Abstract
Measures of entrepreneurship, such as average establishment size and the prevalence of start-ups, correlate strongly with employment growth across and within urban areas. Is it possible for entrepreneurship to occur outside of urban areas and be active in rural areas such as Ohio, Pennsylvania, and West Virginia? There are causal links of entrepreneurial finance to industry or city growth but little link of the evidence of entrepreneurship outside of urban areas overall. This chapter examines the regional variation in startup concentration used to predict employment in the rural areas of Pennsylvania, Ohio, and West Virginia by metropolitan statistical area (MSA)/micropolitan areas for the year 2017. The authors find significant differences in new firm formation rates from industrial regions to technologically progressive regions using the generalized linear models (GLM). Variations in firm birth rates are explained by industrial size, population growth, the number of startups, human capital variables, and establishments.
TopExisting Research
It is well understood that startups create most new jobs in the United States’ economy, and these jobs promote regional economic development (Haltiwanger, Jarmin, & Miranda, 2013). Schumpeter (1911, 1947) originally posited that startups are recognized as playing an important role in driving growth through innovation. In fact, startups create new jobs because they are sources of innovation that are good investment opportunities and create employment.
It has been argued that urban success depends upon a city’s level of entrepreneurship or that entrepreneurship is mainly relegated to urban areas. This claim was famously made in Chinitz’s (1961) comparison of New York and Pittsburgh and invoked by Saxenian (1994) to show the contrasts of regional performance of Boston and Silicon Valley. Glaeser, Kerr, and Ponzetto (2010) also document the strength of this relationship when modelling entrepreneurship through start-up employment shares. Similar conclusions are also reached by Delgado, Porter, and Stern (2010) as well as Gennaioli et al. (2012).
Key Terms in this Chapter
Generalized Linear Models (GLM): It is a flexible generalization of ordinary linear regression (OLS) that allows for the dependent variable to have error distribution models other than a normal distribution.
Metropolitan Statistical Area (MSA): It is a geographical region with a relatively high population density at its core and close economic ties throughout the area. MSAs are defined by the U.S. Office of Management and Budget (OMB), and the MSAs are used by federal government agencies for statistical purposes.
Micropolitan Areas: It is a geographical region in which the labor market and statistical areas in the United States are centered around an urban area with a population of at least 10,000 but fewer than 50,000 people. It is defined by the U.S. Office of Management and Budget (OMB), and they are used by federal government agencies for statistical purposes.
Entrepreneurship: It is the process of designing, launching and running a new business, which often starts as a small business. It can also be described as the capacity and willingness to develop, organize, and manage a venture along with taking risks to earn a profit.
Proprietorship: It is a business model which an individual and his/her company are considered a single entity for tax purposes. A proprietorship is often not registered with the state as a corporation.
Startup Concentrations: It is a very young company founded by one or more entrepreneurs to develop a unique product or service that is introduced to the market. Its initial funding is usually from its own finances or from families and friends.