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We provide evidence on narratives about the macroeconomy - the stories people tell to explain macroeconomic phenomena - in the context of a historic surge in inflation. In surveys with more than 10,000 US households and 100 academic experts, we measure economic narratives in open-ended survey responses and represent them as Directed Acyclic Graphs. Households' narratives are strongly heterogeneous, coarser than experts' narratives, focus more on the supply side than on the demand side, and often feature politically loaded explanations. Households' narratives matter for their inflation expectation formation, which we demonstrate with descriptive survey data and a series of experiments. Informed by these findings, we incorporate narratives into an otherwise conventional New Keynesian model and demonstrate their importance for aggregate outcomes.
We examine the evolution of spatial house price dispersion during Germany's recent housing boom. Using a dataset of sales listings, we find that house price dispersion has significantly increased, which is driven entirely by rising price variation across postal codes. We show that both price divergence across labor market regions and widening spatial price variation within these regions are important factors for this trend. We propose and estimate a directed search model of the housing market to understand the driving forces of rising spatial price dispersion, highlighting the role of housing supply, housing demand and frictions in the matching process between buyers and sellers. While both shifts in housing supply and housing demand matter for overall price increases and for regional divergence, we find that variation in housing demand is the primary factor contributing to the widening spatial dispersion within labor market regions.
I provide a solution method in the frequency domain for multivariate linear rational expectations models. The method works with the generalized Schur decomposition, providing a numerical implementation of the underlying analytic function solution methods suitable for standard DSGE estimation and analysis procedures. This approach generalizes the time-domain restriction of autoregressive-moving average exogenous driving forces to arbitrary covariance stationary processes. Applied to the standard New Keynesian model, I find that a Bayesian analysis favors a single parameter log harmonic function of the lag operator over the usual AR(1) assumption as it generates humped shaped autocorrelation patterns more consistent with the data.
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.
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 examines the dynamic relationship between firm leverage and risktaking. We embed the traditional agency problem of asset substitution within a multi-period model, revealing a U-shaped relationship between leverage and risktaking, evident in data from both the U.S. and Europe. Firms with medium leverage avoid risk to preserve the option of issuing safe debt in the future. This option is valuable because safe debt does not incur the expected cost of bankruptcy, anticipated by debt-holders due to future risk-taking incentives. Our model offers new insights on the interaction between companies' debt financing and their risk profiles.
Regulating IP exclusion/inclusion on a global scale: the example of copyright vs. AI training
(2024)
This article builds upon the literature on inclusion/inclusivity in IP law by applying these concepts to the example of the scraping and mining of copyright-protected content for the purpose of training an artificial intelligence (AI) system or model. Which mode of operation dominates in this technological area: exclusion, inclusion or even inclusivity? The features of AI training appear to call for universal and sustainable “inclusivity” instead of a mere voluntary “inclusion” of AI provider bots by copyright holders. As the overview on the copyright status of AI training activities in different jurisdictions and emerging laws on AI safety (such as the EU AI Act) demonstrates, the global regulatory landscape is, however, much too fragmented and dynamic to immediately jump to an inclusive global AI regime. For the time being, legally secure global AI training requires the voluntary cooperation between AI providers and copyright holders, and innovative techno-legal reasoning is needed on how to effectuate this inclusion.
We use a structural VAR model to study the German natural gas market and investigate the impact of the 2022 Russian supply stop on the German economy. Combining conventional and narrative sign restrictions, we find that gas supply and demand shocks have large and persistent price effects, while output effects tend to be moderate. The 2022 natural gas price spike was driven by adverse supply
shocks and positive storage demand shocks, as Germany filled its inventories before the winter. Counterfactual simulations of an embargo on natural gas imports from Russia indicate similar positive price and negative output effects compared to what we observe in the data.
The EU Commission proposed a regulation on artificial intelligence (AI) on 21 April 2021, which categorizes the use of AI in “social credit” as a prohibited application. This paper examines the definition and structure of the Social Credit System in China, which comprises various systems operating at different levels and sectors. The analysis focuses on two main subsystems: the database and one-stop inquiry platform for financial credit records, and the social governance tool designed to facilitate legal and political compliance. The development of the commercial customer credit reference is also explored. This paper further discusses the impacts and concerns associated with the implementation of the Chinese social credit system to raise awareness. The objective is to offer insights from the existing system and contribute to the ongoing discussion on regulating AI applications in social credit within the EU.