The interplay between tax policy and entrepreneurial activity has been a popular topic of political discourse, especially among state-level policymakers, with the promotion of small business start-ups and success being a key policy goal. The effect of state policy on entrepreneurship has also been the focus in the most recent empirical economics literature. We expand upon that literature in several important ways. First, while most of the recent studies have relied upon conventional fixed effects regression models, we argue that such an approach misses the inherent trends in both tax policies and small business outcomes within states over time. We explore dynamic specifications to capture those trends. Second, while most of the prior research has focused on extensive-margin indicators of small business activity (e.g., self-employment rates or counts of small businesses), we consider a number of intensive-margin measures of state nonfarm proprietors' success. This is based on our assumption that entrepreneurial sustainability and performance following the initial start-up are more important from a policy perspective than simple counts of small businesses. Our paper is the first to use nonfarm proprietors' income as a direct measure of entrepreneurial success at the state level. We investigate several measures of small business performance derived from nonfarm proprietors' income and employment data, including a measure of productivity (i.e. nonfarm proprietors' income per employed person). Third, we extend the earlier research by including a longer panel (1978-2009) of state data. Despite these innovations, our empirical results echo the recent studies in this area and suggest that most of the highly-visible state tax policies do not have statistically significant impacts on entrepreneurial performance.
We examine the effect of prescription opioids on county labor market outcomes, using data from the Prescription Drug Monitoring Programs of ten U.S. states and labor data from the Bureau of Labor Statistics. We achieve causal identification by exploiting plausibly exogenous variation in the concentration of high-volume prescribers as instruments (using Medicare Part D prescriber data). We find strong adverse effects on labor force participation rates, employmentto-population ratios, and unemployment rates. Notably, a 10 percent increase in prescriptions causes a 0.56 percentage point reduction in labor force participation, similar to the drop attributed to the 1984 liberalization of Disability Insurance.
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