Causality and Endogeneity
John AntonakisBusiness and Economics, University of LausanneSamuel BendahanBusiness and Economics, University of LausannePhilippe JacquartThe Wharton School, University of PennsylvaniaRafael LaliveBusiness and Economics, University of Lausanne
2014en
ABI
Abstract
Most leadership and management researchers ignore one key design and estimation problem rendering parameter estimates uninterpretable: Endogeneity. We discuss the problem of endogeneity in depth and explain conditions that engender it using examples grounded in the leadership literature. We show how consistent causal estimates can be derived from the randomized experiment, where endogeneity is eliminated by experimental design. We then review the reasons why estimates may become biased (i.e., inconsistent) in non-experimental designs and present a number of useful remedies for examining causal relations with non-experimental data. We write in intuitive terms using nontechnical language to make this chapter accessible to a large audience.
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Cited by 20 references