How Large is Congressional Dependence in Agriculture? Bayesian Inference about ‘Scale’ and ‘Scope’ in Measuring a Spatial Externality
利用2001年农业法案的国会投票数据，通过贝叶斯模型平均和马尔可夫链蒙特卡洛方法，估计了投票行为中空间相互依赖的强度和地理范围。
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.