Dear all,

I would like to ask for help in interpreting the coefficient of OLS and the coefficient of the PPML Gravity model. My dependent variable is tax payments. I used the log of tax payment for OLS estimation. Meanwhile, for estimation using the PPML Gravity model, I used tax payment (without using log). I used PPML estimation due to many zero-tax payments in my data.
I use ordinary least squares (OLS) with the following specification:

yi = α + β1 〖T1〗i + β2 〖T2〗i + β3 T3〗i + γXi + εi

where outcome yi is log of tax payment; 〖T1〗_i, 〖T2〗_i, and 〖T3〗_i are binary variables indicating the treatment messages (T1 = deterrence, T2 = trust, and T3 = reciprocity) respectively, for individual i; X_i is a vector of control variable comprising taxpayers' observable characteristics (gender, age, location, and status); and ε_i is an error term.

Results after running my model for OLS (log of tax payments)

β1 = 0.6476
β2 = 0.1849
β3 = 0.1471

Results after running my model for PPML (tax payments)

β1 = 1.1088
β2 = 0.3181
β3 = 0.2505


Iam so lost and I hope somebody can help me on how to interpret this coefficient. Thank you so much.

Best,

Krisnanto