Reconsideration of a simple approach to quantile regression for panel data

Galina Besstremyannaya () and Sergei Golovan ()
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Galina Besstremyannaya: Centre for Economic and Financial Research at New Economic School
Sergei Golovan: New Economic School

No w0248, Working Papers from Center for Economic and Financial Research (CEFIR)

Abstract: The note discusses a fallacy in the approach proposed by Ivan Canay (2011, The Econometrics Journal) for constructing a computationally simple two-step estimator in a quantile regression model with quantile-independent fixed effects. We formally prove that the estimator gives an incorrect inference for the constant term due to violation of the assumption about additive expansion of the first-step estimator, which requires the independence of its terms. Our simulations show that Canay's confidence intervals for the constant term are wrong. Finally, we focus on the fact that finding a sqrt(nT) consistent within estimator, as required by Canay's procedure, may be problematic. We provide an example of a model, for which we formally prove the non-existence of such an estimator.

Keywords: quantile regression; panel data; fixed effects; inference (search for similar items in EconPapers)
JEL-codes: C21 C23 (search for similar items in EconPapers)
Pages: 7 pages
Date: 2018-11
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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