Open Access

The lack of a European Deposit Insurance Scheme (EDIS) – often referred to as the ‘third pillar’ of Banking Union – has been criticized since the inception of the EU Banking Union. The Crisis Management and Deposit Insurance (CMDI) framework needs to rely heavily on banks’ internal loss absorbing capacity and provides little flexibility in terms of industry resolution funding. This design has, among others, led to the rare application of the CMDI, particularly in the case of small and medium sized retail banks. This reluctance of resolution authorities weakens any positive impact the CMDI may have on market discipline and ultimately financial stability. After several national governments pushed back against the establishment of an EDIS, the Commission recently took a different approach and tried to reform the CMDI comprehensively, without seeking to erect a ‘third pillar’. The overarching rationale of the CMDI Proposal is to make resolution funding more flexible. To this end, the proposal seeks to facilitate contributions from (national) deposit guarantee schemes (DGS). At the same time, the CMDI Proposal tries to broaden the scope of resolution to include smaller and medium sized banks. This paper provides an assessment of the CMDI Proposal. It argues that the CMDI Proposal is a step in the right direction but cannot overcome fundamental deficiencies in the design of the Banking Union.

Cross-predictability denotes the fact that some assets can predict other assets' returns. I propose a novel performance-based measure that disentangles the economic value of cross-predictability into two components: the predictive power of one asset's signal for other assets' returns (cross-predictive signals) and the amount of an asset's return explained by other assets' signals (cross-predicted returns). Empirically, the latter component dominates the former in the overall cross-prediction effects. In the crosssection, cross-predictability gravitates towards small firms that are strongly mispriced and difficult to arbitrage, while it becomes more difficult to cross-predict returns when market capitalization and book-to-market ratio rise.

This paper introduces a machine learning approach to quantify altruism from the linguistic style of textual documents. We apply our method to a central question in (social) entrepreneurship: How does altruism impact entrepreneurial success? Specifically, we examine the effects of altruism on crowdfunding outcomes in Initial Coin Offerings (ICOs). The main result suggests that altruism and ICO firm valuation are negatively related. We, then, explore several channels to shed some light on whether the negative altruism-valuation relation is causal. Our findings suggest that it is not altruism that causes lower firm valuation; rather, low-quality entrepreneurs select into altruistic projects, while the marginal effect of altruism on high-quality entrepreneurs is actually positive. Altruism increases the funding amount in ICOs in the presence of high-quality projects, low asymmetric information, and strong corporate governance.

This paper shows that support for climate action is high across survey participants from all EU countries in three dimensions: (1) Participants are willing to contribute personally to combating climate change, (2) they approve of pro-climate social norms, and (3) they demand government action. In addition, there is a significant perception gap where individuals underestimate others' willingness to contribute to climate action by over 10 percentage points, influencing their own willingness to act. Policymakers should recognize the broad support for climate action among European citizens and communicate this effectively to counteract the vocal minority opposed to it.

How does the design of debt repayment schedules affect household borrowing? To answer this question, we exploit a Swedish policy reform that eliminated interest-only mortgages for loan-to-value ratios above 50%. We document substantial bunching at the threshold, leading to 5% lower borrowing. Wealthy borrowers drive the results, challenging credit constraints as the primary explanation. We develop a model to evaluate the mechanisms driving household behavior and find that much of the effect comes from households experiencing ongoing flow disutility to amortization payments. Our results indicate that mortgage contracts with low initial payments substantially increase household borrowing and lifetime interest costs.