Abstract
The number of food hubs—businesses that aggregate and distribute local food—in the United States is growing, fueled in part by increasing public support. However, there have been few data-driven assessments of the economic impacts of these ventures. Using an input-output-based methodology and a unique data set from a successful food hub, we measure net and gross impacts of a policy supporting their development. We estimate a gross output multiplier of 1.75 and an employment multiplier of 2.14. Using customer surveys, we estimate that every $1 increase in final demand for food hub products generates a $0.11 reduction in purchases in other sectors.
Highlights
The number of food hubs—businesses that aggregate and distribute local food—in the United States is growing, fueled in part by increasing public support
We consider a scenario in which an exogenous shock increases final demand for food hub products and services by $1 million
This study develops a replicable empirical framework for conducting assessments of the impacts of food hub organizations
Summary
The number of food hubs—businesses that aggregate and distribute local food—in the United States is growing, fueled in part by increasing public support. The role of small-scale and medium-scale producers in developing local and regional food systems has attracted renewed attention as their importance in supplying alternative food markets has gained recognition (Low and Vogel 2011). Despite the purported potential for local food systems to increase farm sales, for small-scale and mid-scale producers, and support rural economic development, the U.S Department of Agriculture (USDA) acknowledged a “lack of distribution systems for moving local foods into mainstream markets” Large-scale supermarket retail and wholesale operations demand large volumes, low prices, and consistent quantities and qualities that meet increasingly strict safety standards, and the procurement systems in such markets are often vertically and horizontally integrated, global in scale, and aimed at maximizing efficiency (King et al 2010, Richards and Pofahl 2010, Sexton 2010, Tropp, Ragland, and Barham 2008)
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