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  • DiD models with continuous treatment versions

    Hi all,

    I am examining how job security perception updating in response to unemployment rate shocks differ by mental health status. I have so far used fixed effects linear regression models, regressing job security satisfaction ratings (ranging from 0-10) on the past 6-month average local unemployment rate (a continuous variable), including individual, region, and year fixed effects, and estimating separate models by mental health status, defined as a dummy variable indicating poor or fair mental health.

    I am also interested in looking into whether any of the new difference-in-differences models with continuous treatment versions would be applicable in this case, where all individuals would be treated but with different intensities over time? But I am unsure of a specific approach that I can use. Would anyone familiar with these new methods be able to provide any guidance?

    Thank you very much.


  • #2
    Email Sant'Anna or Calloway (or maybe Jeff Wooldridge has thoughts on this). DID in binary treatments is involved, with continuous treatments I'm sure the details get a lot more complicated.

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