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I am looking for neighborhood level data on employment statistics. Specifically, I would like the number of unemployed individuals and the number of individuals who found jobs each month for each neighborhood. I would prefer to define "neighborhood" as geographically small as possible (I'm thinking census tract).

If there is a data set for just one city (Chicago or New York), that would be good enough.

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  • You can find data at the neighborhood level but not as frequent as you want, and you can find monthly data for larger geographical areas. I wonder how accurate a model you could make by combining these. You could test the model by seeing how well you can predict a neighborhood sample from the prior neighborhood sample and the most recent monthly coarse-grained data.
    – Ed Staub
    Apr 24, 2015 at 21:35
  • @EdStaub I would love to try to estimate that model. Where are such data available?
    – gannawag
    Apr 24, 2015 at 21:37
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    I'm not the best person to ask, but you can find down to the tract level, 5-year data (and maybe 3-year, didn't check, but not 1-year) here at the American Community Survey. I believe this is available in a bulk downloadable form, but don't have time to chase it. Monthly data by city is available from the Bureau of Labor Statistics here.
    – Ed Staub
    Apr 24, 2015 at 23:41

2 Answers 2

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You will not find such observed data at such a small geographic level in the public sphere. Apart from small area estimation models that predict the proportion in an area based on indirect information, no such data surveys the population with enough of a sample that can sufficiently monitor the unemployed in a small area each and every month.

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Cambridge, MA has data at the neighborhood level at https://data.cambridgema.gov/Neighborhood-Census-Data/2007-2011-Median-Income-by-Neighborhood/ujy3-unjj. The methodology is as follows:

These median incomes were estimated in a two step process. Income related blockgroup data from the 2007-2011 American Community Survey recompiled by the Cambridge Community Development Department to align with approximate neighborhood boundaries. Median values were then interpolated for each geographic area from the compiled distribution of incomes.

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