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Matching points: Supplementing instruments with covariates in triangular models

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  • Feng, Junlong

Abstract

Models with a discrete endogenous variable and an instrument that takes on fewer values are common in economics. This paper presents a new method that matches pairs of covariates and instruments to restore the order condition in this scenario and to achieve point-identification of the outcome function. The outcome function must be monotonic in a scalar disturbance, but it can be nonseparable. The first stage for the discrete endogenous variable needs to have a multi-index structure but allows for multidimensional heterogeneity. This paper also provides estimators of the outcome function. Two empirical examples of the return to education and of selection into Head Start illustrate the usefulness and limitations of the method.

Suggested Citation

  • Feng, Junlong, 2024. "Matching points: Supplementing instruments with covariates in triangular models," Journal of Econometrics, Elsevier, vol. 238(1).
  • Handle: RePEc:eee:econom:v:238:y:2024:i:1:s0304407623002956
    DOI: 10.1016/j.jeconom.2023.105579
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    Keywords

    Nonparametric identification; Triangular model; Instrumental variable; Endogeneity; Generalized propensity score;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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