In our Microsoft Excel add-in, CDXZipStream, there are three data feeds (CDXState, CDXCounty, and CDXCBSA) that provide population estimates for their respective geographies for each of the past ten years. (These data feeds are available in the CDXZipStream Premium and Premium ACS versions.) These population estimates are developed by the U.S. Census Bureau, and the entire time series of estimates beginning with the most recent decennial census is revised annually. Ultimately these provide an extremely accurate historical picture of population growth trends over the previous decade, a very useful piece of information for many industries ranging from home construction to car sales.
To access these population estimates within Microsoft Excel, select the first worksheet cell that starts your list of geographic locations. For instance, here is a list of counties in an Excel workbook:
When working with county lists, use the format "County|State", where a vertical bar delimiter is used to separate the county name and state two-letter abbreviation. When working with state lists, you must also use the state two-letter abbreviation. For Core-Based Statistical Areas (CBSA’s) use the five-digit designation by the Office of Management and Budget, which can be found on the census website. For instance, the Akron, Ohio CBSA has the five-digit designation 10420.
After selecting the first cell in the list, click on the CDXZipStream button on the main toolbar, and on the main dialog select the appropriate feed (in this case, CDXCounty) and desired years of estimated data:
Click “Get Data” and the requested data for the last ten years is returned to the worksheet (only partial data is shown here):
You can now use Excel’s calculational and charting capabilities to look for population trends. For instance, do you need to locate a franchise to take advantage of high population growth within a particular county, state, or CBSA? The combination of CDXZipStream and Microsoft Excel can quickly help you quantify trends that will allow you to make decisions based on hard, accurate data.