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How Large is Congressional Dependence in Agriculture? Bayesian Inference about ‘Scale’ and ‘Scope’ in Measuring a Spatial Externality

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  • Garth Holloway
  • Donald J. Lacombe
  • Timothy M. Shaughnessy

Abstract

type="main" xml:id="jage12054-abs-0001"> The political economy literature on agriculture emphasises influence over political outcomes via lobbying conduits in general, political action committee contributions in particular, and the pervasive view that political preferences with respect to agricultural issues are inherently geographic. In this context, ‘interdependence’ in Congressional vote behaviour manifests itself in two dimensions. One dimension is the intensity by which neighbouring vote propensities influence one another, and the second is the geographic extent of voter influence. We estimate these facets of dependence using data on a Congressional vote on the 2001 Farm Bill using routine Markov chain Monte-Carlo procedures and Bayesian model averaging, in particular. In so doing, we develop a novel procedure to examine both the reliability and the consequences of different model representations for measuring both the ‘scale’ and the ‘scope’ of spatial (geographic) co-relations in voting behaviour.

Suggested Citation

  • Garth Holloway & Donald J. Lacombe & Timothy M. Shaughnessy, 2014. "How Large is Congressional Dependence in Agriculture? Bayesian Inference about ‘Scale’ and ‘Scope’ in Measuring a Spatial Externality," Journal of Agricultural Economics, Wiley Blackwell, vol. 65(2), pages 463-484, June.
    • Handle: RePEc:bla:jageco:v:65:y:2014:i:2:p:463-484
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    File URL: http://hdl.handle.net/10.1111/jage.2014.65.issue-2
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    Cited by:

    1. Joshua C. Hall & Christopher Shultz & E. Frank Stephenson, 2018. "The political economy of local fracking bans," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(2), pages 397-408, April.

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