IDEAS home Printed from https://ideas.repec.org/p/ecm/ausm04/93.html
   My bibliography  Save this paper

Monotonicity Conditions and Inequality Imputation for Sample Selection and Non-Response Problems

Author

Listed:
  • Lee
  • Myoung-jae

Abstract

Under a sample selection or non-response problem where a response variable y is observed only when a condition δ=1 is met, the identified mean E(y|δ=1) is not equal to the desired mean E(y). But the monotonicity condition E(y|δ=1)≤E(y|δ=0) yields an informative bound E(y|δ=1)≤E(y), which is enough for certain inferences. For example, in a majority voting with δ being vote-turnout, it is enough to know if E(y)>0.5 or not, for which E(y|δ=1)>0.5 is sufficient under the monotonicity. The main question is then whether the monotonicity condition is testable, and if not, when it is plausible. Answering to these queries, when there is a "proxy" variable z related to y but fully observed, we provide a test for the monotonicity; when z is not available, we provide primitive conditions and plausible models for the monotonicity. Going further, when both y and z are binary, bivariate monotonicities of the type P(y,z|δ=1)≤P(y,z|δ=0) are considered, which can lead to sharper bounds for P(y). As an empirical example, a data set on the 1996 US presidential election is analyzed to see if the Republican candidate could have won had everybody voted, i.e., to see if P(y)>0.5 where y=1 is voting for the Republican candidate

Suggested Citation

  • Lee & Myoung-jae, 2004. "Monotonicity Conditions and Inequality Imputation for Sample Selection and Non-Response Problems," Econometric Society 2004 Australasian Meetings 93, Econometric Society.
  • Handle: RePEc:ecm:ausm04:93
    as

    Download full text from publisher

    File URL: http://repec.org/esAUSM04/up.20108.1076996069.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Horowitz, Joel & Manski, Charles, 1997. "Nonparametric Analysis of Randomized Experiments With Missing Covariate and Outcome Data," Working Papers 97-16, University of Iowa, Department of Economics.
    2. Lee, Myoung-jae & Melenberg, Bertrand, 1998. "Bounding quantiles in sample selection models," Economics Letters, Elsevier, vol. 61(1), pages 29-35, October.
    3. Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
    4. DENUIT, Michel & SAILLET, Olivier, 2001. "Nonparametric Tests for Positive Quadrant Dependence," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2001009, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES), revised 01 Apr 2001.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    sample selection; non-response; monotonicity; imputation; orthant dependence;

    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
    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods

    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:ecm:ausm04:93. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/essssea.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.