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.

中文翻译：

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重新考虑面板数据分位数回归的简单方法

本说明讨论了Ivan Canay（2011，计量经济学杂志）提出的方法的谬误，该方法用于在具有分位数无关固定效应的分位数回归模型中构造计算简单的两步估计量。我们正式证明，由于违反了第一步估计量的加法展开式的假设，估计量对常数项给出了错误的推论，这需要其项的独立性。我们的模拟表明，对于固定项，Canay的置信区间是错误的。最后，我们关注一个事实，即按照Canay的程序要求，在估计量内找到一个sqrt（nT）可能是有问题的。我们提供了一个模型示例，我们对其正式证明了这种估计量的不存在。