This article takes a step toward understanding potential causes of wage discrimination in an economy highly dependent on the service industry. Traditionally categorized within the service industry, professional sport leagues such as the National Basketball Association (NBA) provides a unique setting to examine the potential impact of race on salary. We analyze free agency contract signings, which allow us to better capture the determinants of players' wages, from 2011 to 2017 to investigate the prominence of wage discrimination in the NBA. Using weighted linear regression models and the Oaxaca-Blinder decomposition, we find that Black athletes are paid significantly less than their counterparts. In addition, we also identify the presence of consumer discrimination after controlling the exposure of a player to the audience, which is observed through the interaction term between the share of MSA population which is White and an identifier for whether a player is Black.

West Virginia schools are consistently below the national average on the National Assessment of Educational Progress. Using Data Envelopment Analysis, we estimate the technical efficiency of West Virginia school districts. We find less variation in technical efficiency in West Virginia than in similar studies conducted in other states. This appears to be because of state policy imposing homogeneity of input usage. Due to the limited variation in technical efficiency across districts, we cannot analyze how non-school inputs such as socioeconomic factors affect technical efficiency across districts. Summary statistics organized by county economic status, however, suggest that socioeconomic status plays a role. Our results highlight an important limitation of DEA analysis on schools.

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