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State Dependence And Heterogeneity In Health Using A Bias‐Corrected Fixed‐Effects Estimator

Author

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  • Jesus M. Carro
  • Alejandra Traferri

Abstract

SUMMARY This paper estimates a dynamic ordered probit model of self‐assessed health with two fixed effects: one in the linear index equation and one in the cut‐points. This robustly controls for heterogeneity in unobserved health status and in reporting behavior, although we cannot separate both sources of heterogeneity. We find important state dependence effects, and small but significant effects of income and other socioeconomic variables. Having dynamics and flexibly accounting for unobserved heterogeneity matters for those estimates. We also contribute to the bias correction literature in nonlinear panel models by comparing and applying two of the existing proposals to our model. Copyright © 2012 John Wiley & Sons, Ltd.

Suggested Citation

  • 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.
    • Handle: RePEc:wly:japmet:v:29:y:2014:i:2:p:181-207
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    Cited by:

    1. Bartolucci, Francesco & Pigini, Claudia & Valentini, Francesco, 2023. "Testing for state dependence in the fixed-effects ordered logit model," Economics Letters, Elsevier, vol. 222(C).
    2. Chris Muris & Pedro Raposo & Sotiris Vandoros, 2020. "A dynamic ordered logit model with fixed effects," Papers 2008.05517, arXiv.org.
    3. Bo E. Honoré & Chris Muris & Martin Weidner, 2025. "Dynamic ordered panel logit models," Quantitative Economics, Econometric Society, vol. 16(3), pages 899-945, July.
    4. William H. Greene & Mark N. Harris & Bruce Hollingsworth, 2015. "Inflated Responses in Measures of Self-Assessed Health," American Journal of Health Economics, University of Chicago Press, vol. 1(4), pages 461-493, Fall.
    5. repec:spo:wpecon:info:hdl:2441/f6h8764enu2lskk9p2m9mgp8l 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. 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.
    8. Greene, William & Harris, Mark N. & Knott, Rachel & Rice, Nigel, 2023. "Reporting heterogeneity in modeling self-assessed survey outcomes," Economic Modelling, Elsevier, vol. 124(C).
    9. 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).
    10. 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.
    11. 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.
    12. 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.
    13. Lionel WILNER, 2019. "The Dynamics of Individual Happiness," Working Papers 2019-18, Center for Research in Economics and Statistics.
    14. 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.
    15. 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.
    16. 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 St George's, University of London.
    17. Stephen Hoskins & David W. Johnston & Johannes S. Kunz & Michael A. Shields & Kevin E. Staub, 2024. "Heterogeneity in the Persistence of Health: Evidence from a Monthly Micro Panel," Papers 2024-06, Centre for Health Economics, Monash University.
    18. 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.
    19. Chrysanthou, Georgios Marios & Vasilakis, Chrysovalantis, 2018. "The Dynamics and Determinants of Bullying Victimisation," IZA Discussion Papers 11902, Institute of Labor Economics (IZA).
    20. 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).
    21. repec:spo:wpmain:info:hdl:2441/f6h8764enu2lskk9p2m9mgp8l is not listed on IDEAS

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

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