Economic Development, Resilience, and Innovation

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Health Insurance and National Farm Policy

In the midst of national healthcare debates, there has been little discussion of how health, healthcare costs and access, and health insurance fit into national agriculture policy efforts to build a more vibrant and resilient farm economy. Yet Inwood (2015) found that 65% of commercial farmers identified the cost of health insurance as the most serious threat to their farm, more significant than the cost of land, inputs, market conditions, or development pressure. In order to grow the next generation of farmers and increase rural prosperity, there is a need to understand how healthcare costs, access, and insurance affect both agriculture and rural development.

Authors: Shoshanah Inwood, Alana Knudson, Florence A. Becot, Bonnie Braun, Stephan J. Goetz, Jane M. Kolodinsky, Scott Loveridge, Katlyn Morris, Jason Parker, Bob Parsons, Rachel Welborn, Don E. Albrecht

Publication: Choices Date Published: March 1, 2018

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State-Level Cooperative Extension Spending and Farmer Exits

Abstract: Numerous studies have evaluated the impact of Extension on farm productivity and related outcomes. Here we use annual data from 1983 to 2010 covering the 50 U.S. states to examine the impact of Extension on net changes in the number of farmers. The historical transition of farmers out of U.S. agriculture raises the question of whether Cooperative Extension and underlying Hatch-funded research spending keeps farmers in agriculture or accelerates their exit. On balance, nearly 500,000 more farmers left than entered agriculture over the period studied. We estimate that without Extension, as many as 137,700 (or 28%) additional farmers would have disappeared on net. Overall, Extension programs are a remarkably cost effective way of keeping farmers in agriculture. Alternatively, shifting just 1.5% of federal farm program payments to Extension would have reduced net exits over this period by an estimated 11%, or 55,000 farmers.

A related infographic (below) was developed to help share the findings of this research.

Authors: Stephan J. Goetz and Meri Davlasheridze

Publication: Applied Economic Perspectives and Policy Date Published: April 19, 2016

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The interactive effects of human capital and quality of life on economic growth

To bridge the gap in the quality of life (QOL) and economic growth literature and understand the reinforcing effects of QOL and human capital on economic development, we examine the interactive effects of these two factors on wage growth from 2000 to 2007 at the county level across the United States. First, a Rosen–Roback model is employed to estimate implicit values of amenities including climate, clean air and other natural attributes, which are used to generate QOL indices. Second, QOL, human capital represented by the share of college graduates, and their interaction serve as key variables in the wage growth model. An instrumental variable approach and location fixed effects are used to address endogeneity of human capital and control for location-specific unobservable characteristics. Results suggest that human capital and QOL significantly contribute to economic growth and the growth effects are even larger in nonmetropolitan counties. Importantly, we find that the effect of human capital on growth is larger in high-QOL counties and QOL enhances the effect of human capital on growth. Our results provide empirical support for community development strategies through providing utility-enhancing amenities that improve QOL and retain human capital.

Authors: Qin Fan, Stephan J. Goetz, Jiaochen Liang

Publication: Applied Economics Date Published: March 19, 2016

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Targeting Regional Economic Development (TRED)

Authors: Steven Deller, Thomas Harris, John Leatherman

Publication: An online resource published by the Regional Rural Development Centers Date Published: March 14, 2025

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Wal-Mart and County-Wide Poverty

Abstract

Objectives. This study seeks to identify the independent effect of Wal-Mart stores on changes in U.S. family-poverty rates at the county level. We draw on the contributions of a number of disciplines to enhance our understanding of the broader forces that influence poverty.

Methods. A key innovation is that we estimate a two-stage regression model, in which an instrument is created for new Wal-Mart stores from a location equation; this reduces any potential endogeneity bias in the poverty-change equation. In addition, we use spatial econometric methods to correct for spatial dependence bias.

Results. After controlling for other factors determining changes in the poverty rate over time, we find that counties with more initial (1987) Wal-Mart stores and counties with more additions of stores between 1987 and 1998 experienced greater increases (or smaller decreases) in family-poverty rates during the 1990s economic boom period.

Conclusions. Wal-Mart creates both benefits and costs to communities in which the chain locates. These benefits and costs need to be weighed carefully by community decisionmakers in deciding whether to provide public subsidies to the chain.

Authors: Stephan J. Goetz, Hema Swaminathan

Publication: Social Science Quarterly Date Published: May 9, 2006

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