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Classification of nonparametric regression functions in heterogeneous panels

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  • Michael Vogt
  • Oliver Linton

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.

Suggested Citation

  • Michael Vogt & Oliver Linton, 2015. "Classification of nonparametric regression functions in heterogeneous panels," CeMMAP working papers 06/15, Institute for Fiscal Studies.
    • Handle: RePEc:azt:cemmap:06/15
    DOI: 10.1920/wp.cem.2015.0615
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    References listed on IDEAS

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