Determinants of labor productivity in the USA

Abstract

This study aims to examine whether the labor productivity of the US population directly depends on public or private insurance coverage of people, employment level, life expectancies, spending on the public health system as a percentage of GDP, and spending on the public health system in natural terms. Empirical testing was carried out on the USА statistical data for 1987–2021 using a regression model with the fitting procedure backward stepwise selection (in Statgraphics software), and a multivariate adaptive regression spline MARS (using Salford Predictive Modeler software). The research hypothesis was confirmed for only two indicators: life expectancies and spending on the public health system in natural terms. Their impact on labor productivity appeared to be directly proportional. As an indicator, spending on the public health system has a greater impact on the change in productivity (0.0058%), whereas life expectancy has a lesser effect (0.0047%). The study showed that the MARS model provides more objective and accurate results compared to the regression model with the fitting procedure – backward stepwise selection. This conclusion is based on a comparison of real data modeled by both methods. The study proved that labor productivity in the USA grew yearly from 1987 to 2021 (the constant term in the MARS model’s regression equation is +0.48428). To calculate the specific values of labor productivity for each year, a model was developed depending on the optimal basic functions (automatically generated by the MARS model depending on the current values of life expectancies and spending on the public health system in natural terms).