IDEAS home Printed from https://ideas.repec.org/p/aub/autbar/636.05.html
   My bibliography  Save this paper

Parametric and semiparametric estimation of sample selection models: an empirical application to the female labour force in Portugal

Author

Listed:
  • Danilo Coelho
  • Helena Veiga
  • R?rt Veszteg

Abstract

This comment corrects the errors in the estimation process that appear in Martins (2001). The first error is in the parametric probit estimation, as the previously presented results do not maximize the log-likelihood function. In the global maximum more variables become significant. As for the semiparametric estimation method, the kernel function used in Martins (2001) can take on both positive and negative values, which implies that the participation probability estimates may be outside the interval [0,1]. We have solved the problem by applying local smoothing in the kernel estimation, as suggested by Klein and Spady (1993).

Suggested Citation

  • Danilo Coelho & Helena Veiga & R?rt Veszteg, 2005. "Parametric and semiparametric estimation of sample selection models: an empirical application to the female labour force in Portugal," UFAE and IAE Working Papers 636.05, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    • Handle: RePEc:aub:autbar:636.05
    as

    Download full text from publisher

    File URL: http://pareto.uab.es/wp/2005/63605.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ana Fernandez & Juan Rodriquez-Poo, 1997. "Estimation and specification testing in female labor participation models: parametric and semiparametric methods," Econometric Reviews, Taylor & Francis Journals, vol. 16(2), pages 229-247.
    2. Horowitz, Joel L., 1993. "Semiparametric estimation of a work-trip mode choice model," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 49-70, July.
    3. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    4. Heckman, James J, 1974. "Shadow Prices, Market Wages, and Labor Supply," Econometrica, Econometric Society, vol. 42(4), pages 679-694, July.
    5. Maria Fraga O. Martins, 2001. "Parametric and semiparametric estimation of sample selection models: an empirical application to the female labour force in Portugal," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(1), pages 23-39.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fernández-Sainz, Ana I. & Rodríguez-Póo, Juan M., 2010. "An Empirical Investigation of Parametric and Semiparametric Estimation Methods in Sample Selection Models = Investigación empírica de métodos de estimación paramétricos y semiparamétricos de modelos d," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 10(1), pages 99-120, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fernández-Sainz, Ana I. & Rodríguez-Póo, Juan M., 2010. "An Empirical Investigation of Parametric and Semiparametric Estimation Methods in Sample Selection Models = Investigación empírica de métodos de estimación paramétricos y semiparamétricos de modelos d," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 10(1), pages 99-120, December.
    2. Martin Huber & Giovanni Mellace, 2014. "Testing exclusion restrictions and additive separability in sample selection models," Empirical Economics, Springer, vol. 47(1), pages 75-92, August.
    3. Margarita Genius & Elisabetta Strazzera, 2008. "Applying the copula approach to sample selection modelling," Applied Economics, Taylor & Francis Journals, vol. 40(11), pages 1443-1455.
    4. M. Genius & E. Strazzera, 2003. "The copula approach of sampling selection modelling: an application to the recreational value of forests," Working Paper CRENoS 200308, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    5. Huber, Martin & Melly, Blaise, 2011. "Quantile Regression in the Presence of Sample Selection," Economics Working Paper Series 1109, University of St. Gallen, School of Economics and Political Science.
    6. Huber, Martin & Mellace, Giovanni, 2011. "Testing instrument validity in sample selection models," Economics Working Paper Series 1145, University of St. Gallen, School of Economics and Political Science.
    7. Boriss Siliverstovs & Dmitri Koulikov, 2003. "Labor Supply of Married Females in Estonia," Discussion Papers of DIW Berlin 321, DIW Berlin, German Institute for Economic Research.
    8. Wang, Xiaobing & Herzfeld, Thomas & Glauben, Thomas, 2007. "Labor allocation in transition: Evidence from Chinese rural households," China Economic Review, Elsevier, vol. 18(3), pages 287-308.
    9. Ye, Silin & Zhou, Jing & Jiang, Yunwen & Liu, Xiaming, 2023. "Managers as the bridge: How cultural friction influences the integration of cross-border mergers and acquisitions," International Business Review, Elsevier, vol. 32(4).
    10. Assaf Razin & Efraim Sadka, 2007. "Productivity and Taxes as Drivers of FDI," Working Papers 172007, Hong Kong Institute for Monetary Research.
    11. Töpfer, Marina, 2017. "Detailed RIF decomposition with selection: The gender pay gap in Italy," Hohenheim Discussion Papers in Business, Economics and Social Sciences 26-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    12. Arthur Lewbel, 2012. "Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 67-80.
    13. Paul Ellickson & Sanjog Misra, 2012. "Enriching interactions: Incorporating outcome data into static discrete games," Quantitative Marketing and Economics (QME), Springer, vol. 10(1), pages 1-26, March.
    14. Engel, Dirk, 2002. "The Impact of Venture Capital on Firm Growth: An Empirical Investigation," ZEW Discussion Papers 02-02, ZEW - Leibniz Centre for European Economic Research.
    15. repec:hal:wpspec:info:hdl:2441/3vl5fe4i569nbr005tctlc8ll5 is not listed on IDEAS
    16. Leonardo Gasparini & Mariana Marchionni & Walter Sosa Escudero, 2000. "Characterization of inequality changes through microeconometric decompositions. The case of Greater Buenos Aires," IIE, Working Papers 025, IIE, Universidad Nacional de La Plata.
    17. Hans Dietrich & Harald Pfeifer & Felix Wenzelmann, 2016. "The more they spend, the more I earn? Firms' training investments and post-training wages of apprentices," Economics of Education Working Paper Series 0116, University of Zurich, Department of Business Administration (IBW).
    18. Takahiro Hoshino & Yuya Shimizu, 2019. "Doubly Robust-type Estimation of Population Moments and Parameters in Biased Sampling," Keio-IES Discussion Paper Series 2019-006, Institute for Economics Studies, Keio University.
    19. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2018. "Nonparametric estimation in case of endogenous selection," Journal of Econometrics, Elsevier, vol. 202(2), pages 268-285.
    20. James J. Heckman, 2008. "Econometric Causality," International Statistical Review, International Statistical Institute, vol. 76(1), pages 1-27, April.
    21. Martin Huber, 2012. "Identification of Average Treatment Effects in Social Experiments Under Alternative Forms of Attrition," Journal of Educational and Behavioral Statistics, , vol. 37(3), pages 443-474, June.

    More about this item

    Keywords

    parametric estimation; semiparametric estimation; sample selection model;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aub:autbar:636.05. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Xavier Vila (email available below). General contact details of provider: https://edirc.repec.org/data/ufuabes.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.