This research was spurred by the Olympic Training Center’s interest in gathering data to assess the current return on investment for track and field athletes. We predict that athletes who attend the Olympic Training Center should have improved performance in competitions that occur after they have attended the training program. In order to assess these results we have run an endogenous treatment effects model, where we select athletes who have attended the residence program at the Olympic Training Center as participants of the treatment. The Olympic Training Center spends millions of dollars each year to train these athletes, and this study will conclude whether those millions are really worth spending in terms of athletic success.
Currently the richest countries of the world sustain an income almost seventy times that of the poorest ones. Recent literature, such as Eichengreen and Gupta (2009) and Rodrik (2012), suggest that productivity is an important determinant of growth and may explain why some nations are not catching up in the long-run, especially at the sector level. The topic of sectoral value convergence, however, has not been an area of much study. Using time series data on between 56 to 111 economies, this paper finds that absolute convergence occurred only in the manufacturing and services sectors from 1980 to 2010. When conditioned upon human capital, political infrastructure, and a number of sector specific determinants, convergence occurred across countries in agriculture, manufacturing, and services. In addition, increases in human capital are found to improve convergence effects in all three sectors.
The National Basketball Association is one of the most popular professional sports leagues in the world. Franchise owners want the best players on their team to build an increasing fan base, win championships, and generate revenue. Therefore, players displaying key qualities are more likely to receive more money from owners. This paper investigates what productive, physical, and social attributes along with league regulations are most important in predicting a player’s annual salary. The data shows that social attributes have no effect on determining individual salary, but player productivity, Collective Bargaining Agreements, and physical capabilities are significant determinants of salary.