TY  - RPRT
        AU  - Grossmann, Volker
AU  - Osikominu, Aderonke
        TI  - Let the Data Speak? On the Importance of Theory-Based Instrumental Variable Estimations
        PY  - 2019/Jan/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 12080
        UR  - https://www.iza.org/index.php/publications/dp12080
        AB  - In absence of randomized controlled experiments, identification is often aimed via instrumental variable (IV) strategies, typically two-stage least squares estimations. According to Bayes' rule, however, under a low ex ante probability that a hypothesis is true (e.g. that an excluded instrument is partially correlated with an endogenous regressor), the interpretation of the estimation results may be fundamentally flawed. This paper argues that rigorous theoretical reasoning is key to design credible identification strategies, aforemost finding candidates for valid instruments. We discuss prominent IV analyses from the macro-development literature to illustrate the potential benefit of structurally derived IV approaches.
        KW  - Bayes' Rule
KW  - economic development
KW  - identification
KW  - instrumental variable estimation
KW  - macroeconomic theory
        ER  -