IDEAS home Printed from https://ideas.repec.org/a/tsj/stataj/v11y2011i3p439-459.html
   My bibliography  Save this article

GMM estimation of the covariance structure of longitudinal data on earnings

Author

Listed:
  • Aedın Doris

    (National University of Ireland–Maynooth)

  • Donal O’Neill

    (National University of Ireland–Maynooth)

  • Olive Sweetman

    (National University of Ireland–Maynooth)

Abstract

In this article, we discuss generalized method of moments estimation of the covariance structure of longitudinal data on earnings, and we introduce and illustrate a Stata program that facilitates the implementation of the generalized method of moments approach in this context. The program, gmmcovearn, estimates a variety of models that encompass those most commonly used by labor economists. These include models where the permanent component of earnings follows a random growth or random walk process and where the transitory component can follow either an AR(1) or an ARMA(1,1) process. In addition, time-factor loadings and cohort-factor loadings may be incorporated in the transitory and permanent components.

Suggested Citation

  • Aedın Doris & Donal O’Neill & Olive Sweetman, 2011. "GMM estimation of the covariance structure of longitudinal data on earnings," Stata Journal, StataCorp LP, vol. 11(3), pages 439-459, September.
    • Handle: RePEc:tsj:stataj:v:11:y:2011:i:3:p:439-459
    Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj11-3/st0239/
    as

    Download full text from publisher

    File URL: http://www.stata-journal.com/article.html?article=st0239
    File Function: link to article purchase
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Winford H. Masanjala & Chris Papageorgiou, 2008. "Rough and lonely road to prosperity: a reexamination of the sources of growth in Africa using Bayesian model averaging," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 671-682.
    2. Valentino Dardanoni & Giuseppe De Luca & Salvatore Modica & Franco Peracchi, 2012. "A generalized missing-indicator approach to regression with imputed covariates," Stata Journal, StataCorp LP, vol. 12(4), pages 575-604, December.
    3. Carmen Fernandez & Eduardo Ley & Mark F. J. Steel, 2001. "Model uncertainty in cross-country growth regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(5), pages 563-576.
    4. Magnus, Jan R. & Wan, Alan T.K. & Zhang, Xinyu, 2011. "Weighted average least squares estimation with nonspherical disturbances and an application to the Hong Kong housing market," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1331-1341, March.
    5. repec:hal:journl:peer-00815561 is not listed on IDEAS
    6. Danilov, D.L. & Magnus, J.R., 2002. "Estimation of the Mean of a Univariate Normal Distribution When the Variance is not Known," Discussion Paper 2002-77, Tilburg University, Center for Economic Research.
    7. Ley, Eduardo & Steel, Mark F.J., 2007. "Jointness in Bayesian variable selection with applications to growth regression," Journal of Macroeconomics, Elsevier, vol. 29(3), pages 476-493, September.
    8. Dardanoni, Valentino & Modica, Salvatore & Peracchi, Franco, 2011. "Regression with imputed covariates: A generalized missing-indicator approach," Journal of Econometrics, Elsevier, vol. 162(2), pages 362-368, June.
    9. Dmitry Danilov, 2005. "Estimation of the mean of a univariate normal distribution when the variance is not known," Econometrics Journal, Royal Economic Society, vol. 8(3), pages 277-291, December.
    10. Magnus, Jan R. & Powell, Owen & Prüfer, Patricia, 2010. "A comparison of two model averaging techniques with an application to growth empirics," Journal of Econometrics, Elsevier, vol. 154(2), pages 139-153, February.
    11. Xavier Sala-I-Martin & Gernot Doppelhofer & Ronald I. Miller, 2004. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach," American Economic Review, American Economic Association, vol. 94(4), pages 813-835, September.
    12. Jan R. Magnus, 2002. "Estimation of the mean of a univariate normal distribution with known variance," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 225-236, June.
    13. Danilov, Dmitry & Magnus, J.R.Jan R., 2004. "On the harm that ignoring pretesting can cause," Journal of Econometrics, Elsevier, vol. 122(1), pages 27-46, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mirko Felchner, 2015. "Einkommensdynamik bei Selbständigen als Freie Berufe und abhängig Beschäftigte Eine dynamische Paneldatenschätzung mit Daten des Sozio-oekonomischen Panels," FFB-Discussionpaper 101, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)), LEUPHANA University Lüneburg.
    2. Mishra, Aswini Kumar & Gupta, Akul & Bhardwaj, Vedant, 2022. "Permanent inequality versus earnings instability and transmission of income shocks to consumption expenditure in India," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 80-91.
    3. Aedín Doris & Donal O’Neill & Olive Sweetman, 2013. "Identification of the covariance structure of earnings using the GMM estimator," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 11(3), pages 343-372, September.
    4. Olga Bondarenko, 2018. "The Redistributive Effects of Monetary Policy Across Generations," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 244, pages 44-60.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Giuseppe De Luca & Jan R. Magnus, 2011. "Bayesian model averaging and weighted-average least squares: Equivariance, stability, and numerical issues," Stata Journal, StataCorp LP, vol. 11(4), pages 518-544, December.
    2. Magnus, Jan R. & Powell, Owen & Prüfer, Patricia, 2010. "A comparison of two model averaging techniques with an application to growth empirics," Journal of Econometrics, Elsevier, vol. 154(2), pages 139-153, February.
    3. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    4. Judith Anne Clarke, 2017. "Model Averaging OLS and 2SLS: An Application of the WALS Procedure," Econometrics Working Papers 1701, Department of Economics, University of Victoria.
    5. Magnus, J.R. & Powell, O.R. & Prüfer, P., 2008. "A Comparison of Two Averaging Techniques with an Application to Growth Empirics," Other publications TiSEM 0392dffa-51e0-4bc9-9644-f, Tilburg University, School of Economics and Management.
    6. Jan R. Magnus & Wendun Wang & Xinyu Zhang, 2016. "Weighted-Average Least Squares Prediction," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1040-1074, June.
    7. Rockey, James & Temple, Jonathan, 2016. "Growth econometrics for agnostics and true believers," European Economic Review, Elsevier, vol. 81(C), pages 86-102.
    8. De Luca, Giuseppe & Magnus, Jan R. & Peracchi, Franco, 2022. "Sampling properties of the Bayesian posterior mean with an application to WALS estimation," Journal of Econometrics, Elsevier, vol. 230(2), pages 299-317.
    9. Giuseppe Luca & Jan R. Magnus & Franco Peracchi, 2023. "Weighted-Average Least Squares (WALS): Confidence and Prediction Intervals," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1637-1664, April.
    10. Moral-Benito, Enrique, 2010. "Model averaging in economics," MPRA Paper 26047, University Library of Munich, Germany.
    11. Dardanoni, Valentino & De Luca, Giuseppe & Modica, Salvatore & Peracchi, Franco, 2015. "Model averaging estimation of generalized linear models with imputed covariates," Journal of Econometrics, Elsevier, vol. 184(2), pages 452-463.
    12. Marcin Błażejowski & Jacek Kwiatkowski & Jakub Gazda, 2019. "Sources of Economic Growth: A Global Perspective," Sustainability, MDPI, vol. 11(1), pages 1-14, January.
    13. León-González, Roberto & Montolio, Daniel, 2015. "Endogeneity and panel data in growth regressions: A Bayesian model averaging approach," Journal of Macroeconomics, Elsevier, vol. 46(C), pages 23-39.
    14. Aiyar, Shekhar & Duval, Romain & Puy, Damien & Wu, Yiqun & Zhang, Longmei, 2018. "Growth slowdowns and the middle-income trap," Japan and the World Economy, Elsevier, vol. 48(C), pages 22-37.
    15. Crespo Cuaresma, Jesus & von Schweinitz, Gregor & Wendt, Katharina, 2019. "On the empirics of reserve requirements and economic growth," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 253-274.
    16. Bruns, Stephan B. & Ioannidis, John P.A., 2020. "Determinants of economic growth: Different time different answer?," Journal of Macroeconomics, Elsevier, vol. 63(C).
    17. Valentino Dardanoni & Giuseppe De Luca & Salvatore Modica & Franco Peracchi, 2012. "A generalized missing-indicator approach to regression with imputed covariates," Stata Journal, StataCorp LP, vol. 12(4), pages 575-604, December.
    18. Cohen-Cole, Ethan B. & Durlauf, Steven N. & Rondina, Giacomo, 2012. "Nonlinearities in growth: From evidence to policy," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 42-58.
    19. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
    20. Eicher, Theo S. & Papageorgiou, Chris & Roehn, Oliver, 2007. "Unraveling the fortunes of the fortunate: An Iterative Bayesian Model Averaging (IBMA) approach," Journal of Macroeconomics, Elsevier, vol. 29(3), pages 494-514, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tsj:stataj:v:11:y:2011:i:3:p:439-459. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum or Lisa Gilmore (email available below). General contact details of provider: http://www.stata-journal.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.