Using Commodity Flow Survey Microdata and Other Establishment Data to Estimate the Generation of Freight, Freight Trips, and Service Trips: Guidebook (2016) / Chapter Skim
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Pages 22-30
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22 This chapter provides a succinct overview of the models used in the guidebook, the data required, and the aggregation procedures that could be used to obtain estimates of FSA for conglomerates of commercial establishments (e.g., city blocks, TAZs)
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Modeling Methodology 23 • Employment Rate (ER) : This model type is used for situations in which the FSA metric bears a direct relation to establishment employment.
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24 Using Commodity Flow Survey Microdata and Other establishment Data to estimate the Generation of Freight, Freight trips, and Service trips FTG Rates by Employment Bin A modified version of model type C-ER mitigates the problem caused by the use of a constant FTG rate. This model computes FTG rates by employment bins (EB)
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Modeling Methodology 25 Complete Enumeration Recommended use: Complete enumeration is well suited to cases in which data are available for all establishments of interest and the number of establishments is relatively small. This technique is applicable to both linear and non-linear models.
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26 Using Commodity Flow Survey Microdata and Other establishment Data to estimate the Generation of Freight, Freight trips, and Service trips The accuracy of this procedure depends on how representative the small sample is. If the sample is representative of the population, the procedure will provide solid estimates of the overall level of FSA.
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Modeling Methodology 27 Substituting bEi from Equation 12 for fi in Equation 7 and taking b out of the summation term yields Equation 13: (13) 1 1 F E E Ei i n i i n ∑ ∑= β = β = β = = p Equation 13 shows that, if the underlying FSA pattern is proportional to employment, the total FSA could be obtained as the multiplication of the total employment (Ep)
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28 Using Commodity Flow Survey Microdata and Other establishment Data to estimate the Generation of Freight, Freight trips, and Service trips CFS Microdata The CFS is the most important source of freight demand data in the United States, and one of the oldest data collection programs in transportation. The CFS collects data on the movement of goods in the 50 states plus the District of Columbia.
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Modeling Methodology 29 Establishment Survey Data The final data source was a series of three datasets collected by RPI using establishment surveys. The first dataset -- assembled in 2006 as a part of a project conducted for the New York State Department of Transportation (New York State DOT)
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30 Using Commodity Flow Survey Microdata and Other establishment Data to estimate the Generation of Freight, Freight trips, and Service trips Limitations The guidebook models are a significant step forward, offering some of the best models available, but they have some limitations. Among their limitations are the following: • Lack of geographic diversity in the estimation data.
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