Guidebook for Developing Subnational Commodity Flow Data (2013) / Chapter Skim
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Pages 116-135
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From page 116... ...
116 Developing Subnational Commodity Flow Data Using Disaggregation 5.1 Introduction This section provides an examination of how to develop subnational commodity flow data using data disaggregation. The disaggregation of freight flow data is the process of taking a preexisting freight flow database and dividing it into further detail to generate a more refined freight flow database.
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From page 117... ...
Developing Subnational Commodity Flow Data Using Disaggregation 117 Each of these four elements focuses on different aspects of data disaggregation. For transportation agencies that are considering hiring a contractor to disaggregate FAF or TRANSEARCH data, reading the "Key Considerations" section of each step will likely provide enough information for the generation of an RFP on the topic.
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From page 118... ...
118 Guidebook for Developing Subnational Commodity Flow Data data often includes allocating freight flows from these default regions to regions that are compatible with state and metropolitan-level planning regions such as counties, zip codes, or TAZs. FAF data can be obtained at http://ops.fhwa.dot.gov/freight/freight_analysis/faf/index.htm.
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Developing Subnational Commodity Flow Data Using Disaggregation 119 includes information on commercial vehicles registered by state along with truck type and operating characteristics for each state. VIUS was discontinued after the 2002 publication.
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120 Guidebook for Developing Subnational Commodity Flow Data Step 2 -- Determine Geographic Boundaries Key Considerations There are two geographies to consider when conducting a commodity flow disaggregation. First, is the desired geographic unit the most conducive for freight planning activities?
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From page 121... ...
Developing Subnational Commodity Flow Data Using Disaggregation 121 It is generally recommended that a geographic scale be selected that is as large as possible while still sufficiently refined to meet the planning objectives of the transportation planning agency. This recommendation is made because the accuracy of the data disaggregation decreases as the geographic scale decreases.
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122 Guidebook for Developing Subnational Commodity Flow Data daily or average weekday estimates of truck trips and often even estimates of truck trips by time period. Another potential exception is if peak flows are desired.
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Developing Subnational Commodity Flow Data Using Disaggregation 123 peak week container volume is 9,070. Table 5.4 indicates that the peak day of the week is Tuesday with 1,070 (23 percent)
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124 Guidebook for Developing Subnational Commodity Flow Data Implementation Process To select a disaggregation variable, a thorough review of activity variables available at different geographies should be conducted for the region. As mentioned above, some of the most common variables that are used for disaggregation include employment, output, warehouse space, population, revenue, personal income, and geographic area.
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From page 125... ...
Developing Subnational Commodity Flow Data Using Disaggregation 125 • There also is often a wide variation of companies within a single industry even at refined levels of industry codes. For example, NAICS code 326111 is for Plastic Bag and Pouch Manufacturing, while NAICS code 326122 is for Plastics Pipe and Pipe Fitting Manufacturing and NAICS code 326211 is for Tire Manufacturing.
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From page 126... ...
126 Guidebook for Developing Subnational Commodity Flow Data administrative activities occur while the freight-related aspects of the employee's employment often occurs hundreds of miles away in a rural location. • At finer geographic levels, there are typically fewer employment categories available than desired.
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Developing Subnational Commodity Flow Data Using Disaggregation 127 Output (Gross Domestic Product)
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From page 128... ...
128 Guidebook for Developing Subnational Commodity Flow Data Implementation Process There are four disaggregation techniques that are discussed in this section: (1) geographic allocation, (2)
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Developing Subnational Commodity Flow Data Using Disaggregation 129 socioeconomic activity variables was identified. For other commodities, there was no variable that was found to have a strong predictive relationship with commodity flows.
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130 Guidebook for Developing Subnational Commodity Flow Data ∑= ( )
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Developing Subnational Commodity Flow Data Using Disaggregation 131 Select Industry Commodity C ro p P ro d u ct io n Percent of Total Fo re st ry a n d L og gi n g Percent of Total B as ic C h em ic al M an u fa ct u ri n g Percent of Total Basic chemicals 893 1% – 0% 28,779 34% Real estate 14,249 19% 115 1% 242 0% Support activities for agriculture and forestry 10,761 15% 2,811 14% – 0% Forestry and logging products – 0% 12,924 62% 22 0% Petroleum and coal products 4,476 6% 187 1% 6,233 7% Wholesale trade 4,491 6% 1,267 6% 5,054 6% Crop products 8,063 11% 5 0% 886 1% Agricultural chemicals 7,897 11% 29 0% 581 1% Monetary authorities, credit intermediation and related activities 6,415 9% 292 1% 344 0% Electric power generation, transmission, and distribution 2,681 4% 10 0% 3,697 4% Management of companies and enterprises – 0% – 0% 6,224 7% Natural gas distribution 683 1% 1 0% 3,455 4% Truck transportation 1,725 2% 471 2% 1,369 2% Scientific research and development services – 0% – 0% 2,850 3% Plastics and rubber products 738 1% 21 0% 1,501 2% Rights to nonfinancial intangible assets 118 0% 3 0% 2,076 2% Other fabricated metal products 67 0% 19 0% 1,543 2% Maintenance and repair construction 778 1% 32 0% 759 1% Rail transportation 451 1% 71 0% 866 1% Other commodities (products and services) 8,863 12% 2,562 12% 17,556 21% Total intermediate inputs 73,351 100% 20,819 100% 84,037 100% Compensation of employees 14,569 4,115 15,324 Taxes on production and imports, less subsidies (6,707)
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From page 132... ...
132 Guidebook for Developing Subnational Commodity Flow Data firms are constantly adjusting and substituting inputs as market conditions change, technologies change, labor productivity changes, prices for labor and equipment change, and the structure of the industry changes. This limitation is especially problematic if this type of modeling approach is applied to longer period forecasting.
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Developing Subnational Commodity Flow Data Using Disaggregation 133 commodity. We will assume that this region is composed of three counties: Aspen, Birch, and Cedar.
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134 Guidebook for Developing Subnational Commodity Flow Data demonstrated in a report prepared for FHWA (Cambridge Systematics 2009)
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Developing Subnational Commodity Flow Data Using Disaggregation 135 Then a proportional column adjustment occurs based on the new cell values derived from the previous row adjustment and relative to each column total. Thus, in order to arrive at the 5.55 value in the first row and column cell of Table 5.10, the row-adjusted value of 8.50 is divided by the column sum (35.25)
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