This study investigates whether and how financial technologies (FinTech) influence the effectiveness of monetary policy transmission. We use an interacted panel vector autoregression model to explore how the effects of monetary policy shocks change with regional-level FinTech adoption. Results indicate that FinTech adoption generally mitigates the transmission of monetary policy to real GDP, consumer prices, bank loans, and housing prices, with the most significant impact observed in the weakened transmission to bank loan growth. The relaxed financial constraints, regulatory arbitrage, and intensified competition are the possible mechanisms underlying the mitigated transmission.

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.

We assess the cleansing effects of the 2008–2009 financial crisis. U.S. regions with higher levels of supervisory forbearance on distressed banks see less restructuring in the real sector: fewer establishments, firms, and jobs are lost when more distressed banks remain in business. In these regions, the banking sector has been less healthy for several years after the crisis. Regions with less forbearance experience higher productivity growth after the crisis with more firm entries, job creation, and employment, wages, patents, and output growth. Forbearance is greater for state-chartered banks and in regions with weaker banking competition and more independent banks.

Bank regulators interfere with the efficient allocation of resources for the sake of financial stability. Based on this trade-off, I compare how different capital requirements affect default probabilities and the allocation of market shares across heterogeneous banks. In the model, banks‘ productivity determines their optimal strategy in oligopolistic markets. Higher productivity gives banks higher profit margins that lower their default risk. Hence, capital requirements indirectly aiming at high-productivity banks are less effective. They also bear a distortionary cost: Because incumbents increase interest rates, new entrants with low productivity are attracted and thus average productivity in the banking market decreases.

Productivity varies widely between industries and countries, but even more so across individual firms within the same sectors. The challenge for governments is to strike the right balance between policies designed to increase overall productivity and policies designed to promote the reallocation of resources towards firms that could use them more effectively. The aim of this book is to provide the empirical evidence necessary in order to strike this policy balance. The authors do so by using a micro-aggregated dataset for 20 EU economies produced by CompNet, the Competitiveness Research Network, established some 10 years ago among major European institutions and a number of EU productivity boards, National Central Banks, National Statistical institutes, as well as academic Institutions. They call for pan-EU initiatives involving statistical offices and scholars to achieve a truly complete EU market for firm-level information on which to build solidly founded economic policies.

This paper documents a link between bank concentration and markups in nonfinancial sectors. We exploit concentration-increasing bank mergers and variation in banks’ market shares across industries and show that higher credit concentration is associated with higher markups and that high-market-share lenders charge lower loan rates. We argue that this is due to the greater incidence of competing firms sharing common lenders that induce less aggressive product market behavior among their borrowers, thereby internalizing potential adverse effects of higher rates. Consistent with our conjecture, the effect is stronger in industries with competition in strategic substitutes where negative product market externalities are greatest.