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Self-Selection and Direct Estimation of Across-Regime Correlation Parameter

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Abstract

A direct Maximum Likelihood (ML) procedure to estimate the "generally unidentified" across-regime correlation parameter in a two-regime endogenous switching model is here provided. The results of a Monte Carlo experiment confirm consistency of our direct ML procedure, and its relative efficiency over widely applied models and methods. As an empirical application, we estimate a Two-Regime simultaneous equation model of domestic work of Italian married women in which the two regimes are given by their working status (employed or unemployed).

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  • Giorgio Calzolari & Antonino Di Pino, 2014. "Self-Selection and Direct Estimation of Across-Regime Correlation Parameter," Econometrics Working Papers Archive 2014_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    • Handle: RePEc:fir:econom:wp2014_04
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    1. Vijverberg, Wim P. M., 1993. "Measuring the unidentified parameter of the extended Roy model of selectivity," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 69-89.
    2. Chen, Heng & Fan, Yanqin & Liu, Ruixuan, 2016. "Inference for the correlation coefficient between potential outcomes in the Gaussian switching regime model," Journal of Econometrics, Elsevier, vol. 195(2), pages 255-270.
    3. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    4. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College," NBER Working Papers 9546, National Bureau of Economic Research, Inc.
    5. Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," IZA Discussion Papers 767, Institute of Labor Economics (IZA).
    6. Vella, Francis & Verbeek, Marno, 1999. "Estimating and Interpreting Models with Endogenous Treatment Effects," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 473-478, October.
    7. Heckman, James J & Honore, Bo E, 1990. "The Empirical Content of the Roy Model," Econometrica, Econometric Society, vol. 58(5), pages 1121-1149, September.
    8. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "2001 Lawrence R. Klein Lecture Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 361-422, May.
    9. Poirier, Dale J. & Ruud, Paul A., 1981. "On the appropriateness of endogenous switching," Journal of Econometrics, Elsevier, vol. 16(2), pages 249-256, June.
    10. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
    11. Calzolari, Giorgio & Panattoni, Lorenzo, 1988. "Alternative Estimators of FIML Covariance Matrix: A Monte Carlo Stud y," Econometrica, Econometric Society, vol. 56(3), pages 701-714, May.
    12. Poirier, Dale J & Tobias, Justin L, 2003. "On the Predictive Distributions of Outcome Gains in the Presence of an Unidentified Parameter," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(2), pages 258-268, April.
    13. Maddala, G S & Nelson, Forrest D, 1974. "Maximum Likelihood Methods for Models of Markets in Disequilibrium," Econometrica, Econometric Society, vol. 42(6), pages 1013-1030, November.
    14. Michael Lokshin & Zurab Sajaia, 2004. "Maximum likelihood estimation of endogenous switching regression models," Stata Journal, StataCorp LP, vol. 4(3), pages 282-289, September.
    15. James Heckman & Justin L. Tobias & Edward Vytlacil, 2003. "Simple Estimators for Treatment Parameters in a Latent-Variable Framework," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 748-755, August.
    16. Maddala, G.S., 1986. "Disequilibrium, self-selection, and switching models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 3, chapter 28, pages 1633-1688, Elsevier.
    17. Lee, Lung-Fei, 1978. "Unionism and Wage Rates: A Simultaneous Equations Model with Qualitative and Limited Dependent Variables," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 19(2), pages 415-433, June.
    18. Maria Gabriella Campolo & Antonio Di Pino, 2012. "An Empirical Analysis of Women’s Working Time, and an Estimation of Female Labour Supply in Italy," Statistica, Department of Statistics, University of Bologna, vol. 72(2), pages 173-193.
    19. Aakvik, Arild & Heckman, James J. & Vytlacil, Edward J., 2005. "Estimating treatment effects for discrete outcomes when responses to treatment vary: an application to Norwegian vocational rehabilitation programs," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 15-51.
    20. Suzanne Bianchi, 2000. "Maternal employment and time with children: Dramatic change or surprising continuity?," Demography, Springer;Population Association of America (PAA), vol. 37(4), pages 401-414, November.
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    1. Giorgio Calzolari & Maria Gabriella Campolo & Antonino Pino & Laura Magazzini, 2023. "Assessing individual skill influence on housework time of Italian women: an endogenous-switching approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 659-679, June.

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    More about this item

    Keywords

    Endogenous switching model; Across-regime correlation parameter;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

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