Empirical Legal Studies

F-test for Difference Between Two Coefficients in a Regression Estimation

To quickly summarize a discussion on the Stata Blog (here), for those seeking to test whether coefficients for two independent variables in the same regression estimation systematically differ from one another, the basic coding structure follows:

reg a b c

test b = c

A resulting F-test statistic that falls below your significance threshold implies that the difference between the coefficients for independent variables b and c is significant. Obviously, a suite of other post-estimation commands also exists for a host of other issues.

Non-Parametric Regression

While I haven't yet had a chance to use it myself, the recently-released Stata v.15 includes the npregress command. Nonparametric regression, similar to the more traditional parametric regression, predicts a mean of an outcome for a given set of covariates. What separates parametric and nonparametric models, however, includes assumptions about the functional form of the mean conditional on the covariates. In particular, unlike parametric models, "nonparametric regression makes no assumptions about the functional form." Thus, output from nonparametric models supports valid inferences "regardless of the true functional form."

A recent Stata Blog post (here) describes the new command in much greater detail and provides helpful comparisons illustrating output differences between parametric and nonparametric models.

Creating Parallel Trend Plots

Some helpful coding for generating "parallel" (or "stacked") trend plots for two separate variables over the same years is found in a recent exchange on the Statalist Forum (here). An example of the desired output follows.