This paper shows that higher information technology (IT) adoption by banks was associated to a larger increase in corporate lending in the months following the COVID-19 outbreak in Italy. Examining banks with heterogeneous degrees of IT adoption, we investigate the dynamics of credit and its allocation across firms using a new database with detailed information on banks’ IT expenditures and use of innovative technologies matched with bank-firm level data on credit growth before and during the pandemic. Using a diff-in-diff approach, we find that banks with a higher share of IT spending increased their credit more than others during the pandemic. The increase was concentrated in term loans extended to smaller and financially sounder companies; the effect was stronger in the initial phase of tighter restrictions to firm activity and individual mobility, and more significant for undertakings active in the sectors most affected by the shock. We provide evidence that these results are driven by bank’s ability to offer credit entirely online and bank’s use of artificial intelligence for credit risk assessment. Physical proximity between borrowers and lenders was important for credit provision during the pandemic, but only when combined with high level of IT adoption

Time-varying depreciation rates are estimated for research and development of the United States aggregate economy and innovation-intensive industries. Mean annual R&D depreciation rates are 31.5% for software, 41% for pharmaceuticals, 42% for semiconductors, and 30.4% for aggregate economy during 1978–2014. R&D depreciation rates vary across industries. R&D investment demand has separate elasticities in time-varying depreciation, interest rate and price growth, allowing for different rates of technology shifts across industries. Software R&D investment has the same magnitude of elasticities to depreciation, interest rate and price, supporting a user cost to apply. For pharmaceuticals and semiconductors, depreciation leads to more R&D investment that implies the effect of scale. For aggregate economy, depreciation reduces R&D investment more than interest rate, indicating obsolescence. Forecasting of R&D investment is improved at both industry and aggregate level. Forecastable time-varying depreciation, interest rate and price growth predict R&D investment based on the estimated demand function. The in-sample forecast comparison for 2015–2019 confirms the superiority to the alternative methods. Out-of-sample forecasts of R&D investment are carried out through 2025, and R&D capital stocks are constructed across industries and aggregate U.S. economy

Extensive regulatory changes and technological advances have transformed banking systems to a great extent. Banks have reacted to the challenges posed by the new operating environment by creating new products and expanding their activities to some uncharted business areas. In this paper, we study how modern banking which gave birth to the off-balance-sheet leverage activities affected the risk profile of U.S. banks as well as the level of systemic risk before and after the onset of the late 2000s financial crisis. Towards this, we separate on- from off-balance-sheet leverage and capture the latter with different, yet complementary, measures which do not exist in the current literature. Special attention is paid on the deleveraging process that occurred in the banking market after the crisis erupted, which is an additional innovative feature of this study. Our findings reveal that leverage, both explicit and hidden off-the-balance-sheet, increases the individual risk of banking firms making them vulnerable to financial shocks. Reverse leverage, on the other hand, is beneficial for individual banks’ health, but is found to be harmful for financial stability. We also demonstrate that the banks which concentrate on traditional lines of business typically carry less risk compared to those involved with modern financial instruments

Climate change has been recently recognised as a new source of risk for the financial system. Over the last years, several central banks and financial supervisors have recommended investors and financial institutions to assess their exposure to climate-related financial risks. Central banks and financial supervisors have also started to design scenarios for climate stress tests - to- assess how vulnerable the financial system is to climate change. Nevertheless, the financial community falls short of methodologies that allow the successful analysis of the risks that climate change poses to financial stability. Indeed, the characteristics of climate risks (i.e., deep uncertainty, non-linearity and endogeneity) challenge traditional approaches to macroeconomic and financial risk analysis. Embedding climate change in macroeconomic and financial analysis using innovative perspectives is fundamental for a comprehensive understanding of the macrofinancial relevance of climate change. This Special Issue is devoted to the relation between climate risks and financial stability and represents the first comprehensive attempt to fill methodological gaps in this area and to shed light on the financial implications of climate change. It includes original contributions that use a range of methodologies – such as network modelling, dynamic evolutionary macroeconomic modelling and financial econometrics – to analyse climate-related financial risks and the implications of financial policies and instruments aiming at the low-carbon transition. The research insights of these contributions can inform the decisions of central banks and financial supervisors about the integration of climate change considerations into their policies and financial risk assessment

During the 2008 global financial crisis, financial institutions in the United States experienced big losses, and some firms failed. These failures occurred despite the external and internal regulatory mechanisms imposed upon the financial sector aimed at ensuring confidence and stability in the financial system. This study analyzes the impact of macroeconomic and financial stress on the profitability of financial firms. We utilize data from 1980 to 2010 to model firm profitability and stock returns using a panel regression, fixed-effect methodology. Our results show that the profitability of all firms is negatively affected by increases in macroeconomic and financial stress, measured by the National Financial Conditions Index (NFCI) and the Adjusted National Financial Conditions Index (ANFCI), respectively; however financial sector firms have exhibited an increased marginal sensitivity to both stress indexes that began in the 1990s and continued through the financial crisis of 2008. In a further analysis of the financial sector and banks, we show that depository institutions are relatively robust to macroeconomic and financial stress, and financial sector instability is driven by non-depository finance, investment, and real estate firms. Additionally, the largest 33 percent of financial firms and banks exhibit increased sensitivity to macroeconomic stress in the most recent sample. Our results coincide with the risks associated with recent trends in the financial services industry, such as deregulation, global market integration, financial product innovation, and the increasing predominance of non-depository intermediation