Nonparametric identification in panels using quantiles

Victor Chernozhukov, Ivan Fernandez-Val (), Stefan Hoderlein, Hajo Holzmann and Whitney Newey
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Hajo Holzmann: Institute for Fiscal Studies

No CWP66/13, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: This paper considers identification and estimation of ceteris paribus effects of continuous regressors in nonseparable panel models with time homogeneity. The effects of interest are derivatives of the average and quantile structural functions of the model. We find that these derivatives are identified with two time periods for 'stayers', i.e. for individuals with the same regressor values in two time periods. We show that the identification results carry over to models that allow location and scale time effects. We propose nonparametric series methods and a weighted bootstrap scheme to estimate and make inference on the identified effects. The bootstrap proposed allows uniform inference for function-valued parameters such as quantile effects over a region of quantiles or regressor values. An empirical application to Engel curve estimation with panel data illustrates the results.

Date: 2013-12-30
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Related works:
Journal Article: Nonparametric identification in panels using quantiles (2015)
Working Paper: Nonparametric Identification in Panels using Quantiles (2014)
Working Paper: Nonparametric identification in panels using quantiles (2014)
Working Paper: Nonparametric identification in panels using quantiles (2014)
Working Paper: Nonparametric identification in panels using quantiles (2013)
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