How much does financial development contribute to renewable energy growth and upgrading of energy structure in China?

Energy Policy 128 (2019) 114–124

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Opinion paper

How much does financial development contribute to renewable energy growth and upgrading of energy structure in China? Qiang Jia,b,c,1, Dayong Zhangd,

T

⁎,2

a

Business School, Shandong Normal University, Jinan, Shandong 250014, China Center for Energy and Environmental Policy Research, Institutes of Science and Development, Chinese Academy of Sciences, Beijing, China c School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing, China d Research Institute of Economics and Management, Southwestern University of Finance and Economics, Chengdu, China b

ARTICLE INFO

ABSTRACT

Keywords: Energy revolution Energy structure Financial development Renewable energy growth

Developing renewable energy sector and upgrading energy structure have strategically important role in China's commitments against climate changes. Policymakers and authorities have put forward great efforts to make them happen. But one of the key constraints of China's energy revolution is financial issues, which is inevitably linking to the country's financial development. It is of great importance to understand how much financial development contributes to the renewable energy development in China, and more importantly what aspects of financial development matter. Through a time series analysis based on macro-level data, this paper provides clear evidence that financial development is critically important and contributes an overall of 42.42% to the variation of renewable energy growth. Specifically, we are able to demonstrate that capital market is the most important factor, followed by foreign investment. A simple comparison to the EU and the US cases indicates that the EU path is more relevant and should be studied more carefully by the Chinese policymakers.

1. Introduction China relies heavily on energy from fossil fuels, which account for about 90% of its total energy consumption (see Fig. 1). In China, burning fossil fuels, especially coal, results in a great deal of air pollution and is considered the main cause of greenhouse gas (GHG) emissions. The World Resource Institute (WRI, 2012) data show that China is the largest emitter of GHG in the world, followed by the United States. Together, these two countries contribute over 30% of the global aggregate GHG. Facing ever-increasing pressure because of potential global climate change, the leaders of these countries signed a historic agreement on November 12, 2014, to act cooperatively to reduce emissions. China has pledged to reach its peak GHG emissions in 2030 and increase the share of energy from non-fossil fuel sources to around 20% by then. Whether the policies and actions to achieve such an ambitious goal without affecting economic performance, however, is

still open to question. Another associated issue for China is that its economy relies heavily on the international energy market, especially the international crude oil market, the source of over half its total consumption (Zhang et al., 2016c). Instability in the international oil market–in particular, recent price variations and conflicts in the Middle East–can have a significant impact on the Chinese economy. Energy security and the role of energy in sustainable economic growth have become an important concern for policy makers in China. Under pressure to address the country's interests in both environmental responsibility and energy security, the Chinese authorities are considering how to upgrade the structure of energy production and consumption because of the energy sector's strategic importance, and this has been stated clearly and repeatedly since the eleventh five-year plan (FYP; 2006–2010) was presented. While continuously improving energy efficiency is one of the key points, developing forms of

⁎ Correspondence to: Research Institute of Economics and Management, Southwestern University of Finance and Economics, 555 Liutai Avenue, Chengdu 611130, China. E-mail address: [email protected] (D. Zhang). 1 Supports from the National Natural Science Foundation of China under Grant Nos. 71774152 and 91546109, Youth Innovation Promotion Association of Chinese Academy of Sciences (Grant: Y7X0231505) are acknowledged. 2 Supports from the National Natural Science Foundation of China under Grant No. 71573214 are acknowledged. I thank the invaluable comments and suggestions from the participants in the ISEFI-2018 conference, IPAG business school, Paris. Comments from the workshop organized by Energy Studies Institute, National University of Singapore are also appreciated.

https://doi.org/10.1016/j.enpol.2018.12.047 Received 17 September 2018; Received in revised form 26 November 2018; Accepted 27 December 2018 0301-4215/ © 2019 Elsevier Ltd. All rights reserved.

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played an important role in promoting the sector. But, at the same time, the downside of this enthusiasm is irrationality and overinvestment (Zhang et al., 2016b,d), which could represent a waste of resources and bring unhealthy competition. A recent example is the solar PV boom and bust in China. This overinvested industry was seriously affected in 2012 by a series of external shocks (e.g., solar anti-dumping charges by the European Union and the United States). As an emerging industry, renewable energy can be very risky, and various sources of investment are needed for different projects. For example, venture capital or equity financing may be more appropriate for smaller projects with new technology, whereas bank or debt financing is needed for nuclear energy projects, which are much larger (for more discussion, see Zhang et al., 2016d). This cannot be done without the support of a well-established financial system. However, a series of questions needs to be answered to clarify the contribution of financial development, and policy makers need to gain a clearer view of the current status to form better policies. These questions include: How much does financial development in China contribute to renewable energy development? Which part of the financial sector is more important? What is the difference between China and other countries, for example, the United States and countries in the European Union (EU), with respect to financial development? This paper explores these questions using a systemic econometric approach proposed by Diebold and Yilmaz (2009) and provides quantitative answers based on historical data. The paper starts with a general review of financial development in China and then considers the relevant literature to establish a theoretical foundation for why/whether financial development matters for the development of renewable energy. The next section briefly explains the statistical method employed, before describing the data used for the econometric model and explaining why these variables are used. We then report our empirical results and conclude the paper with some policy implications.

Fig. 1. Energy structure in China (source: National Bureau of Statistics).

renewable/clean energy has become more and more important. In 2005, the National People's Congress passed the Renewable Energy Law to give clear legislative support for the development of renewable energy. The thirteenth, and most recent, FYP (2016–2020) further reinforces the importance of developing renewable energy as part of upgrading the country's energy structure. Developing renewable energy is the main focus of work, along with promoting new technologies to improve the efficiency and cleanliness of traditional energy sources that continue to be used. The government will provide further support for developing hydropower, wind, solar, and nuclear energy projects. For example, it plans to install 60 GW (gigawatts) of hydropower in the southwestern region, construct a national new energy demonstration zone in Ningxia, and speed up the development of distributed photovoltaic (PV) projects in the eastern and southern regions and wind power projects in coastal areas. A series of nuclear energy projects has been planned, as part of a goal to reach 58 GW in installed capacity, with a further 30 GW in capacity in construction during the period covered by the thirteenth FYP. In 2020, total installed wind power and solar power should reach 210 GW and 110 GW, respectively. The general objectives are to reform the energy structure, optimize the supply of energy, build clean/low-carbon energy sources, and defend national energy security. Regulation, legislation, and the generally favorable policy environment are all important factors in China's upgrading of the energy structure (Liu, 2019). One of the most important regulatory supports to the renewable energy sector in China is the launch of Renewable Energy Law (REL) in 2005. Zhang et al. (2016d) show that renewable energy sector has switched to a fast track of development since the implementation of REL. Other policies have also been steadily released over the last ten years. Liu (2019) provides a critical review of relevant policies in China and divides these policies to specialized rules and unspecialized rules, which implicitly supporting renewable energy development. Among all factors, financing difficulty is one of the main obstacles faced by renewable energy sector. For example, an earlier discussion on China's policy to support renewable energies by Zhang et al. (2013) emphasizes the importance of financial support to renewable energy projects. Data for the past couple of decades show remarkable achievements and rapid progress in China's renewable energy sector. For example, the share of renewable energy (including hydro, wind, and nuclear power) rose to around 13.6% in 2014 (for more information on energy structure in China between 2000 and 2014, see Fig. 1) and has continued to grow. Investment in renewable energy also experienced rapid increases during this period. According to Bloomberg New Energy Finance (2014), China invested USD 59.6 billion in renewable energy in 2012 and became the biggest investor in the world beginning in 2013. The enthusiasm of Chinese investors in renewable energy has certainly

2. The development of financial markets in China This section offers a brief introduction on the development of financial markets in China over the past couple of decades, with a focus on events related to renewable energy. 2.1. Stock market China has two stock exchanges, both established in 1990 and governed directly by the China Securities Regulatory Commission (CSRC): the Shanghai Stock Exchange and the Shenzhen Stock Exchange. As of the end of December 2016, they ranked fourth and seventh worldwide in terms of market capitalization (Bloomberg). CSRC (2016) reports a total of 3008 listed firms, with market capitalization of RMB 53.1 trillion. Stock market has become a very important source of financing for Chinese firms. Renewable energy, as a relatively new concept, has also benefited from the development of the stock market. Fig. 2 reports the number3 of listed companies that specialize in the four main sources of renewable energy: solar power, wind power, nuclear power, and biomass. In the biomass sector for example, 13 out of 17 firms were listed after 2000. Total capital raised through an initial public offering (IPO) is around RMB 8 billion. Before 2008, the average IPO scale was only RMB 0.257 billion, but then it increased to RMB 0.662 billion. This shows that stock markets provide increasing financial support for renewable energy firms. The role of stock market on renewable energy development, especially in emerging markets, has been shown significant in the recent literature. For example, Liming (2009) compares financing channels for rural renewable energy development of China and India and suggests that stock market has become an increasingly important source 3

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Source: Royal Flush Information Network, http://www.10jqka.com.cn/.

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Fig. 2. Number of listed renewable energy firms.

Fig. 3. Growth of domestic loans offered by financial institutions.

of financing. Paramati et al. (2016) study 20 emerging market economies over the period of 1991–2012, they find a considerable positive role of stock market developments on clean energy uses.

supporting major infrastructure construction and renewable energy projects. The CDB has over RMB 1.5 trillion in outstanding loans to green energy projects, and this is expected to increase. In 2015 alone, the CDB offered RMB 137.1 billion in loans to renewable energy projects.5 Commercial banks have also become more involved in green development in China. By the end of 2015, total outstanding loans from banks to green energy firms exceeded RMB 8 trillion, of which RMB 7 trillion comes from 21 major commercial banks. In fact, borrowing from banks or credit market is still one of the most important source of financing to firms across the world. Ziaei (2015) uses a Panel Vector Autoregressive (PVA) model to investigate the interaction among credit market, energy consumption, emissions and growth in 25 countries. He et al. (2019) study the role of green credit on the development of renewable energy sector in China. They show a non-linear threshold effect between green credit and green development using listed firm data.

2.2. The banking system Banks comprise the most important part of China's financial system and have a much longer history than the stock market. Fig. 3 plots the outstanding loans offered by financial institutions and its growth rate.4 It is argued (e.g., Zhang and Wu, 2012) that in China the banking sector has played a more important role in promoting economic growth than the capital market. In China, policy banks, such as the China Development Bank (CDB), are special institutions that, in addition to commercial banks, provide credit (for an introduction of the history of China's banking system, see Zhang et al., 2016a). This type of bank plays an important role in implementing government policies on strategic development, for example, 4

5

Source: CEInet Statistics Database, http://www.db.cei.gov.cn. 116

China Development Bank annual report, 2015.

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Fig. 4. Growth of foreign direct investment (FDI).

the main determinants of renewable energy consumption in China, and a bidirectional link between them exists in the short run. Their review of the literature shows that, when studying this issue, scholars tend to use either supply-side (e.g., Ma et al., 2008) or demand-side (Sadorsky, 2009a,b) approaches. The production function and technical changes are used in supply-side studies, whereas emissions, energy prices, and income are used in demand-side analysis. Apergis and Payne (2010, 2012) use panel time-series models to establish bidirectional causality between renewable energy consumption and economic growth in member countries of the Organization for Economic Cooperation and Development (OECD) and a larger sample of 80 countries, respectively. Apergis and Payne (2014) extend their previous model one step further to allow for a nonlinear smooth transition mechanism in the panel cointegration framework. Empirical results based on annual data from 1980 to 2010 for seven Central American countries show that emissions, energy prices, and economic growth all have a significant impact on renewable energy consumption in the long run. Ohler and Fetters (2014) study 20 OECD countries from 1990 to 2008 and find bidirectional causality between renewable electricity generation and growth in the gross domestic product (GDP), but the relationship depends on the source of energy. The development of renewable energy is constrained by the source of financing. Although renewable energy projects have attracted a significant amount of investment (Bloomberg New Energy Finance, 2014) in recent years, financing remains an important issue, largely affected by the financial infrastructure. This argument has most recently attracted a series of studies that aim to identify the role of financial development in the adoption of renewable energy. Creti and Nguyen (2018) put forward the importance of energy and environment and raises clear policy challenges in the post Paris Agreement period. Among all factors, financial effects or the financial market implications of the Paris Agreement have been listed as the top issue. Kimura et al. (2016) pay attention to the East Asia Summit region and emphasize the role of financial policies in supporting renewable energy sectors. Their project and collection of relevant studies have made clear statements on the policy relevance of financial development in supporting renewable transition. Individual studies have started to pay attention to the role of financial development in clean development across the world. For example, Chang et al. (2016) explicitly taking financial sector into

2.3. International investment Since the open-up policy was initiated in the late 1970s, foreign capital has become a critical element of China's economic growth. Foreign direct investment (FDI) brings capital, technology, experience, and many other much-needed resources to the Chinese economy. It directly increases China's international trade and promotes innovation, which has far-reaching effects on the structure of the economy. Although the rate of economic growth has slowed in recent years (see Fig. 4), especially since the 2008 global financial crisis, foreign capital still plays an important role. More important, it has shifted toward emerging industries, including renewable energy. Ernst & Young Renewable Energy Country Attractiveness Index (Ernst and Young, 2016) ranks China second after the United States, though the new US president's policies might affect its rank going forward. As China continues to develop its renewable energy sector, international investment in green projects will flow into China. For example, a quickly rising green bonds market in China with strong government support (Kidney and Oliver, 2014) will allow China to become the largest destination for international investment in that sector (Liu, 2016). 3. Literature review Because of the threat of global climate change due to GHG emissions, a growing consensus across the world supports developing renewable energy as a way to reduce the consumption of fossil fuels. Although renewable energy is growing at a rapid pace (International Energy Outlook, 2013), its share of total energy consumption remains relatively small. A large volume of literature has emerged recently to model the development of renewable energy (e.g., Ali et al., 2018; Brunnschweiler, 2010; Omri and Nguyen, 2014; Sadorsky, 2009a,b; Salim and Rafiq, 2012; Zhao and Luo, 2017). These studies aim to identify the determinants of development in renewable energy and of causality between renewable energy development and a set of economic/financial variables, such as economic growth, financial development, energy prices, and emissions. For example, Salim and Rafiq (2012) study six major emerging economies, including China, to discern the determinants of renewable energy consumption. Their empirical results, based on both panel-data and time-series models, suggest that income and pollutant emissions are 117

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consideration in their efforts of building a quantitative index for 16 East Asia countries. Paramati et al. (2016) argue that the development of a stock market and FDI can lead emerging economies to use advanced technologies in clean energy production, which then leads to a higher share of clean energy use. The general idea is that stock market development helps clean energy projects to acquire capital (availability) and allows investors to obtain higher risk-adjusted returns (efficiency). Using a panel of data from 1991–2012 for 20 emerging market economies, their model reports a significant positive impact from output, FDI inflows, and stock market development on the use of clean energy. Their results differ from those of Lee (2013), who finds no significant relationship between FDI inflows and clean energy consumption in the G20 countries. Doytch and Narayan (2016) investigate the relationship between FDI and energy demand using a disaggregated approach. They decompose FDI inflows into sectors and explore how they affect renewable energy consumption. A panel model of 74 countries between 1985 and 2012 is estimated and shows that FDI is an important factor in renewable energy use, but its role differs significantly across countries and industries. Omri et al. (2014) set up a dynamic simultaneousequation model to show that bidirectional causality exists between carbon emission and FDI inflows. Ajmi et al. (2015) explore the links between carbon emission, growth and energy consumption in G7 countries (excluding Germany) and their results support bidirectional causality in a time-varying form. Kim and Park (2016) find additional supporting evidence that financial development matters in emissions reduction, as it has a significant role in the adoption of renewable energy technology. Equity market and credit market development measures are used in their empirical model, using a panel of 30 countries. The impact of financial development differs across renewable energy types, for example, it benefits solar PV more than biomass and geothermal energy. Some recent studies on China have started to investigate the role of financial development and other factors that affect reforms in China's energy consumption structure. For example, Liu and Li (2011) use a Computable General Equilibrium (CGE) model to show that removing subsidies for coal or oil can help China to improve its energy consumption structure. Their simulation results show that cutting subsidies to coal by 3% can increase the share of non-fossil fuel energy by 1.76% compared with the basic scenario. Shahbaz et al. (2013) use a series of financial development measures, such as inflow of FDI, stock market improvements, and banking activities in an unrestricted error correction model to investigate the long-run relationship among financial development, growth, capital, trade, and energy use in China. Their empirical results imply that an increase in energy demand should follow from financial development, which could increase emissions and energy dependence. China should spend more on investing in renewable energy and improve energy efficiency in the long run. Zhang et al. (2016d) study a group of 106 listed renewable energy firms in China using their financial statement information. They find evidence of overinvestment in these firms, meaning that when they have free cash flow, they tend to invest in less profitable projects. Managers of these firms can abuse their power and invest irrationally. Their empirical results also indicate that different financing channels matter in firms’ performance. The development of a financial market matters in this sense, and proper regulation and mechanism design are needed to secure a healthy investment environment in renewable energy. In general, the existing literature shows growing interest in improving renewable energy development further. Clear evidence of the role of financial development has been found, but mostly in a pool of countries. Thus these studies, first of all, are not specific to China. As mentioned earlier, China is the leader in terms of investment in renewable energy. The Chinese government emphasizes further development in renewable energy by aiming to build a green financial system (GFT Force, 2015). The questions for the policy makers are: How much

can financial development contribute to the development of renewable energy, and what forms of financial development matter more? Answers to these questions have not emerged in the existing literature. These cross–country studies, though they provide critical information on the determinants of renewable energy development, do not address China's particular conditions. Second, existing studies focus either on the demand side or the supply side and largely fail to model the entire market in a system. The reality is that all the variables interact. This study adopts a systemic approach and is relevant to the need to upgrade the energy structure over the period covered in China's thirteenth FYP. Factors mentioned in the literature, including the demand side and the supply side, are all included in an unrestricted system. Doing so enables us to address the gap in the literature and provide policy makers in China with critical information. 4. Methodology The model used in this chapter is based on the vector autoregressive model (VAR), which has proved a very useful instrument for studying interactions in a macroeconomic system since it was introduced by Sims (1980). Allowing all variables to be endogenous and adding them to a system, the VAR model provides a simple yet effective way to describe explicitly how economic factors are connected or interact. Interpretation of a VAR model, however, is rather complicated. Coefficients in a VAR model are too numerous to be explained in a standard way. An impulse response function and variance decomposition are often used instead to interpret the model. Both of these methods are essentially forward looking. An impulse response function shows how the system responds to given shocks, whereas the variance decomposition method provides information on how the variation in one variable–measured by forecasting error–is explained by variables (including itself) in the system. Based on the variance decomposition approach, Diebold and Yilmaz (2009) proposed a very intuitive way to interpret the connections within a VAR system and then refined the basic method in Diebold and Yilmaz (2014). Let's assume a covariance stationary K variable VAR (p) model:

yt = c + A1yt

1

+ A2 yt

2

+

+ Apyt

p

+ ut

(1)

where y is a K × 1 vector of time series variables, c is the vector of constant terms, u is the error terms with variance covariance matrix as u = E (ut u t ) , and As are K × K matrices of coefficients. After estimating the model, the forecasting error variance decomposition (FEVD) approach can be used to illustrate the model (please refer to Appendix 1 for a brief technical explanation). FEVD results enable us to derive the following information, first, how much the variation of variable i is explained by each and every other variables through ijH for j = (1, K ) and j i ; second, how much information variable i gains from the system contribution to the system

K j =1

H ji ,

i

K H , j = 1 ij

j

i and its total

j ; and third, the pairwise

Table 1 Variables description. Variables

Description of the original data

Renew01 Renew02 FDI Stock Credit Oil GHG Growth

Shares of renewable energy in total final energy consumption (%) Nonhydro renewable electricity net generation (Billion KWh) Foreign direct investment inflows (% of GDP) Market capitalization of listed domestic companies (% of GDP) Domestic credit provided by financial sector (% of GDP) Brent oil spot price (US dollars per barrel) Total greenhouse gas emissions (Mt of CO2 equivalent) Per capita GDP growth (%)

Note: The units of all variables are valid for the original data. They are all converted to growth rates for the VAR model. 118

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Fig. 5. Renewable energy development in China.

Table 2 Descriptive statistics and unit root test. Statistics

Renew01

Renew02

Stock

Credit

FDI

GHG

Oil

Growth

Mean Median Maximum Minimum Std. Dev. KPSS Test

0.25 0.20 1.40 − 1.00 0.64 0.07

44.78 25.33 273.34 − 69.31 74.31 0.17

1.73 − 1.26 80.32 − 83.07 28.38 0.11

1.24 1.52 19.54 − 10.19 6.71 0.08

− 0.13 − 0.23 2.40 − 1.19 0.80 0.22

5.85 6.22 13.08 − 1.51 4.00 0.14

8.22 10.59 47.07 − 45.12 24.36 0.12

9.29 9.00 13.60 6.70 1.95 0.09

Note: All variables are growth rate. Please refer to Table 1 for original information.

relative contributions for all possible pairs to i if the difference is positive.

H ij

H ji ,

j contributes more

A clear structural change can be seen in the figure after 2008, when nonhydro renewable electricity generation experienced a sharp increase. It is worthwhile to take this into consideration, and therefore we use nonhydro renewable electricity net generation changes as an additional variable for renewable energy development/energy structure in China to check the robustness of the empirical results. All variables are converted into a growth rate to satisfy the stationary condition of the Diebold and Yilmaz (2009) VAR model requirement. Table 2 reports some general statistical information of the variables used in the econometric model. All variables other than FDI inflows have a positive mean growth rate in the full sample period. As FDI inflows are relative to GDP, the negative value may simply reflect that GDP grows at a more rapid rate than FDI inflows. The measure of renewable energy sector growth differs significantly, which is also consistent with Fig. 5. All variables are stationary based on KPSS unit root test results.6

5. Data The data used in this chapter are in annual frequency from 1992 to 2013, which is subject to the availability of stock market data in China. The official stock market data are not available before 1992. Variables used in the empirical model are chosen according to the literature (e.g., Kim and Park, 2016; Shahbaz et al., 2013) and defined in Table 1. Macroeconomic variables include measures of financial development data from the CEInet Statistics Database and the National Bureau of Statistics in China. GHG emissions data come from CAIT (2017),and are used to capture environmental pressures to adopt renewable energy. Oil price and nonhydro renewable electricity net generation information are all from the US Energy Information Administration (EIA) website. Following the literature, three measures of financial development are used, namely, the stock market, credit market, and foreign investment as a percentage of GDP. The first two measures represent the condition for equity financing and debt financing, respectively. The third measure shows the impact of international investment. The share of renewable energy in total final energy consumption is used to represent the structure of energy consumption. To further check the robustness of our model, non-hydro renewable electricity net generation is used. Fig. 5 plots the renewable shares in total energy consumption (lefthand panel) and also the net electricity generation from nonhydro renewable energy. Clearly, renewable energy as a share of total energy consumption in China increased significantly during our sample period, almost doubling from 5.2% in 1993 to 10.2% in 2013. Hydropower has the highest share and differs quite significantly from other renewable forms. When hydropower is removed, net electricity generation from renewable energy sources shows different patterns (right panel of Fig. 5).

6. Empirical results 6.1. The role of financial development on renewable share A seven-variable VAR model is estimated using renewable energy as a share of total energy consumption (growth rate) to represent the structure of energy in China. The interaction in this system can be plotted using pairwise relative contributions between any two variables (see Fig. 6). An arrow from one variable i to another variable j means that i explains more of the variation of j than j contributes to i. The 6

The typical ADF test has very low power with a small sample and thus may yield inaccurate conclusions. The results using an ADF test, however, reveal that most of the variables, except GHG growth and per capita GDP growth, are stationary. The results are not reported but are available upon request from the author. 119

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Table 3 Summary of the system. Variables

From

To

Net

To renew

Renew Stock Credit FDI Oil GHG Growth

79.23% 58.97% 80.13% 81.49% 83.74% 78.04% 89.27%

103.03% 98.45% 77.23% 67.41% 104.14% 81.44% 19.17%

23.80% 39.48% − 2.90% − 14.08% 20.41% 3.40% − 70.10%

N/A 16.25% 13.02% 13.15% 19.60% 15.80% 1.40%

Note: “From” measures how much the variation of one variable gains from the system; “To” measures how much one variable contributes to the variation of the system (excluding the variable itself); “Net” is the difference between “From” and “To”. And the last column, “To Renew” reports the contribution of each variable to the variation of Renew, which totals 79.23% (“From” for Renew). Lag order of this VAR is 2 according to BIC.

market, which contributes the most among the three, explains 16.25% of the variation in renewable energy development. International investment is second. Added together, the empirical model shows that financial market development contributes 42.42% of China's renewable energy development in the past twenty years. The clear message of these empirical results for Chinese policy makers is to reinforce financial development (especially the stock market) and provide further favorable financing policies for renewable energy. Our results provide solid statistical evidence that supports some recent movements in China on promoting the establishment of China's green financial system. 6.2. Robustness check with nonhydro renewable growth To check the robustness of the empirical findings reported in the previous section, we use an alternative measure to represent the changes in China's energy structure. Here the growth rate of nonhydro renewable electricity generation is used. Hydropower is the most important source of clean/renewable energy. However, its development has some distinctive features that differ from those of other forms of renewable energy. First, its regional distribution is unbalanced, being concentrated in southwestern China. Transmission of electricity from these regions to eastern China is costly; at the same time, the cost of development in those power-rich regions is rising. Second, hydro projects are often big and require large state investment. Moreover, the approval procedure is lengthy and potentially involves many different branches in the government. In addition, although it solves some environmental issues, it may at the same time generate others. Hydropower's special characteristics make nonhydropower a more important direction of energy structure reform. In fact, nonhydro renewable development has already taken a greater role. As for what the data (Fig. 5) show, the nonhydro part of renewable energy has increased remarkably since 2008. It is therefore necessary for us to check how much our econometric system works without hydropower. A similar seven-variable VAR model is estimated using the growth rate of nonhydro renewable growth rate replacing the share of renewable energy growth. The results are reported in Figs. 8 and 9. Fig. 8 plots the summary of this new system graphically. There are quite a few changes though the role of stock market development remains the most important contributor to this system. The contributions to the variation in nonhydro renewable growth from other variables are plotted in Fig. 9, which confirms the general pattern found earlier. Oil price changes and GHG emissions are the top two contributors, followed by Stock. Combining the contributions from Stock, Credit and FDI, financial market development contributes 22.74% of the variation. Though the number is smaller, the general pattern remains.

Fig. 6. Pairwise interactions of the system.

variable with highest relative contribution to the system is marked in red (and the lines associated with this variable). Blue is used for the variable with the lowest value (or with the highest relative gain from the system). The figure shows that stock market development (in red) has a very important role in the system, and it contributes the most to the system (in terms of net value). Economic growth (in blue), however, has the highest net gain from the system, and it gains relatively more than it contributes to all other variables. Among three financial development measures, the stock market and the credit market are net contributors to the share of renewable energy. Oil price changes are another net contributor to China's energy structure. Table 3 summarizes how the system works in an alternative way. It reports how much one variable contributes to the system (“To”) and how much it gains from the system (“From”). The “Net” measure is relevant to the colored part of Fig. 6, whereas Stock make the highest net contribution (39.48%) to the system and Growth gains the most from the system, with a net gain of 70.10%. The last column decomposes Renew's gain from the system. In total, the system (excluding Renew) contributes 79.23% of Renew's variation. Among all the factors, oil price changes contribute the most (19.60%). GHG has a relatively smaller level of contribution (15.80%). These are not entirely surprising and provide supporting evidence of the previous arguments. Fig. 7 plots these numbers into a bar graph to show the pattern more clearly. If Oil and GHG show the demand side of developing renewable energy, then three financial development measures (Stock, Credit and FDI) can be considered the supply-side factors, and their impact on renewable energy development in China is significant. The stock 120

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Fig. 7. Contributions to the variation of Renewable energy share.

Fig. 8. System interactions (robustness check).

Fig. 9. Contributions to the variation of Non-hydro renewable growth.

2012, roughly the same period as for China.7 Contributions from variables in the system to changes in the renewable share for these two markets are plotted in Fig. 10. The results are clearly different from those in China, especially with

6.3. The case of the United States and EU In terms of the adoption of and investment in renewable energy, the European Union and the United States are the two world leaders, so it is worthwhile to compare what happened in these two markets. To do so, we collect the same set of variables from the World Bank's World Development Indicators (WDI) for these two markets between 1991 and

7

121

WDI data on renewable energy share, GHG emissions ends at 2012.

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Fig. 10. Contributions to the variation of renewable share: the US and EU.

respect to the United States. The total contribution of financial development to its renewable energy share in the United States was only 22.57%, whereas oil price changes alone explained about 33.78%. Financial factors matter much more in the EU market, in which the total contribution to the renewable energy share was 56.02%. This share is similar to that in China, though the most important contributor in the EU market is credit, rather than the stock market. Another major difference between the European Union and China is the relative importance of economic growth. While it contributes only marginally in China, growth contributes over 16.76% of renewable energy development in the European Union. China will move slowly in the direction of these two developed markets. The results found here clearly indicate that the EU pattern is more relevant to the path in China than is the US experience. It is not entirely surprising in that the United States has had the largest and the most developed financial markets for over a century. It also has abundant natural resources, whereas both the European Union and China rely heavily on the international energy market and face higher energy constraints.

growth of international investment as measures of financial development, our empirical results show that the financial sector contributes significantly to shifting the structure of energy in China. Overall, financial sector development explains over 40% of the variation in the changes in the share of renewable energy. Among these financial factors, stock market development is the most important one. It is consistent with the nature of the development of an emerging sector, which is often risky and therefore requires equity financing more than debt financing. Using the growth rate of nonhydro renewable electricity net generation as an alternative measure, we confirm our findings and show that the results are robust. A number of clear policy implications can be drawn from the empirical results. First, our results show that a market mechanism exist in China to support green transition. Renewable energy sector, like others, can significantly benefit from the general development of financial markets. Stock market expansion and credit market reform can provide indirect support to renewable energy development through more efficient and cheap financing opportunities. International capital should also be encouraged to enter renewable energy sector. Second, clear policy measures are needed especially for the credit market. Comparing to the European Union, the role of credit market in China is still weak. Although the idea of establishing a green financial system and the movements of some major banks have already sent clear message to the market, it is unclear how the system can benefit small or medium sized enterprises (SMEs), which is the most active and important forces for green development (Liu et al., 2017). Third, China shares some similarities with the European Union in terms of the importance of financial development but appears to be clearly different from the United States. The EU path may be more relevant to China, as more common fundamental characteristics can be found between them relative to the United States. Given the availability of data, our total sample size is relatively small; therefore, the numerical results should not be overinterpreted, as they may be sensitive to any large variation in the variables. Nonetheless, the general message should remain the same. The message of this empirical investigation of historical data in China is that policy makers should further reinforce the role of the capital market and form policies more favorable to the renewable energy sector. It also provides statistical evidence of the need to establish a green financial system in China.

7. Conclusion and policy implications China's thirteenth FYP reemphasized upgrading the structure of energy as a strategically important direction for development. Clear targets and measures have been planned to increase the share of renewable energy and promote clean energy production. They reflect the Chinese government's goal of reducing emissions and following a clean and sustainable path of economic growth. Significant achievements were made in the past two FYP periods in terms of achieving ambitious emissions reduction targets while under significant economic pressure. Developing renewable energy is often risky and costly, especially at the start. Policy supports are needed to create a favorable environment for boosting this sector. One of the most important foundations is the financial environment. Following the existing literature and China's recent movements on establishing a green financial system, which argues that financial development is important in developing renewable energy, this paper uses time-series data and a recently developed systemic approach to investigate how much financial development has contributed to the growth of renewable energy in China over the past two decades. Using stock market development, credit market growth, and the

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Appendix A The K-variable VAR(p) model can be written in a compact form:

Yt = C + AYt

1

(2)

+ Ut

A is an (Kp × Kp) dimensional matrix and Y , C , U are (Kp × 1) vectors:

Y=

y1 y2

,C=

yp

A1 A2 IK 0 , A = 0 IK

c 0 0

0

0

Ap 0 0 IK

1

Ap ut 0 0 , U = 0 0

0

Forecasting error variance decomposition (FEVD) starts with the mean squared error of the H-step forecast of variable yi : H 1

K

MSE[yi, t (H )] =

(e i

j ek )

2

(3)

j =0 k=1

ei is the column of IK , j = j P , and P is a lower triangular matrix through a Cholesky decomposition of the variance covariance matrix j u = E (ut u t ) ; j = JA J , where J = [IK , 0 , …, 0]. The contribution of variable k to variable i is then given by:

ith

H 1 ik, H

=

(e i

j ek )

2 / MSE [y (H )] i, t

(4)

j=0

In general, FEVD results are sensitive to the order of the variables. Diebold and Yilmaz (2012) suggest to use the generalized variance decomposition approach of Koop et al. (1996) and Pesaran and Shin (1998) to solve the problem of ordering. g ik , H

H 1

=

ii

1

(e i

j

u ek )

2 / MSE [y (H )] i, t

(5)

j =0

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