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Estimation of Dynamic Nonlinear Random Effects Models with Unbalanced Panels

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  • Pedro Albarran
  • Raquel Carrasco
  • Jesus M. Carro

Abstract

This paper presents estimation methods for dynamic nonlinear models with correlated random effects (CRE) when having unbalanced panels. Unbalancedness is often encountered in applied work and ignoring it in dynamic nonlinear models produces inconsistent estimates even if the unbalancedness process is completely at random. We show that selecting a balanced panel from the sample can produce efficiency losses or even inconsistent estimates of the average marginal effects. We allow the process that determines the unbalancedness structure of the data to be correlated with the permanent unobserved heterogeneity. We discuss how to address the estimation by maximizing the likelihood function for the whole sample and also propose a Minimum Distance approach, which is computationally simpler and asymptotically equivalent to the Maximum Likelihood estimation. Our Monte Carlo experiments and empirical illustration show that the issue is relevant. Our proposed solutions perform better both in terms of bias and RMSE than the approaches that ignore the unbalancedness or that balance the sample.

Suggested Citation

  • Pedro Albarran & Raquel Carrasco & Jesus M. Carro, 2019. "Estimation of Dynamic Nonlinear Random Effects Models with Unbalanced Panels," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(6), pages 1424-1441, December.
    • Handle: RePEc:bla:obuest:v:81:y:2019:i:6:p:1424-1441
    DOI: 10.1111/obes.12308
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    References listed on IDEAS

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    1. Jesus M. Carro & Alejandra Traferri, 2014. "State Dependence And Heterogeneity In Health Using A Bias‐Corrected Fixed‐Effects Estimator," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(2), pages 181-207, March.
    2. Rabe-Hesketh, Sophia & Skrondal, Anders, 2013. "Avoiding biased versions of Wooldridge’s simple solution to the initial conditions problem," Economics Letters, Elsevier, vol. 120(2), pages 346-349.
    3. Arellano, Manuel & Honore, Bo, 2001. "Panel data models: some recent developments," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.),Handbook of Econometrics, edition 1, volume 5, chapter 53, pages 3229-3296, Elsevier.
    4. Manuel Arellano, 2003. "Discrete choices with panel data," Investigaciones Economicas, Fundación SEPI, vol. 27(3), pages 423-458, September.
    5. Campa, Jose Manuel, 2004. "Exchange rates and trade: How important is hysteresis in trade?," European Economic Review, Elsevier, vol. 48(3), pages 527-548, June.
    6. Wiji Arulampalam & Mark B. Stewart, 2009. "Simplified Implementation of the Heckman Estimator of the Dynamic Probit Model and a Comparison with Alternative Estimators," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(5), pages 659-681, October.
    7. Mark B. Stewart, 2007. "The interrelated dynamics of unemployment and low-wage employment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 511-531.
    8. Carro, Jesus M., 2007. "Estimating dynamic panel data discrete choice models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 503-528, October.
    9. Bester, C. Alan & Hansen, Christian, 2009. "A Penalty Function Approach to Bias Reduction in Nonlinear Panel Models with Fixed Effects," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 131-148.
    10. Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," Review of Economic Studies, Oxford University Press, vol. 47(1), pages 225-238.
    11. Paul Contoyannis & Andrew M. Jones & Nigel Rice, 2004. "The dynamics of health in the British Household Panel Survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(4), pages 473-503.
    12. Dean R. Hyslop, 1999. "State Dependence, Serial Correlation and Heterogeneity in Intertemporal Labor Force Participation of Married Women," Econometrica, Econometric Society, vol. 67(6), pages 1255-1294, November.
    13. Randall K. Q. Akee & William E. Copeland & Gordon Keeler & Adrian Angold & E. Jane Costello, 2010. "Parents' Incomes and Children's Outcomes: A Quasi-experiment Using Transfer Payments from Casino Profits," American Economic Journal: Applied Economics, American Economic Association, vol. 2(1), pages 86-115, January.
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    Cited by:

    1. Chris Muris & Pedro Raposo & Sotiris Vandoros, 2020. "A dynamic ordered logit model with fixed effects," Papers 2008.05517, arXiv.org.
    2. Beusch, Elisabeth & Van Soest, Arthur, 2020. "A dynamic multinomial model of self-employment in the Netherlands," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 5-32.
    3. Lucchetti, Riccardo & Pigini, Claudia, 2017. "DPB: Dynamic Panel Binary Data Models in gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i08).
    4. Chrysanthou, Georgios Marios & Guilló, María Dolores, 2018. "The dynamics of political party support and egocentric economic evaluations: The Scottish case," European Journal of Political Economy, Elsevier, vol. 52(C), pages 192-213.
    5. Carro, Jesús M. & Albarrán, Pedro & Carrasco, Raquel, 2020. "Using Stata to estimate dynamic correlated random effectsprobit models with unbalanced panels," UC3M Working papers. Economics 30116, Universidad Carlos III de Madrid. Departamento de Economía.
    6. Chrysanthou, Georgios Marios & Guilló, María Dolores, 2016. "The Dynamics of Heterogeneous Political Party Support and Egocentric Economic Evaluations: the Scottish Case," QM&ET Working Papers 16-3, University of Alicante, D. Quantitative Methods and Economic Theory.

    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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