I am new to econometrics and want to verify that I have the correct precise interpretation for the coefficients in my two models.


1. The dependent variable is the % change in workplace mobility. My primary coefficient of interest in the DID framework is: income_category * post, where income_category categorizes all the countries in my sample (n=113) into either a low, low-middle, upper-middle, or high income country and post is a binary variable the designates the time period before/after a policy was implemented. Upper-income countries are the reference group.

The coefficient for low-income * post is 13.27*** and I think that be interpreted as:

Low-income countries’ workplace mobility is, on average, 13.27 percentage points higher than upper-income countries’ workplace mobility after the policy was implemented. The regression coefficient is statistically significant at the 0.01 level, meaning that there is a probability of 0.01 that this result is not due to chance.


2. In the second regression the dependent variable is growth rate and again my primary independent variable of interest is the same income_category * post variable described above.

The coefficient in this model for low-income * post is 2.655*** and I think that is interpreted as:

Low-income countries’ growth rate is, on average, 2.665 percentage points higher than upper-income countries’ growth rate after the policy was implemented. The regression coefficient is statistically significant at the 0.01 level, meaning that there is a probability of 0.01 that this result is not due to chance.


Are my precise interpretations correct?