Chad Turner

How Important are Human Capital, Physical Capital and Total Factor Productivity for Determining State Economic Growth in the United States, 1840-2000?

This paper introduces new data on state-level physical capital by sector and land in the farm sector for the states of the United States from 1840 to 2000. These data are incorporated into aggregate accounting exercises with the aim of comparing cross-state results to those found in cross-country samples. Our aggregate results agree closely with the cross-country literature: input accumulation accounts for most of output growth, between three-fifths and three-quarters, but variation in the growth of TFP accounts for about three-quarters of the variation in the growth rate of output per worker. In convergence accounting, convergence of log TFP accounts for about seventy percent of the observed convergence in log output per worker.

Income and Education of the States of the United States: 1840-2000

This article introduces original annual average years of schooling measures for each state from 1840 to 2000. The paper also combines original data on real state per-worker output with existing data to provide a more comprehensive series of real state output per worker from 1840 to 2000. These data show that the New England, Middle Atlantic, Pacific, East North Central, and West North Central regions have been educational leaders during the entire time period. In contrast, the South Atlantic, East South Central, and West South Central regions have been educational laggards. The Mountain region behaves differently than either of the aforementioned groups. Using their estimates of average years of schooling and average years of experience in the labor force, the authors estimate aggregate Mincerian earnings regressions. Their estimates indicate that a year of schooling increased output by between 8 percent and 12 percent, with a point estimate close to 10 percent. These estimates are in line with the body of evidence from the labor literature.

The Collective Bargaining Effects of NBA Player Productivity Dynamics

We apply quintile regression methodology to player pay and performance data from the 1985-86 to 2005-06 seasons of the National Basketball Association (NBA). In addition to confirming a finding from Hakes and Turner (2007) of systematic bias in pooled OLS regressions of career paths for salary and productivity, the quintile analysis presents two important results regarding NBA salary structure. Unlike Major League Baseball (MLB), the highest ability veteran NBA players suffer salary suppression relative to the lesser-talented players in their debut-year cohort, indicating rents have been transferred from the most able players to players of lesser abilities. Also, while young NBA players in general suffer from salary suppression relative to free agents, as is well-reported in baseball, our regression results show that the highest-ability young players suffer the most salary suppression, and that the effects of the rookie salary cap in the 1995 NBA Collective Bargaining Agreement depressed salaries for young players of all ability levels.

Dynastic Human Capital and Black-White Earnings Differentials in the United States, 1940–2000

We examine whether dynastic human capital (DHC) can explain the black-white wage gap. We fit a quantity-quality model to state-level data on fertility, mortality, and schooling but, notably, not earnings. Racial discrimination raised the cost of black schooling, thus depressing DHC not only of the current generation but of future generations via its role in producing human capital. Birth-state DHC helps explain the wage gap among stayers, while current-state DHC helps explain the gap among movers. These findings highlight the role of intergenerational transmission in the persistence of the wage gap and the role of migration in reducing it.

Productivity Differences: The Importance of Intra-State Black/White Schooling Differences Across the United States, 1840-2000

Using newly created data containing real output per worker, real physical capital per worker, and human capital per worker for US states from 1840 to 2000, Turner et. al (2007) analyze the growth rates of aggregate inputs and total factor productivity (TFP). We continue this line of work by documenting the importance of TFP differences in explaining cross sectional variation in the levels of (log) output. We construct plausible upper bounds on the fraction of the variance in output levels that can be explained by TFP and inputs. Similar to the growth rate analysis, we find that TFP can, on average, explain nearly 90% of output variance while inputs can explain up to only 50% of output variance. We then consider the possibility that one major institutional difference across states, the extent to which blacks were denied access to formal education, might explain TFP differences across states. To this end, we generate and present a years of schooling measures, by race, at the state level from 1840 to 2000. While directly exploiting this series has very little impact on the upper bound of the fraction of output variation that can be explained by inputs, we do find that the size of the gap between white and black years of schooling is negatively related to TFP in the period from 1840 to 1950. We also consider the extent to which time-varying rates of return on education alters the upper bound on the fraction of output variation that can be explained by inputs, finding that time-varying rates have little impact. Finally, we find some evidence for external effects of higher education and physical capital.