IDEAS home Printed from https://ideas.repec.org/a/gam/jecnmx/v6y2018i1p12-d135187.html
   My bibliography  Save this article

Response-Based Sampling for Binary Choice Models With Sample Selection

Author

Listed:
  • Maria Felice Arezzo

    (These authors contributed equally to this work.)

  • Giuseppina Guagnano

    (These authors contributed equally to this work.)

Abstract

Sample selection models attempt to correct for non-randomly selected data in a two-model hierarchy where, on the first level, a binary selection equation determines whether a particular observation will be available for the second level (outcome equation). If the non-random selection mechanism induced by the selection equation is ignored, the coefficient estimates in the outcome equation may be severely biased. When the selection mechanism leads to many censored observations, few data are available for the estimation of the outcome equation parameters, giving rise to computational difficulties. In this context, the main reference is Greene (2008) who extends the results obtained by Manski and Lerman (1977), and develops an estimator which requires the knowledge of the true proportion of occurrences in the outcome equation. We develop a method that exploits the advantages of response-based sampling schemes in the context of binary response models with a sample selection, relaxing this assumption. Estimation is based on a weighted version of Heckman’s likelihood, where the weights take into account the sampling design. In a simulation study, we found that, for the outcome equation, the results obtained with our estimator are comparable to Greene’s in terms of mean square error. Moreover, in a real data application, it is preferable in terms of the percentage of correct predictions.

Suggested Citation

  • Maria Felice Arezzo & Giuseppina Guagnano, 2018. "Response-Based Sampling for Binary Choice Models With Sample Selection," Econometrics, MDPI, vol. 6(1), pages 1-17, March.
    • Handle: RePEc:gam:jecnmx:v:6:y:2018:i:1:p:12-:d:135187
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2225-1146/6/1/12/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2225-1146/6/1/12/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jones,Stewart & Hensher,David A. (ed.), 2008. "Advances in Credit Risk Modelling and Corporate Bankruptcy Prediction," Cambridge Books, Cambridge University Press, number 9780521689540, October.
    2. 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.
    3. Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
    4. Thomas A. Mroz & Yaraslau V. Zayats, 2008. "Arbitrarily Normalized Coefficients, Information Sets, and False Reports of "Biases" in Binary Outcome Models," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 406-413, August.
    5. Van de Ven, Wynand P. M. M. & Van Praag, Bernard M. S., 1981. "The demand for deductibles in private health insurance : A probit model with sample selection," Journal of Econometrics, Elsevier, vol. 17(2), pages 229-252, November.
    6. Boyes, William J. & Hoffman, Dennis L. & Low, Stuart A., 1989. "An econometric analysis of the bank credit scoring problem," Journal of Econometrics, Elsevier, vol. 40(1), pages 3-14, January.
    7. Kayser, Hilke A., 2000. "Gasoline demand and car choice: estimating gasoline demand using household information," Energy Economics, Elsevier, vol. 22(3), pages 331-348, June.
    8. Manski, Charles F & Lerman, Steven R, 1977. "The Estimation of Choice Probabilities from Choice Based Samples," Econometrica, Econometric Society, vol. 45(8), pages 1977-1988, November.
    9. Jeffrey A. Dubin & Douglas Rivers, 1989. "Selection Bias in Linear Regression, Logit and Probit Models," Sociological Methods & Research, , vol. 18(2-3), pages 360-390, November.
    10. Ingram, Gregory K. & Zhi Liu, 1999. "Determinants of motorization and road provision," Policy Research Working Paper Series 2042, The World Bank.
    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. Martin Leo & Suneel Sharma & K. Maddulety, 2019. "Machine Learning in Banking Risk Management: A Literature Review," Risks, MDPI, vol. 7(1), pages 1-22, March.
    2. Watanabe, Hajime & Maruyama, Takuya, 2024. "A Bayesian sample selection model with a binary outcome for handling residential self-selection in individual car ownership," Journal of choice modelling, Elsevier, vol. 51(C).
    3. Lkhagvadorj Munkhdalai & Tsendsuren Munkhdalai & Oyun-Erdene Namsrai & Jong Yun Lee & Keun Ho Ryu, 2019. "An Empirical Comparison of Machine-Learning Methods on Bank Client Credit Assessments," Sustainability, MDPI, vol. 11(3), pages 1-23, January.

    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. Giampiero Marra & Rosalba Radice & Till Bärnighausen & Simon N. Wood & Mark E. McGovern, 2017. "A Simultaneous Equation Approach to Estimating HIV Prevalence With Nonignorable Missing Responses," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 484-496, April.
    2. Eun-Ju Lee & David Eastwood & Jinkook Lee, 2004. "A Sample Selection Model of Consumer Adoption of Computer Banking," Journal of Financial Services Research, Springer;Western Finance Association, vol. 26(3), pages 263-275, December.
    3. Tocco, Barbara & Bailey, Alastair & Davidova, Sophia, 2013. "Determinants to Leave Agriculture and Change Occupational Sector: Evidence from an Enlarged EU," Working papers 155704, Factor Markets, Centre for European Policy Studies.
    4. Filiz Garip, 2012. "An Integrated Analysis of Migration and Remittances: Modeling Migration as a Mechanism for Selection," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 31(5), pages 637-663, October.
    5. González-Cabán, Armando & Loomis, John B. & Rodriguez, Andrea & Hesseln, Hayley, 2007. "A comparison of CVM survey response rates, protests and willingness-to-pay of Native Americans and general population for fuels reduction policies," Journal of Forest Economics, Elsevier, vol. 13(1), pages 49-71, May.
    6. Haan, Michael, 2005. "Summary Of: Are Immigrants Buying to Get In?: The Role of Ethnic Clustering on the Homeownership Propensities of 12 Toronto Immigrant Groups, 1996-2001," Analytical Studies Branch Research Paper Series 2005253e, Statistics Canada, Analytical Studies Branch.
    7. Glenn W. Harrison & Morten I. Lau & Hong Il Yoo, 2020. "Risk Attitudes, Sample Selection, and Attrition in a Longitudinal Field Experiment," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 552-568, July.
    8. James Alm & Mikhail I. Melnik, 2005. "Sales Taxes and the Decision to Purchase Online," Public Finance Review, , vol. 33(2), pages 184-212, March.
    9. Maksym, Obrizan, 2010. "A Bayesian Model of Sample Selection with a Discrete Outcome Variable," MPRA Paper 28577, University Library of Munich, Germany.
    10. Victor Chernozhukov & Ivan Fernandez-Val & Siyi Luo, 2023. "Distribution regression with sample selection and UK wage decomposition," CeMMAP working papers 09/23, Institute for Fiscal Studies.
    11. Victor Chernozhukov & Ivan Fernandez-Val & Siyi Luo, 2018. "Distribution regression with sample selection, with an application to wage decompositions in the UK," CeMMAP working papers CWP68/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Painter, Gary & Gabriel, Stuart & Myers, Dowell, 2001. "Race, Immigrant Status, and Housing Tenure Choice," Journal of Urban Economics, Elsevier, vol. 49(1), pages 150-167, January.
    13. Alfonso Miranda & Sophia Rabe-Hesketh, 2006. "Maximum likelihood estimation of endogenous switching and sample selection models for binary, ordinal, and count variables," Stata Journal, StataCorp LP, vol. 6(3), pages 285-308, September.
    14. Kumar, Kaushalendra & Singh, Abhishek & James, K.S. & McDougal, Lotus & Raj, Anita, 2020. "Gender bias in hospitalization financing from borrowings, selling of assets, contribution from relatives or friends in India," Social Science & Medicine, Elsevier, vol. 260(C).
    15. Gary Painter, 2000. "Tenure Choice with Sample Selection: A Note on the Differences among Alternative Samples," Working Paper 8647, USC Lusk Center for Real Estate.
    16. Ivlevs Artjoms & Hinks Timothy, 2015. "Bribing Behaviour and Sample Selection: Evidence from Post-Socialist Countries and Western Europe," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(2), pages 139-167, April.
    17. J Banasik & J Crook & L Thomas, 2003. "Sample selection bias in credit scoring models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(8), pages 822-832, August.
    18. William H. Greene & David A. Hensher, 2008. "Modeling Ordered Choices: A Primer and Recent Developments," Working Papers 08-26, New York University, Leonard N. Stern School of Business, Department of Economics.
    19. William Greene, 2010. "A stochastic frontier model with correction for sample selection," Journal of Productivity Analysis, Springer, vol. 34(1), pages 15-24, August.
    20. Painter, Gary, 2000. "Tenure Choice with Sample Selection: Differences among Alternative Samples," Journal of Housing Economics, Elsevier, vol. 9(3), pages 197-213, September.

    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:gam:jecnmx:v:6:y:2018:i:1:p:12-:d:135187. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.