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

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

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)463-484
Number of pages22
JournalJournal of Agricultural Economics
Volume65
Issue number2
DOIs
StatePublished - Jun 2014

Keywords

  • Bayesian model averaging
  • Bayesian spatial probit
  • Congressional vote dependence
  • Markov chain Monte-Carlo methods
  • PAC contributions and their effectiveness
  • Political economy
  • Spatial correlations

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