Implementations of tests on the exogeneity of selected variables and their performance in practice

In order to consistently estimate a causal economic relationship at least as many exogenous non-explanatory instrumental variables are required as there are endogenous explanatory variables. This thesis studies various techniques that can be used to classify selected variables as either exogenous or endogenous. These techniques are of great importance as they provide guidance regarding avoiding inconsistency and enhancing efficiency of estimators of the causal effects. Various implementations are first examined in the context of models for cross-section data and subsequently for dynamic panel data models. In addition to standard techniques some more refined alternatives are proposed. The results are used to re-examine various popular studies.