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Split-panel jackknife estimation of fixed-effect models

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  • DHAENE, Geert

    ()
    (K.U.Leuven, Department of Economics, B-3000 Leuven, Belgium)

  • JOCHMANS, Koen

    ()
    (Center for Operations Research and Econometrics (CORE), Université catholique de Louvain (UCL), Louvain la Neuve, Belgium)

Abstract

We propose a jackknife for reducing the order of the bias of maximum likelihood estimates of nonlinear dynamic fixed-effect panel models. In its simplest form, the half-panel jackknife, the estimatorisjust 2θˆ−θ1/2,where θˆ!istheMLEfromthefullpaneland θ1/2 istheaverageofthe two half-panel MLEs, each using T/2 time periods and all N cross-sectional units. This estimatoreliminates the first-order bias of θˆ . The order of the bias is further reduced if two partitions of the panel are used, for example, two half-panels and three 1/3-panels, and the corresponding MLEs.On further partitioning the panel, any order of bias reduction can be achieved. The split-panel jackknife estimators are asymptotically normal, centered at the true value, with variance equal to that of the MLE under asymptotics where T is allowed to grow slowly with N. In analogous fashion, the split-panel jackknife reduces the bias of the profile likelihood and the bias of marginal-effect estimates. Simulations in fixed-effect dynamic discrete-choice models with small T show that the split-panel jackknife effectively reduces the bias and mean squared error of the MLE, and yields confidence intervals with much better coverage.

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Bibliographic Info

Paper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2010003.

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Date of creation: 01 Jan 2010
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Handle: RePEc:cor:louvco:2010003

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Keywords: jackknife; asymptotic bias correction; dynamic panel data; fixed effects;

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Citations

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Cited by:
  1. Iván Fernández-Val & Frank Vella, 2007. "Bias corrections for two-step fixed effects panel data estimators," CeMMAP working papers CWP04/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  2. Alexander Chudik & M. Hashem Pesaran, 2013. "Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Data Models with Weakly Exogenous Regressors," CESifo Working Paper Series 4232, CESifo Group Munich.
  3. Geert Dhaene & Koen Jochmans, 2011. "Profile-score Adjustements for Nonlinearfixed-effect Models," Sciences Po publications info:hdl:2441/eu4vqp9ompq, Sciences Po.
  4. Dennis Kristensen & Bernard Salanie, 2013. "Higher-order properties of approximate estimators," CeMMAP working papers CWP45/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  5. L. Hospido, 2012. "Modelling heterogeneity and dynamics in the volatility of individual wages," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(3), pages 386-414, 04.
  6. Alessandra Casarico & Paola Profeta & Chiara Pronzato, 2012. "On the local labor market determinants of female university enrolment in European regions," Carlo Alberto Notebooks 278, Collegio Carlo Alberto.
  7. Fernández-Val, Iván & Savchenko, Yevgeniya & Vella, Francis, 2013. "Evaluating the Role of Individual Specific Heterogeneity in the Relationship Between Subjective Health Assessments and Income," IZA Discussion Papers 7651, Institute for the Study of Labor (IZA).
  8. Alexander Chudik & M. Hashem Pesaran, 2013. "Large panel data models with cross-sectional dependence: a survey," Globalization and Monetary Policy Institute Working Paper 153, Federal Reserve Bank of Dallas.
  9. Sun, Yixiao & Kim, Min Seong, 2009. "k-step Bootstrap Bias Correction for Fixed Effects Estimators in Nonlinear Panel Models," University of California at San Diego, Economics Working Paper Series qt9gn6n5mr, Department of Economics, UC San Diego.
  10. Dennis Kristensen & Bernard Salanie, 2010. "Higher Order Improvements for Approximate Estimators," Discussion Papers 0910-15, Columbia University, Department of Economics.
  11. Marcus J Chambers & Maria Kyriacou, 2010. "Jackknife Bias Reduction in the Presence of a Unit Root," Economics Discussion Papers 685, University of Essex, Department of Economics.
  12. Alvaro Escribano & Szabolcs Blazsek, 2012. "Patents, secret innovations and firm's rate of return : differential effects of the innovation leader," Economics Working Papers we1202, Universidad Carlos III, Departamento de Economía.
  13. Hyungsik Roger Moon & Martin Weidner, 2013. "Dynamic linear panel regression models with interactive fixed effects," CeMMAP working papers CWP63/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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