This study assesses the impact of China’s Green Credit Guidelines (GCG) 2012 on the quality of firms’ green innovation and their financial asset allocations. While examining patent applications and grants, our findings reveal that, although the GCG 2012 led to a significant increase in green patent applications, its influence on granted patents, especially in the invention category, was minimal. This highlights a discrepancy between innovation intent and quality, suggesting that highpolluting enterprises (HPEs) prioritize rapid policy compliance rather than substantial environmental improvements. However, HPEs seem to prioritize liquidity over long-term financialization, potentially indicating enhanced credit allocation efficiency.

Using the formal implementation of the 2012 Green Credit Guidelines (GCG) as an exogenous shock to construct a quasi-natural experiment, we study the impact of green credit policies on the inefficient investment of heavily polluting firms in China's listed companies from 2008 to 2020. We find that green credit policies can significantly alleviate the inefficient investment of heavily polluting enterprises. By reducing agency costs and long-term liabilities, green credit policies mitigate the problem of inefficient investment in heavily polluting firms. Moreover, the mitigating effect of green credit policies on the inefficient investment of heavily polluting enterprises has significant heterogeneity in terms of property rights, internal characteristics.

Taking the prevalence of the global green development concept and China's green credit development practice as the background, this paper constructs a theoretical model analysis framework with the incentive policy of green credit as the entry point. First, the impact effect of green credit incentive policy is examined using the BVAR model. The results show that the green credit incentive policy suppresses the output level in the short run through the financing constraint channel, but has a positive contribution to output in the long run due to the adjustment of the production structure and the dynamic adjustment of green investment and R&D. Next, the paper constructs a DSGE model embedded with green credit fiscal and tax incentive policies, which explains the impact mechanisms and comparative effects of fiscal and financial policies driving green credit. The model shows that the re-guarantee policy is the most effective and consensual green credit incentive policy. In terms of the policy combination, the combination of the re-guarantee policy and the income tax policy is the current optimal policy pairing, and its policy is able to produce an amplification effect through the balance sheet channels of commercial banks and enterprises at the same time. In addition, a certain intensity of the above policy combination not only can effectively increase the scale of green credit, but also does not produce significant negative shocks to output and inflation. In summary, the findings of this paper provide a useful reference for the formulation and implementation of green credit incentive policies.

In the process of green transformation of China's economy, it is of great practical significance to study the impact of green finance in supporting the development of the real economy, especially the impact of green credit on enterprise innovation, in order to promote the green transformation of enterprises, industrial structure upgrading and sustainable economic development. This paper takes green credit as a perspective and introduces it into the analytical framework of the impact of environmental regulation on corporate green innovation, through theoretical mechanism analysis and empirical testing, in order to reveal the impact and mechanism of green credit on corporate green innovation. It is found that green credit can effectively promote green innovation in heavy polluting enterprises, and it is mainly reflected in the increase of green utility model patent applications with a low degree of inventiveness. The promotion effect of green credit on green innovation is more obvious in regions with lower levels of economic development. Further mechanism analysis shows that green credit policy promotes green innovation of heavy polluting enterprises mainly through the incentive effect brought by changing financing environment and the pressure effect brought by increasing market competition. The findings of this paper can provide references for policy-making departments, banks and enterprises.

Understanding the impacts of new technology and innovations on the banking sector is important and of growing interest. However, there is limited research on the detailed channels of the impacts, and consequently, the evaluations for the aggregate welfare impacts. We contribute both empirically and quantitatively. We construct a new data set for Chinese banks. We ffnd banking innovations can improve efficiency, and mostly reduce non-interest costs but not so much on deposit rates. We show the ffnding is quite robust under a battery of checks. In a new structural, quantitative model, banks have heterogeneous capital, decide innovation investment and also risky lending, face regulations on the capital requirement and have limited liability. When aggregate new technology improves, it can reduce financial intermediation costs and social deadweight loss; however, it will also change the bank’s risk consideration and increases moral hazard when the cost is largely reduced. We also find several other new implications for R&D investment credit policy and Capital Requirement policy (CAR).

Using the regression discontinuity design, a quasi-experiment approach, this paper establishes a causal relationship between the down payment requirement and house prices by exploiting a unique institutional background in Shanghai. In the unique setting, the required minimal down payment ratio jumps at the Inner Ring, a circular elevated highway, from 50% to 70% for a large group of buyers. With transaction level data from the largest real estate broker in Shanghai, we find that a lower required down payment ratio increases the apartment price by 138.8 thousand RMB, around 3.71% of the average transaction price.

We build a unified framework to quantitatively examine population aging and credit market frictions in contributing to Chinese economic growth between 1977 and 2014. We find that demographic changes together with endogenous human capital accumulation account for a large part of the rise in per capita output growth, especially after 2007, as well as some of the rise in savings. Credit policy changes initially alleviate the capital misallocation between private and public firms and lead to significant increases in both savings and output growth. Later, they distort capital allocation. While contributing to further increase in savings, the distortion slows down economic growth. Among factors that we consider, increased life expectancy and financial development in the form of reduced intermediation cost are the most important in driving the dynamics of savings and growth.

Using quarterly data from 1998:Q1 to 2009:Q4 and monthly data from July 2005 to February 2010, this paper examines the impact of key monetary policy variables, including long- term benchmark bank loan rate, money supply growth, and mortgage credit policy indicator, on the real estate price growth dynamics in China. Empirical results consistently demonstrate that lower interest rate, faster money supply growth and loosening mortgage down payment requirement tend to accelerate the subsequent home price growth, and vice versa. These results suggest that Chinese monetary policy actions are the key driving forces behind the change of real estate price growth in China. We also show that hot money flow does not have significant impact on the change of home price growth after controlling for the money supply growth. Finally, a bullish stock market tends to accelerate subsequent home price growth.

Using quarterly data from 1998:Q1 to 2009:Q4 and monthly data from July 2005 to February 2010, this paper examines the impact of key monetary policy variables, including long-term benchmark bank loan rate, money supply growth, and mortgage credit policy indicator, on the real estate price growth dynamics in China. Empirical results consistently demonstrate that lower interest rate, faster money supply growth and loosening mortgage down payment requirement tend to accelerate the subsequent home price growth, and vice versa. These results suggest that Chinese monetary policy actions are the key driving forces behind the change of real estate price growth in China. We also show that hot money flow does not have significant impact on the change of home price growth after controlling for the money supply growth. Finally, a bullish stock market tends to accelerate subsequent home price growth.