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      Endogeneity: A Review and Agenda for the Methodology-Practice Divide Affecting Micro and Macro Research

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          Abstract

          An expanding number of methodological resources, reviews, and commentaries both highlight endogeneity as a threat to causal claims in management research and note that practices for addressing endogeneity in empirical work frequently diverge from the recommendations of the methodological literature. We aim to bridge this divergence, helping both macro and micro researchers understand fundamental endogeneity concepts by: (1) defining a typology of four distinct causes of endogeneity, (2) summarizing endogeneity causes and methods used in management research, (3) organizing the expansive methodological literature by matching the various methods to address endogeneity to the appropriate resources, and (4) setting an agenda for future scholarship by recommending practices for researchers and gatekeepers about identifying, discussing, and reporting evidence related to endogeneity. The resulting review builds literacy about endogeneity and ways to address it so that scholars and reviewers can better produce and evaluate research. It also facilitates communication about the topic so that both micro- and macro-oriented researchers can understand, evaluate, and implement methods across disciplines.

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          Common method biases in behavioral research: A critical review of the literature and recommended remedies.

          Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.
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            Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

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              Initial conditions and moment restrictions in dynamic panel data models

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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Journal of Management
                Journal of Management
                SAGE Publications
                0149-2063
                1557-1211
                January 2021
                October 14 2020
                January 2021
                : 47
                : 1
                : 105-143
                Affiliations
                [1 ]University of Florida
                [2 ]Iowa State University
                [3 ]Oklahoma State University
                [4 ]University of Indiana
                Article
                10.1177/0149206320960533
                3d14fe70-8db8-401e-bd3f-970c7acfacac
                © 2021

                http://journals.sagepub.com/page/policies/text-and-data-mining-license


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