A nonparametric kernel estimator of the drift (diffusion) term in a diffusion model are developed given a preliminary parametric estimator of the diffusion (drift) term. Under regularity conditions, rates of convergence and asymptotic normality of the nonparametric estimators are established. We develop mis- specification tests of parametric diffusion models based on the nonparametric estimators, and derive the asymptotic properties of the tests. We also propose a Markov Bootstrap method for the test statistics to improve on the finite-sample approximations. The finite sample properties of the estimators are examined in a simulation study.
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Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number
2007-01.
Find related papers by JEL classification: C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
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