Industry Crosswalks
Industry Crosswalks
The folder NAICS_and_SIC_Bridges.zip contains weighted crosswalk files for the purpose of bridging Standard Industrial Classification (SIC) codes and North American Industry Classification System (NAICS) codes. SIC codes were the standard industry classification system for decades, but they eventually couldn’t keep up with the changing industrial structure of the 1990s. NAICS codes took over in 1997 and quickly became the reporting system for most government statistics in the US and elsewhere. This switch poses a problem for researchers since it imposes an artificial break in time series data. Unweighted crosswalk tables can help connect the two systems, but the many splits and merges create mappings that are not one-to-one. For situations that require one-to-one translations, researchers find themselves guessing as to the best match. And for situations where splitting and merging is acceptable, choosing weights sometimes feels arbitrary. The crosswalks included here contain weighting variables that make it possible to smoothly bridge between systems and construct consistent time series in a nonarbitrary way. Three different weighting schemes are included. The first based on employment, the second based on number of establishments, and the third based on total payroll.
Download: NAICS_and_SIC_Bridges.zip
Please read documentation file before use. Please cite as:
Schaller, Zachary, and DeCelles, Paul. "Weighted Crosswalks for NAICS and SIC Industry Codes." Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2021-07-14. https://doi.org/10.3886/E145101V1.
Matching US cities to their respective counties is pretty easy if you are dealing with Census Designated Places (CDPs). Just use the awesome Geocorr tool at the Missouri Census Data Center. But there are a lot of unincorporated communities and named places that are simply not CDPs, and sometimes interesting things (like union elections) happen there. So if you are like me and your work deals with small town USA, check out SimpleMaps. And then check out this crosswalk supplement.
City_to_County_Crosswalk_Supplement.csv
City_Names_Dictionary.csv
It takes all the non CDPs from SimpleMaps that fall in more than one county and provides weights that are the estimated shares of a city in each respective county. It also contains a bunch of additional places that were not in SimpleMaps or Geocorr. Places like military bases and old mining towns. Keep in mind that it is not a comprehensive list, just a collection of places I've encountered over time (last update August 2024).
The other file above is a city names dictionary that I have found useful for dealing with misspellings and alternative names for places. It also maps neighborhood names into the larger city/municipality the neighborhood lies in, e.g., North Hollywood, CA is matched to Los Angeles, CA. New York City places are mapped to their respective Boroughs.
Methodology: Geocorr constructs weights from population estimates, and latitude and longitude from population weighted centroids; SimpleMaps from the centroid point in the boundary polygon. Unfortunately, tiny places do not have readily available population data or boundary shape files. To create the estimated weights, I worked with a research assistant to manually view satellite images of the places and eyeball the proportion of the place that landed in one side or the other. Admittedly not the most sophisticated approach, but effective nonetheless. Latitude and longitude values are whatever SimpleMaps provided for the cities that straddled borders, and from GeoHack for additional places that I include. Remember to read-in the FIPS column as a character/string so that leading zeros are not inadvertently dropped!
Shoutout to my RA, Brooke Painter, for helping me with this!
For my purposes, I merged the Geocorr stuff, the SimpleMaps stuff, and this supplement. I can't share the full combined crosswalks on here, but I am happy to send them to you if you shoot me an email request. Ask for City_to_County_Crosswalk_Weighted.csv and City_to_County_Crosswalk_Nonweighted.csv