How do entrepreneurship rates vary across different races?

The purpose of this paper is to examine the time-series dynamics of entrepreneurship rates for different race classifications based on household characteristics over the 1996 through 2013 period.

Using microdata from the Kauffman Foundation, this study investigates the roles of unemployment, homeownership, income, immigration, education, age, gender and marital status in relation to entrepreneurship rates for different race classifications through ridge regression analysis.

Results suggest that the time-series variation in entrepreneurship rates for different race classifications are variable-dependent, moreover, the economic and statistical significance of the candidate explanatory variables are sensitive to the time period under analysis. Unemployment, homeownership, education, age and marital status are significant variables for whites while unemployment, income, immigration and gender variables are significant for blacks. For the case of Native Americans and Asians, the candidate explanatory variables do not explain the time-series variation in entrepreneurship rates for the sample periods in this study.

This study exhibits implications for public policy in helping to promote entrepreneurship at the individual level and help stimulate entrepreneurial activity as a mechanism for promoting economic growth.

The findings suggest the importance of examining entrepreneurship rates across time based on race classifications. This study highlights the importance of conducting ridge regression analysis for different sub-periods in time when assessing entrepreneurship rates.