Economic Development, Resilience, and Innovation

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: December 30, 2024

Tags: TRED

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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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