The Non-Linear Relationship between Air Pollution, Labor Insurance and Productivity: Multivariate Adaptive Regression Splines Approach

Syamsiyatul Muzayyanah, Cheng-Yih Hong (), Rishan Adha and Su-Fen Yang
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Syamsiyatul Muzayyanah: Department of Business Administration, Chaoyang University of Technology, Taichung 413310, Taiwan
Cheng-Yih Hong: Faculty of Finance, Chaoyang University of Technology, Taichung 413310, Taiwan
Su-Fen Yang: Department of Statistics, National Chengchi University, Taipei 11605, Taiwan

Sustainability, 2023, vol. 15, issue 12, 1-20

Abstract: This study explores the non-linear relationship between air pollution, socio-economic factors, labor insurance, and labor productivity in the industrial sector in Taiwan. Using machine learning, specifically multivariate adaptive regression splines (MARS), provides an alternative approach to examining the impact of air pollution on labor productivity, apart from the traditional linear relationships and parametric methods employed in previous studies. Examining this topic is imperative for advancing the knowledge on the effects of air pollution on labor productivity and its association with labor insurance, employing a machine learning framework. The results reveal that air pollution, particularly PM 10 , has a negative impact on labor productivity. Lowering the PM 10 level below 36.2 μg/m 3 leads to an increase in marginal labor productivity. Additionally, the study identifies labor insurance as a significant factor in improving productivity, with a 9% increase in the total number of labor insurance holders resulting in a substantial 42.9% increase in productivity. Notably, a link between air pollution and insurance is observed, indicating that lower air pollution levels tend to be associated with higher labor insurance coverage. This research holds valuable implications for policymakers, businesses, and industries as it offers insights into improving labor productivity and promoting sustainable economic development.

Keywords: particulate pollution; labor productivity; insurance; machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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