Personal Comsumption Expenditures

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    DougO
    All county PCE expenditures are controlled to the current year BEA NIPA accounts for PCE. A bridge table distributing the NIPA PCE categories to the IMPLAN sectors is based on a similar worktable from the BEA I-O benchmark. Data for the spending patterns for each of the income classes come from the BLS consumer expenditure survey (CES). These income classes are controlled to current year US total personal income and to the bridged NIPA PCE for the current year. Dividing each of the spending patterns by the number of US households gives us a spending pattern for the average household in each income class. The number of households by income class for each county (data from Census) is multiplied through the average for each of the respective income classes. The resulting vectors are controlled to personal income for each of the counties and the US NIPA PCE controls in turn (a RAS). The number of households for each income class is unique to each county, but the spending patterns per household are national average. What households buy locally versus importing is based on the region's RPCs. The zip code files have a proportion of the county household spending based on the zip code files' proportionate share of the number of households by income class (from the deciennial census ztma data - a ratio of the zip code ztmas data divided by the data for all ztmas for the county). There are no immediate plans to change the procedures.
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    DougO
    All county PCE expenditures are controlled to the current year BEA NIPA accounts for PCE. A bridge table distributing the NIPA PCE categories to the IMPLAN sectors is based on a similar worktable from the BEA I-O benchmark. Data for the spending patterns for each of the income classes come from the BLS consumer expenditure survey (CES). These income classes are controlled to current year US total personal income and to the bridged NIPA PCE for the current year. Dividing each of the spending patterns by the number of US households gives us a spending pattern for the average household in each income class. The number of households by income class for each county (data from Census) is multiplied through the average for each of the respective income classes. The resulting vectors are controlled to personal income for each of the counties and the US NIPA PCE controls in turn (a RAS). The number of households for each income class is unique to each county, but the spending patterns per household are national average. What households buy locally versus importing is based on the region's RPCs. The zip code files have a proportion of the county household spending based on the zip code files' proportionate share of the number of households by income class (from the deciennial census ztma data - a ratio of the zip code ztmas data divided by the data for all ztmas for the county). There are no immediate plans to change the procedures.
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