Journal article

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

BP2-STS

  • Grossmann, Volker ORCID University of Fribourg, Fribourg, Switzerland; CESifo, Munich , Germany; IZA, Bonn , Germany; CReAM, London , United Kingdom
  • Osikominu, Aderonke University of Hohenheim, Stuttgart, Germany; IAB, New York, United States of America; CESifo, Munich, Germany; IZA, Bonn, Germany; CEPR, London, United Kingdom
  • 2019
Published in:
  • German Economic Review. - Walter de Gruyter GmbH. - 2019, vol. 20, no. 4, p. e831-e851
English 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, the foremost, 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.
Faculty
Faculté des sciences économiques et sociales et du management
Department
Département d'économie politique
Language
  • English
Classification
Economics
License
Rights reserved
Open access status
green
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/322914
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