Identification-Robust Nonparametric Inference in a Linear IV Model

Bertille Antoine and Pascal Lavergne
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Pascal Lavergne: TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement

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Abstract: For a linear IV regression, we propose two new inference procedures on parameters of endogenous variables that are robust to any identification pattern, do not rely on a linear first-stage equation, and account for heteroskedasticity of unknown form. Building on Bierens (1982), we first propose an Integrated Conditional Moment (ICM) type statistic constructed by setting the parameters to the value under the null hypothesis. The ICM procedure tests at the same time the value of the coefficient and the specification of the model. We then adopt a conditionality principle to condition on a set of ICM statistics that informs on identification strength. Our two procedures uniformly control size irrespective of identification strength. They are powerful irrespective of the nonlinear form of the link between instruments and endogenous variables and are competitive with existing procedures in simulations and application.

Keywords: Semiparametric Model; Weak Instruments; Hypothesis Testing (search for similar items in EconPapers)
Date: 2023-07
Note: View the original document on HAL open archive server: https://hal.science/hal-04141433v1
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Published in Journal of Econometrics, 2023, 235 (1), pp.1-24. ⟨10.1016/j.jeconom.2022.01.011⟩

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Related works:
Journal Article: Identification-robust nonparametric inference in a linear IV model (2023)
Working Paper: Identifcation-Robust Nonparametric Inference in a Linear IV Model (2021)
Working Paper: Identification-Robust Nonparametric Inference in a Linear IV Model (2021)
Working Paper: Identification-Robust Nonparametric Inference in a Linear IV Model (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04141433

DOI: 10.1016/j.jeconom.2022.01.011

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