This paper provides both theoretical and empirical analyses of the differences between BigTech lenders and traditional banks in response to monetary policy changes. Our model integrates Knightian uncertainty into portfolio selection and posits that BigTech lenders possess a diminishing informational advantage with increasing firm size, resulting in reduced ambiguity when lending to smaller firms. The model suggests that the key distinction between BigTech lenders and traditional banks in response to shifts in funding costs, triggered by monetary policy changes, is more evident at the extensive margin rather than the intensive margin, particularly during periods of easing monetary policy. Using a micro-level dataset of small business loans from both types of lenders, we provide empirical support for our theoretical propositions. Our results show that BigTech lenders are more responsive in establishing new lending relationships in an easing monetary policy environment, while the differences in loan amounts are not statistically significant. We also discuss other loan terms and the implications of regulatory policies.

The economy is a complex system because market participants do not act independently but adjust their behavior to other agents and to the outcome which emerges from their joint actions (Arthur, 2014). Dependencies among participants can impede policy makers capabilities to influence or steer the course of the economy. Kambhu et al. (2007) argue that to influence developments in financial markets, for instance to prevent crises from spreading, there are only “coarse or indirect options” available for policy makers. Similar to crises which propagate through a complex system, interventions might result in unintended side effects which can also disseminate through the system. Thus, in a complex system, unintended consequences of policy efforts may well be the rule. Policy makers try to ward off or mitigate negative consequences for the economy and society during periods of crisis. For instance, during the Covid crisis large scale support programs for firms in Western economies were set up to avoid bankruptcies. Similarly, during the sovereign debt crisis in the Eurozone, the European Central Bank (ECB) set up large scale asset purchase programs as well as additionally longer-term refinancing operations (LTRO) which provided immediate support to financial market participants’ liquidity positions and thereby prevented a melt-down of the financial system. During these periods, immediate and abundant liquidity supply is of utmost importance. Meanwhile, crisis measures, due to their massive scale and non-specific target group, may entail unknown or unintended side effects for instance on competition among market participants, firms’ investment behavior, or changes in lending strategies and risk taking behavior of banks. Likewise, new regulatory frameworks such as the introduction of new markets can have consequences previously not thought of. For policy makers it is important to know direct effects of policy interventions but also to be aware of the possibility and impact of indirect or unexpected side effects in order to evaluate measures taken and to learn for future design of regulation or intervention.

Syndicated loan data provided by DealScan is an essential input in banking research. This data is rich enough to answer urging questions on bank lending, e.g., in the presence of financial shocks or climate change. However, many data options raise the question of how to choose the estimation sample. We employ a standard regression framework analyzing bank lending during the financial crisis of 2007/08 to study how conventional but varying usages of DealScan affect the estimates. The key finding is that the direction of coefficients remains relatively robust. However, statistical significance depends on the data and sampling choice and we provide guidelines for applied research.

We identify the effect of climate change-related regulatory risks on credit real-location. Our evidence suggests that effects depend borrower's region. Following an increase in salience of regulatory risks, banks reallocate credit to US firms that could be negatively impacted by regulatory interventions. Conversely, in Europe, banks lend more to firms that could benefit from environmental regulation. The effect is moderated by banks' own loan portfolio composition. Banks with a portfolio tilted towards firms that could be negatively a affected by environmental policies increasingly support these firms. Overall, our results indicate that financial implications of regulation associated with climate change appear to be the main drivers of banks' behavior.

Unconventional monetary policy measures like asset purchase programs aim to reduce certain securities' yield and alter financial institutions' investment behavior. These measures increase the institutions' market value of securities and add to their equity positions. We show that the extent of this recapitalization effect crucially depends on the securities' accounting and valuation methods, country-level regulation, and maturity structure. We argue that future research needs to consider these factors when quantifying banks' recapitalization effects and consequent changes in banks' lending decisions to the real sector.

Young people are marching around the globe to ask for measures against climate change and to protect the environment. Using novel survey data, we ask who participates in such powerful movements and what can be learned from our findings. The survey was conducted in German and is based on answers from more than 600 participants. We find that survey respondents are less likely to participate in climate marches like “Fridays for Future” in case they trust more in (large) corporations suggesting a link between trust and climate activism. We also ask whether worries about climate change or attitudes towards more environmentally friendly behavior match their participation frequency in climate marches. Results reveal that respondents being more worried about climate change or the environment tend to participate more often in marches addressing these concerns. Similarly, participation in climate marches correlates positively with acting environmentally sustainable. Hence, our findings might be relevant for corporations in case they want to keep the support of young customers participating in climate marches.

This paper investigates whether and how economic policy uncertainty affects corporate debt maturity. Using a large firm-level dataset for four European countries, we find that an increase in economic policy uncertainty is significantly associated with a shortened debt maturity. Moreover, the impacts are stronger for innovation-intensive firms. We use firms’ flexibility in changing debt maturity and the deviation to leverage target to gauge the causal relationship, and identify the reduced investment and steepened term structure as the transmission mechanisms.

The Swiss National Bank abolished the exchange rate floor versus the Euro in January 2015. Using a synthetic matching framework, we analyze the impact of this unexpected (and therefore exogenous) policy change on the stock market. The results reveal a significant level shift (decline) in asset prices following the discontinuation of the minimum exchange rate. As a novel finding in the literature, we document that the exchange‐rate elasticity of Swiss asset prices is around −0.75. Differentiating between sectors of the Swiss economy, we find that the industrial, financial and consumer goods sectors are most strongly affected by the abolition of the minimum exchange rate.

This paper studies whether and how banks’ technological innovations affect the bank lending channel of monetary policy transmission. We first provide a theoretical model in which banks’ technological innovation relaxes firms’ earning-based borrowing constraints and thereby enlarges the response of banks’ lending to monetary policy changes. To test the empirical implications, we construct a patent-based measurement of bank-level technological innovation, which can specify the nature of technology and tell whether it is related to the bank’s lending business. We find that lending-related innovations significantly strengthen the transmission of the bank lending channel.