Correcting Selection Bias in Innovation and Entrepreneurship Research: A Practical Guide to Applying the Heckman Two-Stage Estimation

41 Pages Posted: 23 May 2022

See all articles by David Bendig

David Bendig

University of Münster

Jonathan Hoke

University of Münster

Date Written: May 10, 2022

Abstract

Concerns about selection bias in empirical innovation and entrepreneurship research receive an increasing relevance and awareness. Mitigating a selection bias can significantly improve the validity of an empirical study and help identify causal inferences. The Heckman two-stage estimation emerged as a powerful method to detect and mitigate sample-induced endogeneity. Our meta-study finds numerous examples in the innovation and entrepreneurship literature where the Heckman two-stage estimation is applied incorrectly and incompletely. We sense considerable confusion concerning theoretical assumptions and methodological aspects in this context. For that reason, this paper offers a practical and comprehensible guide to applying Heckman’s technique. The guide supports scholars and practitioners regardless of their econometrical expertise by offering stepwise descriptions and elaborating on common econometric difficulties.

Keywords: Causal inferences; endogeneity; Heckman estimation; selection bias; two-step estimator; research methods

Suggested Citation

Bendig, David and Hoke, Jonathan, Correcting Selection Bias in Innovation and Entrepreneurship Research: A Practical Guide to Applying the Heckman Two-Stage Estimation (May 10, 2022). Available at SSRN: https://ssrn.com/abstract=4105207 or http://dx.doi.org/10.2139/ssrn.4105207

David Bendig

University of Münster ( email )

Schlossplatz 2
Muenster, D-48149
Germany

Jonathan Hoke (Contact Author)

University of Münster ( email )

Schlossplatz 2
Muenster, D-48149
Germany

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
87
Abstract Views
201
rank
414,851
PlumX Metrics