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ON DISCRETE SAMPLING OF TIME-VARYING CONTINUOUS-TIME SYSTEMS

Published online by Cambridge University Press:  01 August 2009

Peter M. Robinson
Peter M. Robinson*
Affiliation:
London School of Economics
*
*Address correspondence to Peter M. Robinson, Department of Economics, London School of Economics, Houghton Street, London WC2A 2AE, United Kingdom; email: [email protected].
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Abstract

We consider a multivariate continuous-time process, generated by a system of linear stochastic differential equations, driven by white noise, and involving coefficients that possibly vary over time. The process is observable only at discrete, but not necessarily equally-spaced, time points (though equal spacing significantly simplifies matters). Such settings represent partial extensions of ones studied extensively by A.R. Bergstrom. A model for the observed time series is deduced. Initially we focus on a first-order model, but higher-order models are discussed in the case of equally-spaced observations. Some discussion of issues of statistical inference is included.

Type
ARTICLES
Information
Econometric Theory , Volume 25 , Issue 4: Bergstrom Memorial Dedication Issue , August 2009 , pp. 985 - 994
Copyright
Copyright © Cambridge University Press 2009

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