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Classification of nonparametric regression functions in heterogeneous panels

Authors: Michael Vogt and Oliver Linton
Date: 20 February 2015
Type: cemmap Working Paper, CWP06/15
DOI: 10.1920/wp.cem.2015.0615

Abstract

We investigate a nonparametric panel model with heterogeneous regression functions. In a variety of applications, it is natural to impose a group structure on the regression curves. Specifically, we may suppose that the observed individuals can be grouped into a number of classes whose members all share the same regression function. We develop a statistical procedure to estimate the unknown group structure from the observed data. Moreover, we derive the asymptotic properties of the procedure and investigate its finite sample performance by means of a simulation study and a real-data example.

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