Author: Thomas Armstrong Peters

Publisher: National Library of Canada

Published: 1986

Total Pages: 454

ISBN-13: 9780315330290

The least squares estimator of the autoregressive parameter, LS((gamma)), in a first-order stochastic difference equation with independent, identically distributed random innovations is known to be asymptotically unbiased, efficient and consistent (as T ( -->) (INFIN) or (sigma) ( -->) 0) under the proper model specification. Further, LS((gamma)) has a limiting normal distribution around the true parameter, (gamma), if the random innovations are drawn from a normal population. These properties are not observed, however, in sample sizes that are typical of economic time series.