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State-Fueled Energy: Quantitative Comparison of State-Led Overseas Energy Financing in China and Japan

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Abstract

China and Japan own the largest policy banks—state-owned financiers—in the world. Policy banks have recently drawn international attention as the Export–Import Bank of China (CHEXIM) and China Development Bank (CDB) play an important role in China’s overseas economic activities. This paper examines the extent to which the CHEXIM and CDB behave similarly to the Japan Bank for International Cooperation (JBIC), their Japanese counterpart in energy loan approvals. Combining third-party data from a new database of Chinese overseas energy finance and various matching databases, this paper proposes a fixed-effect model to compare the determinants of the CHEXIM, CDB and JBIC’s overseas energy loans from a comparative perspective. Like their Japanese counterparts, Chinese banks exhibit a certain degree of concern for the recipient’s domestic economy but also exhibit risk-seeking tendencies. Contrary to claims that China’s policy bank is a tool to gain geopolitical advantage, geopolitical concerns and energy security do not appear to be determinants of the CHEXIM’s overseas finance decisions.

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Notes

  1. While CHEXIM stresses the similarities between concessional loans and official development assistance (ODA), these loans still differ from “grants” and zero-interest loans (China Exim Bank 2014), thus differentiating themselves from the OECD’s official development assistance, which has near-zero interest rates. The interest rate of concessional loans is usually 2–3%, which is a major difference from that of the ODA. Therefore, this analysis studies concessional loans together with other forms of OOF, mainly non-concessional loans.

  2. The lack of available historical data prevents a comparison between China and Japan during the latter’s period of growth. This study argues that, currently, Japan is still a successor of Japan’s development model in the 1960–1970s, and that despite a series of reforms, the JBIC remains important in Japanese overseas operations.

  3. Energy loans are defined as loans granted to energy-related projects in any primary and secondary energy sectors, including fuels and various types of electricity. In terms of activity, the projects are generally categorized into three types: power generation, transmission and exploration. Combining power generation and exploration in the energy sector is a practice seen in public databases such as AidData and US Energy Information Administration. Due to the difference in loan records, this study identifies “energy loans” based on the following criteria: (1) The included loan must be granted to a project implemented by a domestic company (including its overseas branch) with an overseas destination; (2) involved projects must be related to one of the energy sectors, which include fossil fuels, hydroelectricity, solar energy, nuclear energy, wind energy, etc.; and (3) involved operations must include exploration and processing or power generation and transmission. There are certain correlations between sectors and activities, such as CHEXIM loans to oil sectors, which mostly involve exploration, but its loans to hydroelectric and coal sectors mostly involve power generation (including the export of equipment).

  4. An alternative data source is AidData (AD) from William (2017), which provides all-sector data on loans from China to overseas recipients, including policy banks, commercial banks, and non-financial agencies responsible for technical assistance. This study chose the GDP database (up to 2016) for a more conservative estimate, with several validated, complementary AD entries. AD is constructed using TUFF methodology, which can be summarized in three steps: standardized machine selection of news from the Factiva media database, manual validation, and data quality insurance procedures. This method theoretically offers a wide coverage of data thanks to the massive media collection, and the AD team has overall better resources via news databases such as Factiva. However, there are records that can only be identified from Factiva or non-Chinese sources and cases with inaccurate information. GDP data, on the other hand, stresses open news sources and manual Chinese–English cross-checking to ensure that the project has actually been implemented. Approximately 20% of the AD records are cover GDP data, and about 12% of the AD records are in addition to GDP data. Both databases are accessible online.

  5. Several records are omitted from the regression due to incomplete data.

  6. As mentioned in Table 2, the study uses ln(1 + inv) to avoid negative values from − 1 to 0. Since the amount of loans included in the study is usually large enough, the value of the dependent variable is close to ln(inv).

  7. Deals in other currencies are converted to USD using the annual average exchange rate.

  8. Theoretically, the “technological gap” between the investor and recipient is important for overseas investment; however, the R&D expenditures of the recipient country suffer from an absence of data. Therefore, only the R&D expenditure of the investor is used.

  9. Petrobras, Funding Agreement of USD 5 billion with China Development Bank Corporation, May 2015, http://www.investidorpetrobras.com.br/en/press-releases/funding-agreement-usd-5-billion-china-development-bank-corporation.

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Authors and Affiliations

  1. Global Development Policy Center, Boston University, 53 Baystate Rd., Boston, MA, 02215, USA

    Junda Jin

  2. Xiaonanzhuang Building 38, Unit 7-752, Beijing, 100089, China

    Junda Jin

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  1. Junda Jin
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Jin, J. State-Fueled Energy: Quantitative Comparison of State-Led Overseas Energy Financing in China and Japan. Fudan J. Hum. Soc. Sci. 12, 609–629 (2019). https://doi.org/10.1007/s40647-019-00268-0

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