Summary:
Economic development based on the consumption of large amounts of non-renewable resources is not sustainable in the long term. Under the direction of the CPC Central Committee and through the joint efforts of its citizens, China has made initial steps in controlling its carbon emissions, although the goal of achieving its dual carbon targets remains a challenge. Nonetheless, as an energy sector dominated by fossil fuels is incapable of meeting the required reduction in carbon emissions, the development of low-carbon industries needs to be vigorously promoted to realize the dual carbon targets. However, China's energy sector, which is rich in coal but poor in oil and gas, is difficult to change in the short term. Accordingly, the orderly adjustment of the energy sector and the development of a green and low-carbon national economy is a long-term dynamic optimization process. Overall, China is currently facing a tight transition window and strong pressure to achieve its dual carbon target. In addition, there is growing demand for targeted financing and more effective financial regulation policies. Finance should not only support economic development but also the gradual withdrawal of the traditional energy sector. Investment needs to guide the improvement and replacement of traditional carbon-intensive production capacity by supporting the implementation of higher standards and more efficient production, and the gradual transformation of the energy sector. Accordingly, it is worth examining the optimal regulatory policies for promoting the orderly transformation of the energy sector and their transmission mechanism. This paper uses a E-DSGE model containing heterogeneous enterprises to analyze the transmission mechanism of green credit policy. The effects of this policy are also analyzed in relation to promoting the orderly transformation of the energy sector, expanding the theoretical framework of green credit policy. The findings of this paper have a number of practical implications with respect to determining the optimal regulatory policies for promoting the orderly transformation of the energy sector and designing a reasonable mechanism to enable the central bank to implement effective monetary policy regulations. There are a number of limitations to research in this field. First, theoretical research is lacking on the means of developing low-carbon industries and adjusting the energy structure. Moreover, work still needs to be done to apply green credit policy to the development of a low-carbon energy sector and industries. Thus, it is difficult to fully clarify the transmission mechanism through which green credit policy can best promote the development of low-carbon industries and the upgrade of the energy sector. Second, although numerous studies examine how to promote the development of clean energy and reduce carbon an emission, relatively little research examines the optimal level of policy regulation. Determining the optimal regulatory level is important as such interventions can easily generate economic imbalances and negative impacts in the short term. This paper adds to the literature by constructing an E-DSGE model that includes high carbon and low carbon enterprises. The model depicts the behavioral choices and financing decisions of different enterprises and can better explain the transmission of monetary policy. In addition, in the context of a differentiated energy sector, we conduct a welfare analysis of monetary policies with different regulatory aims and discuss the optimal regulatory policies for preventing short-term economic imbalances, meeting the consumption demand of enterprises and residents and promoting the smooth and orderly transformation of the energy sector. The results of this paper show that in the long run, the optimization and upgrading of the energy sector is an inevitable task for the country and its citizens. Although we find that green credit policy can promote the development of low-carbon industries, if it exceeds the optimal policy requirement in the short term, it may lead to a decline in total output, lower consumption and reduced employment. Thus, the proportion of coal-generated electricity should continue to be reduced and the development of low-carbon industries should be encouraged through green credit policy guidance. To achieve a smooth transformation of the energy sector, the relevant authorities need to pay more attention to optimizing regulatory policy and full play to the guiding role of green credit policy to prevent economic imbalances in the short term. Great importance also needs to be attached to the role of transition finance in adjusting the energy sector.
马理, 张人中, 马威, 牛慕鸿. 能源结构有序调整与绿色信贷政策调控[J]. 金融研究, 2023, 511(1): 94-112.
MA Li, ZHANG Renzhong, MA Wei, NIU Muhong. Orderly Adjustment of Energy Structure and Regulation of Green Credit Policies. Journal of Financial Research, 2023, 511(1): 94-112.
Angelopoulos, K, Economides G and Philippopoulos A. 2013. “First-and Second-best Allocations under Economic and Environmental Uncertainty”, International Tax and Public Finance, 20 (3): 360～380.
[22]
Beaudry ,P. and Portier F. 2004. “An Exploration into Pigou's Theory of Cycles”, Journal of Monetary Economics, 51 (6): 1183～1216.
[23]
Bernanke, B. S and Gertler M. 2001. “Should Central Banks Respond to Movements in Asset Prices？”, American Economic Review, 91 (2): 253～257.
[24]
Chaudhry, S. M, Ahmed R, Shafiullah M and Duc Huynh T L. 2020. “The Impact of Carbon Emissions on Country Risk: Evidence from the G7 Economies”, Journal of Environmental Management, 265: 110533.
[25]
Christensen, I. and Dib A. 2008. “The Financial Accelerator in an Estimated New Keynesian Model”, Review of Economic Dynamics, 11 (1): 155～178.
[26]
Christiano, L. J, Eichenbaum M and Evans C L. 2005. “Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy”, Journal of Political Economy, 113 (1): 1～45.
[27]
Gali, J. and Gertler M. 1999. “Inflation Dynamics: A Structural Econometric Analysis”, Journal of Monetary Economics, 2 (44): 195～222.
[28]
Golosov, M, Hassler J, Krusell P and Tsyvinski A. 2014. “Optimal Taxes on Fossil Fuel in General Equilibrium”, Econometrica, 82 (1): 41～48.
[29]
Herbst, E. P. and Schorfheide F. 2016. “Bayesian Estimation of DSGE Models”, Princeton University Press.
[30]
Horvath, M. 2000. “Sectoral Shocks and Aggregate Fluctuations”, Journal of Monetary Economics, 1 (45): 69～106.
[31]
Iacoviello, M. and Neri S. 2010. “Housing Market Spillovers: Evidence from an Estimated DSGE Model”, American Economic Journal: Macroeconomics, 2 (2): 125～164.
[32]
Kahn, M. E., Mohaddes K, Ng R N C, Pesaran M H, Raissi M and Yang J. 2021. “Long-term Macroeconomic Effects of Climate Change: A Cross-country Analysis”, Energy Economics, 105624.
[33]
Kirkpatrick, A. J. and Bennear L S. 2014. “Promoting Clean Energy Investment: An Empirical Analysis of Property Assessed Clean Energy”, Journal of Environmental Economics and Management, 68 (2): 357～375.
[34]
Li, Z, Liao G, Wang Z and Huang Z. 2018. “Green Loan and Subsidy for Promoting Clean Production Innovation”, Journal of Cleaner Production, 187: 421～431.
[35]
Merkl, C. and J. Gali. 2008. “ Monetary Policy, Inflation, and the Business Cycle: An Introduction to the New Keynesian Framework”, Journal of Economics, 95 (2): 179～181.
[36]
Paramati, S. R., Apergis N and Ummalla M. 2017. “Financing Clean Energy Projects Through Domestic and Foreign Capital: The Role of Political Cooperation among the EU, the G20 and OECD Countries”, Energy Economics, 61: 62～71.
[37]
Reboredo, J. C. and Ugolini A. 2018. “The Impact of Energy Prices on Clean Energy Stock Prices. A Multivariate Quantile Dependence Approach”, Energy Economics, 76: 136～152.
[38]
Semieniuk, G, Campiglio E, Mercure J F, Volz U and Edwards N R. 2021. “Low‐Carbon Transition Risks for Finance”, Wiley Interdisciplinary Reviews: Climate Change, 12 (1): 678～702
[39]
Sun, J, Wang F, Yin H and Zhang B. 2019. “Money Talks: The Environmental Impact of China's Green Credit Policy”, Journal of Policy Analysis and Management, 38 (3): 653～680.
[40]
Tan, Y. and Uprasen U. 2021. “Carbon Neutrality Potential of the ASEAN-5 Countries: Implications from Asymmetric Effects of Income Inequality on Renewable Energy Consumption”, Journal of Environmental Management, 299: 113635.
