Classification of Nonparametric Regression Functions in Heterogeneous Panels

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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Year of publication:	2015
Authors:	Vogt, Michael
Other Persons:	Linton, Oliver (contributor)
Publisher:	[2015]: [S.l.] : SSRN
Subject:	Theorie \| Theory \| Regressionsanalyse \| Regression analysis \| Nichtparametrisches Verfahren \| Nonparametric statistics \| Panel \| Panel study

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