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On a model for a time series of cross-sections

Published online by Cambridge University Press:  14 July 2016

P. M. Robinson
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Abstract

Dynamic stationary models for mixed time series and cross-section data are studied. The models are of simple, standard form except that the unknown coefficients are not assumed constant over the cross-section; instead, each cross-sectional unit draws a parameter set from an infinite population. The models are framed in continuous time, which facilitates the handling of irregularly-spaced series, and observation times that vary over the cross-section, and covers also standard cases in which observations at the same regularly-spaced times are available for each unit. A variety of issues are considered, in particular stationarity and distributional questions, inference about the parameter distributions, and the behaviour of cross-sectionally aggregated data.

Keywords

RANDOM COEFFICIENT MODELSCONTINUOUS-TIME PROCESSESASYMPTOTIC EXPANSIONS

Information

Type
Part 2—Estimation for Time Series
Information
Journal of Applied Probability , Volume 23 , Issue A: Essays in Time Series and Allied Processes , 1986, pp. 113 - 125
Copyright
Copyright © 1986 Applied Probability Trust 

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