COINTEGRATION BETWEEN U.S. WHEAT MARKETS

Average monthly price data from twelve hinterland markets and the Houston port price for wheat are studied in a cointegration framework using the Engle‐Granger “two‐step” procedure and Johansen's maximum likelihood procedure. Out‐of‐sample forecasts from an error correction model are compared t...

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Bibliographic Details
Published in:Journal of regional science 1993-11, Vol.33 (4), p.481-501
Main Authors: Bessler, David A., Fuller, Stephen W.
Format: Article
Language:English
Subjects:
Agricultural commodities
Agricultural production
Bgi / Prodig
Commodity prices
Comparative analysis
Econometrics
Economic theory
Error correction & detection
General methodology
Grain
Price levels
Regression analysis
Statistical and stochastic methods
Wheat
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Summary:Average monthly price data from twelve hinterland markets and the Houston port price for wheat are studied in a cointegration framework using the Engle‐Granger “two‐step” procedure and Johansen's maximum likelihood procedure. Out‐of‐sample forecasts from an error correction model are compared to those from a vector autoregression fit to levels and a univariate autoregression fit to first differences. This comparison suggests that modeling these (cointegrated) data as a levels vector autoregression, rather than as an error‐correction process, results in significantly higher error bias, but lower error variance, at long horizons.
ISSN:0022-4146
1467-9787
DOI:10.1111/j.1467-9787.1993.tb00844.x