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.

This study identifies an incentive-compatible mechanism to foster individual environmental engagement. Utilizing a dataset comprising 100,000 randomly selected users of Ant Forest—a prominent personal carbon accounting platform embedded within Alipay, China's leading BigTech super-app—we provide causal evidence that individuals strategically engage in eco-friendly behaviors to enhance their credit limits, particularly when approaching borrowing constraints. These behaviors not only illustrate the green nudging effect of BigTech but also generate value for the platform by leveraging individual green actions as soft information, thereby improving the efficiency of credit allocation. Using a structural model, we estimate an annual green value of 427.52 million US dollars generated by linking personal carbon accounting with BigTech credit. We also show that the incentive-based mechanism surpasses green mandates and subsidies in improving consumer welfare and overall societal welfare. Our findings highlight the role of an incentive-aligned approach, such as integrating personal carbon accounts into credit reporting frameworks, in addressing environmental challenges.

This paper examines the consequences of Chinese regulators deviating from a long-standing full bailout policy in addressing the distress of a city-level commercial bank. This policy shift led to a persistent widening of credit spreads and a significant decline in funding ratios for negotiable certificates of deposit issued by small banks relative to large ones. Our empirical analysis reveals a novel contagion mechanism driven by reduced confidence in future bailouts (implicit non-guarantee), contributing to the subsequent collapse of other small banks. However, in the longer term, this policy shift improved price efficiency, credit allocation, and discouraged risk-taking among small banks.

We estimate the financial and real effects of a subsidy program on imported capital goods recently implemented in China. We identify ffrms that have access to the subsidy program by combining data on catalogues of eligible products periodically released by the government and product-level import data. Our findings demonstrate that following the implementation of the program, eligible firms experience an increase in borrowing and gain access to loans at lower interest rates compared to non-eligible firms. This improved financial situation enables them to expand their fixed-asset investments, increase total output, and enhance their export performance. The expansion of production capacity also leads to improved investment efffciency and greater profitability. Further analysis reveals that the effects of the policy are particularly pronounced for non-state-owned enterprises and small firms in relatively competitive industries. This finding suggests that these firms face ex-ante financial constraints, and their marginal rate of return to capital is large.

This paper investigates the consequences of Chinese regulators deviating from a long-standing full bailout policy in addressing a city-level commercial bank’s distress. This event led to a persistent widening of credit spreads and a significant decline in funding ratios for negotiable certificates of deposit issued by small banks relative to large ones. Our empirical analysis pinpoints a novel contagion mechanism marked by diminished confidence in bank bailouts, which accounts for the subsequent collapse of several other small banks. However, the erosion of confidence in government guarantees enhances price efficiency and credit allocation while discouraging risk taking among small banks.

Using a proprietary bank-loan-level dataset, we find a surprising negative relation between loan spreads and minimum wage. We propose a stylized model to explain the relation: banks filter out the low-quality borrowers after the wage shocks, resulting in a separating equilibrium. Our evidence is consistent with the model’s predictions: (1) city-level and firm-level evidence shows that an increase in minimum wage is negatively associated with the likelihood of obtaining bank loans, especially for labor-intensive borrowers, (2) deal-level evidence shows that both the average default rate and loan spreads decrease when minimum wage rises, and (3) subsequently, labor intensive firms that are still able to obtain bank loans when minimum wage rises outperform their peers. Our findings suggest that as more credit resources are allocated to better quality firms and leave other firms far more behind, the existence of such credit reallocation effects can exacerbate the divergence between higher and lower quality firms induced by an increase in minimum wages.

We study how government intervention in the bank loan granting process affects firms’ leverage dynamics. We exploit the setup of administrative approval centers (AACs) in China, a program aiming to reduce bureaucracy in business activities, as a quasi-natural experiment. On average, AACs help to shorten the leverage rebalancing period by as much as a quarter. This acceleration pattern persists in under-leveraged firms, which issue more debt to rebalance accordingly. Cross-sectional analyses show that the positive effect of AACs on leverage adjustment is more pronounced for firms that are in poorer legal environment, with more financial constraints, or less politically connected. ics.

Peer-to-Peer lending platforms encourage borrowers to obtain various credit certificates for information disclosure. Using unique data from one of China's largest Peer-to-Peer platforms, we show that borrowers of lower credit quality obtain more certificates to boost their credit profiles, while higher-quality ones do not. Uninformed credulous lenders take these nearly costless certificates as a positive signal to guide their nvestments. Consequently, loans applied by borrowers with more credit certificates have higher funding success but worse repayment performance. Overall, we document credit certificates fail to accurately signal borrowers' qualities due to adverse selection, resulting in distorted credit allocation and investment inefficiency.

We study credit allocation across  rms and its real e ects during China's economic stimulus plan of 2009-2010. We match con dential loan-level data from the 19 largest Chinese banks with  rm-level data on manufacturing  rms. We document that the stimulus-driven credit expansion disproportionately favored state-owned rms and  rms with lower average product of capital, reversing the process of capital reallocation towards private  rms that characterized China's high growth before 2008. We argue that implicit government guarantees for state-connected  rms become more prominent during recessions and can explain this reversal.

Using proprietary individual level loan data, this paper explores the economic consequences of the 2009 bank entry deregulation in China. Such deregulation leads to higher screening standards, lower interest rates, and lower delinquency rates for corporate loans from entrant banks. Consequently, in deregulated cities, private firms with bank credit access increase asset investments, employment, net income, and ROA. In contrast, the performance of state-owned enterprises (SOEs) does not improve following deregulation. Deregulation also amplifies bank credit from productive private firms to inefficient SOEs due mainly to SOEs’ soft budget constraints. This adverse effect accounts for 0.31% annual GDP losses.