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Split-Panel Jackknife Estimation of Fixed-Effect Models

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  • Geert Dhaene
  • Koen Jochmans

    (Département d'économie)

Abstract

Maximum-likelihood estimation of nonlinear models with fixed effects is subject to the incidental-parameter problem. This typically implies that point estimates suffer from large bias and confidence intervals have poor coverage. This paper presents a jackknife method to reduce this bias and to obtain confidence intervals that are correctly centered under rectangular-array asymptotics. The method is explicitly designed to handle dynamics in the data and yields estimators that are straightforward to implement and that can be readily applied to a range of models and estimands. We provide distribution theory for estimators of index coefficients and average effects, present validity tests for the jackknife, and consider extensions to higher-order bias correction and to two-step estimation problems. An empirical illustration on female labor-force participation is also provided.

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Paper provided by Sciences Po Departement of Economics in its series Sciences Po Economics Discussion Papers with number 2014-03.

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Date of creation: Mar 2014
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Handle: RePEc:spo:wpecon:info:hdl:2441/f6h8764enu2lskk9p2m9mgp8l

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Keywords: bias reduction; dependent data; incidental-parameter problem; jackknife; nonlinear model;

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Cited by:
  1. Dennis Kristensen & Bernard Salanie, 2010. "Higher Order Improvements for Approximate Estimators," Discussion Papers 0910-15, Columbia University, Department of Economics.
  2. 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.
  3. 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.
  4. Alexander Chudik & M. Hashem Pesaran, 2013. "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Globalization and Monetary Policy Institute Working Paper 146, Federal Reserve Bank of Dallas.
  5. Laura Hospido, 2007. "Modelling heterogeneity and dynamics in the volatility of individual wages," Banco de Espa�a Working Papers 0738, Banco de Espa�a.
  6. Geert Dhaene & Koen Jochmans, 2011. "Profile-score Adjustements for Nonlinearfixed-effect Models," Sciences Po publications info:hdl:2441/eu4vqp9ompq, Sciences Po.
  7. 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.
  8. 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.
  9. Francis Vella & Ivan Fernandez-Val, 2007. "Bias Corrections for Two-Step Fixed Effects Panel Data Estimators," Boston University - Department of Economics - Working Papers Series WP2007-010, Boston University - Department of Economics.
  10. 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.
  11. 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.
  12. repec:spo:wpecon:info:hdl:2441/eu4vqp9ompqllr09j0031f620 is not listed on IDEAS
  13. 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).
  14. 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.
  15. Iván Fernández-Val & Martin Weidner, 2013. "Individual and time effects in nonlinear panel models with large N,T," CeMMAP working papers CWP60/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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