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Vogt, Michael
Linton, Oliver
Year of Publication: 
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cemmap working paper, Centre for Microdata Methods and Practice CWP06/15
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.
Classification of regression curves
k-means clustering
kernel estimation
nonparametric regression
panel data
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Working Paper

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