Many instruments: Implementation in Stata

Abstract

In recent decades, econometric tools for handling instrumental-variable regressions characterized by many instruments have been developed. We introduce a command, mivreg, that implements consistent estimation and testing in linear instrumental-variables regressions with many (possibly weak) instruments. mivreg covers both homoskedastic and heteroskedastic environments, estimators that are both nonrobust and robust to error nonnormality and projection matrix limit, and parameter tests and specification tests both with and without correction for existence of moments. We also run a small simulation experiment using mivreg and illustrate how mivreg works with real data.

Female Underperformance Hypothesis Revisited: Methodological Review and Empirical Testing

“…Our strategy for identifying the presence of endogenous variables includes a set of statistics that test for endogeneity, the weak-instrument problem, and overidentifying restrictions. If an endogeneity problem is not present in the model, the OLS estimator is more efficient than the model, including instrumental variables (Anatolyev & Skolkova, 2019). Therefore, it is essential to compare both estimators to evaluate which is more efficient (OLS vs. 2SLS).…”

It’s a matter of confidence. Institutions, government stability and economic outcomes

“…The proposed solution is aFuller (1977) like estimator with standard errors that are robust to heteroskedasticity and many instruments. Recently,Anatolyev and Skolkova (2019) have made available a Stata command that performs the H-FUL estimator: mivreg.12 We acknowledge that the use of panel data techniques would make the empirical analysis more robust. However, there is in general very little variation of constitutional systems at country level, and our data are no exception to this.…”