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New Minimum Chi-Square Methods in Empirical Finance

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  • Tauchen, George E.

Abstract

This paper reviews recently developed simulation-based minimum chi-square estimators for structural models. Particular attention is paid to selection of the auxiliary model that defines the GMM-type criterion used in the minimum chi-square estimation. Considerations of statistical efficiency and behavior under misspecification make a strong case for using a very flexible, nonparametric approach to select the auxiliary model. To avoid a numerically ill-behaved GMM criterion function, the dynamic stability of the auxiliary model must also be verified, though, interestly, the dynamic stability of the structural model itself is automatically enforced and need not be imposed in estimation. The empirical application involves estimation of a single-fator diffusion model for the 30-day Eurodollar interest rate.

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Bibliographic Info

Paper provided by Duke University, Department of Economics in its series Working Papers with number 95-42.

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Date of creation: 1995
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Publication status: Published in ADVANCES IN ECONOMICS AND ECONOMETRICS: THEORY AND APPLICATIONS, Vol. III, Econometric Society Monographs No. 28, David M. Kreps and Kenneth F. Wallis (eds.), Cambridge University Press, 1997, pages 279-317
Handle: RePEc:duk:dukeec:95-42

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Postal: Department of Economics Duke University 213 Social Sciences Building Box 90097 Durham, NC 27708-0097
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Web page: http://econ.duke.edu/

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Cited by:
  1. Martin, V.L. & Wilkins, N.P., 1997. "Indirect Estimation of Arfima and Varfima Models," Department of Economics - Working Papers Series 547, The University of Melbourne.
  2. Rómulo Chumacero & Jorge Quiroz, 1996. "La Tasa Natural de Crecimiento de la Economía Chilena: 1985-1996," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 33(100), pages 453-472.
  3. Durham, Garland B., 2003. "Likelihood-based specification analysis of continuous-time models of the short-term interest rate," Journal of Financial Economics, Elsevier, vol. 70(3), pages 463-487, December.
  4. Andersen, Torben G. & Lund, Jesper, 1997. "Estimating continuous-time stochastic volatility models of the short-term interest rate," Journal of Econometrics, Elsevier, vol. 77(2), pages 343-377, April.
  5. Mc Manus, Des & Watt, David, 1999. "Estimating One-Factor Models of Short-Term Interest Rates," Working Papers 99-18, Bank of Canada.

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