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    Identification of the covariance structure of earnings using the GMM estimator


    O'Neill, Donal (2013) Identification of the covariance structure of earnings using the GMM estimator. Journal of Economic Inequality, 11. pp. 343-372. ISSN 1569-1721

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    Abstract

    In recent years there has been a rapid growth in the number of studies that have used the GMM estimator to decompose the earnings covariance structure into its permanent and transitory parts. Using a heterogeneous growth model of earnings, we consider the performance of the estimator in this context. We use Monte Carlo simulations to examine the sensitivity of parameter identification to key features such as panel length, sample size, the degree of persistence of earnings shocks and the specification of the earningsmodel. We show that long panels allow the identification of the model, even when persistence in transitory shocks is high. Short panels, on the other hand, are insufficient to identify individual parameters of the model even with moderate levels of persistence.

    Item Type: Article
    Keywords: Identification; GMM; Covariance structure of earnings;
    Academic Unit: Faculty of Social Sciences > Economics, Finance and Accounting
    Item ID: 8692
    Identification Number: https://doi.org/10.1007/s10888-012-9216-5
    Depositing User: Donal O'Neill
    Date Deposited: 28 Aug 2017 09:40
    Journal or Publication Title: Journal of Economic Inequality
    Publisher: Springer Verlag
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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