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    Testing for Slope Heterogeneity Bias in Panel Data Models

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    Author
    Campello, Murillo
    Galvao, Antonio F.
    Juhl, Ted
    Affiliation
    Univ Arizona, Dept Econ
    Issue Date
    2018-06-18
    Keywords
    Bias
    Corporate investment
    Fixed effects
    Individual heterogeneity
    Slope heterogeneity
    Testing
    
    Metadata
    Show full item record
    Publisher
    AMER STATISTICAL ASSOC
    Citation
    Murillo Campello, Antonio F. Galvao & Ted Juhl (2019) Testing for Slope Heterogeneity Bias in Panel Data Models, Journal of Business & Economic Statistics, 37:4, 749-760, DOI: 10.1080/07350015.2017.1421545
    Journal
    JOURNAL OF BUSINESS & ECONOMIC STATISTICS
    Rights
    Copyright © 2019 American Statistical Association Journal of Business & Economic Statistics.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Standard econometric methods can overlook individual heterogeneity in empirical work, generating inconsistent parameter estimates in panel data models. We propose the use of methods that allow researchers to easily identify, quantify, and address estimation issues arising from individual slope heterogeneity. We first characterize the bias in the standard fixed effects estimator when the true econometric model allows for heterogeneous slope coefficients. We then introduce a new test to check whether the fixed effects estimation is subject to heterogeneity bias. The procedure tests the population moment conditions required for fixed effects to consistently estimate the relevant parameters in the model. We establish the limiting distribution of the test and show that it is very simple to implement in practice. Examining firm investment models to showcase our approach, we show that heterogeneity bias-robust methods identify cash flow as a more important driver of investment than previously reported. Our study demonstrates analytically, via simulations, and empirically the importance of carefully accounting for individual specific slope heterogeneity in drawing conclusions about economic behavior.
    Note
    12 month embargo; published online: 18 June 2018
    ISSN
    0735-0015
    DOI
    10.1080/07350015.2017.1421545
    Version
    Final accepted manuscript
    ae974a485f413a2113503eed53cd6c53
    10.1080/07350015.2017.1421545
    Scopus Count
    Collections
    UA Faculty Publications

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