IDEAS home Printed from https://ideas.repec.org/p/cep/stiecm/380.html
   My bibliography  Save this paper

On Intercept Estimation in the Sample Selection Model

Author

Listed:
  • Marcia M Schafgans
  • Victoria Zinde-Walsh

Abstract

We provide a proof of the consistency and asymptotic normality of the estimator suggested by Heckman (1990) for the intercept of a semiparametrically estimated sample selection model. The estimator is based on 'identification at infinity' which leads to non-standard convergence rate. Andrews and Schafgans (1998) derived asymptotic results for a smoothed version of the estimator. We examine the optimal bandwidth selection for the estimators and derive asymptotic MSE rates under a wide class of distributional assumptions. We also provide some comparisons of the estimators and practical guidelines.

Suggested Citation

  • Marcia M Schafgans & Victoria Zinde-Walsh, 2000. "On Intercept Estimation in the Sample Selection Model," STICERD - Econometrics Paper Series 380, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  • Handle: RePEc:cep:stiecm:380
    as

    Download full text from publisher

    File URL: https://sticerd.lse.ac.uk/dps/em/em380.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    2. Andrews, Donald W K, 1991. "Asymptotic Normality of Series Estimators for Nonparametric and Semiparametric Regression Models," Econometrica, Econometric Society, vol. 59(2), pages 307-345, March.
    3. Moshe Buchinsky, 1998. "The dynamics of changes in the female wage distribution in the USA: a quantile regression approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(1), pages 1-30.
    4. Donald W. K. Andrews & Marcia M. A. Schafgans, 1998. "Semiparametric Estimation of the Intercept of a Sample Selection Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 497-517.
    5. Lung-Fei Lee, 1982. "Some Approaches to the Correction of Selectivity Bias," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 49(3), pages 355-372.
    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. Alpert, Abby & Powell, David, 2014. "Estimating Intensive and Extensive Tax Responsiveness: Do Older Workers Respond to Income Taxes?," Working Papers 987-1, RAND Corporation.
    2. D’Haultfœuille, Xavier & Maurel, Arnaud & Zhang, Yichong, 2018. "Extremal quantile regressions for selection models and the black–white wage gap," Journal of Econometrics, Elsevier, vol. 203(1), pages 129-142.
    3. Zhewen Pan, 2023. "On semiparametric estimation of the intercept of the sample selection model: a kernel approach," Papers 2302.05089, arXiv.org.
    4. Abby Alpert & David Powell, 2014. "Estimating Intensive and Extensive Tax Responsiveness Do Older Workers Respond to Income Taxes?," Working Papers WR-987-1, RAND Corporation.
    5. Katrin Hussinger, 2008. "R&D and subsidies at the firm level: an application of parametric and semiparametric two-step selection models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 729-747.
    6. Biavaschi, Costanza, 2016. "Recovering the counterfactual wage distribution with selective return migration," Labour Economics, Elsevier, vol. 38(C), pages 59-80.
    7. Vuong Quoc, Duy, 2012. "Determinants of household access to formal credit in the rural areas of the Mekong Delta, Vietnam," MPRA Paper 38202, University Library of Munich, Germany.
    8. Abby Alpert & David Powell, 2012. "Tax Elasticity of Labor Earnings for Older Individuals," Working Papers wp272, University of Michigan, Michigan Retirement Research Center.
    9. Marcia M. A. Schafgans, 2004. "Finite sample properties for the semiparametric estimation of the intercept of a censored regression model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(1), pages 35-56, February.
    10. Arulampalam, Wiji & Corradi, Valentina & Gutknecht, Daniel, 2021. "Intercept Estimation in Nonlinear Selection Models," IZA Discussion Papers 14364, Institute of Labor Economics (IZA).
    11. McGovern, Mark E. & Canning, David & Bärnighausen, Till, 2018. "Accounting for non-response bias using participation incentives and survey design: An application using gift vouchers," Economics Letters, Elsevier, vol. 171(C), pages 239-244.
    12. Samuel Sekyi, 2017. "Rural Households' Credit Access and Loan Amount in Wa Municipality, Ghana," International Journal of Economics and Financial Issues, Econjournals, vol. 7(1), pages 506-514.
    13. Mark McGovern & David Canning & Till Bärnighausen, 2018. "Accounting for Non-Response Bias using Participation Incentives and Survey Design," CHaRMS Working Papers 18-02, Centre for HeAlth Research at the Management School (CHaRMS).
    14. Malmendier, Ulrike M. & Botsch, Matthew J., 2020. "The Long Shadows of the Great Inflation: Evidence from Residential Mortgages," CEPR Discussion Papers 14934, C.E.P.R. Discussion Papers.

    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. Marcia M. A. Schafgans, 2000. "On Intercept Estimation in the Sample Selection Model," Econometric Society World Congress 2000 Contributed Papers 0730, Econometric Society.
    2. Katrin Hussinger, 2008. "R&D and subsidies at the firm level: an application of parametric and semiparametric two-step selection models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 729-747.
    3. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.
    4. Schafgans, Marcia M. A., 2000. "Gender wage differences in Malaysia: parametric and semiparametric estimation," Journal of Development Economics, Elsevier, vol. 63(2), pages 351-378, December.
    5. James J. Heckman, 2005. "Micro Data, Heterogeneity and the Evaluation of Public Policy Part 2," The American Economist, Sage Publications, vol. 49(1), pages 16-44, March.
    6. Claudia PIGINI, 2012. "Of Butterflies and Caterpillars: Bivariate Normality in the Sample Selection Model," Working Papers 377, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    7. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    8. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    9. Li, Qi, 1996. "On the root-N-consistent semiparametric estimation of partially linear models," Economics Letters, Elsevier, vol. 51(3), pages 277-285, June.
    10. Jan De Loecker & Jozef Konings, 2003. "Creative Destruction and Productivity Growth in an Emerging Economy Evidence from Slovenian Manufacturing," LICOS Discussion Papers 13803, LICOS - Centre for Institutions and Economic Performance, KU Leuven.
    11. repec:hal:wpspec:info:hdl:2441/3vl5fe4i569nbr005tctlc8ll5 is not listed on IDEAS
    12. Linton, Oliver, 1995. "Second Order Approximation in the Partially Linear Regression Model," Econometrica, Econometric Society, vol. 63(5), pages 1079-1112, September.
    13. Abhimanyu Gupta & Myung Hwan Seo, 2023. "Robust Inference on Infinite and Growing Dimensional Time‐Series Regression," Econometrica, Econometric Society, vol. 91(4), pages 1333-1361, July.
    14. Jim Levinsohn & Wendy Petropoulos, 2001. "Creative Destruction or Just Plain Destruction?: The U.S. Textile and Apparel Industries since 1972," NBER Working Papers 8348, National Bureau of Economic Research, Inc.
    15. Lee, Jungyoon & Robinson, Peter M., 2016. "Series estimation under cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 190(1), pages 1-17.
    16. Lewbel, Arthur & Linton, Oliver, 2003. "Nonparametric estimation of homothetic and homothetically separable functions," LSE Research Online Documents on Economics 2066, London School of Economics and Political Science, LSE Library.
    17. White, Halbert & Hong, Yongmiao, 1999. "M-Testing Using Finite and Infinite Dimensional Parameter Estimators," University of California at San Diego, Economics Working Paper Series qt9qz123ng, Department of Economics, UC San Diego.
    18. Jungyoon Lee & Peter Robinson, 2016. "Series estimation under cross-sectional dependence," LSE Research Online Documents on Economics 63380, London School of Economics and Political Science, LSE Library.
    19. Chzhen, Yekaterina & Mumford, Karen, 2011. "Gender gaps across the earnings distribution for full-time employees in Britain: Allowing for sample selection," Labour Economics, Elsevier, vol. 18(6), pages 837-844.
    20. Gabriel Montes-Rojas, 2011. "Robust Misspecification Tests for the Heckman's Two-Step Estimator," Econometric Reviews, Taylor & Francis Journals, vol. 30(2), pages 154-172.
    21. Alejandro Badel & Ximena Peña, 2010. "Decomposing the Gender Wage Gap with Sample Selection Adjustment: Evidence from Colombia," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 25(2), pages 169-191, Diciembre.

    More about this item

    Keywords

    Asymptotic normality; sample selection model; semiparametric estimation;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

    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:cep:stiecm:380. 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: the person in charge (email available below). General contact details of provider: https://sticerd.lse.ac.uk/_new/publications/ .

    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.