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Statistical Inference for a Random Coefficient Autoregressive Model
P. M. Robinson
Scandinavian Journal of Statistics
Vol. 5, No. 3 (1978), pp. 163-168
Published by: Wiley on behalf of Board of the Foundation of the Scandinavian Journal of Statistics
Stable URL: http://www.jstor.org/stable/4615707
Page Count: 6
You can always find the topics here!Topics: Statism, Time series, Random variables, Autoregressive models, Estimators, Sine function, Economic models, Statistical estimation, Stochastic processes, Autocorrelation
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A first-order autoregressive (AR(1)) model is considered, involving a coefficient that is a random variable, and may vary over realizations. In the usual AR(1) model the coefficient has a degenerate distribution, and is thus constant over realizations. We show how moments of the coefficient can be identified in terms of the autocovariances. Using mixed cross-section and time series data, we show how the moments can be estimated, and establish the strong consistency and asymptotic normality of the estimators. We suggest several parametric forms for the distribution of the coefficient, and show how unknown parameters may be determined. The results are applied to real data.
Scandinavian Journal of Statistics © 1978 Board of the Foundation of the Scandinavian Journal of Statistics