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Matching Points: Supplementing Instruments with Covariates in Triangular Models

Junlong Feng

arXiv 2 Apr 2019 · Econometrics · publishedJournal of Econometrics (2023) · 7 citations (OpenAlex)

arXiv:1904.01159 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Models with a discrete endogenous variable are typically underidentified when the instrument takes on too few values. This paper presents a new method that matches pairs of covariates and instruments to restore point identification in this scenario in a triangular model. The model consists of a structural function for a continuous outcome and a selection model for the discrete endogenous variable. The structural outcome function must be continuous and monotonic in a scalar disturbance, but it can be nonseparable. The selection model allows for unrestricted heterogeneity. Global identification is obtained under weak conditions. The paper also provides estimators of the structural outcome function. Two empirical examples of the return to education and selection into Head Start illustrate the value and limitations of the method.

Citation extraction

39
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Chernozhukov and Hansen (2005) An IV model of quantile treatment effects1.00084100%
2Newey and Powell (2003) Instrumental variable estimation of nonparametric models0.92843100%
3D'Haultfuille and Février (2015) Identification of nonseparable triangular models with discrete instruments0.84333100%
4Das (2005) Instrumental variables estimators of nonparametric models with discrete endogenous regressors0.84333100%
5Imbens and Newey (2009) Identification and estimation of triangular simultaneous equations models without additivity0.84333100%
6Newey, Powell, and Vella (1999) Nonparametric estimation of triangular simultaneous equations models0.84333100%
7Torgovitsky (2015) Identification of nonseparable models using instruments with small support0.84333100%
8Heckman and Vytlacil (2005) Structural equations, treatment effects, and econometric policy evaluation0.73732100%
9Caetano and Escanciano (2020) Identifying multiple marginal effects with a single instrument0.64422100%
10Card (1995) Using geographic variation in college proximity to estimate the return to schooling0.64422100%

Showing the top 10 of 39 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
11420 Identification with possibly invalid IVs0.64422
2Dummy Endogenous Variables in Weakly Separable Multiple Index Models without Monotonicity0.40511
3Treatment Effects with Targeting Instruments0.40511
4Endogeneity in Weakly Separable Models without Monotonicity0.40511
51420 Dynamic Discrete-Continuous Choice Models: Identification and Conditional Choice Probability Estimation0.40511
6A condition for the identification of multivariate models with binary instruments with Corrigendum and Addendum0.40511