Nonparametric identification in panels using quantiles

Victor Chernozhukov, Ivan Fernandez-Val, Stefan Hoderlein and Whitney Newey

No CWP54/14, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: This paper considers identi?cation 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 ?nd that these derivatives are identi?ed with two time periods for “stayers”, i.e. for individuals with the same regressor values in two time periods. We show that the identi?cation results carry over to models that allow location and scale time e?ects. We propose nonparametric series methods and a weighted bootstrap scheme to estimate and make inference on the identi?ed e?ects. The bootstrap proposed allows inference for function-valued parameters such as quantile e?ects uniformly over a region of quantile indices and/or regressor values. An empirical application to Engel curve estimation with panel data illustrates the results.

Keywords: Panel data; nonseparable model; average e?ect; quantile e?ect; Engel curve (search for similar items in EconPapers)
Date: 2014-12-31
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (2)

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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 (2013)
Working Paper: Nonparametric identification in panels using quantiles (2013)
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