Let the Data Speak? On the Importance of Theory-Based Instrumental Variable Estimations
Volker Grossmann () and
Aderonke Osikominu ()
Additional contact information
Aderonke Osikominu: University of Hohenheim
No 12080, IZA Discussion Papers from Institute of Labor Economics (IZA)
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
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Working Paper: Let the Data Speak? On the Importance of Theory-Based Instrumental Variable Estimations (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:iza:izadps:dp12080
Ordering information: This working paper can be ordered from
IZA, Margard Ody, P.O. Box 7240, D-53072 Bonn, Germany
Access Statistics for this paper
More papers in IZA Discussion Papers from Institute of Labor Economics (IZA) IZA, P.O. Box 7240, D-53072 Bonn, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Holger Hinte ().