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The Boll Weevil Versus “King Cotton”

Published online by Cambridge University Press:  03 March 2009

Kent Osband
Affiliation:
Department of Economics, University of California, Berkeley, California 94720 and Russian Research Center, Harvard University, Cambridge, Massachusetts 02138.

Abstract

The boll weevil's impact on southern agriculture poses a dilemma. Micro-level evidence suggests the weevil triggered a transition out of cotton, but macro-level indicators fail to register much long-term impact. Econometric simulation of boll weevil impact—taking into account the low demand elasticity for southern cotton, differences between states in the timing and levels of infestation, and long-term supply and demand shifts independent of the weevil—shows that the two sets of evidence are not inconsistent.

Type
Articles
Copyright
Copyright © The Economic History Association 1985

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References

I wish to thank Richard Sutch, Albert Fishlow, Peter Lindert, Claudia Goldin, Peter Temin, and anonymous referees for many helpful criticisms of earlier versions of this paper.Google Scholar

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4 Since what is eaten by the weevil need not be harvested, this assumption may exaggerate the marginal weevil impact. Replacing W with W to the k–th power, for k less than 1, equates a 1 percent weevil loss with a k percent price drop. In the model described in the next section, regressions were run for various values of k, but reductions in k consistently worsened the fit.Google Scholar

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11 The rough equivalence between af/ad and the ratio of foreign to domestic production in those years suggests that U.S. and foreign cotton were very close substitutes.Google Scholar

12 From a theoretical standpoint, one would probably not expect γ, the growth rate of the cooton farmer pool, to be independent of the pattern of farmer discouragement. Independence could only hlod if new entrants share the same attitudes (in a probabilistic sense) as currently active cotton farmers. However, alternative specifications with γ dependent on expected shadow price S e did not generate statistically significant parameter estimates.Google Scholar

13 Because the 1909 starting date postdates some severe infestations in Texas and Louisiana and imposes rather arbitrary assumptions about price expectations in that year, the first two or three years of simulations provide less reliable comparisons than later years do.Google Scholar

14 Tables available from author upon request.Google Scholar

15 Differences in timing of equivalent flows out of cotton production may have influenced the proportion of discouraged farmers leaving the South entirely. So the findings must be slightly quanlified with respect to out-migration.Google Scholar

16 Another way in which harvest price may affect supply id though its influence on choice of harvest methods. With higher prices fields may be picked more closely.Google Scholar