Econometric models of Manitoba crop acreage demand and yield response under risk and uncertainty

The purpose of this research is to estimate econometric models of crop supply response for Manitoba using data aggregated at the provincial level for 1960-1987. In contrast to most other studies, this research (a) decomposes crop supply response to price into the acreage and yield components which...

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Bibliographic Details
Main Author: Mundang, Atikarn
Published: 2012
Online Access:http://hdl.handle.net/1993/7379
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Summary:The purpose of this research is to estimate econometric models of crop supply response for Manitoba using data aggregated at the provincial level for 1960-1987. In contrast to most other studies, this research (a) decomposes crop supply response to price into the acreage and yield components which are estmimated separately and (b) estimates duality models incorporated risk aversion. First, ad hoc static and distriubted lag models of crop yield response to expected price and price variance for crops were estimated. In static models expected price was insignificant and price variance was often significant. In contrast a distributed lag in expected prices was often significant in risk-neutral models, and distributed lags in expected prices and price variance were generally significant. Second, static duality models of crop acreage allocations were estimated. Models with yields (or the distribution of yields) predetermined relative to acreage decisions were emphaized. Results generally indicated that both mean and variance of revenues per acre (or of crop prices) were significant allowing for risk aversion and uncertainty of either (but not both) crop prices or crop yields. Third, dynamic duality models of crop yields were formulated assuming adjustment costs for crop yields as well as for capital investment, nonstatic expectations for prices and crop acreages, risk aversion and price uncertainty (risk is modelled as timeless rather than as temporal). Preliminary results indicate that price variance and lags in adjustment are significant in crop yield equations, as in the earlier ad hoc distributed lag models.