargo Screening Inputs for I-O Models Airport Reductions in Freight Cargo Screening Costs Gross Industry Surplus on Cargo Screening Costs TSA Analysis Industry Estimates TSA Analysis Industry Estimate TSA Analysis Industry Estimate IAH -0.6% -0.9% $8,944,118 $12,775,705 $751,501 $1,073,438 JFK -2.7% -3.8% $25,241,205 $36,054,330 $2,120,813 $3,029,352 MCI -0.4% -0.6% $247,949 $354,169 $20,833 $29,758 RNO* -0.1% -0.1% $71,619 $102,300 $6,018 $8,595 SDF 0.0% 0.0% $101,236 $144,605 $8,506 $12,150 For Louisville, the reductions in freight and counterbalancing increases in cargo screening impacts results in the direct impacts presented in Table 31. Table 31. Air Cargo Screening Inputs for SDF I-O Modeling Grand Total Changes Lower Estimate Upper Estimate Transport by air ($51,508.67) ($77,872.01) Support activities/ air transport $77,377.38 $108,817.06 Couriers/messengers ($27,412,405.25) ($41,118,607.87) Off-Airport (WorldPort “extra") ($4,839,148.84) ($7,258,723.25) Total Changes ($32,225,685.38) ($48,346,386.07) Due to the size of the Courier/Messenger industry, losses are concentrated in that sector, though they also occur in transport by air and the off-airport traded sectors, in this case study illustrated by the additional truck transportation and warehousing deemed attributable to the presence of UPS’ Worldport facility. Some offsetting gains occur in the support activities for air transportation for the additional screening services required. According to the IMPLAN model, these direct impacts of between $32.2 million and 48.3 million would result in between $53.6 million and $80.4 million in total impact, as shown in Table 32, below. 1-65

Table 32. Economic Impact Associated with Cargo Screening Impact Type Employment Labor Income Value Added Output Lower Estimate Direct Effect -157.2 ($11,475,207) ($20,125,328) ($32,225,686) Indirect Effect -70.1 ($3,179,270) ($4,886,944) ($8,072,442) Induced Effect -114.3 ($4,481,191) ($8,005,972) ($13,313,055) Total Effect -341.5 ($19,135,668) ($33,018,244) ($53,611,183) Upper Estimate Direct Effect -235.8 ($17,217,366) ($30,192,855) ($48,346,388) Indirect Effect -105.1 ($4,769,869) ($7,331,823) ($12,110,970) Induced Effect -171.5 ($6,723,483) ($12,011,991) ($19,974,624) Total Effect -512.5 ($28,710,718) ($49,536,669) ($80,431,982) Impacts of Jet Fuel Price Fluctuations The second elasticity model developed for this study examines the impacts of jet-fuel price increases on air cargo demand. It examined the impacts associated with 10 to 30 percent increases in jet-fuel prices, using a stepwise regression approach. Table 33 presents the impacts of a 10, 20, and 30 percent increase in jet fuel prices on demand for air cargo at each of the five case study airports. For every 10 percent increase in jet- fuel prices, air cargo demand is estimated to decline by 0.7 percent. Table 33. Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) on Demand for Air Cargo Impacts of Jet Fuel Prices Increases on Demand for Air Cargo Airport 10% 20% 30% IAH (6,368,857) (12,737,715) (19,106,572) JFK (21,150,552) (42,301,105) (63,451,657) MCI (1,354,130) (2,708,260) (4,062,390) RNO (781,291) (1,562,582) (2,343,873) SDF (33,956,926) (67,913,853) (101,870,779) Reduction in Air Cargo -0.7% -1.5% -2.2% Applying these values to the on-airport operations yields the following results for the 10, 20, and 30-percent increases in jet-fuel prices. As shown in Table 34, the reduction in output ranges from $52.3 million to $156.9 million for 10 percent and 30 percent increases in jet fuel prices, respectively. 1-66

Table 34. Economic Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) Impact Type Employment Labor Income Value Added Output 10% increase in fuel price .7% decrease in cargo volume Direct Effect -144.3 -$11,402,914 -$21,022,400 -$32,078,992 Indirect Effect -64.7 -$2,889,766 -$4,410,014 -$7,245,367 Induced Effect -113.6 -$4,365,234 -$7,798,001 -$12,971,530 Total Effect -322.6 -$18,657,914 -$33,230,414 -$52,295,889 20% increase in fuel price 1.5% decrease in cargo volume Direct Effect -309.2 -$24,434,817 -$45,047,999 -$68,740,697 Indirect Effect -138.6 -$6,192,355 -$9,450,030 -$15,525,787 Induced Effect -243.4 -$9,354,072 -$16,710,002 -$27,796,135 Total Effect -691.3 -$39,981,244 -$71,208,030 -$112,062,619 20% increase in fuel price 1.5% decrease in cargo volume Direct Effect -432.9 -$34,208,743 -$63,067,199 -$96,236,975 Indirect Effect -194.1 -$8,669,298 -$13,230,041 -$21,736,102 Induced Effect -340.8 -$13,095,701 -$23,394,002 -$38,914,590 Total Effect -967.8 -$55,973,742 -$99,691,242 -$156,887,667 Applying the same reductions to the off-airport traded sector results in additional reductions in output ranging from $10.8 million to $32.5 million for 10 percent and 30 percent increases in jet fuel prices, respectively. 1-67

Table 35. Output impacts of Jet Fuel Price Increases (10, 20, and 30 percent) Impact Type Employment Labor Income Value Added Output 10% increase in fuel price 0.7% decrease in cargo volume Direct Effect -47.5 -$2,291,790 -$2,943,883 -$5,645,674 Indirect Effect -20.4 -$895,086 -$1,407,476 -$2,288,008 Induced Effect -25.5 -$979,909 -$1,751,495 -$2,912,916 Total Effect -93.4 -$4,166,784 -$6,102,854 -$10,846,597 20% increase in fuel price 1.5% decrease in cargo volume Direct Effect -101.7 -$4,910,978 -$6,308,320 -$12,097,872 Indirect Effect -43.8 -$1,918,042 -$3,016,020 -$4,902,875 Induced Effect -54.7 -$2,099,805 -$3,753,203 -$6,241,962 Total Effect -200.2 -$8,928,824 -$13,077,544 -$23,242,709 30% increase in fuel price 2.1% decrease in cargo volume Direct Effect -142.4 -$6,875,369 -$8,831,648 -$16,937,021 Indirect Effect -61.3 -$2,685,258 -$4,222,428 -$6,864,025 Induced Effect -76.6 -$2,939,727 -$5,254,485 -$8,738,747 Total Effect -280.2 -$12,500,353 -$18,308,561 -$32,539,792 The sheer volume of the courier and messenger activity at SDF yields far greater impacts on that than other off-airport operations when applying a similar percentage decline. Case Study 3 – George Bush Intercontinental Airport, Houston, TX George Bush Intercontinental Airport (IAH), Houston’s largest airport is located just 23 miles north of downtown Houston. Officially opening in the summer of 1969, the Airport is owned and operated by the Houston Airport System which is a self-supporting system generating revenue through user fees and lease agreements. The Airport is the 7th busiest U.S. airport for both total traffic and international passenger traffic and utilizes 5 runways on 11,000 acres of land. The Airport currently offers nonstop service to over 110 destination in the U.S. and 70 destinations worldwide. IAH ranks in the top 25 airports worldwide for total passengers. In 2010 the airport’s five terminals handled 40.5 million passengers, which represented a small 1.2 percent increase from 2009. Similar to most other airports, IAH saw a decrease in the number of total aircraft movements – down 1.3 percent from the previous year (Houston Airport System 2012). As the 16th largest U.S. air cargo hub, IAH is an ideal consolidation and distribution point. It currently hosts 880,000 square feet of cargo area with a capacity to handle up to 1,450,000 tons of cargo which includes the newly expanded IAH CargoCenter. The annual amount of cargo handled in 2010 also increased by 13.6 percent. International cargo increased by approximately 20 percent with most of the volume carried in 1-68

wide-body passenger aircraft. At the same time, domestic cargo increased by 11.5 (Houston Airport System 2012). The industry trend to minimize freighter use was reflected in a one percent decrease in all-cargo movements. Overall, IAH was ranked 7th in the top ten airports in North America by the ACI World Airport Traffic Report in 2010. IAH has an aggressive marketing program strongly emphasizing Transpacific and Latin American traffic. This section describes the structure of the Houston regional economy in 2009, and the method for estimating the economic impact of air cargo through IAH airport. These estimates are presented at the scale of the ten-county region, comprised of Austin, Brazoria, Chambers, Fort Bend, Galveston, Harris, Liberty, Montgomery, San Jacinto, and Waller counties. Airports play an essential role in supporting the growth of a metropolitan economy like the Houston region. They directly employ hundreds of workers and provide millions of dollars in direct economy activity and taxes and other revenues to local government. They also support the growth of the regional economy by moving people, goods, and services that originate in, or are transported through, the region. Airports and related aviation facilities become structurally integrated into a region’s economy and provide it with competitive advantages. Airports enable industries that either depend on, or learn to take advantage of, efficient air transportation to access domestic and international markets. In the Houston region, IAH and the region’s smaller airports play this vital role. The primary objective of this analysis is to estimate the current economic impacts associated with the air cargo movement, estimating the economic output, employment, personal income, of that activity, and to document the analysis so as to make it easily replicable for other airports in other regions. This section describes the structure of the Houston Metropolitan economy in 2009, using a Houston region-specific version of the IMPLAN impact analysis software.6 It then presents the methods used to estimate the air cargo contribution to the economy, and finally presents estimates of economic impact of that air cargo movement. The model is used to measure changes in the regional economy that result from a change in activity relative to a baseline representation of the economy. The sources of the activity being measured vary, but typically involve changes in production or consumption activities, government policies, infrastructure, or changes in costs or technology. For any change in economic activity, the impacts on the economy can be reported on one of three levels: • Direct impacts represent the initial change in final demand for the industry sector(s) in question. For this analysis, we are estimating the economic activity associated with air cargo in Houston. 6 The IMPLAN model is based on an input-output modeling framework, and uses secondary source data and proprietary analytic methods to estimate empirical input-output relationships from a combination of national technological relationships and county-level measures of economic activity. 1-69

• Indirect impacts represent the response as supplying industries increase output to accommodate the initial change in final demand. These indirect beneficiaries spend money for supplies and services, which results in another round of indirect spending, and so on. Indirect impacts are often referred to as “supply-chain” impacts. • Induced impacts are generated by the spending of households who benefit from the additional wages and income they earn through direct and indirect economic activity. The increase in income, in effect, increases the purchasing power of households. Induced impacts are also described as “consumption-driven” effects. This cycle of direct, indirect, and induced spending does not go on forever. It continues until the spending eventually leaks out of the economy as a result of taxes, savings, or purchases of non-locally produced goods and services or “imports”. Houston Regional Economy This section summarizes the Houston economy, and presents an economic portrait of the region’s economy in terms of employment and output by industry for the base year of 2009. According to the BEA, Houston is one of 366 MSAs in the United States. Based on its 2009 population estimate of 5,867,489, it is ranked 6th in size in the United States. Its per-capita personal income is about 17 percent higher than the national average. According to IMPLAN, there are an estimated 3.5 million jobs across 410 industries in the region. The top industries by employment are presented in Table 36. Houston’s top industries ranked by output are presented in Table 37. Table 36. Top Ten Industries, Ranked by Employment Houston Region, 2009 Code Description Employment Labor Income Output 438 State & local govt, education 206,200 $12,000,810,000 $13,633,090,000 413 Food services and drinking places 204,124 $4,454,105,000 $12,042,710,000 319 Wholesale trade businesses 155,329 $13,753,630,000 $35,985,460,000 360 Real estate establishments 144,085 $2,651,987,000 $26,323,530,000 20 Extraction of oil and natural gas 111,311 $20,697,070,000 $78,225,240,000 36 Construction of other new nonresidential structures 105,933 $5,846,335,000 $13,298,820,000 369 Architectural, engineering, and related services 105,312 $9,217,233,000 $15,180,520,000 382 Employment services 98,694 $3,023,581,000 $4,415,131,000 437 State & local govt, non-education 98,470 $5,406,622,000 $6,142,000,000 394 Offices of physicians, dentists, and other health practitioners 73,271 $6,001,712,000 $9,886,075,000 Source: MIG 2011b. 1-70

Table 37. Top Ten Industries, Ranked by Output Houston Region, 2009 Code Description Employment Labor Income Output 115 Petroleum refineries 12,319 $5,855,176,000 $131,604,200,000 20 Extraction of oil and natural gas 111,311 $20,697,070,000 $78,225,240,000 120 Petrochemical manufacturing 12,394 $1,932,184,000 $69,195,790,000 319 Wholesale trade businesses 155,329 $13,753,630,000 $35,985,460,000 361 Imputed rental activity for owner-occupied dwellings 0 $0 $26,463,550,000 360 Real estate establishments 144,085 $2,651,987,000 $26,323,530,000 28 Drilling oil and gas wells 16,519 $2,320,788,000 $21,301,580,000 31 Electric power generation, transmission, and distribution 14,795 $3,296,287,000 $16,581,100,000 206 Mining and oil and gas field machinery manufacturing 28,454 $3,101,443,000 $15,422,700,000 369 Architectural, engineering, and related services 105,312 $9,217,233,000 $15,180,520,000 Source: MIG 2011b. The scale of economic activity occurring in the Houston region would not have been possible without development of the water, rail, highway, and airport infrastructure that enables businesses to take maximum advantage of the region’s location in the central US. The regional economic impacts of air cargo through IAH are directly related to the scale and composition of the air cargo forecasts (i.e., international versus domestic, and belly cargo versus all-cargo freighters). Estimating IAH Air Cargo Contribution to the Regional Economy This section summarizes the methods used to estimate IAH’s current contribution to the regional economy. This effort quantifies the impact the air cargo through the airport has on the economy at a particular moment in time, using input-output modeling and analysis recommended by the FAA (Butler and Kiernan 1992). Measuring the economic impact of the cargo activity at the airport involves tracing the linkages between the airport’s cargo activity level, expressed in terms of airport operations and air cargo volumes, and the sectors of the economy that interact with them. These linkages produce the “direct,” or initial round of economic impact. Direct impacts, in turn, stimulate “indirect” impacts, from the supply of goods and services to businesses at the airport or production of goods for shipment by air. A third round of economic impacts, called “induced” impacts, results from the spending of income earned by direct and indirect employees. The sum of indirect and induced impacts is often referred to as the “multiplier effect” on direct impacts. Total economic impact is the sum of the direct, indirect, and induced impacts. As noted in the introduction, the first and perhaps most obvious source of IAH-related economic impact is the employees who work there. Though many are present to support the air passengers (such as passenger and visitor service providers), many are associated with airport 1-71

operations and air cargo, including cargo-handling companies, customs agents, TSA, customs brokers, container freight stations, freight forwarders, trucking companies, and other cargo- related services. A second important impact related to airport economic activity is the passenger impact, including expenditures for lodging, food, retail purchases, entertainment, transportation services and parking, among others. Again, the scope of this effort is focused on air cargo, rather than on passengers. The final category of impact is the contribution of air cargo to the regional economy. The presence of a well-functioning air cargo system is what allows a region to export goods and services and develop traded-sector industries for the purposes of export. While every region has some need for local-serving goods and services (haircuts, restaurant meals, etc.), a region’s ability to export additional goods and services increases its economic potential. While the concept is simple, the analysis of economic impacts of air cargo shipments is part of a developing area of economic research that is still limited. We will explore these limitations and some analytic approaches to them in this section. Airport Operations As noted earlier, the first and most obvious source of IAH-related economic impact is the employees who work there. Those associated with air cargo include airlines handling cargo, third-party cargo-handling companies, customs agents, TSA, customs brokers, container freight stations, freight forwarders, trucking companies, and other cargo-related services. Employment data were provided by the airport authority for the number of employees with security badges. These data were supplemented by the project surveys of air carriers and third-party cargo-handling companies. These combined data yielded the cargo-related employment estimates presented in the remainder of this section. Table 38. Estimated Employment by Industry Group, IAH, 2010 Industry Estimated Employment Transport by Air 726 Support Activities for Air Transportation 439 Couriers and messengers 686 Total 1,851 Source: IAH Airport, Employer surveys, and estimates by TransSolutions (IAH study 2010). Running the resulting number of direct jobs through the IMPLAN model generates the direct, indirect, and induced jobs, output, labor income, and value added of this activity (movement of air cargo). These 1,851 direct jobs have an estimated aggregated labor income of over $116 million, or an average per-job compensation of $62,850. The estimated output value generated from those jobs is over $338 million, as shown in Table 39. 1-72

Table 39. Estimated Economic Impact, Air Cargo Operations, IAH Impact Type Employment Labor Income Value Added Output Direct Effect 1,851.0 $116,340,215 $166,346,325 $338,456,519 Indirect Effect 654.9 $40,051,279 $72,684,391 $148,621,695 Induced Effect 925.0 $42,122,921 $79,801,351 $130,628,887 Total Effect 3,430.9 $198,514,416 $318,832,067 $617,707,100 Source: MIG 2011b. In addition to the direct impacts, these 1,851 jobs would have an additional indirect impact of an estimate nearly 655 indirect jobs with over $40 million in labor income and over $148 million in output, and an additional 925 induced jobs with $42 million in labor income and $130 million in output, as shown in Table 39. Air Cargo Impacts to Regional Economy More difficult to quantify is the contribution of air cargo to the regional economy. However, it is generally agreed that export industries are concentrated in regions with direct and efficient access to air cargo operations. In the absence of this access, companies that rely on these services would likely re-locate to other regions with such access. As noted earlier, the analysis of economic impacts of air cargo shipments is part of a developing area of economic research. One important issue that remains unanswered is the potential for shippers to utilize other airports in the region to export goods in the presence of air cargo supply constraints. For example, there are other airports within the trade area of IAH. This factor is important for modeling IAH’s contribution to the regional economy. It would be unreasonable, for example, to simply subtract the entire value of goods exported by air, because this subtraction would grossly overstate the economic impacts of air cargo (i.e., the value of the goods shipped by air). Another issue is the few systematic sources of air cargo data. ACI-NA collects annual data on-airport operations, passengers and weight of air cargo, principally to evaluate airports and rank them by size. For the value of shipments, however, one of the only sources is the CFS undertaken every five years by a partnership between the BTS and the Census Bureau. FAF integrates data from a variety of sources to create a comprehensive picture of freight movement among states and major metropolitan areas by all modes of transportation. With data from the 2007 CFS and additional sources, FAF version 3 (FAF3) provides estimates for tonnage and value by origin, destination, commodity, and mode for 2007, the most recent year, and forecasts through 2040. According to the FAF, over 791 million tons of goods were shipped from the Houston Metropolitan area. Of that, nearly 250,000 tons were shipped via air (including truck and air).7 The largest proportion of goods shipped by air is machinery by weight, comprising 34 percent of 7 The modes tracked by the Commodity Flow Survey are: For-hire truck, Private truck, Rail, Air (including Truck and Air), Shallow draft vessel, Deep draft vessel, Pipeline, Parcel/U.S. Postal Service/courier, Other, and Unknown. 1-73

the weight of commodities shipped by air. In terms of value, electronics is slightly higher in value terms, nearly 39 percent of the value of goods shipped by air but less than 17 percent of the weight of goods shipped by air in 2007, which makes sense as those commodities are often light, but of relatively high value. Other major commodities shipped via air include plastics/rubber, precision instruments, and articles of base metal, as shown in Table 40. Table 40. Shipment Characteristics by Commodity for Air Transportation (including Truck and Air) for Houston Metropolitan Area of Origin: 2007 Value Weight M$ Percent of Total Value Tons (Thousands) Percent of Total Weight Alcoholic beverages 4.33 0.03% 0.61 0.25% Animal feed 1.31 0.01% 0.11 0.05% Articles-base metal 432.25 2.57% 22.38 8.96% Base metals 74.01 0.44% 6.52 2.61% Basic chemicals 168.13 1.00% 4.43 1.77% Cereal grains 0.21 0.00% 0.04 0.01% Chemical prods. 179.59 1.07% 8.68 3.47% Coal-n.e.c. 2.50 0.01% 1.44 0.58% Electronics 6,490.16 38.65% 42.25 16.91% Fertilizers 0.02 0.00% 0.00 0.00% Furniture 56.13 0.33% 2.03 0.81% Live animals/fish 22.16 0.13% 2.14 0.86% Machinery 5,894.25 35.10% 84.33 33.74% Meat/seafood 1.17 0.01% 0.30 0.12% Metallic ores 8.61 0.05% 0.36 0.14% Milled grain prods. 0.68 0.00% 0.30 0.12% Misc. mfg. prods. 309.02 1.84% 4.98 1.99% Mixed freight 364.16 2.17% 2.48 0.99% Motorized vehicles 100.48 0.60% 5.30 2.12% Newsprint/paper 0.01 0.00% 0.01 0.00% Nonmetal min. prods. 33.01 0.20% 1.40 0.56% Nonmetallic minerals 0.55 0.00% 0.66 0.26% Other ag prods. 18.89 0.11% 1.73 0.69% Other foodstuffs 5.76 0.03% 1.30 0.52% Paper articles 5.59 0.03% 1.00 0.40% Pharmaceuticals 78.86 0.47% 0.56 0.22% Plastics/rubber 193.35 1.15% 33.53 13.42% Precision instruments 1,658.07 9.87% 11.91 4.77% Printed prods. 50.34 0.30% 1.57 0.63% Textiles/leather 160.44 0.96% 6.22 2.49% Tobacco prods. 0.92 0.01% 0.03 0.01% Transport equip. 471.92 2.81% 1.04 0.42% Wood prods. 3.92 0.02% 0.27 0.11% Total 16,790.78 100% 249.92 100% Source: BTS 2009. 1-74

Clearly, the presence of the IAH airport and its well-functioning air cargo operations enables the air transport of this nearly $17 billion in exports. However, a portion of these exports would continue to leave the region in the absence of the IAH airport, using other modes, or through a combination of modes to reach an alternative airport. For an illustration, let us examine the nearly $6.5 billion of electronics exported from the region. The FAF and CFS use Standard Transportation Classification Codes (STCC) whereas IMPLAN uses the IMPLAN industry codes. Unfortunately, international trade in electronics and other commodities not historically carried by railroads is not well-represented in the STCC, and there are several electronics-related manufacturing industries in IMPLAN. To select an appropriate industry, the first thing would be to evaluate total employment and output for a potential industry. For example, in Houston, some of the electronics industries are small, with only a handful of employees, as shown in Table 41. 1-75

Table 41. Employment, Output, and Employee Compensation of Industry Codes 234 through 249 Industry Code Description Employment Output Employee Compensation 234 Electronic computer manufacturing 6,496.00 $8,444,266,496 $929,792,000 235 Computer storage device manufacturing 7.6 $5,813,081 $721,615 236 Computer terminals and other computer peripheral equipment manufacturing 358 $161,496,688 $31,774,904 237 Telephone apparatus manufacturing 69.1 $35,220,008 $5,740,229 238 Broadcast and wireless communications equipment manufacturing 79.4 $41,965,576 $6,862,952 239 Other communications equipment manufacturing 167 $56,209,872 $10,589,846 240 Audio and video equipment manufacturing 111.1 $64,382,104 $6,929,096 241 Electron tube manufacturing 0 $0 $0 242 Bare printed circuit board manufacturing 501.5 $102,211,008 $30,264,414 243 Semiconductor and related device manufacturing 1,087.40 $745,661,568 $158,196,944 244 Electronic capacitor, resistor, coil, transformer, and other inductor manufacturing 306 $53,095,824 $16,604,259 245 Electronic connector manufacturing 81.9 $17,726,202 $3,631,496 246 Printed circuit assembly (electronic assembly) manufacturing 622.6 $227,634,032 $52,766,300 247 Other electronic component manufacturing 1,158.70 $267,425,664 $99,531,240 248 Electromedical and electrotherapeutic apparatus manufacturing 745.7 $345,771,392 $64,623,396 249 Search, detection, and navigation instruments manufacturing 346.1 $123,891,152 $23,133,980 Source: MIG 2011b. The largest is the electronic computer manufacturing industry, with 6,496 employees and $8.4 billion in output. It is likely that the $6.5 billion of exported electronics are commodities produced by a combination of industries, including electronic computer manufacturing. To select the industries for the modeling and to avoid over- or under-stating the impacts, the analyst would want to review the levels of output per worker and compensation-per-worker for the range of industries, as shown in Table 42. 1-76

Table 42. Per-worker Output and Employee Compensation of Industry Codes 234 through 249 Industry Code Description Employment Output per Worker Compensation- per-Worker 234 Electronic computer manufacturing 6,496.00 $1,299,917.87 $143,133.00 235 Computer storage device manufacturing 7.6 $764,879.08 $94,949.34 236 Computer terminals and other computer peripheral equipment manufacturing 358 $451,108.07 $88,756.72 237 Telephone apparatus manufacturing 69.1 $509,696.21 $83,071.33 238 Broadcast and wireless communications equipment manufacturing 79.4 $528,533.70 $86,435.16 239 Other communications equipment manufacturing 167 $336,586.06 $63,412.25 240 Audio and video equipment manufacturing 111.1 $579,496.89 $62,368.10 241 Electron tube manufacturing 0 NA NA 242 Bare printed circuit board manufacturing 501.5 $203,810.58 $60,347.78 243 Semiconductor and related device manufacturing 1,087.40 $685,728.87 $145,481.83 244 Electronic capacitor, resistor, coil, transformer, and other inductor manufacturing 306 $173,515.76 $54,262.28 245 Electronic connector manufacturing 81.9 $216,437.14 $44,340.61 246 Printed circuit assembly (electronic assembly) manufacturing 622.6 $365,618.43 $84,751.53 247 Other electronic component manufacturing 1,158.70 $230,798.02 $85,899.06 248 Electromedical and electrotherapeutic apparatus manufacturing 745.7 $463,686.99 $86,661.39 249 Search, detection, and navigation instruments manufacturing 346.1 $357,963.46 $66,841.90 Source: MIG 2011b. For the most part, the electronics-related industries have similar levels of output-per- worker and employee compensation-per-worker; however, levels for the electronic computer manufacturing industry are among the highest (at nearly $1.3 million average per-worker output and over $143,000 in average per-worker compensation). As such, to avoid overstating the impacts, it is reasonable to model the impacts using a combination of this largest industry and another representative industry whose output-per-worker and compensation-per-worker fall more in the middle of the range, such as other electronic component manufacturing (Industry Code 247) with per-worker output averaging $230,800 and per-worker compensation averaging $84,750 (Minnesota IMPLAN Group, 2011b.) 1-77

According to the Houston Airport System, there was an aggregated total value of $7.2 billion in exported goods shipped through the Houston airport in 2009. Of that, $3.1 billion was classified as industrial equipment and computers, as shown in Table 43. These values are roughly half those reported from the FAF whose “air” category includes truck and air, and therefore, may include goods shipped from other airports. Table 43. Top Exports by Weight and their Estimated Value, Houston 2009 Rank Top Commodities Air Cargo Exports Weight (KG) Air Cargo Exports Value ($) 1 Industrial Equipment and Computers 44,840,986 3,127,150,859 2 Articles of Iron or Steel 13,297,438 122,924,227 3 Electrical Machinery, Equipment and Parts 11,397,772 1,178,203,472 4 Optic, Photographic, Medical, Surgical Instruments 7,578,404 1,093,271,364 5 Iron and Steel 4,266,317 9,265,833 6 Plastics and Plastic Articles 3,733,719 66,945,591 7 Metal Tools, Cutlery, Etc. 2,350,414 291,425,435 8 Miscellaneous Chemical Products 1,822,211 59,458,838 9 Aircraft, Spacecraft and Parts Thereof 1,371,784 750,409,353 10 Inorganic Chemicals 1,362,419 37,969,218 Totals (includes commodities not shown above) 110,731,668 7,230,003,104 Source: Houston Airport System, Houston and the World, 2012 International Air Cargo Data. To complete the illustration, evaluating the impacts of $3.1 billion in exported electronics might involve modeling the impacts associated with $1.6 billion electronic computer manufacturing and $1.5 billion in electronic component manufacturing as shown in Table 44. Table 44. Economic Impact of $3.1 Billion in Electronic Manufacturing Impact Type Employment Labor Income Value Added Output Direct Effect 10,739.4 $1,123,202,763 $1,785,063,755 $3,100,000,063 Indirect Effect 6,140.0 $437,344,449 $727,238,123 $1,215,059,723 Induced Effect 9,240.2 $421,212,476 $797,820,446 $1,306,313,610 Total Effect 26,119.6 $1,981,759,687 $3,310,122,324 $5,621,373,395 Source: MIG 2011b. The $1.6 billion in electronic computer manufacturing and $1.5 billion in electronic component manufacturing have direct employment of over 10,700 employees, with over $1.1 billion in employee compensation and nearly $1.8 billion in value added, plus an additional 6,140 indirect employees, and another 9,240 induced employees. This $3.1 billion modeled in this example is but a portion of the nearly $17 billion in value of commodities exported from the Houston region, according to the FAF, and the over $7.2 billion in value of commodities exported from the Houston Airport, according to the Houston Airport System. 1-78

Cargo Screening and Jet Fuel Elasticity Modeling The effects of the 100-percent cargo screening rule and volatility in jet-fuel prices were analyzed and described in a separate section of this report, with price models developed to estimate the elasticity of demand upon price changes from the increased costs of the additional cargo screening and the increase in the price of air cargo due to increases in jet-fuel prices. Cargo Screening Impacts The elasticity analysis noted that the cargo screening includes three effects to be captured in the I-O models applied at the case-study airports: • The reduced demand for air cargo modeled as a contraction in the industries engaged in air cargo operations • Increased output by air transportation engaged in air cargo screening activities • Increased output for air transportation companies due to overhead applied to air cargo screening costs (this third impact serves to counterbalance the first effect) Table 45 presents the air cargo inputs required for the I-O models. The reduction in freight presented in this table represents the percentage reduction in total (cargo-only and cargo transported on-board passenger airplanes) cargo. The impacts vary depending on the price elasticity modeled at each airport and the scale of air cargo transported on-board passenger aircraft. As noted previously in this report, the screening rule does not affect cargo-only aircraft. The negative economic effects reduce the economic output of the industry. The cargo screening costs and industry markup attached to those costs reflect the price increase that is passed on to the customer. These values reflect increased revenue/output to the air transportation and supporting industries. Table 45. Air Cargo Screening Inputs for I-O Models Airport Reductions in Freight Cargo Screening Costs Gross Industry Surplus on Cargo Screening Costs TSA Analysis Industry Estimates TSA Analysis Industry Estimate TSA Analysis Industry Estimate IAH -0.6% -0.9% $8,944,118 $12,775,705 $751,501 $1,073,438 JFK -2.7% -3.8% $25,241,205 $36,054,330 $2,120,813 $3,029,352 MCI -0.4% -0.6% $247,949 $354,169 $20,833 $29,758 RNO* -0.1% -0.1% $71,619 $102,300 $6,018 $8,595 SDF 0.0% 0.0% $101,236 $144,605 $8,506 $12,150 1-79

For Houston, the reductions in freight and counterbalancing increases in cargo screening impacts results in the direct impacts identified in Table 46. Though there are losses in the Transport by Air and Courier/Messenger industries, losses are concentrated in the off-airport traded sectors, in this case study illustrated by the electronics industry. Some offsetting gains occur in the support activities for air transportation for the additional screening services required. For air transport support activities, the increase in output associated with screening activities more than offsets the losses resulting from reductions in freight due to the inelastic demand measure (0.23) calculated for IAH. Table 46. Air Cargo Screening Inputs for IAH I-O Modeling Grand Total Changes Lower Estimate Upper Estimate Transport by air ($696,799.06) ($1,099,012.10) Support activities/ air transport $8,617,331.34 $12,285,525.00 Couriers/messengers ($255,652.37) ($383,478.55) Off-Airport example (electronics) ($18,600,000.00) ($27,900,000.00) Total Changes ($10,935,120.10) ($17,096,965.64) According to the IMPLAN model, these direct impacts of between nearly $11 and $17 million would result in between $19 and $30 million in total impact. As noted earlier, the losses occur mostly in the traded-sector industries, illustrated in this case study by the electronics industry. These industries tend to have high wages and high output per worker, while gains occur in support activities for air transportation, an industry with relatively lower output per worker. As such, employment impacts seem low relative to the output impacts, as shown in Table 47 below. Table 47. Economic Impact Associated with Cargo Screening Impact Type Employment Labor Income Value Added Output Lower Estimate Direct Effect -1.2 ($1,416,321) ($5,248,857) ($10,935,010) Indirect Effect -20.0 ($1,840,594) ($3,228,926) ($5,451,864) Induced Effect -19.4 ($888,585) ($1,681,356) ($2,756,602) Total Effect -40.6 ($4,145,501) ($10,159,139) ($19,143,475) Upper Estimate Direct Effect -7.1 ($2,555,684) ($8,335,944) ($17,096,965) Indirect Effect -31.5 ($2,834,219) ($4,955,888) ($8,373,362) Induced Effect -32.1 ($1,468,339) ($2,778,740) ($4,554,947) Total Effect -70.7 ($6,858,241) ($16,070,571) ($30,025,274) Impacts of Jet Fuel Fluctuations The second elasticity model developed examines the impacts of jet fuel price increases on air cargo demand. It examined the impacts associated with 10-30 percent increases in jet fuel prices, using a stepwise regression approach. 1-80

Table 48 presents the impacts of a 10, 20, and 30 percent increase in jet fuel prices on demand for air cargo at each of the five case study airports. For every 10 percent increase in jet fuel prices, air cargo demand is estimated to decline by 0.7 percent. Table 48. Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) on Demand for Air Cargo Impacts of Jet Fuel Prices Increases on Demand for Air Cargo Airport 10% 20% 30% IAH (6,368,857) (12,737,715) (19,106,572) JFK (21,150,552) (42,301,105) (63,451,657) MCI (1,354,130) (2,708,260) (4,062,390) RNO (781,291) (1,562,582) (2,343,873) SDF (33,956,926) (67,913,853) (101,870,779) Reduction in Air Cargo -0.7% -1.5% -2.2% Applying these values to the on-airport operations yields the results for the 10, 20, and 30-percent increases in jet-fuel prices presented in Table 49. Table 49. Economic Impacts of Jet Fuel Price Inreases (10, 20, and 30 percent) on Airport Operations Impact Type Employment Labor Income Value Added Output 10% increase in fuel price .7% decrease in cargo volume Direct Effect (12.96) ($814,382) ($1,164,424) ($2,369,196) Indirect Effect (4.58) ($280,359) ($508,791) ($1,040,352) Induced Effect (6.48) ($294,860) ($558,609) ($914,402) Total Effect (24.02) ($1,389,601) ($2,231,824) ($4,323,950) 20% increase in fuel price 1.5% decrease in cargo volume Direct Effect (27.77) ($1,745,103) ($2,495,195) ($5,076,848) Indirect Effect (9.82) ($600,769) ($1,090,266) ($2,229,325) Induced Effect (13.88) ($631,844) ($1,197,020) ($1,959,433) Total Effect (51.46) ($2,977,716) ($4,782,481) ($9,265,607) 20% increase in fuel price 1.5% decrease in cargo volume Direct Effect (38.87) ($2,443,145) ($3,493,273) ($7,107,587) Indirect Effect (13.75) ($841,077) ($1,526,372) ($3,121,056) Induced Effect (19.43) ($884,581) ($1,675,828) ($2,743,207) Total Effect (72.05) ($4,168,803) ($6,695,473) ($12,971,849) 1-81

Applying the same reductions to the off-airport traded sector, results in the economic impacts estimated presented in Table 50. Table 50. Economic Impacts of Jet Fuel Price Increases (10, 20, and 30 percent) on Off-Airport Activities Impact Type Employment Labor Income Value Added Output 10% increase in fuel price 0.7% decrease in cargo volume Direct Effect (75.2) ($7,862,419) ($12,495,446) ($21,700,000) Indirect Effect (43.0) ($3,061,411) ($5,090,667) ($8,505,418) Induced Effect (64.7) ($2,948,487) ($5,584,743) ($9,144,195) Total Effect (182.8) ($13,872,318) ($23,170,856) ($39,349,614) 20% increase in fuel price 1.5% decrease in cargo volume Direct Effect (161.1) ($16,848,041) ($26,775,956) ($46,500,001) Indirect Effect (92.1) ($6,560,167) ($10,908,572) ($18,225,896) Induced Effect (138.6) ($6,318,187) ($11,967,307) ($19,594,704) Total Effect (391.8) ($29,726,395) ($49,651,835) ($84,320,601) 30% increase in fuel price 2.1% decrease in cargo volume Direct Effect (225.5) ($23,587,258) ($37,486,339) ($65,100,001) Indirect Effect (128.9) ($9,184,233) ($15,272,001) ($25,516,254) Induced Effect (194.0) ($8,845,462) ($16,754,229) ($27,432,586) Total Effect (548.5) ($41,616,953) ($69,512,569) ($118,048,841) The sheer volume of the off-airport impacts yields far greater impacts than on-airport operations when applying a similar percentage decline. These results show the importance and far-ranging effects of an efficient air transportation system on a healthy regional economy. Case Study 4 – John F. Kennedy International Airport, New York, NY John F. Kennedy International Airport (JFK), originally known as Idlewild Airport, was established in 1942 and is owned and operated by the Port Authority of New York and New Jersey (PANYNJ). The airport is approximately 15 miles from midtown Manhattan. Today, JFK functions as one of America’s leading international gateway airports, with more than 80 airlines operating from its gates. JFK sits on 4,930 acres of land and currently contains seven operational passenger terminals that contain more than 150 gates. JFK is one of the world’s leading international air cargo centers with more than six million square feet of office and warehouse space spread out over four cargo areas. The entire area comprising the cargo operation at JFK is designated as a Foreign Trade Zone. A total of 1,700 acres dedicated to air cargo activities is divided into Cargo Areas A, B, C, and D. JFK currently has approximately 500 cargo companies based on or around the airport. The carriers are served by ten ground handling services and by hundreds of long and short haul trucking companies. JFK is also home to the northeast region’s U.S. Customs headquarters. 1-82

JFK was ranked 19th in the world for total cargo handling in 2010. Cargo volumes increased by 17.5 percent from 2009 but the total of 1.3 million tons was well below the 2000 peak of 1.9 million. International freight was up by 23 percent in 2010 placing JFK 15th worldwide. Passenger traffic was relatively flat, and aircraft movements at JFK dropped 4.2 percent in 2010 compared to the previous year. However, both domestic and international passenger traffic has grown over the last decade with domestic traffic growing almost 64 percent since 2000. This is due in large part to the growth of JetBlue operations at JFK which has very little cargo capacity (Port Authority New York New Jersey 2012). Currently, transatlantic freight makes up the largest market share for freight at JFK topping out at 45 percent of the market with transpacific freight making up 31 percent of the market. In total, international freight comprises 82 percent of the cargo being processed at JFK while domestic freight represents the remaining 18 percent of the market (Port Authority New York New Jersey 2012). JFK is expected to pursue South and Latin American, African and Eastern European markets over the next 20 years as the European market reaches maturity (Port Authority New York New Jersey 2012). New York-Northern New Jersey-Long Island, NY-NJ-PA MSA (NY Portion) Economic Profile While the overall impact analysis that follows relates to the entire metropolitan area, the market analysis, which focuses on the disposition of exports, necessarily focuses on the New York State portion of the MSA, which hosts JFK International. The assumption is that air freight traffic emanating west of the Hudson River is largely in the market area of Newark Liberty International Airport. The New York state area includes 10 of 23 counties that comprise the entire MSA: the five counties of New York City proper (Bronx, Kings, New York, Queens, and Richmond), the two counties that comprise the western portion of Long Island (Nassau and Suffolk), and three suburban counties on “mainland” New York (Putnam, Rockland, and Westchester. The 23-county New York-Northern New Jersey-Long Island, NY-NJ-PA (NYC) MSA is the most populous metropolitan area in the United States with 18,897,109 inhabitants as of 2010.8 That year it also had nation’s largest metropolitan economy with a total GDP of $1.28 trillion dollars.9 It may come as no surprise then that the composition of the regional economy is more diversified and complex than most other regional economies in the U.S. Major Industries in the New York Portion of the NYC MSA As shown in Table 51, the largest sectors of the regional economy (as ranked by payroll- based location quotient) are in the professional service occupations. Number one on the list is the Finance and Insurance sector, with total employment of 360,885 and total annual wages of $84,646,337,886, for an average annual wage per employee of over $230,000. Real estate rental and leasing is next on the list, with total employment of 142,915 earning an aggregate $8,499,094,293 for an average annual salary of approximately $60,000. Commodity-producing 8 Census 2010 9 BEA 2010 1-83

sectors such as Manufacturing and Agricultural and Mining come in the bottom three positions. This suggests that large volumes of goods required of New York area residents and firms are not produced in the region. Likewise, the sector Transportation and Warehousing ranks low, suggesting that local distributing agents do not play a dominating role in supplying the region with goods that the region demands. Instead, agents from outside of the area do so. Table 51. Sector Payroll Location Quotient, Employment, and Payroll for NY MSA (New York Portion), 2010 NAICS Description LQ Jobs Payroll ($1,000) Average Payroll 11 Agriculture, Forestry, Fishing and Hunting 0.11 5,995 $212,852 $35,505 21 Mining, Quarrying, and Oil and Gas Extraction 0.09 3,403 $339,537 $99,776 22 Utilities 0.57 13,612 $1,798,700 $132,141 23 Construction 0.71 192,510 $12,732,695 $66,140 31 Manufacturing 0.41 256,521 $17,814,825 $69,448 42 Wholesale Trade 0.69 208,714 $15,885,152 $76,110 44 Retail 0.67 517,434 $17,115,621 $33,078 48 Transportation and Warehousing 0.59 143,073 $6,778,352 $47,377 51 Information 1.43 181,055 $18,914,665 $104,469 52 Finance and Insurance 2.77 360,885 $84,646,338 $234,552 53 Real Estate and Rental and Leasing 1.54 142,915 $8,499,094 $59,470 54 Professional, Scientific, and Technical Services 1.09 411,584 $41,572,278 $101,006 55 Management of Companies and Enterprises 1.25 87,489 $15,014,586 $171,617 56 Administrative and Support, Waste Management, & Remediation Services 0.78 270,152 $12,607,593 $46,669 61 Educational Services 1.36 191,278 $9,420,094 $49,248 62 Health Care and Social Assistance 0.81 805,756 $38,036,297 $47,206 71 Arts, Entertainment, and Recreation 1.22 97,168 $4,928,580 $50,722 72 Accommodation and Food Services 0.76 361,040 $9,564,573 $26,492 81 Other Services (except Public Administration) 1.01 214,021 $8,489,208 $39,665 99 Unclassified 1.48 19,112 $751,489 $39,320 Total 4,483,717 $325,122,529 $72,512 1-84

At the finer level of three-digit NAICS codes (Table 52), white-collar professions continue to dominate. A notable exception is Apparel Manufacture, which employed a total of 18,259 people earning an aggregate $965,840,676 for an average annual salary of $52,897. Table 52. Top Ten Industries by Three-Digit NAICS Code, 2010 3-Digit NAICS Description LQ Employment Payroll Average Payroll 523 Securities, Commodity Contracts, and Other Financial Investments and Related Activities 5.95 173,765 $61,693,480,861 $355,040 515 Broadcasting (except Internet) 2.89 32,160 $3,920,802,704 $121,916 315 Apparel Manufacturing 2.61 18,259 $965,840,676 $52,897 485 Transit and Ground Passenger Transportation 2.45 47,909 $1,733,842,960 $36,190 512 Motion Picture and Sound Recording Industries 2.42 36,873 $3,541,451,716 $96,045 519 Other Information Services 2.19 19,628 $2,003,248,633 $102,061 712 Museums, Historical Sites, and Similar Institutions 2.17 11,320 $555,762,884 $49,096 525 Funds, Trusts, and Other Financial Vehicles 2.04 7,022 $1,108,889,832 $157,917 531 Real Estate 1.90 128,657 $7,636,604,091 $59,356 533 Lessors of Nonfinancial Intangible Assets (except Copyrighted Works) 1.79 2,274 $250,744,139 $110,266 By drilling down to the finest level of detail, six-digit NAICS, it is evident that the region is a significant exporter of some specific products (Table 53). Average payroll in these sectors are above average for manufacturing, suggesting that the goods produced are likely of high value, and high value-to-weight items are the most likely to be shipped by air. The top 20 list is comprised almost exclusively of apparel items, including women’s dresses, men’s neckware, fur and leather, and apparel for infants. Other manufactured goods include beet sugar, cane sugar, and electronic coils. 1-85

Table 53. Top 20 Manufacturing Sectors in New York Portion of NYC MSA by Six-digit NAICS 6-Digit NAICS Description LQ Employment Payroll Average Payroll 315231 Women's and Girls' Cut and Sew Lingerie, Loungewear, and Nightwear Manufacturing 7.56 595 $45,065,064 $75,740 315233 Women's and Girls' Cut and Sew Dress Manufacturing 7.42 2,598 $207,840,150 $80,000 315234 Women's and Girls' Cut and Sew Suit, Coat, Tailored Jacket, and Skirt Manufacturing 5.75 584 $52,955,634 $90,677 315993 Men's and Boys' Neckwear Manufacturing 5.46 245 $17,725,458 $72,349 339913 Jewelers' Material and Lapidary Work Manufacturing 4.29 739 $25,007,623 $33,840 315239 Women's and Girls' Cut and Sew Other Outerwear Manufacturing 4.22 2,059 $201,246,500 $97,740 339911 Jewelry (except Costume) Manufacturing 3.94 4,360 $246,165,170 $56,460 315292 Fur and Leather Apparel Manufacturing 3.67 231 $10,121,252 $43,815 315291 Infants' Cut and Sew Apparel Manufacturing 3.49 73 $3,677,728 $50,380 312221 Cigarette Manufacturing 3.19 152 $216,354,787 $1,423,387 315991 Hat, Cap, and Millinery Manufacturing 3.08 574 $28,628,882 $49,876 311313 Beet Sugar Manufacturing 3.05 912 $58,492,605 $64,137 316110 Leather and Hide Tanning and Finishing 2.94 628 $32,607,895 $51,923 316211 Rubber and Plastics Footwear Manufacturing 2.73 244 $17,439,782 $71,475 315212 Women's, Girls', and Infants' Cut and Sew Apparel Contractors 2.72 7,006 $188,334,484 $26,882 315232 Women's and Girls' Cut and Sew Blouse and Shirt Manufacturing 2.28 370 $43,644,231 $117,957 334518 Watch, Clock, and Part Manufacturing 2.14 567 $31,090,410 $54,833 315221 Men's and Boys' Cut and Sew Underwear and Nightwear Manufacturing 2.14 73 $3,460,867 $47,409 311312 Cane Sugar Refining 2.09 258 $33,680,445 $130,544 334416 Electronic Coil, Transformer, and Other Inductor Manufacturing 2.03 754 $47,571,197 $63,092 1-86

New York City Area Freight (NY Portion) Freight Movements New York City MSA (NY Portion) Air Exports Results from a direct survey data of air freight carriers provided somewhat fragmentary information. This was undoubtedly due to the lack of official PANYNJ support for the endeavor. Clearly, past work was done on the topic for JFK: the objective of this study, however, was to perform an independent assessment in as uniform a manner across airports as possible. It was therefore clear that the analysis needed to lean on secondary data for air shipments. The best and most complete publicly available data on trade for subregions of U.S. states are widely known to be Version 3 of the Freight Analysis Framework (FAF3) Origin-Destination Data, which are available online from the U.S. Department of Transportation.10 Table 54 shows the total weight and value of goods shipped by air from the New York portion of the NYC MSA. 10 Last accessed in June 2012 at http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/. For details on how the FAF3 data are estimated see Southworth et al. (2010) at http://faf.ornl.gov/fafweb/Data/FAF3ODCMOverview.pdf. 1-87

Table 54. Total Air Exports from NY Portion of NYC MSA, 2007 SCTG Total Out Air Total Tons in 2007 (Thousands) Total M$ in 2007 Air Share (Value) 1 Live animals/fish 11.3 $176 68.8% 2 Cereal grains 0.0 $0 0.0% 3 Other ag prods. 5.1 $47 0.5% 4 Animal feed 1.6 $18 2.5% 5 Meat/seafood 1.0 $8 0.1% 6 Milled grain prods. 0.5 $1 0.0% 7 Other foodstuffs 10.5 $45 0.3% 8 Alcoholic beverages 1.7 $17 0.2% 9 Tobacco prods. 1.0 $6 0.2% 13 Nonmetallic minerals 2.2 $4 1.6% 14 Metallic ores 0.9 $21 58.8% 19 Coal-n.e.c. 1.9 $4 0.1% 20 Basic chemicals 16.0 $822 30.0% 21 Pharmaceuticals 12.5 $2,383 7.9% 23 Chemical prods. 49.5 $1,314 16.2% 24 Plastics/rubber 27.5 $689 6.2% 26 Wood prods. 1.9 $10 0.2% 27 Newsprint/paper 0.7 $1 0.1% 28 Paper articles 13.7 $68 2.5% 29 Printed prods. 19.1 $452 4.4% 30 Textiles/leather 24.8 $890 2.2% 31 Nonmetal min. prods. 9.4 $214 7.1% 32 Base metals 33.5 $323 5.7% 33 Articles-base metal 37.3 $677 5.5% 34 Machinery 79.4 $9,470 20.7% 35 Electronics 51.9 $8,225 26.7% 36 Motorized vehicles 8.5 $252 1.4% 37 Transport equip. 7.0 $3,511 75.2% 38 Precision instruments 31.6 $6,017 34.0% 39 Furniture 2.6 $82 1.4% 40 Misc. mfg. prods. 17.0 $24,364 41.0% 43 Mixed freight 1.9 $199 1.2% Total 483.7 $60,310 14.5% To meaningfully employ the FAF3 data, Quarterly Census of Employment and Wages (QCEW) were matched to Standard Classification of Transported Goods (SCTG) categories used by FAF3 (Appendix A provides a NAICS to SCTG crosswalk). Table 55 resulted. Note that less than 6 percent of all employment and payroll reported in Table 55 for the New York portion of the New York City MSA is in sectors producing those commodities. 1-88

Table 55. Employment and Payroll of Commodity-producing Industries by Commodity, New York State Portion of NYC Metropolitan Area, 2007 SCTG Description LQ Emp. Payroll 1 Live animals/fish 0.21 1,489 $67,459,095 2 Cereal grains 0.01 9 $313,142 3 Other ag prods. 0.09 3,518 $114,126,711 4 Animal feed 0.18 569 $40,136,638 5 Meat/seafood 0.15 3,498 $175,169,538 6 Milled grain prods. 0.22 2,922 $104,804,942 7 Other foodstuffs 0.44 16,088 $904,859,929 8 Alcoholic beverages 0.39 1,386 $99,556,465 9 Tobacco prods. 2.28 156 $216,797,013 10 Building stone 0.40 709 $36,701,908 11 Natural sands 0.12 349 $25,576,641 12 Gravel 0.44 272 $12,390,538 13 Nonmetallic minerals 0.06 49 $4,374,383 14 Metallic ores 1.23 2,543 $270,136,299 15 Coal 0.00 0 $0 16 Crude petroleum 0.01 377 $36,284,079 17 Gasoline 0.00 22 $1,913,800 18 Fuel oils 0.00 0 $0 19 Coal-n.e.c. 0.34 931 $111,528,579 20 Basic chemicals 0.21 1,433 $119,152,224 21 Pharmaceuticals 0.67 15,693 $1,247,241,929 22 Fertilizers 0.05 110 $5,279,624 23 Chemical prods. 0.41 6,012 $466,855,355 24 Plastics/rubber 0.28 9,567 $645,602,769 25 Logs 0.01 55 $2,208,505 26 Wood prods. 0.20 4,482 $205,309,182 27 Newsprint/paper 0.34 3,016 $267,105,167 28 Paper articles 0.43 5,153 $312,156,461 29 Printed prods. 0.47 11,680 $615,971,776 30 Textiles/leather 1.39 26,189 $1,408,427,481 31 Nonmetal min. prods. 0.38 4,541 $324,702,646 32 Base metals 0.39 5,765 $542,462,439 33 Articles-base metal 0.31 21,694 $1,216,749,349 34 Machinery 0.28 13,278 $1,037,817,034 35 Electronics 0.44 25,338 $2,375,145,863 36 Motorized vehicles 0.26 9,550 $719,227,279 37 Transport equip. 0.48 12,881 $1,535,496,275 38 Precision instruments 0.38 17,234 $1,396,006,181 39 Furniture 0.48 8,221 $386,109,983 40 Misc. mfg. prods. 0.81 14,610 $804,782,303 41 Waste/scrap 0.00 0 $0 43 Mixed freight 0.25 147 $6,510,656 Total 251,536 $17,862,450,181 Table 56 reveals most of the industries have payroll location quotients substantially lower than 1.0, the threshold typically used to identify industries that export. As with RNO, the list of exported commodities does not appear to be closely connected to production of the local economy, suggesting again many goods exiting JFK have their origins outside the study region. 1-89

Table 56 shows payroll of the production sectors that we have identified as producing goods for export via air freight. As described above, these are aggregate QCEW sectors related to the commodities shipped that have a location quotient greater than 0.3. The “air base payroll” is calculated by taking the portion of the total sector payroll beyond the 0.3 threshold and then the percentage of that commodity that is shipped by air. A threshold of 0.3 has been identified by Stevens, Treyz, and Lahr (1989) as the norm for interstate shipment of commodities. Table 56. Portion of Commodity-producing Industries Directly Related to Air Freight, New York Portion of NYC MSA SCTG Description M$07 Air Air Share $$ LQ Air Base Payroll 7 Other foodstuffs $44.8 0.3% 0.44 $1,040,526 8 Alcoholic beverages $17.3 0.2% 0.39 $74,492 9 Tobacco prods. $6.2 0.2% 2.28 $310,873 14 Metallic ores $21.5 59% 1.23 $127,847,192 19 Coal-n.e.c. $4.2 0.1% 0.34 $31,426 21 Pharmaceuticals $2,382.6 7.9% 0.67 $59,613,934 23 Chemical prods. $1,314.0 16.2% 0.41 $40,355,620 27 Newsprint/paper $0.7 0.1% 0.34 $87,850 28 Paper articles $67.8 2.5% 0.43 $2,049,620 29 Printed prods. $452.2 4.4% 0.47 $11,048,581 30 Textiles/leather $889.6 2.2% 1.39 $24,547,022 31 Nonmetal min. prods. $214.2 7.1% 0.38 $8,583,580 32 Base metals $323.5 5.7% 0.39 $14,115,803 33 Articles-base metal $676.7 5.5% 0.31 $12,371,578 35 Electronics $8,224.6 26.7% 0.44 $259,300,819 37 Transport equip. $3,511.0 75.2% 0.48 $647,811,775 38 Precision instruments $6,016.6 34.0% 0.38 $173,109,521 39 Furniture $82.4 1.4% 0.48 $2,398,472 40 Misc. mfg. prods. $24,363.6 41.0% 0.81 $171,630,950 Total $1,556,329,635 Table 57 presents the total economic impacts of JFK air cargo outflows on the entire New York metropolitan area. As can be observed from Section II, Line 1 of the table, the $1.543 billion in payroll required to produce the $6.31 billion in goods shipped out of JFK translates to 22,506 jobs (annual average pay per job of $68,560) and more than $2.4 billion is state GDP for New York. Further Section II, Line 2 shows that this direct economic effect of the goods shipped out of JFK is supported by 23,085 jobs with a combined payroll of nearly $1.74 billion ($75,530 per job) and $3.15 billion in state GDP. In this vein, the lower-paying jobs of the air cargo-producing industries of the region are supported by higher-paying jobs in Finance, Health, and other assorted service industries (see Section I of Table 57). Section IV of Table 57 shows estimates of the total tax revenues that state and local governments receive annually due to the existence of outgoing cargo shipments from JFK. About $619.0 million (44.6 percent) of the $1.39 billion in tax revenues generated are estimated as indirect business taxes. By level of government 50.5 percent of all tax revenues are estimated to be federal tax revenues, 20.8 percent as state revenues, and 21.2 percent as local tax revenues. 1-90

Note that the gap between state and local tax revenues is generated largely via indirect business taxes. Table 57. Total Economic Impacts of JFK Air Cargo Outflows on the New York Metropolitan Area Output ($Thousands) Employment (jobs) Compensation ($Thousands) GDP ($Thousands) I. Total Effects (Direct + Indirect/Induced) 1. Agriculture, Forestry, Fishing, and Hunting 33,060.7 129 4,957.4 11,727.2 2. Mining 829,675.7 2,173 140,103.7 388,381.2 3. Utilities 161,757.5 105 24,701.1 91,278.9 4. Construction 8,782.9 32 2,852.4 3,942.8 5. Manufacturing 6,790,085.3 24,310 1,701,870.9 2,387,718.9 6. Wholesale Trade 596,631.7 2,246 198,673.4 382,679.9 7. Retail Trade 280,675.0 2,472 98,890.8 165,895.7 8. Transportation and Warehousing 166,544.3 816 57,211.5 79,643.0 9. Information 286,988.2 441 55,466.0 158,637.1 10. Finance, Insurance, Real Estate, Rental, and Leasing 1,159,148.1 1,118 178,962.2 738,157.3 11. Professional and Business Services 910,323.8 4,032 421,571.3 642,594.9 12. Educational Services, Health Care, and Social Assistance 556,962.3 4,395 273,070.7 338,308.6 13. Arts, Entertainment, Recreation, Accommodation, and Food Services 248,019.0 2,380 80,235.8 134,346.3 14. Other Services (except Government) 115,499.5 943 48,076.2 64,907.8 Total Effects 12,144,153.9 45,591 3,286,643.2 5,588,219.7 II. Distribution of Effects and Multipliers 1. Direct Effects 6,305,048.5 22,506 1,543,002.9 2,435,910.7 2. Indirect/Induced Effects 5,839,105.5 23,085 1,743,640.3 3,152,309.0 3. Total Effects 12,144,153.9 45,591 3,286,643.2 5,588,219.7 4. Multipliers (= 3 / 1) 1.926 2.03 2.130 2.294 III. Composition of GDP 1. Compensation (Net of Taxes) 3,286,643.2 2. Taxes 618,976.2 a. Local 148,538.6 b. State 251,407.2 c. Federal 219,030.4 3. Profits, Dividends, Rents, and Other 1,682,600.3 4. Total GDP (= 1 + 2 + 3) 5,588,219.7 IV. Tax Accounts Business Household Total 1. Earnings (Net of Taxes) 3,286,643.2 3,155,177.4 ---------------- 2. Taxes 618,976.2 769,589.9 1,388,566.1 a. Local 148,538.6 146,126.8 294,665.5 b. State 251,407.2 140,720.9 392,128.1 c. Federal 219,030.4 482,742.1 701,772.5 1-91

New York City MSA (NY Portion) Air Imports Table 58 shows the total weight and value of goods shipped by air from the New York portion of the NYC MSA. All of these shipments were assumed to be distributed by wholesalers within the region. Table 58. Total Air Imports to NY Portion of NYC MSA SCTG AIR Total KTons in 2007 Total M$ in 2007 AirShare of $ 1 Live animals/fish 23.3 $318 52.4% 2 Cereal grains 0.1 $0 0.0% 3 Other ag prods. 25.8 $248 3.5% 4 Animal feed 2.1 $121 12.4% 5 Meat/seafood 2.7 $44 0.3% 6 Milled grain prods. 0.6 $3 0.1% 7 Other foodstuffs 5.7 $74 0.5% 8 Alcoholic beverages 3.0 $30 0.3% 9 Tobacco prods. 0.2 $5 0.1% 13 Nonmetallic minerals 1.3 $2 0.5% 14 Metallic ores 0.2 $7 8.9% 19 Coal-n.e.c. 1.1 $1 0.0% 20 Basic chemicals 9.8 $2,725 56.6% 21 Pharmaceuticals 19.0 $5,329 24.9% 22 Fertilizers 0.0 $0 0.0% 23 Chemical prods. 18.3 $823 8.8% 24 Plastics/rubber 22.0 $447 5.0% 26 Wood prods. 2.8 $22 0.4% 27 Newsprint/paper 0.0 $1 0.0% 28 Paper articles 4.7 $50 1.5% 29 Printed prods. 10.3 $205 1.6% 30 Textiles/leather 170.8 $6,174 23.6% 31 Nonmetal min. prods. 12.9 $185 3.5% 32 Base metals 13.4 $141 2.2% 33 Articles-base metal 15.4 $535 4.1% 34 Machinery 83.1 $7,325 15.6% 35 Electronics 64.9 $6,507 18.4% 36 Motorized vehicles 18.4 $356 1.6% 37 Transport equip. 2.6 $1,081 34.6% 38 Precision instruments 33.2 $4,767 36.9% 39 Furniture 6.9 $150 2.0% 40 Misc. mfg. prods. 30.7 $24,396 53.5% 43 Mixed freight 13.7 $2,749 6.8% Total 618.7 $64,820 15.1% As noted in the sector detail by two-digit NAICS, the local wholesale sector employs 208,714 workers with an aggregate payroll of $15.8 billion. By applying national wholesale margins to the value of the imported commodities as well as applying labor compensation’s share of the margin at the national level, about 2.0 percent of all wholesale trade production in 1-92

the region is estimated to be generated by incoming JFK air freight. This amounts to 3,505 jobs and $310.0 million in payroll in the region’s wholesale industry. Freight-Related Airport Operations and Shipping Industry Usably complete responses were received from 17 freight forwarders, 22 air carriers, the airport, and 2 shippers. Where data on payroll for an organization was missing, we used industry-average pay levels and the number of jobs reported by the survey respondent to estimate the payroll. When jobs were not reported but payroll levels were, industry-average wage levels were used to estimate the number of jobs. Table 59 summarizes the results of the survey data and the aforementioned estimation procedure for the total population of organizations involved in airport freight-related operations, such as freight forwarders and shippers, at JFK. The figures listed below are the total employees and payroll that are directly related to air cargo freight activities. Table 59. Summary of Survey of JFK Airport Freight Operations and Related Activity Summary Total Employment Total Pay FF Air Service 249 $10,636,571 Air Carrier 2,571 $101,705,988 Airport 24,700 $1,354,194,478 Shipper 172 $6,392,000 Total 27,692 $1,472,929,037 One point of comparison for this survey is the 2010 QCEW for Scheduled Freight Air Transportation (NAICS 481112) and the Air Carrier information in Table 59 above. The QCEW data reveal that officially, according to the US Bureau of Labor Statistics, 1,067 jobs with a payroll of $120,157,858. Thus, the study survey reports 240 percent the QCEW jobs and about 85 percent of its payroll. Clearly, the payroll figure is within reasonable bounds. Of course, LaGuardia Airport is within this region as well; but it has little freight throughput, so its air freight payroll should be negligible. The employment differential is more of a quandary since with the exception of three smaller firms, the 22 carriers tended to report that their employees in air freight worked full-time. In any event, rather than follow jobs numbers from the survey we held by the payroll numbers, and assumed that they represented a census of air freight employers at the airport. Later we use industry-average pay levels to estimate the employment levels in the model. Total Economic Impacts of Freight-related Airport Operations and Warehousing of Inflows The Rutgers Economic Advisory Service’s input-output modeling system (R/ECON I-O) perfectly estimated the jobs affiliated with the payroll for freight forwarders. To effect (mimic) in the modeling exercise the direct of the “airport industry” (as no such industry exists), however, its payroll was equally split between the model’s industry representing “Support activities for transportation” and one representing “Office administrative services.” As a result, the model’s underlying data system estimated that more jobs should exist than suggested by the 1-93

survey work. Given the already higher average pay of the Office administrative services industry, only the job count related to the Support activities for transportation was ratcheted downward. The job count estimated by the model for Air carriers was lower than derived via the survey. They were respectfully upwardly adjusted to match that obtained via the survey. Such blatant adjustment of known effects from those estimated via economic models is best practice in the field of economic modeling. The rationale behind the adjustment is that the model produces the job estimates using industry-average rates of pay for a specific year. In the case of the R/ECON I-O model used, the underlying regional economic data are for the year 2010. Table 60 presents the total economic impacts of JFK air cargo inflows (related as direct effects only to the wholesale trade sector) plus those for air freight and related industries on the New York metropolitan area. As can be observed from Section II, Line 1 of the table, the $1.783 billion in payroll at the airport and the wholesale trade facilities affiliated with JFK traffic translates to 17,908 jobs (annual average pay per job of $99,560) and nearly $2.78 billion in state GDP for New York. Further Section II, Line 2 shows that this direct economic effect is supported by 24,181 other jobs with a combined payroll of nearly $1.6 billion ($66,000 per job) and $3.09 billion in state GDP. Thus, higher-paying jobs at or near the airport are supported by lower-paying jobs, largely those in Retail Trade, health Care, and Entertainment industries (see Section I of Table 60), although the supporting jobs are well distributed across a large array of industries. Section IV of Table 60 shows estimates of the total tax revenues that state and local governments receive annually due to the existence of outgoing cargo shipments from JFK. About $791 million (50.0 percent) of the $1.582 billion in tax revenues generated are estimated as indirect business taxes. By level of government 46.4 percent are estimated to be federal tax revenues, 34.3 percent as state revenues, and 19.3 percent as local tax revenues. State tax revenues from wholesaling activities are assumed to dominate state tax revenues insofar as indirect business taxes are concerned. Of course, all such revenues, and some federal revenues as well, might not accrue due to the extent of traffic that is likely handled at JFK’s Free Trade Zone. 1-94

Table 60. Total Economic Impacts of JFK Air Cargo Inflows on the New York Metropolitan Area Output ($Thousands) Employment (jobs) Compensation ($Thousands) GDP ($Thousands) I. Total Effects (Direct + Indirect/Induced) 1. Agriculture, Forestry, Fishing, and Hunting 33,523.4 131 5,028.4 11,894.9 2. Mining 1,910.3 6 506.5 830.2 3. Utilities 110,758.6 73 16,669.5 61,599.5 4. Construction 7,942.7 29 2,579.5 3,565.7 5. Manufacturing 500,347.8 1,482 99,830.9 169,917.9 6. Wholesale Trade 1,227,761.1 4,622 408,834.3 787,486.5 7. Retail Trade 290,574.0 2,559 102,378.5 171,746.7 8. Transportation and Warehousing 3,817,973.2 11,493 908,657.8 1,465,722.6 9. Information 329,629.1 488 58,264.2 178,625.3 10. Finance, Insurance, Real Estate, Rental, and Leasing 1,268,925.1 1,201 184,988.2 813,340.5 11. Professional and Business Services 2,310,792.1 10,846 1,151,977.4 1,605,976.5 12. Educational Services, Health Care, and Social Assistance 549,589.4 4,338 269,464.9 333,781.2 13. Arts, Entertainment, Recreation, Accommodation, and Food Services 385,061.1 3,903 123,432.3 204,244.9 14. Other Services (except Government) 112,339.8 920 46,670.5 62,983.2 Total Effects 10,947,127.8 42,089 3,379,282.9 5,871,715.5 II. Distribution of Effects and Multipliers 1. Direct Effects 5,645,355.7 17,908 1,782,973.9 2,780,068.1 2. Indirect/Induced Effects 5,301,772.1 24,181 1,596,309.0 3,091,647.4 3. Total Effects 10,947,127.8 42,089 3,379,282.9 5,871,715.5 4. Multipliers (= 3 / 1) 1.939 2.35 1.895 2.112 III. Composition of GDP 1. Compensation (Net of Taxes) 3,379,282.9 2. Taxes 790,920.4 a. Local 155,037.8 b. State 398,283.4 c. Federal 237,599.2 3. Profits, Dividends, Rents, and Other 1,701,512.1 4. Total GDP (= 1 + 2 + 3) 5,871,715.5 IV. Tax Accounts Business Household Total 1. Earnings (Net of Taxes) 3,379,282.9 3,244,111.6 ---------------- 2. Taxes 790,920.4 791,282.1 1,582,202.5 a. Local 155,037.8 150,245.6 305,283.5 b. State 398,283.4 144,687.4 542,970.8 c. Federal 237,599.2 496,349.1 733,948.3 1-95

Case Study 5 – Reno-Tahoe International Airport, Reno, Nevada Reno-Tahoe International Airport (RNO) originally built in 1929 was named Hubbard Field. It is currently ranked as the 60th busiest commercial airport in the U.S. and sits on 1,450 acres of land. RNO currently serves eight commercial airlines. These carriers operate out of 23 gates at the main terminal, in which Southwest currently makes up 56.4 percent of the market share. The three runways at RNO provide substantial operating capacity and currently accommodate approximately 140 commercial airline operations daily. RNO is also home to the Reno Air National Guard whose base consists of a 60 acre complex on the west side of the airport. The airport served more than 3.8 million passengers in 2010, up 1.8 percent from the previous year. However, total aircraft movements were down 7.3 percent from 2009 (Reno- Tahoe Airport Authority 2012). Domestic cargo is the only product processed through the airport. Currently, no scheduled international cargo or airmail is handled at the airport. This is due in large measure to the proximity of Reno to large shipping hubs in San Francisco, Los Angeles, and to a lesser extent Seattle and Vancouver. The airport has the potential to grow its domestic cargo market, since it is ideally located to serve numerous West Coast distribution centers, online fulfillment centers, and the Tahoe/Reno Industrial Center, which is being marketed to be the largest industrial park in the world upon completion. Currently, four cargo companies operate out of RNO, including Capital Cargo International, DHL, FedEx and UPS as well as numerous ad-hoc charters throughout the year. In 2010, the Airport handled more than 56,000 tons of cargo; this is approximately a 10 percent increase from 2009 (Reno-Tahoe Airport Authority 2012). Reno-Sparks Regional Economy Reno is a city of 213,00011 located in western Nevada near Lake Tahoe. The area is known for its casinos and associated gambling industries. Unlike Las Vegas, its larger neighbor to the south, the land around Reno can support development without major water-diverting infrastructure. Prior to Nevada’s legalization of gambling in 1931, Reno was a regional transportation hub. Located at a crossing of the Truckee River en route to the Donner Pass in the Sierra Nevada Mountains, the city got its start as a railroad town on the Central Pacific Railway.12 Reno’s sister city, Sparks, developed around a switch yard on the Southern Pacific Railroad. With the rise of Las Vegas and the expansion of legalized gambling nationwide, the area declined as a gambling destination; still, gaming and related tourism remain the area’s primary industry. Similarly, with rail freight’s decline vis-à-vis truck and air freight, the city’s fortunes as a transportation hub have also diminished. Still, the area remains home to numerous distribution centers and online fulfillment centers. For its size, Reno-Tahoe International Airport houses an exceptional number of air cargo carriers, including Capital Cargo International, DHL, FedEx Express, and UPS, as well as numerous ad-hoc charters throughout the year. As a result, on average more than 150 tons of cargo arrive/depart daily through the Reno-Tahoe International Airport. Moreover, tonnages shipped through RNO have been rising in recent years (Reno- Tahoe Airport Authority 2012). 11 2005-2009 ACS 12 http://www.city-data.com/us-cities/The-West/Reno-History.html 1-96

The Reno-Sparks Metropolitan Statistical Area includes Washoe County (Reno) and Storey County (Sparks). The 2010 Census counts 421,407 people in Washoe County (with a nonfarm employment of 173,120)13 and just 4,010 people in Storey County (with a nonfarm employment of 352 in 2009).14 Carson City, the capital and an independent city, is not part of the MSA, although it is just a 40 minute drive from Reno. Nonetheless, Carson City’s 55,274 residents (and 22,258 in nonfarm employment)15 also depend on the RNO. Table 61 displays the Reno-Sparks MSA economy by supersector. Reflecting well the economic base of the economy, Accommodation and food services; Transportation and warehousing; Arts, entertainment, and recreation are the only supersectors with payroll locations quotients notably greater than 1.0. Given that payroll figures are better indicators of productivity than are employment numbers or job counts, it is presumed that a payroll location quotient (the industry’s share of local activity relative to that share for the industry nationwide) yields a proxy for the supply/demand ratio for the industry. Thus, supersectors with LQs greater than 1.0 should be more than self-sufficient (and abnormally concentrated) in the Reno-Sparks MSA, and clearly forming a substantial portion of the region’s export base. In this vein, they are expected to yield net sources of wealth to the region. Table 61. Employment, Payroll, and Payroll Location Quotients (LQs) by Two-digit NAICS for the Reno-Sparks MSA (2010) NAICS Description LQ Jobs Payroll (thousands) Average Salary 11 Agriculture, Forestry, Fishing and Hunting 0.10 214 $3,973 $18,566 21 Mining, Quarrying, and Oil and Gas Extraction 0.81 548 $62,336 $113,752 22 Utilities 0.93 774 $58,653 $75,779 23 Construction 1.19 8,778 $423,931 $48,295 31-33 Manufacturing 0.72 12,121 $620,010 $51,152 42 Wholesale Trade 1.00 8,346 $455,255 $54,548 44-45 Retail 1.07 20,580 $541,646 $26,319 48-49 Transportation and Warehousing 1.87 10,637 $426,332 $40,080 51 Information 0.49 2,335 $130,075 $55,707 52 Finance and Insurance 0.59 5,628 $361,674 $64,263 53 Real Estate and Rental and Leasing 1.05 3,371 $115,008 $34,117 54 Professional, Scientific, and Technical Services 0.81 9,456 $611,302 $64,647 55 Management of Companies and Enterprises 1.35 3,376 $322,728 $95,595 56 Administrative and Support and Waste Management and Remediation Services 0.95 11,234 $305,799 $27,221 61 Educational Services 0.46 1,828 $62,937 $34,429 62 Health Care and Social Assistance 1.09 19,941 $1,010,593 $50,679 71 Arts, Entertainment, and Recreation 1.48 5,166 $119,226 $23,079 72 Accommodation and Food Services 2.52 28,883 $629,309 $21,788 81 Other Services (except Public Administration) 1.19 5,962 $199,014 $33,380 99 Unclassified 0.70 92 $7,124 $77,437 Total 0 159,270 $6,466,928 $40,604 Source: R/ECON I-O 13 http://quickfacts.census.gov/qfd/states/32/32031.html 14 http://quickfacts.census.gov/qfd/states/32/32029.html 15 http://quickfacts.census.gov/qfd/states/32/32510.html 1-97

Major Industries in Reno-Sparks With greater sectoral articulation, Table 62 shows, regardless of size, the ten three-digit NAICS industries that are most heavily concentrated in the Reno-Sparks economy. The economic profile for the metropolitan area solidifies. Accommodation (721), largely casino resort hotels around Lake Tahoe, tops the list with a payroll location quotient of 7.29. The subsector supports an annual average of 16,129 employees at an average annual salary of $26,857 dollars (for a total labor income of over $433.2 million). The Warehousing and storage subsector’s LQ of 4.69 puts it in the number two spot, with 4,046 employees who earn an average salary of $39,034 (for a total labor income of $157.9 million). Miscellaneous manufacturing occupies the third spot. In that subsector, 2,003 workers are involved in the manufacture of miscellany, bringing home an average salary of $63,471 (for a total labor income of $127.1 million). Curiously, Amusements, gambling, and recreation (713) – the industry to which the number one industry, accommodation, likely owes a great deal, posts a more modest LQ of 2.72. Mining, except oil and gas; Couriers and messengers; Funds, trusts, and other financial vehicles; and Transit and ground passenger transportation; also have payroll location quotients above 2.0. Table 62. Ten Highest Payroll LQ Industries among Three Digit NAICS for the Reno-Sparks MSA, 2010 NAICS Description LQ Jobs Payroll (thousands) Average Salary 721 Accommodation 7.29 16,129 $433,178 $26,857 493 Warehousing and Storage 4.69 4,046 $157,933 $39,034 339 Miscellaneous Manufacturing 3.19 2,003 $127,132 $63,471 713 Amusement, Gambling, and Recreation Industries 2.72 4,578 $97,129 $21,216 212 Mining (except Oil and Gas) 2.26 448 $40,840 $91,160 492 Couriers and Messengers 2.24 1,724 $65,561 $38,028 525 Funds, Trusts, and Other Financial Vehicles 2.16 257 $23,375 $90,952 485 Transit and Ground Passenger Transportation 2.13 819 $29,936 $36,552 451 Sporting Goods, Hobby, Book, and Music Stores 1.87 1,444 $27,774 $19,234 484 Truck Transportation 1.74 2,665 $119,658 $44,900 In drilling even deeper, Table 63 ranks the top 20 manufacturing subsectors with even further refinement (six-digit NAICS) by payroll location quotient. Topping the list is All other miscellaneous manufacturing, which includes “coin-operated amusement machines,” “coin- operated gambling devices,” and “slot machines” manufacturing. Not surprisingly, International Game Technology (IGT), a Reno-based gaming-machine manufacturer, reported revenues of $1.9 billion in 2010. Clearly, legal gaming and related tourism are core industries of the Reno- Sparks metropolitan area. It is also clear that in Reno-Sparks, local commodity exporting six- digit industries are fairly small in size with the possible exceptions of both All Other Miscellaneous Manufacturing and Search, Detection, Navigation, Guidance, Aeronautical, and Nautical System and Instrument Manufacturing. 1-98

Table 63. The Ten Manufacturing Six-digit NAICS Sectors Most Highly Concentrated in the Reno-Sparks MSA, 2010 NAICS Description LQ Jobs Payroll (thousands) Average Salary 339999 All Other Miscellaneous Manufacturing 36.52 1,607 $109,841 $68,352 334418 Printed Circuit Assembly (Electronic Assembly) Manufacturing 6.54 345 $21,201 $61,452 332911 Industrial Valve Manufacturing 5.85 223 $10,785 $48,363 332112 Nonferrous Forging 4.58 40 $2,264 $56,596 314912 Canvas and Related Product Mills 4.51 94 $3,681 $39,165 322215 Nonfolding Sanitary Food Container Manufacturing 4.36 103 $3,030 $29,414 331315 Aluminum Sheet, Plate, and Foil Manufacturing 4.10 103 $5,119 $49,700 331522 Nonferrous (except Aluminum) Die-Casting Foundries 4.10 32 $1,207 $37,713 334511 Search, Detection, Navigation, Guidance, Aeronautical, and Nautical System and Instrument Manufacturing 3.80 945 $70,633 $74,744 337212 Custom Architectural Woodwork and Millwork Manufacturing 3.79 52 $3,450 $66,344 332322 Sheet Metal Work Manufacturing 3.72 499 $20,269 $40,620 322223 Coated Paper Bag and Pouch Manufacturing 3.62 42 $1,650 $39,274 334514 Totalizing Fluid Meter and Counting Device Manufacturing 3.50 68 $2,957 $43,491 322233 Stationery, Tablet, and Related Product Manufacturing 3.34 18 $778 $43,248 334310 Audio and Video Equipment Manufacturing 3.22 98 $6,416 $65,474 326111 Plastics Bag and Pouch Manufacturing 3.18 174 $5,856 $33,658 335129 Other Lighting Equipment Manufacturing 3.12 46 $1,802 $39,181 325910 Printing Ink Manufacturing 3.10 36 $2,382 $66,176 332913 Plumbing Fixture Fitting and Trim Manufacturing 3.07 54 $1,894 $35,069 323119 Other Commercial Printing 3.05 154 $7,132 $46,311 Commodity-producing Industries by SCTG Code Results from a direct survey of air freight carriers provided fragmentary information at best. The responded population was small, and those who did respond at RNO provided data that were not generally complete. It was therefore clear that the analysis needed to lean on secondary data for air shipments. The best and most complete publicly available data on trade for subregions of U.S. states are widely known to be Version 3 of the Freight Analysis Framework (FAF3) Origin-Destination Data, which are available online from the U.S. Department of Transportation.16 To meaningfully employ the FAF3 data, Quarterly Census 16 Last accessed in June 2012 at http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/. For details on how the FAF3 data are estimated see Southworth et al. (2010) at http://faf.ornl.gov/fafweb/Data/FAF3ODCMOverview.pdf. 1-99

of Employment and Wages (QCEW) were matched to Standard Classification of Transported Goods (SCTG) categories used by FAF3 (Appendix A provides a NAICS to SCTG crosswalk). Table 64 resulted. Note that less than 10 percent of all Reno-Sparks employment and just more than 10 percent of its aggregate payroll are engaged in producing the relevant commodities. Moreover, most pertinent industries have LQs substantially lower than 1.0, the threshold generally applied to assume an industry exports. Table 64. Employment and Payroll by SCTG Category in the Reno-Sparks MSA, 2010 SCTG Description Payroll LQ Jobs Payroll ($Thousands) 1 Live animals/fish 0.29 66 $1,892 2 Cereal grains 0.00 0 $0 3 Other ag prods. 0.04 40 $933 4 Animal feed 0.28 108 $1,229 5 Meat/seafood 0.28 206 $6,387 6 Milled grain prods. 0.58 138 $5,507 7 Other foodstuffs 0.50 443 $20,499 8 Alcoholic beverages 0.01 1 $45 9 Tobacco prods. 0.00 0 $0 10 Building stone 1.65 87 $2,990 11 Natural sands 0.94 72 $3,900 12 Gravel 0.00 0 $0 13 Nonmetallic minerals 0.48 13 $718 14 Metallic ores 12.26 395 $53,515 15 Coal 0.00 0 $0 16 Crude petroleum 0.06 40 $3,332 17 Gasoline 0.05 6 $585 18 Fuel oils 0.00 0 $0 19 Coal-n.e.c. 0.29 36 $1,887 20 Basic chemicals 0.25 47 $2,881 21 Pharmaceuticals 0.04 39 $1,504 22 Fertilizers 0.12 5 $230 23 Chemical prods. 0.36 123 $8,110 24 Plastics/rubber 0.85 925 $38,667 25 Logs 0.34 36 $1,148 26 Wood prods. 0.81 513 $16,615 27 Newsprint/paper 0.21 76 $3,330 28 Paper articles 1.24 407 $18,014 29 Printed prods. 1.25 751 $32,440 30 Textiles/leather 0.28 229 $5,720 31 Nonmetal min. prods. 0.47 158 $8,008 32 Base metals 0.32 191 $8,977 33 Articles-base metal 1.01 1,839 $79,414 34 Machinery 0.47 705 $34,329 35 Electronics 0.57 1,056 $61,640 36 Motorized vehicles 0.18 212 $9,659 37 Transport equip. 0.39 346 $24,898 38 Precision instruments 1.26 1,348 $92,926 39 Furniture 0.50 177 $8,097 40 Misc. mfg. prods. 5.98 1,798 $118,320 41 Waste/scrap 0.00 0 $0 43 Mixed freight 0.00 0 $0 Total 12,632 $678,345 1-100

Reno Area Air Freight Movements As was discussed previously, the analysis of air freight necessarily leaned on publically available data from FAF3. Many (74 to be precise) of FAF3‘s 123 regions are metropolitan areas. Unfortunately the Reno-Sparks MA is not one of them. In fact, it lies with the FAF3 region called “Remainder of Nevada.” That is, it is all of Nevada excluding both Nye County and Clark County, the latter containing Las Vegas and its suburbs. The “Remainder of Nevada” therefore comprises more than just the Reno-Sparks MSA, and while Reno is undoubtedly the largest city of this geography, it contains less than half of the region’s population, which itself comprises about half of the state’s total. Indeed, it well may be that RNO services much of this broader region with its air freight needs. “Remainder of Nevada” Outflows Table 65 shows air freight export commodities by SCTG code for the year 2007. In total, the Reno-Sparks MSA exported $299.3 million worth of goods by air. Comparing Table 65 to the profile in the previous section, it is evident that air freight exports are not particularly representative of the economy as a whole. This is not surprising given the economy’s heavy reliance on casinos and related tourism as well as the geographical mismatch between the MSA and the FAF3 region represented by Table 65. Still, it certainly makes clear that the economy (from either geographic perspective) also does not depend highly on air freight. Table 65. Air Freight (including Truck-Air) for the Remainder of Nevada, Total Originating, 2007 SCTG Description Kilotons Air Shipments ($Million) Air Freight Share ($) 5 Meat/seafood 1.84 $20.1 4.2% 20 Basic chemicals 0.00 $0.8 2.3% 21 Pharmaceuticals 0.03 $90.8 3.0% 23 Chemical prods. 0.34 $2.0 0.1% 24 Plastics/rubber 0.60 $3.0 0.3% 29 Printed prods. 0.77 $4.4 0.6% 30 Textiles/leather 0.33 $26.5 2.2% 31 Nonmetal min. prods. 0.00 $0.2 0.0% 32 Base metals 0.25 $2.0 0.4% 33 Articles-base metal 0.05 $0.6 0.0% 34 Machinery 0.00 $5.6 0.1% 35 Electronics 0.28 $94.4 3.0% 36 Motorized vehicles 0.25 $27.4 1.9% 39 Furniture 0.05 $1.0 0.4% 40 Misc. mfg. prods. 0.00 $1.2 0.1% 43 Mixed freight 1.36 $19.4 0.5% Total 6.16 $299.3 Source: FAF3 (2007) 1-101

Reconciling originating shipments with local MSA production was a challenge. In fact it became immediately apparent since Pharmaceuticals – a top air freight export for the region according to the FAF3 – does not register as a major production sector in the QCEW data for Reno-Sparks (addressed below). Regardless, $90.8 million worth of pharmaceuticals left RNO by aircraft in 2007. SCTG category 21, Pharmaceutical Products, refers to finished products ready for medical use (and not the raw base chemicals). It also includes bandages, sutures, dental fillings, and other such non-medicinal products. Although Pharmaceuticals loom large as an export from RNO, the largest export sector actually was SCTG Code 35, Electronic and other Electrical Equipment and Components, and Office Equipment. This commodity category includes computer equipment and circuits, audio-video equipment, light bulbs, some (mainly smaller) domestic appliances, electric motors, among other things. In 2007, $94.4 million in electronics were shipped from Reno. Both of these top commodities have high value-to-weight ratios, consistent with expectations for expensive air shipment. The largest next category, Meat, Fish, and Seafood, and their Preparations has a lower value-to-weight ratio, but considerably more urgency since such food goods are typically deemed best when fresh. The category includes meat, poultry, fish fresh, chilled or frozen (or dried, salted, or boiled in the case of some sea foods). About $20.1 million in meat, fish, and seafood and their preparations took flight from RNO in 2007. Table 66 shows payroll of the Reno-Sparks MSA production sectors that likely produce goods for export by air freight. As described above, these are aggregate QCEW sectors related to the commodities shipped that have a location quotient greater than 0.3. The “air base payroll” is calculated by taking the portion of the total sector payroll beyond the 0.3 threshold and then the percentage of that commodity that is shipped by air. We use a threshold of 0.3 rather than 1.0 here for two reasons (1) because using the more conventional LQ threshold of 1.0 yielded insufficient capacity for a reasonable estimate of air freight from the Reno-Sparks area given its dominance in the “Rest of Nevada” space economy and (2) Stevens, Treyz, and Lahr (1989) found that assuming an LQ threshold of 0.3 was better than using the usual 1.0 threshold when estimating the share of production that is used locally for goods-producing sectors. Table 66. Air Freight (including Truck-Air) for the Remainder of Nevada, Total Originating from Reno-Sparks MSA, 2007 CTG Description Air Shipments ($Million) Air Share of $s Payroll LQ Est. Payroll (Thousands) 23 Chemical prods. $2.0 0.1% 0.36 $3.1 24 Plastics/rubber $3.0 0.3% 0.85 $75.3 29 Printed prods. $4.4 0.6% 1.25 $162.4 31 Nonmetal min. prods. $0.2 0.0% 0.47 $1.7 32 Base metals $2.0 0.4% 0.32 $25.8 33 Articles-base metal $0.6 0.0% 1.01 $23.4 34 Machinery $5.6 0.1% 0.47 $34.2 35 Electronics $94.4 3.0% 0.57 $1,205.0 39 Furniture $1.0 0.4% 0.50 $21.9 40 Misc. mfg. prods. $1.2 0.1% 5.98 $73.7 Total $114.40 $1,626.4 1-102

Despite the lower threshold a disjoint clearly exists. After combining data from FAF3 and on local production capabilities, just $6.87 million of goods that are shipped out of RNO can derive from the Reno-Sparks metropolitan area. As shown in Table 66 this equates to $1.626 million in payroll estimated for the metropolitan area. That is, those commodities shipped from RNO, according to FAF3, tend not to have a corresponding production presence according to the US Bureau of Labor Statistics. This forces the conclusion that outward-bound goods from RNO’s catchment area tend to be produced outside the MSA itself. Still, the MSA benefits from the economic activity, presumably through warehousing and other support services. Table 67 presents the total economic impacts of RNO air cargo outflows on the Reno- Sparks metropolitan area. As can be observed from Section II, Line 1 of the table, the $1.623 million in payroll required to produce the $6.87 million in goods shipped out of RNO translates to 44 jobs (annual average pay per job of $37,200) and nearly $2.5 million in state GDP for Nevada. Further Section II, Line 2 shows that this direct economic effect of the goods shipped out of RNO is supported by 33 jobs with a combined payroll of nearly $1.70 million ($51,900 per job) and $3.30 million in state GDP. In this vein the lower-paying jobs of the air cargo-producing industries of the region are supported by higher-paying jobs in Finance, Health, and other assorted service industries (see Section I of Table 67). Section IV of Table 67 shows estimates of the total tax revenues that state and local governments receive annually due to the existence of outgoing cargo shipments from RNO. About $0.67 million (56.8 percent) of the $1.18 million in tax revenues generated are estimated as indirect business taxes. By level of government 61.9 percent are estimated to be federal tax revenues, 22.7 percent as state revenues, and 15.4 percent as local tax revenues. Low local property taxes and a lack of state personal income taxes in Nevada account for this unusually skewed revenue distribution. 1-103

Table 67. Total Economic Impacts of RNO Air Cargo Outflows on the Reno-Sparks Metropolitan Area Output ($Thousands) Employment (jobs) Compensation ($Thousands) GDP ($Thousands) I. Total Effects (Direct + Indirect/Induced) 1. Agriculture, Forestry, Fishing, and Hunting $36.2 0 $5.6 $12.6 2. Mining $1.3 0 $0.2 $0.7 3. Utilities $130.0 0 $16.3 $70.6 4. Construction $10.7 0 $3.2 $4.8 5. Manufacturing $7,662.1 48 $1,802.0 $2,773.4 6. Wholesale Trade $747.2 3 $250.5 $479.2 7. Retail Trade $312.7 3 $103.6 $184.8 8. Transportation and Warehousing $273.2 2 $88.1 $140.7 9. Information $194.6 1 $42.4 $109.0 10. Finance, Insurance, Real Estate, Rental, and Leasing $1,146.7 1 $107.9 $738.0 11. Professional and Business Services $954.1 7 $441.6 $666.8 12. Educational Services, Health Care, and Social Assistance $612.4 6 $312.4 $372.4 13. Arts, Entertainment, Recreation, Accommodation, and Food Services $269.4 4 $86.9 $146.5 14. Other Services (except Government) $153.0 1 $58.7 $87.3 Total Effects $12,503.6 76 $3,319.6 $5,786.8 II. Distribution of Effects and Multipliers 1. Direct Effects $6,874.2 44 $1,623.8 $2,488.9 2. Indirect/Induced Effects $5,629.4 33 $1,695.8 $3,297.9 3. Total Effects $12,503.6 76 $3,319.6 $5,786.8 4. Multipliers (= 3 / 1) 1.819 1.75 2.044 2.325 III. Composition of GDP 1. Compensation (Net of Taxes) $3,319.6 2. Taxes $671.8 a. Local $158.9 b. State $268.0 c. Federal $244.9 3. Profits, Dividends, Rents, and Other $1,795.5 4. Total GDP (= 1 + 2 + 3) $5,786.8 IV. Tax Accounts Business Household Total 1. Earnings (Net of Taxes) 3,319.6 3,186.8 ---------------- 2. Taxes 671.8 510.8 1,182.6 a. Local 158.9 23.3 182.1 b. State 268.0 0.0 268.0 c. Federal 244.9 487.6 732.5 Remainder of Nevada Inflows Table 68 shows air freight inflows by SCTG code for the year 2007. These cargo inflows total $395.8 million. The commodities flown in by air are strikingly similar to the commodities flow outwardly by air. With just only 43 SCTG codes in total, some overlap is inevitable. Interestingly, Pharmaceuticals and Electronics occupy the top two spots on both lists. Both sectors produce highly specialized products, so having a strong local supply does not preclude the need to import like goods. 1-104

Table 68. Air Freight (including Truck) to the “Remainder of Nevada,” 2007 SCTG Description Air Shipments Air Share (of $) Kilotons $ Millions 5 Meat/seafood 0.00 $0.0 0.0% 20 Basic chemicals 0.01 $0.3 0.1% 21 Pharmaceuticals 0.41 $96.3 5.5% 23 Chemical prods. 0.81 $10.3 1.0% 27 Newsprint/paper 0.58 $0.6 0.3% 29 Printed prods. 0.02 $6.5 0.9% 30 Textiles/leather 0.05 $0.3 0.0% 33 Articles-base metal 0.00 $3.8 0.3% 34 Machinery 2.49 $25.4 0.6% 35 Electronics 0.35 $116.5 2.2% 36 Motorized vehicles 4.03 $37.4 1.4% 37 Transport equip. 0.00 $9.2 15.5% 38 Precision instruments 0.02 $24.1 1.8% 39 Furniture 0.00 $0.0 0.0% 40 Misc. mfg. prods. 9.02 $64.3 5.0% 43 Mixed freight 0.00 $0.8 0.0% Total 17.79 $395.8 Source: FAF3 (2007) A significant import that does not register as an export is SCTG 38, Precision Instruments. In 2007, 24.1 million dollars in precision instruments were flown into the Remainder of Nevada. The precision instruments category includes eyeglasses, photographic equipment, surveying instruments, medical apparatus, and certain items for industrial testing. As evidenced by the high (highest, even) weight-to-value ratio, such pieces can be very expensive, likely rendering their shipping cost comparatively insignificant. As noted in the sector detail by two-digit NAICS, the local wholesale sector employs 8,346 workers with an aggregate payroll of $455 million. This sector is undoubtedly affected by the incoming air shipments. Hence we applied wholesale margins to all of the incoming air shipments. The average of these margins was around 18 percent or about $7.4 million in net income for the Wholesale Trade sector. This corresponds to about $2.47 million in labor compensation to the industry or about 0.5 percent of the local payroll share. Freight-related Airport Operations and Shipping Industry Table 69 summarizes data from a survey of airport freight operations and the related industries, freight forwarders and shippers were included in the population of potential survey respondents. No results were reported for shippers. The table displays the total employees and payroll that are directly related to air cargo freight activities. In total, usably complete responses were received for four freight forwarders, three carriers, and the airport. 1-105

Table 69. Air Freight and Related Industries at RNO, 2011 Summary Jobs Payroll (Thousands) Freight forwarding 9 $356.7 Air carrier 13 $554.8 Airport 220 $12,061.7 Shippers - $0.0 Total 242 $12,973.2 Total Economic Impacts of Freight-related Airport Operations and Warehousing of Inflows The Rutgers Economic Advisory Service’s input-output modeling system (R/ECON I-O) perfectly estimated the jobs affiliated with the payroll for freight forwarders. To effect (mimic) in the modeling exercise the direct of the “airport industry” (as no such industry exists), however, its payroll was equally split between the model’s industry representing “Support activities for transportation” and one representing “Office administrative services.” As a result, the model’s underlying data system estimated that more jobs than suggested by the survey work. Given the already higher average pay of the Office administrative services industry, only the job count related to the Support activities for transportation was ratcheted downward. The job count estimated by the model for Air carriers was lower than derived via the survey. They were upwardly adjusted to match that obtained via the survey. Such blatant adjustment of known effects from those estimated via economic models is best practice in the field of economic modeling. The rationale behind the adjustment is that the model produces the job estimates using industry-average rates of pay for a specific year. In the case of the R/ECON I-O model used, the underlying regional economic data are for the year 2010. Table 70 presents the total economic impacts of RNO air cargo inflows (related as direct effects only to the wholesale trade sector) and air freight and related industries on the Reno- Sparks metropolitan area. As can be observed from Section II, Line 1 of the table, the $15.29 million in payroll at airport and the wholesale trade facilities affiliated with RNO traffic translates to 274 jobs (annual average pay per job of $55,800) and nearly $23.4 million in state GDP for Nevada. Further Section II, Line 2 shows that this direct economic effect is supported by 261 other jobs with a combined payroll of nearly $12.1 million ($46,300 per job) and $24.3 million in state GDP. Thus, higher-paying jobs at or near the airport are supported by lower-paying jobs, largely those in Retail Trade and Entertainment industries (see Section I of Table 70), although the supporting jobs are well distributed across a large array of industries. Section IV of Table 70 shows estimates of the total tax revenues that state and local governments receive annually due to the existence of outgoing cargo shipments from RNO. About $0.67 million (57.4 percent) of the $9.88 million in tax revenues generated are estimated as indirect business taxes. By level of government 56.8 percent are estimated to be federal tax revenues, 28.3 percent as state revenues, and 14.9 percent as local tax revenues. Recall that low local property tax rates and a lack of state personal income taxes in Nevada account for the low tax accumulations for these jurisdictions. 1-106

Table 70. Total Economic Impacts of RNO Air Cargo Inflows on the Reno-Sparks Metropolitan Area Output ($Thousands) Employment (jobs) Compensation ($Thousands) GDP ($Thousands) I. Total Effects (Direct + Indirect/Induced) 1. Agriculture, Forestry, Fishing, and Hunting $314.4 2 $48.4 $109.6 2. Mining $2.5 0 $0.5 $1.3 3. Utilities $882.0 1 $111.7 $483.3 4. Construction $84.0 0 $25.0 $37.7 5. Manufacturing $3,151.8 18 $672.4 $1,086.6 6. Wholesale Trade $9,810.1 43 $3,289.6 $6,292.2 7. Retail Trade $2,837.7 26 $940.3 $1,677.3 8. Transportation and Warehousing $25,696.4 171 $7,717.0 $12,634.0 9. Information $1,873.6 10 $385.1 $1,040.6 10. Finance, Insurance, Real Estate, Rental, and Leasing $10,274.9 13 $949.5 $6,614.0 11. Professional and Business Services $17,468.9 155 $9,236.2 $12,423.1 12. Educational Services, Health Care, and Social Assistance $5,388.5 50 $2,748.6 $3,275.8 13. Arts, Entertainment, Recreation, Accommodation, and Food Services $2,394.0 35 $767.0 $1,292.8 14. Other Services (except Government) $1,240.2 11 $476.3 $706.0 Total Effects $81,418.9 535 $27,367.8 $47,674.4 II. Distribution of Effects and Multipliers 1. Direct Effects $40,714.5 274 $15,287.4 $23,398.9 2. Indirect/Induced Effects $40,704.4 261 $12,080.5 $24,275.5 3. Total Effects $81,418.9 535 $27,367.8 $47,674.4 4. Multipliers (= 3 / 1) $2.000 1.95 $1.790 $2.037 III. Composition of GDP 1. Compensation (Net of Taxes) $27,367.8 2. Taxes $5,672.2 a. Local $1,281.7 b. State $2,795.2 c. Federal $1,595.4 3. Profits, Dividends, Rents, and Other $14,634.3 4. Total GDP (= 1 + 2 + 3) $47,674.4 IV. Tax Accounts Business Household Total 1. Earnings (Net of Taxes) $27,367.8 $26,273.1 ---------------- 2. Taxes $5,672.2 $4,211.6 $9,883.8 a. Local $1,281.7 $191.8 $1,473.5 b. State $2,795.2 $0.0 $2,795.2 c. Federal $1,595.4 $4,019.8 $5,615.2 1-107

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