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Linear Programming versus Positively Estimated Supply Functions: An Empirical and Methodological Critique
Author(s) -
Shumway C. Richard,
Chang Anne A.
Publication year - 1977
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.2307/1240025
Subject(s) - linear programming , econometrics , series (stratigraphy) , profit (economics) , linear regression , time series , economics , regression , regression analysis , elasticity (physics) , computer science , statistics , mathematics , mathematical optimization , microeconomics , paleontology , materials science , composite material , biology
This paper examines whether supply relations derived from a static profit‐maximizing linear programming model can be used as information to explain supply response with at least the same reliability as partial adjustment regression models. Programming estimates of direct supply elasticities of California commodities are compared with estimates from time‐series regressions. Differences on individual crops are considerable, but on average the elasticity estimates are comparable. Programming parameters are combined with time‐series data to test whether imposing such relative parameters on time‐series models need not significantly reduce their predictive ability. This imposition does not reduce predictive ability or significantly improve it.