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A simple approach to quantile regression for panel data
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DOI：10.1111/j.1368-423X.2011.00349.x.png)
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Abstract
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This paper provides a set of sufficient conditions that point identify a quantile regression model with fixed effects. It also proposes a simple transformation of the data that gets rid of the fixed effects under the assumption that these effects are location shifters. The new estimator is consistent and asymptotically normal as both n and T grow.
Keywords:
Deconvolution
Panel data models
Quantile regression
Two-step estimator
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