Barton H. Hamilton

Does Entrepreneurship Pay? An Empirical Analysis of the Returns to Self-Employment

Possible explanations for earnings differentials in self‐employment and paid employment are investigated. The empirical results suggest that the nonpecuniary benefits of self‐employment are substantial: Most entrepreneurs enter and persist in business despite the fact that they have both lower initial earnings and lower earnings growth than in paid employment, implying a median earnings differential of 35 percent for individuals in business for 10 years. The differential cannot be explained by the selection of low‐ability employees into self‐employment and is similar for three alternative measures of self‐employment earnings and across industries. Furthermore, the estimated earnings differentials may understate the differences in compensation across sectors since fringe benefits are not included in the measure of employee compensation.

Team Incentives and Worker Heterogeneity: An Empirical Analysis of the Impact of Teams on Productivity and Participation

This paper identifies and evaluates rationales for team participation and for the effects of team composition on productivity using novel data from a garment plant that shifted from individual piece rate to group piece rate production over three years. The adoption of teams at the plant improved worker productivity by 14 percent on average. Productivity improvement was greatest for the earliest teams and diminished as more workers engaged in team production, providing support for the view that teams utilize collaborative skills, which are less valuable in individual production. High‐productivity workers tended to join teams first, despite a loss in earnings in many cases, suggesting nonpecuniary benefits associated with teamwork. Finally, more heterogeneous teams were more productive, with average ability held constant, which is consistent with explanations emphasizing mutual team learning and intrateam bargaining.

Does Surgical Quality Improve in the American College of Surgeons National Surgical Quality Improvement Program: An Evaluation of All Participating Hospitals

Background/Objective:The National Surgical Quality Improvement Program (NSQIP) has demonstrated quality improvement in the VA and pilot study of 14 academic institutions. The objective was to show that American College of Surgeons (ACS)-NSQIP helps all enrolled hospitals. Methods:ACS-NSQIP data was used to evaluate improvement in hospitals longitudinally over 3 years (2005–2007). Improvement was defined as reduction in risk-adjusted “Observed/Expected” (O/E) ratios between periods with risk adjustment held constant. Multivariable logistic regression-based adjustment was performed and included indicators for procedure groups. Additionally, morbidity counts were modeled using a negative binomial model, to estimate the number of avoided complications. Results:Multiple perspectives reflected improvement over time. In the analysis of 118 hospitals (2006–2007), 66% of hospitals improved risk-adjusted mortality (mean O/E improvement: 0.174; P < 0.05) and 82% improved risk adjusted complication rates (mean improvement: 0.114; P < 0.05). Correlations between starting O/E and improvement (0.834 for mortality, 0.652 for morbidity), as well as relative risk, revealed that initially worse-performing hospitals had more likelihood of improvement. Nonetheless, well-performing hospitals also improved. Modeling morbidity counts, 183 hospitals (2007), avoided ∼9598 potential complications: ∼52/hospital. Due to sampling this may represent only 1 of 5 to 1of 10 of the true total. Improvement reflected aggregate performance across all types of hospitals (academic/community, urban/rural). Changes in patient risk over time had important contributions to the effect. Conclusions:ACS-NSQIP indicates that surgical outcomes improve across all participating hospitals in the private sector. Improvement is reflected for both poor- and well-performing facilities. NSQIP hospitals appear to be avoiding substantial numbers of complications- improving care, and reducing costs. Changes in risk over time merit further study.

The Small Firm Effect and the Entrepreneurial Spawning of Scientists and Engineers

Scientists and engineers in small firms are far more likely than their large firm counterparts to enter entrepreneurship. We label this phenomenon the small firm effect and explore its origins. In particular, we identify four classes of explanations for the small firm effect---preference sorting, ability sorting, opportunity cost, and the possibility that workers in small firms develop entrepreneurial human capital---and examine the empirical evidence for each. We find that preference sorting does play a role in generating the small firm effect: small firms attract those with prior preferences for autonomy who are similarly drawn into entrepreneurship. Similarly, ability sorting plays a role: those who ultimately become entrepreneurs may be drawn first to small firms because they offer tighter pay-for-performance links and can subsequently improve their expected earnings by becoming entrepreneurs, or because the skills required for success in small firms are also valuable in entrepreneurship. Evidence suggests that although those with the very least to lose do enter entrepreneurship with greater frequency, opportunity cost has at best a modest role to play in explaining the small firm effect. Finally, we interpret evidence that prior experience in small firms predicts positive performance outcomes in the early stages of entrepreneurship as suggesting that workers in small firms may develop entrepreneurial human capital that makes them better entrepreneurs. This effect may be largest among those of high ability.

Hospital Mergers and Acquisitions: Does Market Consolidation Harm Patients?

Debate continues on whether consolidation in health care markets enhances efficiency or instead facilitates market power, possibly damaging quality. We compare the quality of hospital care before and after mergers and acquisitions in California between 1992 and 1995. We analyze inpatient mortality for heart attack and stroke patients, 90-day readmission for heart attack patients, and discharge within 48 h for normal newborn babies. Recent mergers and acquisitions have not had a measurable impact on inpatient mortality, although the associated standard errors are large. Readmission rates and early discharge increased in some cases. The adverse consequences of increased market power on the quality of care require further substantiation.

Alcohol and Earnings: Does Drinking Yield a Wage Premium

This paper examines the relationship between alcohol consumption and earnings for prime-age males. Wage differentials for nondrinkers, moderate drinkers, and heavy drinkers are estimated using a polychotomous choice model, which accounts for the endogenous relationship between drinking and earnings. The authors find that moderate alcohol consumption leads to increased earnings relative to abstention. However, heavy drinking leads to reduced earnings relative to moderate drinking. Heavy drinkers possess flatter age-earnings profiles and attain lower returns for higher education than nondrinkers and moderate drinkers. These results are in contrast to previous research on substance abuse, which finds no earnings drop-off for heavy users.

Racial discrimination and professional basketball salaries in the 1990s

Racial differences in professional basketball player salaries are examined to determine whether the 20% premium paid to whites in the mid-1980s has persisted into the 1990s. OLS and tobit regressions indicate no difference between white and black salaries, controlling for player and team characteristics for the 1994 - 95 season. However, censored quantile regressions show substantial racial differences at certain points in the salary distribution. Whites earn less than blacks at the lower end of the distribution, although the difference is not statistically significant, and varies with minutes played. In contrast, whites receive a significant premium (18%) at the upper end of the salary distribution. These findings are consistent with a form of consumer discrimination in which sports fans prefer to see white star players, all else equal.

Semiparametric Bayes analysis of longitudinal data treatment models

This paper is concerned with the problem of determining the effect of a binary treatment variable on a continuous outcome given longitudinal observational data and non-randomly assigned treatments. A general semiparametric Bayesian model (based on Dirichlet process mixing) is developed which contains potential outcomes and subject level outcome-specific random effects. The model is subjected to a fully Bayesian analysis based on Markov chain Monte Carlo simulation methods. The methods are used to compute the posterior distribution of the parameters and potential outcomes. The sampled posterior output from the simulation is also used to construct treatment effect distributions at the unit level (and at other levels of aggregation), marginalized over all unknowns of the model, including the unknown distribution of responses and treatments, and treatment effects matched by treatment probability. A real data example, dealing with the wage premium associated with union membership, is considered in detail where quantities such as the average treatment effect, the treatment effect on the treated, and matched treatment effects are derived and illustrated.

Bayesian analysis of cross-section and clustered data treatment models

This paper is concerned with the problem of determining the effect of a categorical treatment variable on a response given that the treatment is non-randomly assigned and the response (on any given subject) is observed for one setting of the treatment. We consider classes of models that are designed for such problems. These models are subjected to a fully Bayesian analysis based on Markov chain Monte Carlo methods. The analysis of the treatment effect is then based on, amongst other things, the posterior distribution of the potential outcomes (counter-factuals) at the subject level, which is obtained as a by-product of the MCMC simulation procedure. The analysis is extended to models with categorical treatments and binary and clustered outcomes. The problem of model comparisons is also considered. Different aspects of the methodology are illustrated through two data examples.

The Gender Gap in NIH Grant Applications

Many qualified women scientists stop applying for NIH grants in the late postdoctoral and early faculty years.