Self-employment by US county: key predictors

Abstract

Purpose Some US counties are more likely to generate entrepreneurial opportunities than others. This paper aims to determine the linkages between US counties with disproportionately high shares of entrepreneurs and specific attributes of the entrepreneurial support system. Design/methodology/approach Non-farm proprietorship (NFP) has been used as a proxy for entrepreneurship and self-employment. NFP employment data were collected from the US Bureau of Economic Analysis by county. Data on all independent variables were obtained from the US Census and Bureau of Economic Analysis by county and subject to stepwise linear regression analysis. Findings Results revealed a strong positive relationship between the percent of NFP employment by county and the percent real estate, rental and leasing employment and construction employment as well as percent Hispanic and median age. Practical implications In attempting to encourage NFP employment, policymakers should be more aware of the key predictors that shape county-wide entrepreneurial ecosystems to enhance competitive advantage. Better understanding of the needs and experiences of different types of entrepreneurs and ecosystems can enhance overall quality of life and economic opportunity levels in a community. Originality/value The explicit spatial context of this paper has sometimes been overlooked in the traditional entrepreneurship literature, as such, this paper helps fill that gap. The findings provide a disaggregated analysis that can help better understand the key predictors that can drive the local choices of entrepreneurs and help local policymakers to build more competitive communities.

Non-farm proprietorship employment by micropolitan county

“…They also found that higher shares of employment in FIRE can spur NFP employment growth. Bignall and Debbage (2020) recently partly confirmed some of these trends at a more disaggregated scale of analysis in a study that analyzed the geography of NFP for 800 of the most populated counties in the US. They found that the share of NFP employment by county was highly uneven with significant clusters in Atlanta, New York, eastern Texas and Oklahoma, south Florida and northern California.…”

“…In a recent article, Kline et al (2020) referred to entrepreneurs as "some of the most significant change agents in development" (p. 15). Although there is no universal definition of entrepreneurship (Backman and Lööf, 2015), nonfarm proprietorship (NFP) employment has been commonly used as a proxy to better understand the determinants of growth and spatial distribution of entrepreneurship and self-employment (Goetz and Rupasingha, 2009;Debbage and Bowen, 2018;Bignall and Debbage, 2020). Since the Great Recession, NFP employment has played an increasingly important role in local economies growing by 25.5% from 35.5 million workers in 2009 to 44.6 million workers in 2018 (U.S. Bureau of Economic Analysis, 2020).…”

“…large, under-skilled immigrant labor pools and elderly populations looking to supplement incomes) and a self-employment of opportunity (e.g. access to capital and vibrant real estate markets) (Bignall and Debbage, 2020;Debbage and Bowen, 2018;Goetz and Rupasingha, 2009;Stam, 2009), the situation at the micropolitan scale will depart notably from this convention. We will suggest that while thriving construction and real estate markets may lie at the heart of NFP employment Nonfarm proprietorship employment generation and a related self-employment of opportunity, the notion that micropolitan communities with disproportionately large elderly populations are surrogate indicators for "out of necessity" self-employment may be partially flawed.…”

Agri-food entrepreneurship. Harvesting, growing and reseeding the orchard through a bibliometric study

“…In particular, 64 items were not consistent with the first criterion (e.g. Bignall and Debbage, 2020; Hazarika et al. , 2016), 36 items were omitted based on criterion 2 (e.g.…”

“…In particular, 64 items were not consistent with the first criterion (e.g. Bignall and Debbage, 2020;Hazarika et al, 2016), 36 items were omitted based on criterion 2 (e.g. Rong-Da Liang, 2017;Wu, 2015) and 51 were removed following the last criterion (e.g.…”