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Estimating Endogenous Effects on Ordinal Outcomes

Author

Listed:
  • Andrew Chesher

    (Institute for Fiscal Studies and University College London)

  • Adam Rosen

    (Institute for Fiscal Studies and Duke University)

  • Zahra Siddique

    (Institute for Fiscal Studies)

Abstract
Recent research underscores the sensitivity of conclusions drawn from the application of econometric methods devised for quantitative outcome variables to data featuring ordinal outcomes. The issue is particularly acute in the analysis of happiness data, for which no natural cardinal scale exists, and which is thus routinely collected by ordinal response. With ordinal responses, comparisons of means across di?erent populations and the signs of OLS regression coe?cients have been shown to be sensitive to monotonic transformations of the cardinal scale onto which ordinal responses are mapped. In many applications featuring ordered outcomes, including responses to happiness surveys, researchers may wish to study the impact of a ceteris paribus change in certain variables induced by a policy shift. Insofar as some of these variables may be manipulated by the individuals involved, they may be endogenous. This paper examines the use of instrumental variable (IV) methods to measure the e?ect of such changes. While linear IV estimators suffer from the same pitfalls as averages and OLS coe?cient estimates when outcome variables are ordinal, nonlinear models that explicitly respect the ordered nature of the response variable can be used. This is demonstrated with an application to the study of the effect of neighborhood characteristics on subjective well-being among participants in the Moving to Opportunity housing voucher experiment. In this context, the application of nonlinear IV models can be used to estimate marginal effects and counterfactual probabilities of categorical responses induced by changes in neighborhood characteristics such as the level of neighborhood poverty.

Suggested Citation

  • Andrew Chesher & Adam Rosen & Zahra Siddique, 2019. "Estimating Endogenous Effects on Ordinal Outcomes," CeMMAP working papers CWP66/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:66/19
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    References listed on IDEAS

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    5. Chesher, Andrew & Smolinski, Konrad, 2012. "IV models of ordered choice," Journal of Econometrics, Elsevier, vol. 166(1), pages 33-48.
    6. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
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    Cited by:

    1. Aradillas-López, Andrés & Rosen, Adam M., 2022. "Inference in ordered response games with complete information," Journal of Econometrics, Elsevier, vol. 226(2), pages 451-476.
    2. Andrew Chesher & Adam Rosen, 2020. "Econometric Modeling of Interdependent Discrete Choice with Applications to Market Structure," CeMMAP working papers CWP25/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Eleni Aristodemou, 2021. "A discrete choice model for partially ordered alternatives," CeMMAP working papers CWP35/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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