IDEAS home Printed from https://ideas.repec.org/a/taf/jnlasa/v108y2013i503p1090-1104.html
   My bibliography  Save this article

Semiparametric Efficient and Robust Estimation of an Unknown Symmetric Population Under Arbitrary Sample Selection Bias

Author

Listed:
  • Yanyuan Ma
  • Mijeong Kim
  • Marc G. Genton

Abstract

We propose semiparametric methods to estimate the center and shape of a symmetric population when a representative sample of the population is unavailable due to selection bias. We allow an arbitrary sample selection mechanism determined by the data collection procedure, and we do not impose any parametric form on the population distribution. Under this general framework, we construct a family of consistent estimators of the center that is robust to population model misspecification, and we identify the efficient member that reaches the minimum possible estimation variance. The asymptotic properties and finite sample performance of the estimation and inference procedures are illustrated through theoretical analysis and simulations. A data example is also provided to illustrate the usefulness of the methods in practice.

Suggested Citation

  • Yanyuan Ma & Mijeong Kim & Marc G. Genton, 2013. "Semiparametric Efficient and Robust Estimation of an Unknown Symmetric Population Under Arbitrary Sample Selection Bias," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(503), pages 1090-1104, September.
  • Handle: RePEc:taf:jnlasa:v:108:y:2013:i:503:p:1090-1104
    DOI: 10.1080/01621459.2013.816184
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01621459.2013.816184
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/01621459.2013.816184?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. A. Colin Cameron & Pravin K. Trivedi, 2010. "Microeconometrics Using Stata, Revised Edition," Stata Press books, StataCorp LP, number musr, March.
    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. Mikhail Zhelonkin & Marc G. Genton & Elvezio Ronchetti, 2016. "Robust inference in sample selection models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(4), pages 805-827, September.
    2. Wang Miao & Peng Ding & Zhi Geng, 2016. "Identifiability of Normal and Normal Mixture Models with Nonignorable Missing Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1673-1683, October.
    3. Laura Borrajo & Ricardo Cao, 2021. "Nonparametric estimation for big-but-biased data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(4), pages 861-883, 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. Giuliani, Elisa & Martinelli, Arianna & Rabellotti, Roberta, 2016. "Is Co-Invention Expediting Technological Catch Up? A Study of Collaboration between Emerging Country Firms and EU Inventors," World Development, Elsevier, vol. 77(C), pages 192-205.
    2. Jarle Aarstad & Olav Andreas Kvitastein & Stig-Erik Jakobsen, 2019. "What Drives Enterprise Product Innovation? Assessing How Regional, National, And International Inter-Firm Collaboration Complement Or Substitute For R&D Investments," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 23(05), pages 1-25, June.
    3. Altorjai, Szilvia, 2013. "Over-qualification of immigrants in the UK," ISER Working Paper Series 2013-11, Institute for Social and Economic Research.
    4. Sara Serra, 2016. "Temporary contracts' transitions: the role of training and institutions," Working Papers w201611, Banco de Portugal, Economics and Research Department.
    5. Robert A. Jackson & Matthew Pietryka, 2022. "The influence of becoming a parent on political participation in the United States," Social Science Quarterly, Southwestern Social Science Association, vol. 103(3), pages 565-580, May.
    6. Tocco, Barbara & Bailey, Alastair & Davidova, Sophia & Raimondi, Valentina, 2015. "Women and Part-Time Farming: Understanding Labor Supply Decisions in Italian Farm Households," 2015 Conference, August 9-14, 2015, Milan, Italy 211932, International Association of Agricultural Economists.
    7. Costa-Font, Joan & Vilaplana-Prieto, Cristina, 2022. "Health shocks and housing downsizing: How persistent is ‘ageing in place’?," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 490-508.
    8. Guillaume Claveres & Thomas Y. Mathä & Giuseppe Pulina & Jan Stráský & Nicolas Woloszko & Michael Ziegelmeyer, 2020. "Housing and inequality: The case of Luxembourg and its cross-border workers," BCL working papers 144, Central Bank of Luxembourg.
    9. Hanna Dudek & Joanna Myszkowska-Ryciak & Agnieszka Wojewódzka-Wiewiórska, 2021. "Profiles of Food Insecurity: Similarities and Differences across Selected CEE Countries," Energies, MDPI, vol. 14(16), pages 1-19, August.
    10. Yuejia Zhang, 2018. "Gain or pain? New evidence on mixed syndication between governmental and private venture capital firms in China," Small Business Economics, Springer, vol. 51(4), pages 995-1031, December.
    11. Valeria Di Cosmo & Laura Malaguzzi Valeri, 2018. "How Much Does Wind Power Reduce $$\text {CO}_{2}$$ CO 2 Emissions? Evidence from the Irish Single Electricity Market," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(3), pages 645-669, November.
    12. Alobo Loison, Sarah & Hillbom, Ellen, 2020. "Regional evidence of smallholder-based growth in Zambia’s livestock sector," World Development Perspectives, Elsevier, vol. 19(C).
    13. Nilsson, Jerker & Helgesson, Matilda & Rommel, Jens & Svensson, Ellinor, 2020. "Forest-owner support for their cooperative's provision of public goods," Forest Policy and Economics, Elsevier, vol. 115(C).
    14. 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.
    15. Bertoli, Simone & Marchetta, Francesca, 2015. "Bringing It All Back Home – Return Migration and Fertility Choices," World Development, Elsevier, vol. 65(C), pages 27-40.
    16. Cecere, Grazia & Mancinelli, Susanna & Mazzanti, Massimiliano, 2014. "Waste prevention and social preferences: the role of intrinsic and extrinsic motivations," Ecological Economics, Elsevier, vol. 107(C), pages 163-176.
    17. Holmes, Mark J. & Otero, Jesús & Panagiotidis, Theodore, 2013. "On the dynamics of gasoline market integration in the United States: Evidence from a pair-wise approach," Energy Economics, Elsevier, vol. 36(C), pages 503-510.
    18. Sara C. Santos Cruz & Aurora A. C. Teixeira, 2021. "Spatial analysis of new firm formation in creative industries before and during the world economic crisis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 67(2), pages 385-413, October.
    19. Andrés Rodríguez-Pose & Tobias D. Ketterer, 2012. "Do Local Amenities Affect The Appeal Of Regions In Europe For Migrants?," Journal of Regional Science, Wiley Blackwell, vol. 52(4), pages 535-561, October.
    20. Paul Kwame Nkegbe & Naasegnibe Kuunibe & Samuel Sekyi, 2017. "Poverty and malaria morbidity in the Jirapa District of Ghana: A count regression approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1293472-129, January.

    More about this item

    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:taf:jnlasa:v:108:y:2013:i:503:p:1090-1104. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UASA20 .

    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.