The Effect of Human Capital on C[O.sub.2] Emissions: Macro Evidence from China.

AuthorYao, Yao
  1. INTRODUCTION

    Investing in human capital has been shown to generate various benefits. For instance, human capital is conducive to labor productivity and facilitates economic growth (Schultz, 1961; Romer, 1990; Barro, 1991). It is also associated with many social externalities such as better health and lower crime participation, to name a few (see the survey of Sianesi and van Reenen, 2003). Yet, while these externalities have sparked growing attentions, the environmental benefits owing to human capital accumulation remains less understood.

    We attempt to fill this gap by studying the association between human capital and carbon dioxide (C[O.sub.2]) emissions for a panel of Chinese provinces over the period 1997-2016. China is an appealing context as it pledges to cut C[O.sub.2] emissions ambitiously in the Paris Agreement and has been investing education rigorously since the 1990s (Naughton, 2007; UNFCCC, 2017). (1)

    Empirically, we estimate the long-run relationship between human capital and C[O.sub.2] emissions. Our results suggest that human capital embodied in younger workers and workers with advanced human capital exerts a negative and significant effect on C[O.sub.2] emissions. Our results, which account for cross-sectional dependence and structural breaks, reveal that a one-year increase in average schooling reduces C[O.sub.2] emissions by 12 per cent. This result is driven by younger workers aged between 25 to 44 years old in which their one more schooling year is associated with 26.8 per cent lower C[O.sub.2] emissions. While these figures may appear large, our dataset demonstrates that it takes about ten years of efforts for China to attain one extra year of formal schooling. (2) On another metric of human capital, we find that a one per cent increase in advanced human capital, which is proxied by the share of workers with a tertiary qualification, reduces C[O.sub.2] emissions by 5.7 per cent.

    Our study relates and contributes to at least three strands of literature. The first strand is a set of emerging studies that address the nexus between human capital and energy consumption at the macro level (Salim et al., 2017; Shahbaz et al., 2019; Yao et al., 2019). These studies have consistently revealed a negative human capital-energy consumption association at either regional or country levels. Specifically, Yao et al. (2019) analyzed a panel of OECD economies over the period 1965-2014 and added that human capital reduces dirty energy consumption but increases clean energy consumption. This novel finding suggests that human capital accumulation may improve environmental quality through switching away from fossil fuel which is a primary cause of C[O.sub.2] emissions.

    The second strand of related literature is constituted of several firm-level studies that attempt to understand whether and how human capital reshapes firms' polluting behaviors (Blackman and Kildegaard, 2010; Gangadharan, 2006; Lan and Munro, 2013; Cole et al., 2008). These studies generally reported a positive nexus between human capital and environmental outcomes. A consensus of the underlying mechanisms is that firms with a higher stock of human capital are more likely to exhibit better environmental compliance and adopt cleaner production technology.

    The third set of studies, which are most closely related to ours, is an embryonic, and predominantly very recent, literature has directly associated human capital and several pollutants, including C[O.sub.2] emissions. Using a cross-sectional dataset of the U.S. states, Goetz et al (1998) documented that, conditional on income, population density and industrial composition, the states with better educated population appear to have cleaner ambient environment. Using the time series observations between 1978 and 2018 from China, Li and Ouyang (2019) found that human capital promotes C[O.sub.2] emissions in the short run but reduces it in the long run. To address the potential nonlinear relationship between human capital and C[O.sub.2] emissions, Yao et al. (2020) assembled a historical OECD panel over the period 1870-2014, finding that human capital started to alleviate carbon emissions since the 1960s.

    We build, and improve, especially on this third set of studies in several important manners. Each of these studies provides estimates using either time series or cross-country dataset. We employ a panel of Chinese provinces over the period 1997-2016, which constitutes a more homogeneous panel. Our sample thus diminishes the unobserved differences that often plague cross-country studies (Madsen et al., 2018). Meanwhile, the context of China offers a unique advantage to our estimation. Exposure to pollution is believed to be endogenous as better educated cohorts may sort into regions with better environmental quality (Neidell, 2009; Graff Zivin and Neidell, 2012). While this self-selection process could be addressed through instrumental variable (IV), finding valid IV ward. Assuming the pre-2014 trend maintains, it means China needs to come up a way to lower carbon intensity growth by another three percentage points. When the upper bound target (65 per cent reduction) is pursed, the task becomes more pressing.

    Another innovation of our study is that we not only examine the association between the overall level of human capital, proxied by the number of total schooling years, and C[O.sub.2] emissions, but also consider its distribution across different age cohorts. This strategy enables us to understand the underlying mechanisms through which human capital may affect C[O.sub.2] emissions. Moreover, to capture the heterogeneous effects of human capital on C[O.sub.2] emissions, we also break qualification, which is another proxy of human capital, into secondary and tertiary levels. (4) This distinction is important because advanced human capital, usually obtained from tertiary education, is unlikely to exert the same effect on the environmental quality as basic human capital obtained from primary and secondary educations (Gemmell, 1996). The underlying explanation is that production-relevant skills are embodied in those individuals who have acquired advanced qualifications. Specifically, more educated workers imply that the cost of complying with more stringent environmental standards, such as through adopting cleaner production technologies, will be lower (Dasgupta et al., 2000; Lan and Munro, 2013; Yao et al., 2020).

    Our final contribution rests on investigating the mechanisms underlying the established human capital-C[O.sub.2] emissions nexus. While it is challenging at the macro level, we take the advantage of disaggregated emissions by energy sources and end emitters. Specifically, to examine whether technology effect attributed to human capital accumulation is at play, we use industrial C[O.sub.2] emissions due to cement production process. Since the process emissions, by definition, have fully excluded the C[O.sub.2] emissions accrued to energy consumption, the negative effect exerted by human capital could only be operating through technology effect (e.g. more environmentally-friendly production process).

    Our findings offer new insights to the policy circle. To date, conventional solutions like command-and-control remain the fundamental tools for the Chinese government to control pollution. The outcomes, however, are achieved at the expense of substantial welfare loss (Zhang, 2017). Given China is an authoritarian state still riddled with red tape, the efficiency and effectiveness of those regulation-based tools are further constrained (Wang and Wheeler, 2005; Dean et al., 2009). The market-based policy instruments are expected to fill the void. However, available instruments like carbon tax and emission trading scheme (ETS) are still at an early stage and yet to be fully implemented, making their efforts on abating C[O.sub.2] emissions marginal at best. With this backdrop, we suggest investing in human capital could be used to facilitate carbon reduction and to control other pollutions without distorting economic growth much. We do recognize that human capital accumulation is neither the necessarily only, nor the most important way for abating C[O.sub.2] emissions. Nevertheless, we believe this study improves our understanding of social benefits associated with human capital accumulation, extending them to the perspective of environmental protection.

    The rest of this paper is organized as follows: Section 2 setups conceptual framework which guides our empirical investigation. Section 3 explains the dataset and econometric methods.

    Section 4 presents baseline results and section 5 performs sensitivity checks. We attempt to identify the potential mechanisms in section 6. The last section concludes and discusses policy implications.

  2. CONCEPTUAL FRAMEWORK AND EMPIRICAL MODEL

    2.1 Conceptual framework

    To explore the association between human capital and C[O.sub.2] emissions, we discuss the potential channels accrued to production and household sectors separately. (5)

    In the production sector, human capital accumulation is expected to promote environmental quality because better-educated workers are conducive to both innovation and the diffusion of abatement technologies (Blackman and Kildegaard, 2010; Lan and Munro, 2013). Specifically, firms with higher human capital tend to be long-run oriented, emphasizing their sustainable development by exercising more stringent pollution controls. On the other hand, firms managed by better-educated professionals tend to follow higher standards of social responsibility, making them less likely to violate external environmental regulations (Dasgupta et al., 2000; Gangadharan, 2006; Blackman and Kildegaard, 2010; Lan and Munro, 2013).

    In the household sector, better educated families tend to value the environment more and modify their behavior in ways that alleviate environmental impacts, such as greater use of recycling (Goetz et al., 1998...

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