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Using experimental data from a comprehensive field study, we explore the causal effects of algorithmic discrimination on economic efficiency and social welfare. We harness economic, game-theoretic, and state-of-the-art machine learning concepts allowing us to overcome the central challenge of missing counterfactuals, which generally impedes assessing economic downstream consequences of algorithmic discrimination. This way, we are able to precisely quantify downstream efficiency and welfare ramifications, which provides us a unique opportunity to assess whether the introduction of an AI system is actually desirable. Our results highlight that AI systems’ capabilities in enhancing welfare critically depends on the degree of inherent algorithmic biases. While an unbiased system in our setting outperforms humans and creates substantial welfare gains, the positive impact steadily decreases and ultimately reverses the more biased an AI system becomes. We show that this relation is particularly concerning in selective-labels environments, i.e., settings where outcomes are only observed if decision-makers take a particular action so that the data is selectively labeled, because commonly used technical performance metrics like the precision measure are prone to be deceptive. Finally, our results depict that continued learning, by creating feedback loops, can remedy algorithmic discrimination and associated negative effects over time.
In this paper we adopt the Hamiltonian Monte Carlo (HMC) estimator for DSGE models by implementing it into a state-of-the-art, freely available high-performance software package. We estimate a small scale textbook New-Keynesian model and the Smets-Wouters model on US data. Our results and sampling diagnostics confirm the parameter estimates available in existing literature. In addition we combine the HMC framework with the Sequential Monte Carlo (SMC) algorithm which permits the estimation of DSGE models with ill-behaved posterior densities.
Incentivized experiments in which individuals receive monetary rewards according to the outcomes of their decisions are regarded as the gold standard for preference elicitation in experimental economics. These task-related real payments are considered necessary to reveal subjects' "true preferences". Using a systematic, large-sample approach with three subject pools of private investors, professional investors, and students, we test the effect of task-related monetary incentives on risk preferences elicited in four standard experimental tasks. We find no systematic differences in behavior between subjects in the incentivized and non-incentivized regimes. We discuss implications for academic research and for applications in the field.
Discussions regarding the planned European Deposit Insurance Scheme (EDIS), the missing third pillar of the European Banking Union, have been ongoing since the Commission published its initial legisla-tive proposal in 2015. A breakthrough in negotiations has yet to be achieved. The gridlock on EDIS is most commonly attributed to moral hazard concerns over insufficient risk reduction harboured on the side of northern member states, particularly Germany, due to the weak state of some other member states’ banking sectors. While moral hazard based on uneven risk reduction is helpful for explaining divergent member-state preferences on the scope of necessary risk reduction, this does not explain preferences on the institutional design of EDIS. In this paper, we argue that contrary to persistent differences on necessary risk reduction, preferences regarding the institutional design of EDIS have become more closely aligned. We analyse how preferences on EDIS developed in the key member states of Germany, France, and Italy. In all sampled countries, we find path-dependent benefits con-nected to the current design of national Deposit Guarantee Schemes (DGS) that shifted preferences of the banking sector or significant subsectors in favour of retaining national DGSs. Overall, given that a compromise on risk-reduction can be accomplished, we argue that current preferences in these key member states provide an opportunity to implement EDIS in the form of a reinsurance system that maintains national DGSs in combination with a supranational fund.
We employ a representative sample of 80,972 Italian firms to forecast the drop in profits and the equity shortfall triggered by the COVID-19 lockdown. A 3-month lockdown generates an aggregate yearly drop in profits of about 10% of GDP, and 17% of sample firms, which employ 8.8% of the sample’s employees, become financially distressed. Distress is more frequent for small and medium-sized enterprises, for firms with high pre-COVID-19 leverage, and for firms belonging to the Manufacturing and Wholesale Trading sectors. Listed companies are less likely to enter distress, whereas the correlation between distress rates and family firm ownership is unclear.
(JEL G01, G32, G33)
We analyze the ESG rating criteria used by prominent agencies and show that there is a lack of a commonality in the definition of ESG (i) characteristics, (ii) attributes and (iii) standards in defining E, S and G components. We provide evidence that heterogeneity in rating criteria can lead agencies to have opposite opinions on the same evaluated companies and that agreement across those providers is substantially low. Those alternative definitions of ESG also a↵ect sustainable investments leading to the identification of di↵erent investment universes and consequently to the creation of di↵erent benchmarks. This implies that in the asset management industry it is extremely dicult to measure the ability of a fund manager if financial performances are strongly conditioned by the chosen ESG benchmark. Finally, we find that the disagreement in the scores provided by the rating agencies disperses the e↵ect of preferences of ESG investors on asset prices, to the point that even when there is agreement, it has no impact on financial performances.
Die durch das Zweite Corona-Steuerhilfegesetz erfolgte Ausweitung des Verlustrücktrags ist dem Grunde nach ein hochgradig geeignetes und insbesondere breitenwirksames Mittel zur Stützung der Konjunktur. Das vorliegende Policy White Paper legt dar, dass allerdings Art und Umfang der gewählten Ausweitung unzureichend sind. Hierzu analysieren die Verfasser, wie sich die Ausweitung auf Unternehmen unterschiedlicher Größe und Rechtsform auswirkt. Auf Basis dieser Analyse zei-gen sie sodann, dass gemessen an den verfolgten konjunkturpolitischen Zielen es geboten gewesen wäre und weiterhin geboten ist, den Verlustrücktrag auf die Gewerbesteuer zu erstrecken.
The Wirecard scandal is a wake-up call alerting German politics to the importance of securities market integrity. The role of market supervision is to ensure the smooth functioning of capital markets and their integrity, creating trust among and acceptance by investors locally and globally. The existing patchwork of national supervisory practice in Europe is under discussion today, in the wake of Brexit that will end the role of London as a de-facto lead supervisor in stock and bond markets. A fundamental overhaul of a fragmented securities markets supervisory regime in Europe would offer the potential to lead to the establishment of an independent European Single Market Supervisor (ESMS). Endowed with strong enforcement powers, and supported by the existing national agencies, the ESMS would be entrusted with ensuring a uniform market standard as to transparency and other issues of market integrity across Europe. This would not rule out maintaining a variety of market organization structures at the national level. The ESMS would need executive powers in the world of markets (i.e. securities and trading), much like the SSM in the world of banking. To fill this new role, ESMS would have to be established as a new, independent institution, including an enormously scaled up staff if compared, e.g., to ESMA.
Accounting for financial stability: Bank disclosure and loss recognition in the financial crisis
(2020)
This paper examines banks’ disclosures and loss recognition in the financial crisis and identifies several core issues for the link between accounting and financial stability. Our analysis suggests that, going into the financial crisis, banks’ disclosures about relevant risk exposures were relatively sparse. Such disclosures came later after major concerns about banks’ exposures had arisen in markets. Similarly, the recognition of loan losses was relatively slow and delayed relative to prevailing market expectations. Among the possible explanations for this evidence, our analysis suggests that banks’ reporting incentives played a key role, which has important implications for bank supervision and the new expected loss model for loan accounting. We also provide evidence that shielding regulatory capital from accounting losses through prudential filters can dampen banks’ incentives for corrective actions. Overall, our analysis reveals several important challenges if accounting and financial reporting are to contribute to financial stability.
Using a nonlinear Bayesian likelihood approach that fully accounts for the zero lower bound on nominal interest rates, the authors analyze US post-crisis business cycle dynamics and provide reference parameter estimates. They find that neither the inclusion of financial frictions nor that of household heterogeneity improve the empirical fit of the standard model, or its ability to provide a joint explanation for the post-2007 dynamics. Associated financial shocks mis-predict an increase in consumption. The common practice of omitting the ZLB period in the estimation severely distorts the analysis of the more recent economic dynamics.