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Zur Reform der Einlagensicherung: Elemente einer anreizkompatiblen Europäischen Rückversicherung
(2020)
Bankeinlagen bis 100.000 Euro sind de jure überall im Euroraum gleichermaßen vor Verlusten geschützt. De facto hängt der Wert dieser gesetzlichen Haftungszusage unter anderem von der Ausstattung des nationalen Sicherungsfonds und der relativen Größe des Bankensektors in einer Volkswirtschaft ab. Um die Homogenität des Einlagenschutzes zu gewährleisten und die Bankenunion zu vollenden, bedarf es einer einheitlichen europäischen Einlagensicherung. Die bestehende implizite Risikoteilung im Euroraum ist ordnungspolitisch nicht wünschenswert. Ferner kann eine explizite und glaubwürdige Zweitsicherung Fehlanreize zur Übernahme exzessiver Risiken verhindern, bevor es zum Schadensfall kommt. Daher plädiert dieser Beitrag für ein zweistufiges, streng subsidiär organisiertes Rückversicherungsmodell: Nationale Erstversicherungen würden einen festgeschriebenen Teil, die europäische Rückversicherung nachrangig den Rest der Deckungssumme besichern. Die Rückversicherung gewährt diese Liquiditätshilfen in Form von Kassenkrediten. Weil die Haftung auf nationaler Ebene verbleibt, werden Risiken geteilt aber nicht vergemeinschaftet. Marktgerechte Prämien müssen nicht nur das individuelle Risikogewicht einer Bank sondern auch länderspezifische Risikofaktoren berücksichtigen. Zuletzt braucht der Rückversicherer umfangreiche Aufsichtsrechte, um die Zahlungsfähigkeit der Erstversicherer mit Hinblick auf die nationalen Haftungspflichten jederzeit sicherzustellen.
We show that High Frequency Traders (HFTs) are not beneficial to the stock market during flash crashes. They actually consume liquidity when it is most needed, even when they are rewarded by the exchange to provide immediacy. The behavior of HFTs exacerbate the transient price impact, unrelated to fundamentals, typically observed during a flash crash. Slow traders provide liquidity instead of HFTs, taking advantage of the discounted price. We thus uncover a trade-o↵ between the greater liquidity and efficiency provided by HFTs in normal times, and the disruptive consequences of their trading activity during distressed times.
This paper presents causal evidence of the effects of boardroom networks on firm value. We exploit exogenous variation in network centrality arising from a ban on interlocking directorates of Italian financial and insurance companies. We leverage this shock to show that firms that become more central in the network as a result of the shock experience positive abnormal returns around the announcement date. We find that information dissemination plays a central role: results are driven by firms that have higher idiosyncratic volatility, low analyst coverage, and more uncertainty surrounding their earnings forecasts. We also find that firms benefit more from boardroom centrality when they are more central in the input-output network, as this reinforces information complementarities, or when they are less central in the cross-ownership network, as well as when they suffer from low profitability and low growth opportunities. Network centrality also results in higher compensation for board directors.
Using an original dataset on professional networks of directors sitting on the boards of large US corporations, we examine how personal relationships are used by firms to improve job match quality in the high-skill segment of the labor market. Analyzing explicit social connection data between new hires and recruiters, we are able to test predictions of well established job referral models. We find that referred executive directors have a fifteen percent longer tenure than their non-referred counterparts. Referred executive directors also tend to be similar to their referrers on multiple dimensions, giving support to network homophily hypotheses.
We study whether and how time preferences change over the life cycle, exploiting representative long-term panel data. We estimate the age patterns of discount rates from age 25 to 80. In order to identify age effects, we have to disentangle them from cohort and period factors. We address this identification problem by estimating individual fixed effects models, where we substitute period effects with determinants of time preferences that depend on calendar years. We find that discount rates decrease with age and the decline is remarkably linear over the life cycle.
This paper provides an overview of how to use "big data" for economic research. We investigate the performance and ease of use of different Spark applications running on a distributed file system to enable the handling and analysis of data sets which were previously not usable due to their size. More specifically, we explain how to use Spark to (i) explore big data sets which exceed retail grade computers memory size and (ii) run typical econometric tasks including microeconometric, panel data and time series regression models which are prohibitively expensive to evaluate on stand-alone machines. By bridging the gap between the abstract concept of Spark and ready-to-use examples which can easily be altered to suite the researchers need, we provide economists and social scientists more generally with the theory and practice to handle the ever growing datasets available. The ease of reproducing the examples in this paper makes this guide a useful reference for researchers with a limited background in data handling and distributed computing.
We introduce Implied Volatility Duration (IVD) as a new measure for the timing of uncertainty resolution, with a high IVD corresponding to late resolution. Portfolio sorts on a large cross-section of stocks indicate that investors demand on average about seven percent return per year as a compensation for a late resolution of uncertainty. In a general equilibrium model, we show that `late' stocks can only have higher expected returns than `early' stocks if the investor exhibits a preference for early resolution of uncertainty. Our empirical analysis thus provides a purely market-based assessment of the timing preferences of the marginal investor.