The perils of endogeneity and instrumental variables in strategy research: Understanding through simulations

Matthew Semadeni, Michael C. Withers, Samuel Certo

Research output: Contribution to journalArticle

176 Scopus citations


In this paper we use simulations to examine how endogeneity biases the results reported by ordinary least squares (OLS) regression. In addition, we examine how instrumental variable techniques help to alleviate such bias. Our results demonstrate severe bias even at low levels of endogeneity. Our results also illustrate how instrumental variables produce unbiased coefficient estimates, but instrumental variables are associated with extremely low levels of statistical power. Finally, our simulations highlight how stronger instruments improve statistical power and that endogenous instruments can report results that are inferior to those reported by OLS regression. Based on our results, we provide a series of recommendations for scholars dealing with endogeneity.

Original languageEnglish (US)
Pages (from-to)1070-1079
Number of pages10
JournalStrategic Management Journal
Issue number7
StatePublished - Jul 2014



  • endogeneity
  • instrumental variables
  • ordinary least squares
  • simulations
  • strategy research

ASJC Scopus subject areas

  • Business and International Management
  • Strategy and Management

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