Indirect Estimation of Stochastic Differential Equation Models: Some Computational Experiments
AbstractIn this paper we consider the estimation of some stochastic differential equation models by an indirect estimation method proposed by Gourieroux, Monfort and Renault (1993) using discrete data. The performance of this method is analysed via Monte Carlo experiments. In particular, we examine the Vasicek and the Cox, Ingersoll and Ross models used in financial economics and a system of three stochastic differential equations proposed by P.C.B. Phillips in 1972. These results show the ability of indirect estimation to remove the bias resulting from the discretisation of the continuous model. Citation Copyright 1996 by Kluwer Academic Publishers.
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Bibliographic InfoArticle provided by Society for Computational Economics in its journal Computational Economics.
Volume (Year): 9 (1996)
Issue (Month): 3 (August)
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- Giorgio Calzolari & Francesca Di Iorio & Gabriele Fiorentini, 1998.
"Control variates for variance reduction in indirect inference: Interest rate models in continuous time,"
Royal Economic Society, vol. 1(Conferenc), pages C100-C112.
- Gabriele Fiorentini & Francesca Di Iorio & Giorgio Calzolari, 1998. "- Control Variates For Variance Reduction In Indirect Inference: Interest Rate Models In Continuous Time," Working Papers. Serie AD 1998-09, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
- Calzolari, Giorgio & Di Iorio, Francesca & Fiorentini, Gabriele, 1996. "Control variates for variance reduction in indirect inference: interest rate models in continuous time," MPRA Paper 23160, University Library of Munich, Germany, revised Nov 1996.
- Di Iorio, Francesca & Calzolari, Giorgio, 2006. "Discontinuities in indirect estimation: An application to EAR models," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 2124-2136, April.
- Giorgio Calzolari & F. Di Iorio & G. Fiorentini, 1999. "Indirect Estimation of Just-Identified Models with Control Variates," Econometrics Working Papers Archive quaderno46, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
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