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Estimation of a censored regression panel data model using conditional moment restrictions efficiently

Author

Listed:
  • Charlier, G.W.P.

    (Tilburg University, School of Economics and Management)

  • Melenberg, B.

    (Tilburg University, School of Economics and Management)

  • van Soest, A.H.O.

    (Tilburg University, School of Economics and Management)

Abstract

A new semiparametric estimator for the censored regression panel data model with fixed effects is introduced. It is based upon an estimator proposed by Honore for the case of two time periods combined with ideas of Newey to improve the efficiency. The estimator is more efficient than Honore's and is generalized to the case of a balanced or unbalanced panel of more than two waves. Estimation is performed in two steps. Using Honore's estimator in a first step, efficient GMM using conditional moment restrictions is applied. The performance of this estimator is compared to that of Honore's and other existing estimators in an empirical example concerning labour income of married females, using panel data from the Dutch Socio-Economic Panel, 1984-1988. Attention is paid to specification testing and the sensitivity of the results for the choice of smoothness parameters.
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Suggested Citation

  • Charlier, G.W.P. & Melenberg, B. & van Soest, A.H.O., 1995. "Estimation of a censored regression panel data model using conditional moment restrictions efficiently," Other publications TiSEM 8bb5cab0-e58a-477b-88e9-8, Tilburg University, School of Economics and Management.
  • Handle: RePEc:tiu:tiutis:8bb5cab0-e58a-477b-88e9-8ae4346889dd
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    Cited by:

    1. Stefan Hochguertel & Henry Ohlsson, 2009. "Compensatory inter vivos gifts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 993-1023.
    2. Botosaru, Irene & Muris, Chris & Pendakur, Krishna, 2023. "Identification of time-varying transformation models with fixed effects, with an application to unobserved heterogeneity in resource shares," Journal of Econometrics, Elsevier, vol. 232(2), pages 576-597.
    3. Picchio, Matteo & van Ours, Jan C., 2011. "Market imperfections and firm-sponsored training," Labour Economics, Elsevier, vol. 18(5), pages 712-722, October.
    4. Kalwij, Adriaan S., 2003. "A maximum likelihood estimator based on first differences for a panel data Tobit model with individual specific effects," Economics Letters, Elsevier, vol. 81(2), pages 165-172, November.
    5. Stefan Hochguertel, 2003. "Precautionary motives and portfolio decisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 61-77.
    6. Hochgürtel, S., 1997. "Precautionary Motives and Portfolio Decisions," Discussion Paper 1997-55, Tilburg University, Center for Economic Research.
    7. Hochgürtel, S., 1997. "Precautionary Motives and Portfolio Decisions," Other publications TiSEM a6aa05be-cbd8-4f92-ac8e-8, Tilburg University, School of Economics and Management.
    8. Adriaan Kalwij, 2015. "Two tests for strict exogeneity in a correlated random effects panel data Tobit model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(2), pages 115-125, May.
    9. Schmit, Todd M. & Dong, Diansheng & Chung, Chanjin & Kaiser, Harry M. & Gould, Brian W., 2002. "Identifying The Effects Of Generic Advertising On The Household Demand For Fluid Milk And Cheese: A Two-Step Panel Data Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 27(1), pages 1-22, July.
    10. Badi Baltagi & Seuck Song, 2006. "Unbalanced panel data: A survey," Statistical Papers, Springer, vol. 47(4), pages 493-523, October.
    11. Irene Botosaru & Chris Muris & Krishna Pendakur, 2020. "Intertemporal Collective Household Models: Identification in Short Panels with Unobserved Heterogeneity in Resource Shares," CeMMAP working papers CWP26/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Irene Botosaru & Chris Muris, 2022. "Identification of time-varying counterfactual parameters in nonlinear panel models," Papers 2212.09193, arXiv.org, revised Nov 2023.

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