While payroll taxes are paid in the county of employment, personal income taxes on that same income are paid in the county of residence, and these two places differ for commuters. Additionally, household demand is generated at the location of the household (that is, at the employee’s place of residence). Therefore, a proper measure of regional and inter-regional induced effects requires accounting for these inter-regional flows of employment-based income. IMPLAN derives region specific commuting flows as described below.
It should be noted that while IMPLAN accounts for commuting precisely so that more spending is kicked off in the place of residence than in the place of work, where that spending ultimately occurs is based largely on IMPLAN’s trade flow model. For example, suppose that an employee in Mecklenburg County, NC lives in neighboring Rowan County and therefore takes his Employee Compensation less payroll taxes (unofficially termed “Commuter EC” for the purposes of this article) home with him to Rowan County, where he then pays personal income taxes on that income. Now suppose that this individual likes to go bowling, but there is no bowling alley in Rowan County. These bowling expenditures occur back in Mecklenburg County. Thus, while the commuting data ensure that the employee’s demand originates in the place of residence, the fulfillment of that demand may occur in the place of work (or any number of other counties).
COUNTY COMMUTING DATA
Initial estimates of Commuter EC between counties is derived from U.S. Census data. The Census Bureau's Journey-To-Work (JTW) data provide information on commuting flows of people from county-of-residence to county-of-employment (including commuting to the same county as residence, or intra-commuting). IMPLAN combines the Census county-to-county commuting data with IMPLAN's own annual estimates of county-level Commuter EC to estimate flows of compensation from the county in which compensation is earned back to the county of residence. Commuter EC is the remaining portion of Employee Compensation (EC) once payroll taxes and foreign commuting are removed. This adjustment needs to be made as payroll taxes are paid in the region in which compensation is earned and foreign commuting is treated as a leakage from the model. On the question of foreign commuting, IMPLAN uses U.S. level data on worker earnings that flow out of and into the country, from NIPA, distributed to states and counties based on EC and household income, respectively.
Unfortunately, the Census's JTW data are lagged compared to IMPLAN's annual Commuter EC estimates. Therefore, IMPLAN turns to the BEA REA data on earnings flows, which while only providing in- and out-flow data for a region and not its flow partner, are more up-to-date. As the JTW data include intra-flows and the REA gross flows data do not, IMPLAN also utilizes REA data on earnings by place of work to derive intra flows. These data (the gross in- and out-flows and the intra-flows) are used as controls in a matrix RAS of the Commuter EC previously derived from the JTW data. As the REA data are also lagged, IMPLAN does not control strictly to their values. Once completed, updated coefficients of commuting flows are derived, which are applied to annual county-level Commuter EC values.
The resulting county level commuting flows are utilized in the generation of regional SAMs. Their inclusion allows for the calculation of the share of regionally generated compensation that leaks from the region (i.e., the region’s in-commuting rate).
The in-commuting rate is then used to determine leakages of EC in a region. For example, a region with a 25% in-commuting rate will see 25% of earned EC stemming from an impact analysis treated as leakage from the local economy.
The Commuter EC data are also utilized in Multi-Regional Input-Output analysis (MRIO); Commuter EC outflows from a region to linked model regions generate induced effects in the linked model regions. To continue with the prior example, if the entirety of the 25% in-commuting rate in the direct effect region represented commuters from the linked region, then the entirety of the 25% leaked Commuter EC in the direct effect region would be treated as additional household income in the linked region.
Note, in-commuting rates are region specific but not Industry specific. If your analysis of an Industry requires that you adjust the in-commuting rate, please see our article on adjusting compensation to account for a known in-commuting rate.
ZIP CODE & CONGRESSIONAL DISTRICTS COMMUTING DATA
Flows of Commuter EC (EC less payroll taxes) between zip codes are calculated by distributing the flows of Commuter EC between the Counties to which those zip codes belong among those zip codes. The shares for out-flows of Commuter EC are based on total EC generated by each zip code in the county, while the shares for in-flows of Commuter EC are based on total receipts of EC less payroll taxes by households in each of the zip codes. Commuter EC flows for zip code-based regions like Congressional Districts or custom city models are simply sums of the component zip codes’ Commuter EC flows.
Video: The RAS Technique
Written December 2, 2019