Hey Jim: Krishnan and Ed are correct and on target. The 2012-2016 and forthcoming 2017-2021 CTPP do NOT include the “extended workplace allocation”. Previous packages (1990?, 2000, and 2006/2010) DID have extended workplace allocation. Allocation is the Census Bureau term for missing value imputation. “Standard Workplace Allocation” is Census-speak for “primary imputation”. This process imputes workplace location down to the county, place and MCD level. (Imputation down to MCD-level is evident in “strong MCD” states such as Vermont. Vermont has 255 MCDs, and 184 Census Tracts!) The standard allocation is needed for the Census Bureau to provide county-to-county commute patterns to OMB for purposes of defining metropolitan areas. “Extended Workplace Allocation” is “secondary imputation” down to the TAZ, TAD and Tract levels. My recommendation: Factor up the 2012-2016 CTPP commuter flows (TAZ-to-TAZ, TAD-to-TAD, tract-to-tract) to match county-to-county-by-mode control totals. Compare commute length frequency distributions before and after this “grossing up” process. It’s an in-elegant imputation procedure. Also, use household travel survey data on home-based-work trips per worker (or home-work-home tours per worker, in activity models) to factor up workers to “observed home-based work trips” or “observed home-work-home tours”. Normalize the 2012-2016 data to a single year estimate, say, 2013 or 2014 or 2015. Use published single-year ACS data on workers by county-of-residence, county-of-work, and intra-county workers. Use the single-year ACS PUMS data for inter-county commute controls. An alternative to normalizing to a particular year, say, 2014, would be to use the single-year ACS PUMS at the PUMA of residence to PUMA of work (POWPUMA). Since POWPUMAs are always counties, the result would be a somewhat rectangular commute matrix of PUMAs-to-counties (by means of transportation). Unless you have really small counties (<100,000 population) which muddies up the analysis. In my ideal world, you’d somehow have your population microsimulation software create a base year (say, 2014) commuter matrix at a very detailed geographic level, that is somehow “trained” by data from the CTPP, published ACS data, and PUMS. And somewhere along the line it would be useful to integrate the Census Bureau’s LEHD data into the jumble. I would recommend the statistical software package “R” for census data analyses, including the packages tidycensus, lehdr, and ctppr (hopefully we’ll see a ctppr package that will handle the new 2017-21 CTPP). I would recommend the iPUMS (eh-PUMS) site to retrieve PUMS data. And the iPUMS project “NHGIS” for retrieving older, pre-2000 census data. Actually, I’d recommend trying out the tidycensus for PUMS data, as well. That’s about all I have for now. Chuck Purvis Hayward, California The 2012-2016 CTPP