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Control variates for variance reduction in indirect inference: Interest rate models in continuous time

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  • GIORGIO CALZOLARI
  • FRANCESCA DI IORIO
  • GABRIELE FIORENTINI

Abstract

Simulation estimators, such as indirect inference or simulated maximum likelihood, are successfully employed for estimating stochastic differential equations. They adjust for the bias (inconsistency) caused by discretization of the underlying stochastic process, which is in continuous time. The price to be paid is an increased variance of the estimated parameters. The variance suffers from an additional component, which depends on the stochastic simulation involved in the estimation procedure. To reduce this undesirable effect, one could increase the number of simulations (or the length of each simulation) and thus the computational cost. Alternatively, this paper shows how variance reduction can be achieved, at virtually no additional computational cost, by use of control variates. The Ornstein-Uhlenbeck process, used by Vasicek to model the short-term interest rate in continuous time, and the square-root process, used by Cox, Ingersoll and Ross, are explicitly considered and experimented with. Monte Carlo experiments show a global efficiency gain of almost 50% over the simple indirect estimator.

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Bibliographic Info

Article provided by Royal Economic Society in its journal The Econometrics Journal.

Volume (Year): 1 (1998)
Issue (Month): ConferenceIssue ()
Pages: C100-C112

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Handle: RePEc:ect:emjrnl:v:1:y:1998:i:conferenceissue:p:c100-c112

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Keywords: Efficient Monte Carlo; Variance reduction techniques; Control variates; Indirect inference; Euler discretization; Short-term interest rate; Stochastic differential equation.;

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References

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  1. Bianchi, Carlo & Cleur, Eugene M, 1996. "Indirect Estimation of Stochastic Differential Equation Models: Some Computational Experiments," Computational Economics, Society for Computational Economics, vol. 9(3), pages 257-74, August.
  2. Hendry, David F. & Harrison, Robin W., 1974. "Monte Carlo methodology and the small sample behaviour of ordinary and two-stage least squares," Journal of Econometrics, Elsevier, vol. 2(2), pages 151-174, July.
  3. Chan, K C, et al, 1992. " An Empirical Comparison of Alternative Models of the Short-Term Interest Rate," Journal of Finance, American Finance Association, vol. 47(3), pages 1209-27, July.
  4. Brennan, Michael J. & Schwartz, Eduardo S., 1979. "A continuous time approach to the pricing of bonds," Journal of Banking & Finance, Elsevier, vol. 3(2), pages 133-155, July.
  5. BROZE, Laurence & SCAILLET, Olivier & ZAKOIAN, Jean-Michel, . "Quasi-indirect inference for diffusion processes," CORE Discussion Papers RP -1327, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  6. Hendry, David F., 1984. "Monte carlo experimentation in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 16, pages 937-976 Elsevier.
  7. Vasicek, Oldrich, 1977. "An equilibrium characterization of the term structure," Journal of Financial Economics, Elsevier, vol. 5(2), pages 177-188, November.
  8. Broze, Laurence & Scaillet, Olivier & Zakoian, Jean-Michel, 1995. "Testing for continuous-time models of the short-term interest rate," Journal of Empirical Finance, Elsevier, vol. 2(3), pages 199-223, September.
  9. Calzolari, Giorgio & Sterbenz, Frederic P, 1986. "Control Variates to Estimate the Reduced Form Variances in Econometric Models," Econometrica, Econometric Society, vol. 54(6), pages 1483-90, November.
  10. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
  11. Bianchi, C. & Cesari, R. & Panattoni, L., 1994. "Alternative Estimators of the Cox, ingersoll and Ross Model of the Term Structure of Interest Rates: A Monte Carlo Comparison," Papers 236, Banca Italia - Servizio di Studi.
  12. Michael J. Brennan and Eduardo S. Schwartz., 1979. "A Continuous-Time Approach to the Pricing of Bonds," Research Program in Finance Working Papers 85, University of California at Berkeley.
  13. Calzolari, Giorgio, 1979. "Antithetic variates to estimate the simulation bias in non-linear models," Economics Letters, Elsevier, vol. 4(4), pages 323-328.
  14. Cox, John C & Ingersoll, Jonathan E, Jr & Ross, Stephen A, 1985. "A Theory of the Term Structure of Interest Rates," Econometrica, Econometric Society, vol. 53(2), pages 385-407, March.
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Cited by:
  1. Giorgio Calzolari & Francesca Di Iorio & Gabriele Fiorentini, 2001. "Indirect inference and variance reduction using control variates," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1-2), pages 39-53.
  2. 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".
  3. 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.
  4. Liesenfeld, Roman & Breitung, Jörg, 1998. "Simulation based methods of moments in empirical finance," SFB 373 Discussion Papers 1998,59, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  5. Enrique Sentana & Giorgio Calzolari & Gabriele Fiorentini, 2004. "Indirect Estimation Of Conditionally Heteroskedastic Factor Models," Working Papers wp2004_0409, CEMFI.
  6. Giorgio Calzolari & F. Mealli & C. Rampichini, 2001. "Alternative Simulation-Based Estimators of Logit Models with Random Effects," Econometrics Working Papers Archive quaderno48, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

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