A Stochastic Frontier Analysis of the Human Capital Effects on the Manufacturing Industries’ Technical Efficiency in the United States

Abstract

This study seeks to establish substantive empirical evidence on the role of college and non-college labour in productivity through technical efficiency in the manufacturing sector in the U.S. economy. This investigation fits a Cobb-Douglas stochastic frontier function with inefficiency effects to a set of panel data for 15 manufacturing industries over the period from 1998 to 2019. The contribution of this paper lies in the application of the stochastic frontier analysis following the approach of Caudill et al. (1995) by estimating and testing stochastic frontier production functions, assuming the presence of heteroscedasticity in the one-sided error term (inefficiency), which provides robust estimates of the technical efficiency measures. This paper also contributes to the literature in the sense that it follows the Hadri (1999) approach and its extension for panel data, Hadri et al. (2003), assuming the existence of heteroscedasticity in both error terms (the one-sided inefficiency term and the two-sided symmetric random noise). The rationale for the double heteroscedasticity estimation is that it results in more accurate measures of the effects of the technical efficiency determinants. Therefore, it adds another layer of confidence in the economic analysis of the impact of human capital components on the manufacturing sector efficiency and by extension, its productivity. The stochastic frontier results show the effects of highly educated workers and low educated workers – proxied by college and non-college labour – on technical inefficiency. This is where the maximum likelihood estimates suggest that the increase in the percentage of the hours worked by college workers tends to contribute positively to technological efficiency in the U.S. manufacturing industries. While on the minus side, it can be noted that the rise in the share of the hours worked by non-college persons seems to have negative impact on efficiency in these industries. JEL Codes: J24, D24, C23, C24, Q12 Keywords: human capital, technical efficiency, stochastic frontier production, double heteroscedasticity, panel data