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DISTRIBUTED LAGS AND BARLEY ACREAGE RESPONSE ANALYSIS

DISTRIBUTED LAGS AND BARLEY ACREAGE RESPONSE ANALYSIS The need to incorporate production response lags in agricultural supply models is established, and two such lags are considered: the familiar adaptive expectations geometric lag, and a more general polynomial lag. These distributed lag supply response models are applied to Australian barley data for the period 1946‐47 to 1968‐69. A number of statistical problems associated with the adaptive expectations model are discussed, and in particular it is concluded that lags both in the formation of price expectations and in acreage adjustment should be considered when using geometric lag models. While the polynomial lag model does not provide useful results in the present study, its simplicity and flexibility suggest it may be useful in other studies requiring distributed lag models. The short run and long run price elasticity of barley supply estimates are compared with Gruen et al. [14] supply elasticities for the other major rural commodities, from which it appears that barley has a higher short run elasticity but a lower long run elasticity than wheat, wool and meat. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Australian Journal of Agricultural Resource Economics Wiley

DISTRIBUTED LAGS AND BARLEY ACREAGE RESPONSE ANALYSIS

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Publisher
Wiley
Copyright
Copyright © 1974 Wiley Subscription Services, Inc., A Wiley Company
ISSN
1364-985X
eISSN
1467-8489
DOI
10.1111/j.1467-8489.1974.tb00132.x
Publisher site
See Article on Publisher Site

Abstract

The need to incorporate production response lags in agricultural supply models is established, and two such lags are considered: the familiar adaptive expectations geometric lag, and a more general polynomial lag. These distributed lag supply response models are applied to Australian barley data for the period 1946‐47 to 1968‐69. A number of statistical problems associated with the adaptive expectations model are discussed, and in particular it is concluded that lags both in the formation of price expectations and in acreage adjustment should be considered when using geometric lag models. While the polynomial lag model does not provide useful results in the present study, its simplicity and flexibility suggest it may be useful in other studies requiring distributed lag models. The short run and long run price elasticity of barley supply estimates are compared with Gruen et al. [14] supply elasticities for the other major rural commodities, from which it appears that barley has a higher short run elasticity but a lower long run elasticity than wheat, wool and meat.

Journal

The Australian Journal of Agricultural Resource EconomicsWiley

Published: Aug 1, 1974

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