In the wake of the Great Recession, local policymakers are working harder than ever to differentiate their areas as friendly to small businesses and economic development. As part of these efforts, billions of public dollars are spent every year to attract companies, big and small, through the use of venture capital, tax incentives, public-private partnerships, workforce training, capital improvements, and many other tools. As economic development has become more competitive, policymakers are offering more and more to attract jobs and new opportunities for their constituencies. Though it is clear that these financial incentives are producing results in some areas, there are other environmental factors that policymakers can improve to attract more new businesses.
One of the areas most overlooked when comparing competing metro areas is a livability factor, or quality of life, that makes certain areas more attractive to individuals and thus businesses. One of the most often cited reasons for the location of a new business, especially a small business, is quality of life, yet it is one of the areas policymakers most often overlook in attracting entrepreneurs and the highly skilled people who most often work for them.1, 2, 3
After all, in addition to the fact that an entrepreneur wants to start their business in a place where it can thrive, making economic and tax factors important, the person must also want to live there. This is especially true for high-tech and computer-related businesses that can increasingly be created and sustained virtually anywhere. Quality of life, though not always the first consideration in deciding where to start a business, can be the X factor that differentiates two competitive metro areas.
The primary reason that quality of life is so often overlooked in this process is that it can be difficult to measure objectively. Quality of life is a subjective, intangible thing that can mean different things to different people. People have different priorities in terms of their quality of life, and they cannot be totally controlled for. In addition, things such as geography and weather are out of policymakers’ control. For example, the mayor of Lincoln, Neb., cannot simply move his city to the beach to attract more tech startups.
To assemble an objective QOL index, a variety of factors were compiled by metro area, ranging from life expectancy to the share of childhood poverty. The most influential variables on new business startups fall under four different categories, each generally synonymous with a high quality of living: public safety, public education, child welfare and recreation.
This study attempts to construct as objective a measure of quality of life as possible, based on concepts that are widely accepted as contributing to a higher standard of living. More important, it also attempts to include measures that can at least nominally be influenced by local policymakers and their decisions. It is important for the purpose of this study that quality of life be a dynamic measure, susceptible to changes in public policy. Based on this research, this study then attempts to go a step further by comparing the objective Quality of Life Index, or QOL, to business formation in U.S. metropolitan statistical areas. By comparing the measures, we can see how much entrepreneurial decisions may be influenced by, or at the very least correlated to, quality of life.
To assemble an objective QOL, a variety of factors were compiled by metro area, ranging from life expectancy to the share of childhood poverty. Data limitations on some variables prevented the inclusion of a handful of metro areas and all metro divisions from being included in this study.4
The most influential variables on new business startups fall under four different categories, each generally synonymous with a high quality of living: public safety, public education, child welfare and recreation. Data from 2011 were used, as it was the most recent year for which full data were available. Specific measures include:
Impacts on Business Formation
- Per capita crime rate
- High school or equivalent educational attainment rate
- Per capita access to recreational facilities
- Percentage of children living in poverty under the age of 5
Not surprisingly, the results show a high quality of life across a large concentration of relatively established Northeast and upper Midwest and West metro areas. With one notable exception, each of the metro areas in the top 10 score better than average in each of the four categories. However, particularly low rates for both crime and child poverty are the most common attribute among metro areas with the highest QOLs. This indicates higher income levels, often accompanied by higher levels of business startups. The major exception in the top 10 is Ocean City, NJ, which has an abnormally high concentration of recreational facilities relative to its population.
The 10 metro areas with the lowest QOL scores, by contrast, were across California’s Central Valley and the South. Each performed generally poor across all four facets of the QOL, with no easily discernible pattern except that each is home to some of the highest levels of poverty in the country. In general, the South performed the worst of the four census regions, with only a handful of metro areas in the top quartile. Metro areas with secularly declining industries such as nondurable manufacturing and lacking a dynamic private service industry driver typically fared the worst within the region.
Quality-of-life factors appear to be able to explain roughly a third of new-business formations across the country by metro area.
It is important, however, not to jump to conclusions too quickly based solely on these measures. Correlation does not necessarily indicate causation. Therefore, it is possible, and likely probable, that a relatively low QOL is at least partly the result of a dearth of new-business activity, and not necessarily the total cause of it.
The results of the comparison between QOL and new-business formations show significant, but not perfect, correlation. Based solely upon the econometric results of the analysis, QOL factors appear to be able to explain roughly a third of new-business formations across the country by metro area. However, when looked at from a deeper regional perspective, QOL takes on a larger significance within new business formations. Thus, while QOL may be only a secondary factor in determining which metro areas experience the most new business growth nationwide, it becomes a much more significant driver of growth within specific regions themselves.
Looking to Policy
The results of this study demonstrate that QOL can be both a cause and an effect of higher business formation rates and economic development. More important, this study concludes that there are areas of public policy that can create a more fertile environment for business investment beyond the tax and regulatory environment.
Large discrepancies between regional competitors can be used to explain differing results in economic development efforts. Metro areas in competitive regions can use a higher QOL as a trump card in attracting more entrepreneurs and the highly skilled workers who typically work for them. Generally, the greater the differentiation in QOL, the greater the differentiation of the number of successful new businesses being started. Furthermore, QOL proved more influential on startups in areas experiencing faster in-migration and population growth. Taken in concert with efforts to create a sound business environment from a tax and regulatory perspective, a strong focus on public safety, public education, child welfare, and recreation by local policymakers is vital in attracting entrepreneurs and high-skilled workers into the local economy. Thus, local policymakers should be concerned with making their areas more profitable and more livable.