I have a dataset that covers loan applications from the year 2012 to 2017. It also includes information on the borrower (e.g., age, income, employment status) and information on the loan (loan duration, loan amount, interest rate).
I have a regression where the main independent variable of interest is a gender dummy (1 = female) and the dependent variable is a loan interest rate. I run two specifications of this model. In the first I include, besides the gender dummy, a set of borrower- and loan-level control variables. The second model is identical to the first one, but here I add year and country fixed effects.
In the first model, the coefficient of the gender dummy is negative and statistically insignificant. In the second model, the coefficient of the gender dummy now becomes positive and statistically significant. Can someone help my grasp why the sign of the coefficient flips when adding the year and country fixed effects to the model and why it becomes significant? Or what kind of further testing or analysis I can do to figure this out myself?