Dear Statalist!
I have a dataset that covers loan applications from 2012 to 2017. The columns include information on both the loan (e.g., the interest rate, loan duration, loan amount) and the borrower (e.g., income, employment status, gender, age). Using a regression approach, I want to investigate whether gender has an effect on the interest rate of a loan.
I have two different specifications of the regression model. The DV is the interest rate in both models. In the first model, I include a gender dummy (0 = male, 1 = female) and a set of loan and borrower-level controls. The second models uses the same gender and control variables as in the first model but here I add year and country fixed effects. For both models, I use the reghdfe command with vce(robust). In the first model, I use the noabsorb option and in the second model absorb(year country).
When I look at the coefficient of the gender dummy in the first model, it is negative but not statistically significant. However, in the second specification where I include year and country fixed effects the coefficient flips sign and becomes statistically significant. I do not quite yet grasp how the inclusion of the fixed effects contribute to the flipping of the sign and the coefficient becoming statistically significant. What could be an explanation? Or what further analyses or testing could I do to figure this out?
Many thanks!
I have a dataset that covers loan applications from 2012 to 2017. The columns include information on both the loan (e.g., the interest rate, loan duration, loan amount) and the borrower (e.g., income, employment status, gender, age). Using a regression approach, I want to investigate whether gender has an effect on the interest rate of a loan.
I have two different specifications of the regression model. The DV is the interest rate in both models. In the first model, I include a gender dummy (0 = male, 1 = female) and a set of loan and borrower-level controls. The second models uses the same gender and control variables as in the first model but here I add year and country fixed effects. For both models, I use the reghdfe command with vce(robust). In the first model, I use the noabsorb option and in the second model absorb(year country).
When I look at the coefficient of the gender dummy in the first model, it is negative but not statistically significant. However, in the second specification where I include year and country fixed effects the coefficient flips sign and becomes statistically significant. I do not quite yet grasp how the inclusion of the fixed effects contribute to the flipping of the sign and the coefficient becoming statistically significant. What could be an explanation? Or what further analyses or testing could I do to figure this out?
Many thanks!
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