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Inference in instrumental variables models with heteroskedasticity and many instruments

Federico Crudu (), Giovanni Mellace () and Zsolt Sándor ()

Department of Economics University of Siena from Department of Economics, University of Siena

Abstract: This paper proposes novel inference procedures for instrumental variable models in the presence of many, potentially weak instruments that are robust to the presence of heteroskedasticity. First, we provide an Anderson-Rubin-type test for the entire parameter vector that is valid under assumptions weaker than previously proposed Anderson-Rubin-type tests. Second, we consider the case of testing a subset of para- meters under the assumption that a consistent estimator for the parameters not under test exists. We show that under the null the proposed statistics have Gaussian limiting distributions and derive alternative chi square approximations. An extensive simulation study shows the competitive finite sample properties in terms of size and power of our procedures. Finally, we provide an empirical application using college proximity instruments to estimate the returns to education.

Keywords: Instrumental variables; heteroskedasticity; many instruments; jackknife; inference (search for similar items in EconPapers)
JEL-codes: C12 C13 C23 (search for similar items in EconPapers)
Date: 2020-02
New Economics Papers: this item is included in nep-ore
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Working Paper: Inference in instrumental variables models with heteroskedasticity and many instruments (2017) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:usi:wpaper:821

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