In this paper we postulate, measure, and evaluate the importance of cost-impacts from spatial and industrial spillovers for analysis of economic performance. To accomplish this, we incorporate measures of "activity levels" of related states and industries in a cost function model, and estimate their associated thick market and agglomeration effects in terms of shadow values and elasticities. We focus on the food processing sector, the proximity of own-industry activity in neighboring states, and the supply- and demand- side "drivers", associated with urbanization and localization economies (represented by the GSP and agricultural intensity in the own and neighboring states). We find significant cost-savings benefits to a states food processing sector of being close to other food manufacturing centers (high levels of food processing activity in neighboring states). We also find it beneficial to be in a state with high purchasing power (demand), and to have neighboring states that are agriculture-based (supply). However, it also seems costly to actually be located in a heavily agricultural or rural state, possibly due to diseconomies from "thin markets" associated with infrastructure support and labor markets.
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Paper provided by University of California, Davis, Department of Agricultural and Resource Economics in its series Working Papers with number
11982.
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