ArellanoBlundellBis

ArellanoBlundellBis is a statistical method used in econometrics to estimate the causal effect of a treatment or intervention on an outcome variable. It is particularly useful in settings where the treatment assignment is not random, and there are potential confounders that could bias the estimate. The method was developed by Manuel Arellano, David Blundell, and Xavier Bis. It is an extension of the Arellano-Bond estimator, which is used for panel data with endogenous regressors.

The ArellanoBlundellBis estimator is based on the idea of using instrumental variables to control for the endogeneity of the regressors. In the context of panel data, this means using a variable that is correlated with the treatment but uncorrelated with the error term to instrument for the endogenous regressors. The estimator is consistent and asymptotically normal, making it a reliable tool for estimating causal effects in the presence of endogeneity.

The ArellanoBlundellBis estimator has been widely used in empirical research in economics and other social sciences. It has been applied to a variety of settings, including labor economics, health economics, and education economics. The method has also been extended to handle more complex data structures, such as clustered data and data with multiple treatments.

In summary, ArellanoBlundellBis is a powerful tool for estimating causal effects in the presence of endogeneity. It is based on the idea of using instrumental variables to control for the endogeneity of the regressors, and it has been widely used in empirical research in economics and other social sciences. The method is consistent and asymptotically normal, making it a reliable tool for estimating causal effects in a variety of settings.