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UNIFORM CONVERGENCE RATES OF KERNEL ESTIMATORS WITH HETEROGENEOUS DEPENDENT DATA

Published online by Cambridge University Press:  01 October 2009

Dennis Kristensen*
Affiliation:
Columbia University and CREATES
*
*Address correspondence to Dennis Kristensen, Economics Department, Columbia University, 1018 International Affairs Building, MC 3308, 420 West 118th Street, New York, NY 10027, USA; e-mail: [email protected].

Abstract

The main uniform convergence results of Hansen (2008, Econometric Theory 24, 726–748) are generalized in two directions: Data are allowed to (a) be heterogeneously dependent and (b) depend on a (possibly unbounded) parameter. These results are useful in semiparametric estimation problems involving time-inhomogeneous models and/or sampling of continuous-time processes. The usefulness of these results is demonstrated by two applications: kernel regression estimation of a time-varying AR(1) model and the kernel density estimation of a Markov chain that has not been initialized at its stationary distribution.

Type
NOTES AND PROBLEMS
Copyright
Copyright © Cambridge University Press 2009

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