After responding to the points raised by some of my colleagues last week about the ACS 2004 data, I have received two more comments. The first one is from Richard Lin, who is hoping that the quality of the ACS data by Census 2010 will be “equal or even better” than that of the long-form. This is not possible because the proposed larger sample size of 2005-2009 (Full Nationwide Implementation) is about 70 percent of the sample size of the long-form. Even if Congress approves funding for five years as requested by the CB, the quality of the ACS data will be lower than the census long-form because of many other reasons, including the ACS sample is weighted to an estimated population rather than census, might not include group quarters population, excludes the impacts of significant discontinuities in population and employment characteristics, and is not conducted in one year. In addition, the CB is promising to provide us with TAZ or Census Tract level data after five year accumulation of ACS data. According to sampling theory, the sampling errors in the ACS data at the zonal level will be much greater than that at the county level. We all love to have accurate current TAZ level data for our planning studies but this won’t happen because of the limitations of the proposed ACS methodology and data collection procedures. Finally, I would like to ask this question. If you are working for the City of Oakland, CA and you know that the City is growing, which population number would you prefer for 2004: Census 2000 of 399,000 or ACS estimated number of 365,000? Glen Ahlert suggested to perform a liner regression on the annual ACS data with respect to year for the areas that are undergoing continual population or employment growth. Then interpolate or extrapolate to the year of interest, than to average the annual ACS data. He also stated correctly that regression analysis won’t be reliable for areas that experienced significant discontinuities in land use and transportation development. I don’t think the CB will accept such a method because it does not work for the whole country.