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    A principal components approach to cross-section dependence in panels

    Coakley, Jerry and Fuertes, A.M. and Smith, Ron (2002) A principal components approach to cross-section dependence in panels. In: 10th International Conference on Panel Data, 2002, Berlin, Germany. (Unpublished)

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    Abstract

    The use of GLS to deal with cross-section dependence in panels is not feasible where N is large relative to T since the disturbance covariance matrix is rank deficient. Neither is it the appropriate response if the dependence results from omitted global variables or common shocks correlated with the included regressors. These can be proxied by the principal components of the residuals from a baseline regression. It is shown that the OLS estimates from a regression augmented by these principal components are unbiased and consistent using sequential limits for large T, large N. Simulations show that this leads to a substantial reduction in bias even for relatively small T and N panels. An empirical application indicates that the impact of cross section dependence seems to strengthen the case for long run PPP.

    Metadata

    Item Type: Conference or Workshop Item (Paper)
    School: School of Business, Economics & Informatics > Economics, Mathematics and Statistics
    Depositing User: Sarah Hall
    Date Deposited: 20 Oct 2020 18:19
    Last Modified: 20 Oct 2020 18:19
    URI: https://eprints.bbk.ac.uk/id/eprint/41050

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