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An alternative test for conditional unconfoundedness using auxiliary variables

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  • Fang, Ying
  • Tang, Shengfang
  • Cai, Zongwu
  • Lin, Ming

Abstract

This paper proposes an alternative test procedure for testing the conditional unconfoundedness assumption which is an important identification condition commonly imposed in the literature of program analysis and policy evaluation. We transform the conditional unconfoundedness test to a nonparametric conditional moment test using an auxiliary variable which is independent of the treatment assignment variable conditional on potential outcomes and observable covariates. The proposed test statistic is shown to have a limiting normal distribution under the null hypothesis of conditional independence. Monte Carlo simulations are conducted to examine the finite sample performances of the proposed test statistics. Finally, the proposed test method is applied to test the conditional unconfoundedness in the real example of the return to college education.

Suggested Citation

  • Fang, Ying & Tang, Shengfang & Cai, Zongwu & Lin, Ming, 2020. "An alternative test for conditional unconfoundedness using auxiliary variables," Economics Letters, Elsevier, vol. 194(C).
    • Handle: RePEc:eee:ecolet:v:194:y:2020:i:c:s0165176520302111
    DOI: 10.1016/j.econlet.2020.109320
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    References listed on IDEAS

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    10. Zongwu Cai & Ying Fang & Ming Lin & Shengfang Tang, 2020. "Inferences for Partially Conditional Quantile Treatment Effect Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202005, University of Kansas, Department of Economics, revised Feb 2020.
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    Cited by:

    1. Ying Fang & Ming Lin & Shengfang Tang & Zongwu Cai, 2021. "Testing Conditional Independence in Macroeconomic Policy Evaluation for Time Series Data," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202118, University of Kansas, Department of Economics, revised Sep 2021.

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    More about this item

    Keywords

    Conditional unconfoundedness; Moment test; Treatment effect;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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