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Entrepreneurial finance, credit cards, and race

Journal of Financial Economics 2012 106(1), 182-195
This paper examines the impact of financial deregulation on entrepreneurship. We assess the impact of credit card deregulation on transitions into self-employment using state-level removal of credit card interest rate ceilings following the US Supreme Court's 1978 Marquette decision as a quasi-natural experiment. We find that credit card deregulation increases the probability of entrepreneurial entry, with a particularly strong effect for black entrepreneurs. We demonstrate that these effects are magnified in states with a history of racial discrimination and link the results to discrimination-based barriers to entry.

The Impact of City Contracting Set-Asides on Black Self-Employment and Employment

Journal of Labor Economics 2014 32(3), 507-561
In the 1980s, many US cities initiated programs reserving a proportion of government contracts for minority-owned businesses. The staggered introduction of these set-aside programs is used to estimate their impacts on the self-employment and employment rates of African American men. Black business ownership rates increased significantly after program initiation, with the black-white gap falling 3 percentage points. The evidence that the racial gap in employment also fell is less clear as it depends on assumptions about the continuation of preexisting trends. The black gains were concentrated in industries heavily affected by set-asides, and they mostly benefited the better educated.

Eponymous Entrepreneurs

American Economic Review 2017 107(6), 1638-1655
We demonstrate that eponymy—firms being named after their owners—is linked to superior firm performance, but is relatively uncommon (about 19 percent of firms in our data). We propose an explanation based on eponymy creating an association between the entrepreneur and her firm that increases the reputational benefits/costs of successful/unsuccessful outcomes. We develop a corresponding signaling model, which further predicts that these effects will be stronger for entrepreneurs with rarer names. We find support for the model's predictions using a unique panel dataset consisting of over 1.8 million firms. (JEL D82, L25, L26, M13)