Filling in missing tract-level median household income data from 2021 ACS 5 yr estimates

I'm a graduate student working with ACS data for the first time, so I apologize in advance for any basic questions!

I'm working with tract-level median household income data from the 2021 ACS 5 year estimates for the city of San Francisco. 7 of my 240 focal census tracts are missing estimates (from what I can tell from the documentation, likely because there were too few survey respondents), and I want to fill in the missing data for the purpose of my analysis. 

My original thought was that I would fill in from past year's 5 yr estimates for the same tracts, applying a correction to account for inflation--ie I would fill in from 2020 estimates, and if that was missing, from 2019 estimates, etc. However, I was warned by a colleague that I should thinking about spatial correlation and not just temporal correlation. 

Is there a best practice method for filling in missing ACS tract level data? Any advice would be much appreciated!

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  • Hi Kelley--

    Your intuition is right. Median HH income might be missing (1) because Census redacted it, because of excessive MOE. (2) The other reason for a missing stat would be: if the tract has no households.

    In the first situation, I like your solution: Fill in a value from a prior year. The tracts data was collected during a 5-year survey window, so the 2016-20 stats and the 2017-21 stats should be in the same ballpark.  (of course: the 2016-20 data may have been redacted for the same reason, excessive MOE.)

    So, I'll offer my approach to creating placeholder values -- as ugly as it is. (Dear readers, do not @ me complaints.)  
    For placeholder values, analyze table B19001 : number of households in sixteen income levels. Analyze that table to find the 50th percentile category among estimated households.  Example: Tract 27145011600 does not have a published median HH income.  But table B19001 shows the median is in the range 75,000-99,999. I will use 87,500 as placeholder. (Or you can imagine a fancier approach.) 

    It's an ugly approach I'm suggesting. But if you really! need placeholders for your 7 missing tracts, consider it.

    --Todd Graham

  • One of my favorite expressions is "The perfect is the enemy of the good." It holds especially true when dealing with estimates.

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