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

40 Pages Posted: 28 Jan 2019

See all articles by Volker Grossmann

Volker Grossmann

University of Fribourg - Faculty of Economics and Social Science; Institute for the Study of Labor (IZA); CESifo (Center for Economic Studies and Ifo Institute)

Aderonke Osikominu

University of Hohenheim

Multiple version iconThere are 2 versions of this paper

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

JEL Classification: C10, C36, O11

Suggested Citation

Grossmann, Volker and Osikominu, Aderonke, Let the Data Speak? On the Importance of Theory-Based Instrumental Variable Estimations. IZA Discussion Paper No. 12080. Available at SSRN: https://ssrn.com/abstract=3323195

Volker Grossmann (Contact Author)

University of Fribourg - Faculty of Economics and Social Science ( email )

Fribourg, CH 1700
Switzerland

Institute for the Study of Labor (IZA)

P.O. Box 7240
Bonn, D-53072
Germany

CESifo (Center for Economic Studies and Ifo Institute)

Poschinger Str. 5
Munich, DE-81679
Germany

Aderonke Osikominu

University of Hohenheim ( email )

Stuttgart
Germany

Register to save articles to
your library

Register

Paper statistics

Downloads
5
Abstract Views
31
PlumX Metrics