2003
DOI: 10.1177/1476127003001001218
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Correcting for Endogeneity in Strategic Management Research

Abstract: The field of strategic management is predicated fundamentally on the idea that managements' decisions are endogenous to their expected performance implications. Yet, based on a review of more than a decade of empirical research in the Strategic Management Journal, we find that few papers econometrically correct for such endogeneity. In response, we now describe the endogeneity problem for cross-sectional and panel data, referring specifically to management's choice among discrete strategies with continuous per… Show more

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Cited by 1,104 publications
(897 citation statements)
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References 25 publications
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“…A failure to statistically correct for this endogeneity may not only lead to biased estimates, but also to faulty conclusions about our key propositions (Hamilton & Nickerson, 2003). If manufacturers who produce PLs self-select themselves and/or are selected by the discounter on the basis of unobservable characteristics that affect both shelf presence and PL production, a problem of selection bias may arise.…”
Section: Modelmentioning
confidence: 99%
“…A failure to statistically correct for this endogeneity may not only lead to biased estimates, but also to faulty conclusions about our key propositions (Hamilton & Nickerson, 2003). If manufacturers who produce PLs self-select themselves and/or are selected by the discounter on the basis of unobservable characteristics that affect both shelf presence and PL production, a problem of selection bias may arise.…”
Section: Modelmentioning
confidence: 99%
“…Thus participation in an IC broadcast search problem solving process does not occur randomly but is instead predicated on endogenous choices made by individual solvers. Therefore, any regression analysis that does not take into account the self-selection decisions of individuals will result in biased coefficient estimates due to omitted variables that affect both the decision to participate and the resulting outcome (Hamilton and Nickerson 2003).…”
Section: Section 5 Estimation Strategymentioning
confidence: 99%
“…The relevance of the instrument variables is obtained by the Fstatistic of the instruments which was 12.5. After estimating the first stage probit model with branching as a dependent variable, we generated the Inverse Mills Ratio in STATA 9.0 using the code by Hamilton and Nickerson (2003). In the second-stage model, we introduce the Inverse Mills Ratio in place of the branching variable as an instrumented branching variable.…”
Section: Robustnessmentioning
confidence: 99%