Does Human Capital Matter for China’s Green Growth?—Examination Based on Econometric Model and Machine Learning Methods

Xiaoxue Liu, Fuzhen Cao and Shuangshuang Fan ()
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Xiaoxue Liu: School of Economics, Beijing Technology and Business University, Beijing 100048, China
Fuzhen Cao: School of Economics, Beijing Technology and Business University, Beijing 100048, China
Shuangshuang Fan: School of Management, China University of Mining and Technology-Beijing, Beijing 100086, China

IJERPH, 2022, vol. 19, issue 18, 1-27

Abstract: To tackle the increasingly severe environmental challenges, including climate change, we should pay more attention to green growth (GG), a path to realize sustainability. Human capital (HC) has been considered a crucial driving factor for developing countries to move towards GG, but the impact and mechanisms for emerging economies to achieve GG need to be further discussed. To bridge this gap, this paper investigates the relation between HC and GG in theory and demonstration perspective. It constructs a systematic theoretical framework for their relationship. Then, it uses a data envelopment analysis (DEA) model based on the non-radial direction distance function (NDDF) to measure the GG performance of China’s 281 prefecture level cities from 2011 to 2019. Ultimately, it empirically tests the hypothesis by using econometric model and LightGBM machine learning (ML) algorithm. The empirical results indicate that: (1) There is a U-shaped relationship between China’s HC and GG. Green innovation and industrial upgrading are transmission channels in the process of HC affecting GG. (2) Given other factors affecting GG, HC and economic growth contribute equally to GG (17%), second only to city size (21%). (3) China’s HC’s impact on GG is regionally imbalanced and has city size heterogeneity.

Keywords: human capital; green economy efficiency; green innovation; LightGBM machine learning; green growth; industrial upgrading (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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