Knowledge that Transforms

We develop a dynamic framework to study banks’ incentives to take excessive risk in an emerging economy, where bank default probability and excess bank risk-taking are modeled endogenously. We calibrate it for the 1998 Peruvian economy. We find that the infinite-period feature amplifies banks’ incentives to take excessive risk. When we simulate the sudden stop that hit Peru in 1998, the model accurately predicts the substantial short-term rise in the non-performing loans ratio through the rise of the bank default probability.

We analyze how capital requirements from environmental risk exposure affect bank lending to the corporate sector, and how these effects transmit to real economic activity and to greenhouse gas emissions. To do so, we exploit the introduction of a policy in Brazil that required banks to incorporate environmental risks in their capital assessments. Using comprehensive credit data, we find that the policy induces large banks to reallocate their lending away from exposed sectors. The credit contraction has no substantial impact on the real activity and greenhouse gas emissions of these sectors, as smaller banks expand their lending afterwards. However, the policy triggers a moderate labor reallocation from small firms (i.e., those with higher costs of switching lenders) and into large firms within environmentally exposed sectors.

We show that financial crises are preceded by changes in specific types of narrative information contained in newspaper article titles. Our novel international dataset and the resulting empirical evidence are gathered by integrating information from a large panel of economic news articles in global newspapers between the years 1870 and 2016 with conventional macroeconomic and financial indicators. We find that the predictive information of newspaper article titles that signals coming crisis episodes is substantial over and above the macroeconomic and financial indicators. Feature contribution analysis and crisis case studies reveal that the new indicators capture more detailed, but still generalizable information on the buildup of crises.

This paper explores the relationship between environmental, social and governance (ESG) information and systemic risk, an increasingly important issue for both regulators and investors. While ESG ratings are widely used to assess a company’s non-financial performance, the impact of these factors on financial stability and systemic risk is still under debate. By extending the Forecast Error Variance Decomposition (FEVD) method with a double regularization on both the underlying vector autoregressive (VAR) parameters and the covariance matrix of the VAR residuals, we are able to address the curse of dimensionality within each estimation. This allows us to examine how vulnerable a company is and how much systemic impact a company has given its specific ESG. Looking at a larger sample of European stocks over the period 2007-2022, we empirically show that both the best and worst ESG performers have the largest impact on the financial system in normal times. However, during a crisis, companies with the best ESG ratings generate significant spillovers throughout the system. These findings highlight the importance of incorporating ESG factors into systemic risk assessments and monitoring companies’ ESG performance to ensure financial stability. Policymakers can benefit from this research by supporting investment in high ESG companies to mitigate relevant spillovers during stressed market conditions, when such companies are more interconnected.

We investigate how investors perceive the adoption of the expected-loss model (ELM) for impairment incorporated in IFRS 9. Using a sample of European listed banks covering the period of the standard-setting process of IFRS 9, we examine whether the market perceives the new regulation to increase shareholder wealth. First, we document a positive market reaction to the ELM adoption events. Second, we find that investors perceive that the potential benefits of ELM are more pronounced for larger banks, banks with lower profitability and higher systemic risk, and for those that received a public bailout and with more positively skewed returns. Overall, these results support a “monitoring” channel suggesting that ELM may lead to greater bank transparency and more effective market discipline, fundamental for improving financial stability.

This study explores the effect of an investment system reform (deregulation) on the innovation performance of private firms in China. Using a difference-in-differences approach on the data on patent applications of private firms from 1998 to 2009, this study confirms the positive relationship between investment deregulation and innovation performance. We also find that the positive relationship is moderated by types of innovation, firm size and international orientation, and regional patent promotion policy. The study further finds evidence that investment deregulation stimulates innovation performance through two mechanisms, the escaping competition effect, and the preemptive patenting effect. Moreover, investment deregulation may improve the innovation performance of private firms by encouraging investment in fixed capital.

This paper uses a stylized simulation model to assess the potential impact of climate transition risk on banks' balance sheets in a climate-stress-testing (i.e. short-run) framework. We show that a moderate to high transition risk increases overall bank losses only relatively modestly if the baseline is a stressed macroeconomic scenario. However, even in a benign macroeconomic scenario, if high-carbon assets are at least 13% riskier than comparable assets a fire sale mechanism could amplify an initially contained shock into a systemic crisis, resulting in significant losses for the EU banking sector. We show that transition risks are concentrated, and find that an additional capital buffer of 0.9% risk-weighted assets on average would be sufficient to protect the system.

We examine how climate risk influences analyst forecast accuracy proxied by forecast error and dispersion. Using country-level climate risk estimated with time trends in droughts, we find that analyst forecasts are less accurate for firms in drought-prone countries. This effect of climate risk is stronger when climate risks are denoted in earnings forecasts, and when firms’ home countries have greater reliance on hydroelectric sources in electricity generation, more important agricultural and food industries, and active stances concerning climate change. Overall, our findings suggest noteworthy implications of climate risk on the financial markets via analyst forecast accuracy.

In this study, we examine the relationship between firm-level political risk and stock price crash risk. Using a broad dataset of 4230 U.S. firms, 38,097 firm-year observations from 2002 to 2019, we reveal a positive association between political risk and stock price crash risk. These findings are robust to several model specifications and endogeneity checks. By using the Brexit referendum as a quasi-natural experiment, we provide evidence of a causal relationship between political risk and crash risk. Through channel analysis, we identify that this relationship is mediated via higher idiosyncratic volatility, lower price informativeness, and higher distress risk. We also find that our results are more pronounced in intangible-intensive firms. Interestingly, we show that managers of these firms respond to political risk by engaging in bad news hoarding. Finally, strong (external or internal) corporate governance mechanisms can moderate the positive relationship between political risk and stock price crash risk.

In this paper we present a methodology of model-based calibration of additional capital needed in an interconnected financial system to minimize potential contagion losses. Building on ideas from combinatorial optimization tailored to controlling contagion in case of complete information about an interbank network, we augment the model with three plausible types of fire sale mechanisms. We then demonstrate the power of the methodology on the euro area banking system based on a network of 373 banks. On the basis of an exogenous shock leading to defaults of some banks in the network, we find that the contagion losses and the policy authority’s ability to control them depend on the assumed fire sale mechanism and the fiscal budget constraint that may or may not restrain the policy authorities from infusing money to halt the contagion. The modelling framework could be used both as a crisis management tool to help inform decisions on capital/liquidity infusions in the context of resolutions and precautionary recapitalizations or as a crisis prevention tool to help calibrate capital buffer requirements to address systemic risks due to interconnectedness.