Sample selection bias and Heckman models in strategic management research

Research summary: The use of Heckman models by strategy scholars to resolve sample selection bias has increased by more than 700 percent over the last decade, yet significant inconsistencies exist in how they have applied and interpreted these models. In view of these differences, we explore the dri...

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Vydané v:Strategic management journal Ročník 37; číslo 13; s. 2639 - 2657
Hlavní autori: Certo, S. Trevis, Busenbark, John R., Woo, Hyun-soo, Semadeni, Matthew
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Chichester, UK John Wiley & Sons, Ltd 01.12.2016
Wiley Blackwell
Wiley Periodicals Inc
Predmet:
Bias
Decision making
Economic models
Effectiveness
endogeneity
Heckman models
research methods
sample selection bias
Sampling techniques
Selection bias
Statistical data
Strategic management
ISSN:0143-2095, 1097-0266
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Shrnutí:Research summary: The use of Heckman models by strategy scholars to resolve sample selection bias has increased by more than 700 percent over the last decade, yet significant inconsistencies exist in how they have applied and interpreted these models. In view of these differences, we explore the drivers of sample selection bias and review how Heckman models alleviate it. We demonstrate three important findings for scholars seeking to use Heckman models: First, the independent variable of interest must be a significant predictor in the first stage of a model for sample selection bias to exist. Second, the significance of lambda alone does not indicate sample selection bias. Finally, Heckman models account for sample-induced endogeneity, but are not effective when other sources of endogeneity are present. Managerial summary: When nonrandom samples are used to test statistical relationships, sample selection bias can lead researchers to flawed conclusions that can, in turn, negatively impact managerial decision-making. We examine the use of Heckman models, which were designed to resolve sample selection bias, in strategic management research and highlight conditions when sample selection bias is present as well as when it is not. We also distinguish sample selection bias, a form of omitted variable (OV) bias, from more traditional OV bias, emphasizing that it is possible for models to have sample selection bias, traditional OV bias, or both. Accurately identifying the type(s) of OV bias present is essential to effectively correcting it. We close with several recommendations to improve practice surrounding the use of Heckman models.
Bibliografia:Appendix S1. Stata code
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ArticleID:SMJ2475
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ISSN:0143-2095
1097-0266
DOI:10.1002/smj.2475