Hostname: page-component-76fb5796d-9pm4c Total loading time: 0 Render date: 2024-04-28T08:01:15.988Z Has data issue: false hasContentIssue false

QUASI-INDIRECT INFERENCE FOR DIFFUSION PROCESSES

Published online by Cambridge University Press:  01 April 1998

Laurence Broze
Affiliation:
Gremars, Université de Lille 3 and CORE
Olivier Scaillet
Affiliation:
Université Catholique de Louvain
Jean-Michel Zakoïan
Affiliation:
Université de Lille 1 and CREST

Abstract

We discuss an estimation procedure for continuous-time models based on discrete sampled data with a fixed unit of time between two consecutive observations. Because in general the conditional likelihood of the model cannot be derived, an indirect inference procedure following Gouriéroux, Monfort, and Renault (1993, Journal of Applied Econometrics 8, 85–118) is developed. It is based on simulations of a discretized model. We study the asymptotic properties of this “quasi”-indirect estimator and examine some particular cases. Because this method critically depends on simulations, we pay particular attention to the appropriate choice of the simulation step. Finally, finite-sample properties are studied through Monte Carlo experiments.

Type
Research Article
Copyright
© 1998 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)