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I am building a model to forecast unemployment using GDP, the CPI index and the industrial production index (INDPRO) as covariates. Since I am looking to use stationary time series, I gathered the percentage changes of each of these quantities such that the model now looks something like this:

%Unemployment = f(%GDP, %CPI, %INDPRO)

Is this an econometrically-sound model specification? Or should I use other data transformations since CPI and INDPRO are already expressed in percentages?

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  • $\begingroup$ To see the $%$ change in unemployment due to a $%$ chang in GDP or some other covariate one usually uses a log-log specification. $\endgroup$
    – tdm
    Nov 11, 2021 at 6:42
  • $\begingroup$ @tdm I see, thanks! Should other covariates (like for instance the federal funds rate) be included as logs as well or are they usually kept in their original format? $\endgroup$
    – T. Cowell
    Nov 11, 2021 at 10:20
  • $\begingroup$ These are already in percentages so I guess they should be kept in levels (but I'm not a macro-economist). $\endgroup$
    – tdm
    Nov 12, 2021 at 8:44

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