Match 1860-1920 census data to county subdivisions in 2010 TIGER shapefile

Dear users of this forum,

I am trying to match IPUMS censusdata from 1860-1920 to the county subdivisions in a 2010 TIGER shapefile I downloaded from NHGIS. For some areas county subdivisions were stable from around 1860 to 2010 - that I have checked using historical maps and the names of the county subdivisions in the shapefile (for others not, of course).

Now, the GSIJOIN codes do of course not work since they are meant for merging the geographical units in the 2010 shapefile to 2010 census data. It would be great to at least find a common identifier for the counties in the two files since then I would only have to match the string names of the county subdivisions within the individual counties. As I understand the COUNTYFP10 (shapefile) and the COUNTY (census data) codes are not comparable. Is there any way to find out how COUNTYFP10 converts to the COUNTY code (however imperfectly)?

Any help on this would be greatly appreciated. Thank you!

Because IPUMS-USA uses an integrated code structure to identify counties across time, the COUNTY codes that are appropriate for counties in 2010 should identify the same county backwards in time. COUNTY codes from IPUMS-USA and the GISJOIN codes from NHGIS differ only very slightly. Using the ICPSR County Code list excel document, you can concatenate the values of STATEFIP and COUNTY (appending a G) with the following formula: =CONCATENATE(“G”, TEXT( STATEFIP , “00”), TEXT( COUNTY , “00000”)). This will accurately pad the values to match the format of GISJOIN. This does not create a perfect match, and you should pay special attention to Maryland and Nevada as noted in theCOUNTY User Note, but this should get you most of the way there. I attached a text version of the attribute table for the 2010 county shapefile which you can use to verify the matches between your STATEFIP COUNTY concatenation and the GISJOIN values.
I hope this helps.

US_county_2010_attri.txt (722 KB)

Great, thank you so much! This is working well, all counties can be matched.

Now I tried to match the county subdividions within these counties. This, unfortunately, is not working well at all. I am using the “mcd” code given in the census data and assigned the names from the excel file that is provided on the ipums-page for the “mcd”-variable. Then I tried to match based on these strings with the variable NAMES10 from the TIGER shapefile. I hardly get any matches. The reason does not seem to be that names have different spelling, different case or other such obvious issues. Rather, the names are entirely different.

When I look at historical maps county subdivisions and their names are for many areas very similar to those in the 2010 TIGER shapefile. Do you have any information on how the mcdname variable was created, any map material? Do you know any way how I could match the data to the county subdivisions using the “mcd” code and the numerical codes given in the shapefile?

First, it is important to be sure you are using the correct State codes. The Codes for Minor Civil Divisions and Incorporated Municipalities spreadsheet (called FIPS_codes.xls) lists STATEICP codes whereas the NHGIS files use FIPS codes. The relationship between STATEICP and STATEFIP is listed below. Also, the same county differences need to be accounted for here. So in the NHGIS shapefile, the Bethel Connecticut MCD is in STATEFP10==9 and COUTNYFP10==1, while in the IPUMS-USA file Bethel Connecticut is in STATEICP==1 and COUNTY==10. Even when using the accurate State and County codes it will be difficult to match the MCD labels to those found in the NHGIS file as they have been modified to apply over time. However, portions of the codes should match enough to make it clear. For instance, for Autaugaville Alabama (NHGIS: STATEFP10==1 COUTNYFP10==1 \ IPUMS-USA: STATEICP==41 COUNTY==10) is labeled “PRECINCT 3, AUTAUGAVILLE.” I hope this helps.
STATEICP STATEFIP

| 1 | 9 |
| 2 | 23 |
| 3 | 25 |
| 4 | 33 |
| 5 | 44 |
| 6 | 50 |
| 11 | 10 |
| 12 | 34 |
| 13 | 36 |
| 14 | 42 |
| 21 | 17 |
| 22 | 18 |
| 23 | 26 |
| 24 | 39 |
| 25 | 55 |
| 31 | 19 |
| 32 | 20 |
| 33 | 27 |
| 34 | 29 |
| 35 | 31 |
| 36 | 38 |
| 37 | 46 |
| 40 | 51 |
| 41 | 1 |
| 42 | 5 |
| 43 | 12 |
| 44 | 13 |
| 45 | 22 |
| 46 | 28 |
| 47 | 37 |
| 48 | 45 |
| 49 | 48 |
| 51 | 21 |
| 52 | 24 |
| 53 | 40 |
| 54 | 47 |
| 56 | 54 |
| 61 | 4 |
| 62 | 8 |
| 63 | 16 |
| 64 | 30 |
| 65 | 32 |
| 66 | 35 |
| 67 | 49 |
| 68 | 56 |
| 71 | 6 |
| 72 | 41 |
| 73 | 53 |
| 81 | 2 |
| 82 | 15 |
| 98 | 11

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