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50 C H A P T E R 9 Data that support the estimation of the overall national economic impact of airports, multifactor productivity, and consumer surplus will tend to become obsolete over time, to varying degrees, because of changes in the economy, changes in technology, and new research findings. While the overall frame- work may remain applicable, future research will be necessary to both update and enhance the factors shown in this report. In addition, future research may help to refine and establish the robustness of the values used in this study. 9.1 Economic Contributions of U.S. Airports to the National Economy The economic impact studies reviewed for ACRP Proj- ect 03-28 were over a 2005â2011 time frame (the regres- sion analysis was limited to 2006â2011). Also, the studies reviewed were highly diverse regarding methodologies and economic elements counted and reported. This project ben- efitted by having three firms on the research team (EDR Group, ICF SH&E, and Mead & Hunt) that each had a library of previous studies they and others had conducted. However, in addition, the team was aware of many other studies (and par- ticularly the underlying data associated with those studies) that were not obtainable for this research effort. This is particularly true for large hub airportsâwhere studies are often conducted independently of state system economic impact studies. A future research project could develop a method to establish a repository for the timely collection of research data or technical appendices that underlie airport economic impact studies. In addition to the issues of fund- ing and maintaining such a repository, an important con- sideration in creating such a repository is that many of these studies are consultant work products and/or the property of the project sponsors. Therefore, the project sponsors and their consultants will need to be confident of the neutrality of the administration of the repository and the confidentiality of the source data in the repository, as well as appropriate use of data aggregation. To improve tools used to estimate the economic contribu- tions of airports to off-airport industries in their vicinity, a potentially valuable research project would be a study of the value of international air cargo flows of imports and exports to the national economy, as noted below: ⢠Imports: While a portion of imports are consumer goods, imports are widely used in production processes by U.S. industries. There is a need to avoid double counting, as some of the intermediate goods are turned around and exported as finished products with relatively little value added, whereas others have significant value added. Economic contributions of air imports are positive if: (1) intermediate commodi- ties allow U.S. industries to manufacture products that oth- erwise would not be developed in the U.S. and (2) imported goods for final sale allow households and firms to purchase more local goods and services than would be possible with- out lower cost imports. However, these positive economic contributions must be balanced against potentially nega- tive impacts if imports displace U.S. production. ⢠Exports: Well-established methodologies are available to estimate economic benefits derived from the export of com- modities through airports. Research is needed to develop more accurate estimates of the impact of airports by inte- grating mode choices available to shippers, understanding that mode choice is more important for domestic goods, for which truck and air modes could be substituted, rather than international exports,36 other than shipments to Canada or Mexico. ⢠Another research topic suggested by the findings of this study is to estimate the value of international business travel. In part, the productivity effects of business travel are incorpo- rated in the MFP. However, as airports enable air cargo ship- ments in international markets, airports also enable business travel to attract and service international customers. The Future Research
51 danger of double counting between the economic benefits of air cargo and air travel is that business travel often leads to merchandise sales. Therefore, care is necessary to avoid double counting the impacts of business travel and cargo exports. Further research is needed to break out business travel for service sectors from goods-producing sectors of the national economy. As technology evolves, the contri- bution of aviation to the service sector will change. In this context, an important distinction must be made between domestic and international travel. Domestic travel is typi- cally more business-oriented than international travel, although, this varies by market.37 Therefore, the way in which international connections are considered in the analysis must reflect these differences. 9.2 Multifactor Productivity An important future research effort should focus on the linkages between enhancements in air service connectivity and changes in productivity. The research undertaken in this project has established a statistical relationship, but it has not established why this occurs. Future research could explore linkages between connectivity and changes in productivity to further our understanding of why some industriesâ produc- tivity appears more affected by one connectivity measure and not others. This research would require a greater emphasis on modeling the relationships, rather than just undertaking a statistical investigation. The MFP analysis reported here is based on 11 industry sec- tors represented by two-digit NAICS codes, 20 metropolitan regions (encompassing 26 commercial airports), and the dis- crete years 1995, 2000, 2005, and 2010, which span a period that included years of economic expansion and two recessions, but does not include any of the recession years. However, the MFP analysis estimates of the productivity impacts of con- nectivity changes for U.S. airports would be more robust if a future research project incorporates a continuous time series of data and more detailed economic data for at least three- digit NAICS codes (89 sectors, although many are not sensi- tive to airport connectivity). A three-digit approach would allow for a finer differentiation between productivity related to cargo and productivity generated by passenger connectiv- ity. In addition, the sample of MSAs and, therefore, airports could be enlarged to provide a more comprehensive sample of the U.S. economy. Lastly, research could be undertaken to determine whether GA airports (at least large GA facilities) can be usefully incorporated into the MFP framework. More generally, further research should be conducted to better understand and quantify the economic contribution of air cargo and, specifically, what actions airport operators can take to enhance an air cargo analysis. The current research project has explored the relationship between air cargo activ- ity at airports in a sample of metropolitan regions and changes in productivity in selected industry sectors in those regions. However, it is unclear whether the changes in air cargo activ- ity are the cause or effect of changes in productivity. The level of air cargo activity is the result of shipping deci- sions by a wide range of economic actors, including producers, integrators, and third party logistics firms that are independent of integrators. Shipping decisions made by these firms depend on logistics costs, including the value of time service levels of the air cargo industry in relation to the competing service levels offered by other modes (in some cases the same firms provide alternative services by different modes). Therefore, it is neces- sary to develop an improved understanding of the economic consequences of changing service levels on competing modes and how decisions by airport operators can influence the ser- vice levels offered by the air cargo industry (e.g., by improving air cargo handling facilities at the airport or truck access to those facilities). A major difficulty in performing research on the economic effects of air cargo, which constrained the research undertaken as part of this project, is the absence of publicly available data on domestic air cargo shipment patterns that are analogous to the O&D data available for air passenger trips or data on domestic air cargo shipments by industry sector. Data from the Freight Analysis Framework (FAF) and the Commod- ity Flow Survey (the survey on which FAF is based) provides country-to-country flows and modes, but not by specific points of where one mode begins and another ends.38 For example, a commodity originating in Jacksonville, FL might be transported by air to a destination in Springfield, MO. But, through FAF, it is not known if the commodity that flew from Jacksonville International Airport was trucked to Tampa from Miami International Airport or Hartsfield-Jackson Atlanta International Airport, or if it landed in Springfield-Branson National Airport or Lambert-St. Louis International Airport. The preceding are examples, as many more airport pairs are conceivable from the data. Therefore, a major focus of future research should be the integration of existing data on air cargo activity that is currently available, and the development and administration of surveys to begin to assemble the missing data on a regional or national basis. 9.3 Consumer Surplus The consumer surplus analysis incorporated data from air passenger surveys to differentiate business and personal travel. The airport survey data were critical to estimate the number of trips by purpose (business or personal) in each O&D market. The analysis relied on seven surveys covering 10 airports. These survey results were obtained through per- sonal contacts of the research team. The consumer surplus analysis would be enhanced by incorporating the findings
52 from more air passenger surveys. A rich data set that might be explored is the Airport Service Quality Survey conducted at more than 40 airports each quarter by ACI-NA. In addi- tion, passenger survey data are collected for most commercial airports. A future project could include collecting the find- ings of these surveys in one location to enable use for future research. However, the issue of confidentiality and reluctance of survey sponsors to part with detailed survey data is a major constraint. Future research could also improve the analysis of con- sumer surplus undertaken in the current project. It could focus on several aspects: (1) expanding the number of markets considered in the analysis, particularly international markets, in order to provide a more representative sample of U.S. air travel; (2) refining the air travel demand elasticity values used in the analysis; (3) distinguishing between inbound and out- bound international travel, in the same way that the analysis of domestic travel considered the directional travel in each O&D market; and (4) refining the trip purpose estimates for international travel. The analysis performed in the cur- rent project assumes a constant demand elasticity for each market, distinguishing only between short-haul and long- haul domestic markets (with long-haul markets defined as those over 1,500 miles), and a separate demand elasticity of international trips. These values were based on a review of the literature on past studies and represent the median value found in the range of estimates given in the relatively small number of studies identified in the literature. Unfortunately, there have not been many studies that give comparable esti- mates of air travel demand elasticity. Therefore, it would be useful to undertake a more comprehensive air travel demand analysis with an objective to better understanding how air travel demand elasticity varies with market characteristics. The data delineating business and personal trip purpose for international travel was obtained from a fairly large survey of overseas air travelers to and from the United States, con- ducted on an ongoing basis each year for the OTTI of the U.S. Department of Commerce. However, the tabulations of the survey results do not show the trip purpose split for individual airport-pair markets, but rather by country of origin or des- tination (and only for a few selected destination countries in the case of U.S. residents, with other countries grouped into world regions) and port of entry (but only for visitors to the U.S. and only for the major ports of entry, and not by country of origin). In general, more detailed tabulations would not be supported by the sample size; although, more customized analysis is available for a fee. Furthermore, the survey does not include travelers to or from Canada and Mexico (which are not classified as âoverseasâ by the OTTI). However, data on trip purpose of international travelers in specific markets (at least at the level of country of destination) is available from air passenger surveys conducted from time to time at the gateway airports. Therefore, it would be possible to integrate data from multiple surveys to obtain a better understanding of the trip purpose split in the international markets used in the con- sumer surplus analysis. 9.4 Modeling An additional research topic is to integrate investments in air transportation into general equilibrium models and demand-response analyses. These tasks are particularly worth- while if fees to air travelers or prices charged by airlines rise, and instead of consumers having more money from consumer surplus, airlines and airports have more money to invest in air- craft, air transportation support, and airport facilities. Benefits from increased fees or ticket prices to fund investments in airports will generally play out over time on-airport and off- airport, and may attract more travelers due to better facilities or more convenient services, even if prices rise. A CGE model can estimate impacts played out in the economy over time as additional construction is implemented, aircraft and other equipment is purchased and operated (and older equipment is retired), and additional operating funds are expended. How- ever, it should be noted that demand-response is not part of CGE model, and estimates of new passenger attraction would have to be estimated separately and then integrated into the model.
