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State dependence and heterogeneity in health using a bias corrected fixed effects estimator

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  • Carro, Jesús M.
  • Traferri, Alejandra

Abstract

This paper considers the estimation of a dynamic ordered probit of self-assessed health status with two fixed effects: one in the linear index equation and one in the cut points. The two fixed effects allow us to robustly control for heterogeneity in unobserved health status and in reporting behaviour, even though we can not separate both sources of heterogeneity. The contributions of this paper are twofold. First it contributes to the literature that studies the determinants and dynamics of Self-Assessed Health measures. Second, this paper contributes to the recent literature on bias correction in nonlinear panel data models with fixed effects by applying and studying the finite sample properties of two of the existing proposals to our model. The most direct and easily applicable correction to our model is not the best one, and has important biases in our sample sizes

Suggested Citation

  • Carro, Jesús M. & Traferri, Alejandra, 2011. "State dependence and heterogeneity in health using a bias corrected fixed effects estimator," UC3M Working papers. Economics we1118, Universidad Carlos III de Madrid. Departamento de Economía.
    • Handle: RePEc:cte:werepe:we1118
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    1. Rilstone, Paul & Srivastava, V. K. & Ullah, Aman, 1996. "The second-order bias and mean squared error of nonlinear estimators," Journal of Econometrics, Elsevier, vol. 75(2), pages 369-395, December.
    2. Andrew M. Jones & Stefanie Schurer, 2011. "How does heterogeneity shape the socioeconomic gradient in health satisfaction?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(4), pages 549-579, June.
    3. Timothy J. Halliday, 2008. "Heterogeneity, state dependence and health," Econometrics Journal, Royal Economic Society, vol. 11(3), pages 499-516, November.
    4. 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.
    5. ,, 2004. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 20(2), pages 427-429, April.
    6. Jinyong Hahn & Whitney Newey, 2004. "Jackknife and Analytical Bias Reduction for Nonlinear Panel Models," Econometrica, Econometric Society, vol. 72(4), pages 1295-1319, July.
    7. 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.
    8. Blundell,Richard & Newey,Whitney K. & Persson,Torsten (ed.), 2007. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9780521871532.
    9. ,, 2004. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 20(1), pages 223-229, February.
    10. Victor Chernozhukov & Iván Fernández‐Val & Jinyong Hahn & Whitney Newey, 2013. "Average and Quantile Effects in Nonseparable Panel Models," Econometrica, Econometric Society, vol. 81(2), pages 535-580, March.
    11. Blundell,Richard & Newey,Whitney & Persson,Torsten (ed.), 2007. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9780521871549.
    12. Blundell,Richard & Newey,Whitney & Persson,Torsten (ed.), 2007. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9780521692106.
    13. Hahn, Jinyong & Kuersteiner, Guido, 2011. "Bias Reduction For Dynamic Nonlinear Panel Models With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 27(6), pages 1152-1191, December.
    14. 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.
    15. Lindeboom, Maarten & van Doorslaer, Eddy, 2004. "Cut-point shift and index shift in self-reported health," Journal of Health Economics, Elsevier, vol. 23(6), pages 1083-1099, November.
    16. Rilstone, Paul & Ullah, Aman, 2005. "Corrigendum to "The second-order bias and mean squared error of nonlinear estimators": [Journal of Econometrics 75(2) (1996) 369-395]," Journal of Econometrics, Elsevier, vol. 124(1), pages 203-204, January.
    17. Manuel Arellano & Jinyong Hahn, 2016. "A likelihood-Based Approximate Solution to the Incidental Parameter Problem in Dynamic Nonlinear Models with Multiple Effects," Global Economic Review, Taylor & Francis Journals, vol. 45(3), pages 251-274, July.
    18. Blundell,Richard & Newey,Whitney K. & Persson,Torsten (ed.), 2007. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9780521692090.
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    Cited by:

    1. Johannes S. Kunz & Kevin E. Staub & Rainer Winkelmann, 2021. "Predicting individual effects in fixed effects panel probit models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 1109-1145, July.
    2. Geert Dhaene & Koen Jochmans, 2015. "Split-panel Jackknife Estimation of Fixed-effect Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(3), pages 991-1030.
    3. repec:hal:wpspec:info:hdl:2441/f6h8764enu2lskk9p2m9mgp8l is not listed on IDEAS
    4. Fernández-Val, Iván & Savchenko, Yevgeniya & Vella, Francis, 2017. "Evaluating the role of income, state dependence and individual specific heterogeneity in the determination of subjective health assessments," Economics & Human Biology, Elsevier, vol. 25(C), pages 85-98.
    5. repec:hal:spmain:info:hdl:2441/eu4vqp9ompqllr09ij4j0h0h1 is not listed on IDEAS
    6. 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.
    7. repec:hal:spmain:info:hdl:2441/f6h8764enu2lskk9p2m9mgp8l is not listed on IDEAS
    8. Chris Muris & Pedro Raposo & Sotiris Vandoros, 2020. "A Dynamic Ordered Logit Model with Fixed Effects," Department of Economics Working Papers 2020-14, McMaster University.
    9. Chaudhuri, Kausik & Reilly, Kevin T. & Spencer, David A., 2015. "Job satisfaction, age and tenure: A generalized dynamic random effects model," Economics Letters, Elsevier, vol. 130(C), pages 13-16.
    10. Chrysanthou, Georgios Marios & Vasilakis, Chrysovalantis, 2018. "The Dynamics and Determinants of Bullying Victimisation," IZA Discussion Papers 11902, Institute of Labor Economics (IZA).
    11. Lionel WILNER, 2019. "The Dynamics of Individual Happiness," Working Papers 2019-18, Center for Research in Economics and Statistics.
    12. Chappell, Henry W. & McGregor, Rob Roy, 2018. "Committee decision-making at Sweden's Riksbank," European Journal of Political Economy, Elsevier, vol. 53(C), pages 120-133.
    13. Bo E. Honoré & Chris Muris & Martin Weidner, 2021. "Dynamic Ordered Panel Logit Models," Working Papers 2021-14, Princeton University. Economics Department..
    14. Bartolucci, Francesco & Pigini, Claudia & Valentini, Francesco, 2023. "Testing for state dependence in the fixed-effects ordered logit model," Economics Letters, Elsevier, vol. 222(C).
    15. Pigini, Claudia & Presbitero, Andrea F. & Zazzaro, Alberto, 2016. "State dependence in access to credit," Journal of Financial Stability, Elsevier, vol. 27(C), pages 17-34.
    16. 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).
    17. William H. Greene & Mark N. Harris & Bruce Hollingsworth, 2015. "Inflated Responses in Measures of Self-Assessed Health," American Journal of Health Economics, MIT Press, vol. 1(4), pages 461-493, Fall.
    18. Francesco Bartolucci & Claudia Pigini, 2017. "Granger causality in dynamic binary short panel data models," Working Papers 421, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    19. Cubi-Molla, P. & Jofre-Bonet, M. & Serra-Sastre, V., 2013. "Adaptation to Health States: A Micro-Econometric Approach," Working Papers 13/02, Department of Economics, City University London.
    20. Greene, William & Harris, Mark N. & Knott, Rachel & Rice, Nigel, 2023. "Reporting heterogeneity in modeling self-assessed survey outcomes," Economic Modelling, Elsevier, vol. 124(C).
    21. 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 of Labor Economics (IZA).

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    More about this item

    Keywords

    Dynamic ordered probit;

    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
    • I19 - Health, Education, and Welfare - - Health - - - Other

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