Correcting for self-selection based endogeneity in management research: A review and empirical demonstration

Foundational to the discipline of management is the idea that organizational decisions are a function of expected outcomes; hence, the customary empirical approach to employ multivariate techniques that regress performance outcome variables on discrete measures of organizational choices (e.g., investments, trainings, strategies and other managerial decision variables) potentially suffer from self-selection based endogeneity bias. Selectioneffects represent an internal validity threat as they can lead to biased parameters that render erroneous empirical results and incorrect conclusions with regard to the veracity of theoretical assertions. Our review of the empirical literature suggests that the issue of selection-effects has received increasing attention in management; yet, the techniques to correct for selection-effects have not always been employed in the proper manner, thus estimations often suffer from design shortcomings that potentially render flawed empirical findings. We explain the nature of self-selection based endogeneity bias and review the techniques available to researchers in management to correct for selection-effects when organizational decisions are discrete in nature. Employing data on M&A investment decisions and rival-firm value reactions, we provide empirical examples that demonstrate the tradeoffs involved with the alternative techniques.