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A discontinuity test for identification in triangular nonseparable models

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  • Caetano, Carolina
  • Rothe, Christoph
  • Yıldız, Neşe

Abstract

This paper presents a test for the validity of control variable approaches to identification in triangular nonseparable models. Assumptions commonly imposed to justify such methods include full independence of instruments and disturbances and existence of a reduced form that is strictly monotonic in a scalar disturbance. We show that if the data has a particular structure, namely that the distribution of the endogenous variable has a mass point at the lower (or upper) boundary of its support, validity of the control variable approach implies a continuity condition on an identified function, which can be tested empirically.

Suggested Citation

  • Caetano, Carolina & Rothe, Christoph & Yıldız, Neşe, 2016. "A discontinuity test for identification in triangular nonseparable models," Journal of Econometrics, Elsevier, vol. 193(1), pages 113-122.
  • Handle: RePEc:eee:econom:v:193:y:2016:i:1:p:113-122
    DOI: 10.1016/j.jeconom.2016.01.007
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    1. repec:eee:econom:v:208:y:2019:i:2:p:346-366 is not listed on IDEAS

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    Keywords

    Nonseparable model; Triangular systems; Control variable; Instrument validity; Nonparametric identification;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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