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Let the Data Speak? On the Importance of Theory-Based Instrumental Variable Estimations

Volker Grossmann () and Aderonke Osikominu ()
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Aderonke Osikominu: University of Hohenheim

No 12080, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: 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.

Keywords: Bayes' Rule; economic development; identification; instrumental variable estimation; macroeconomic theory (search for similar items in EconPapers)
JEL-codes: C10 C36 O11 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2019-01
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