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Job loss expectations, durable consumption and household finances : evidence from linked survey data
(2019)
Job security is important for durable consumption and household savings. Using surveys, workers express a probability that they will lose their job in the next 12 months. In order to assess the empirical content of these probabilities, we link survey data to administrative data with labor market outcomes. Workers predict job loss quite well, in particular those whose job loss is followed by unemployment. Workers with higher job loss expectations acquire cheaper cars, and are less likely to buy new cars. In line with models of precautionary saving, higher job loss expectations are associated with more savings and less exposure to risky assets.
We study how the informativeness of stock prices changes with the presence of high-frequency trading (HFT). Our estimate is based on the staggered start of HFT participation in a panel of international exchanges. With HFT presence, market prices are a less reliable predictor of future cash flows and investment, even more so for longer horizons. Further, firm-level idiosyncratic volatility decreases, and the holdings and trades by institutional investors deviate less from the market-capitalization weighted portfolio as a benchmark. Our results document that the informativeness of prices decreases subsequent to the start of HFT. These findings are consistent with theoretical models of HFTs' ability to anticipate informed order flow, resulting in decreased incentives to acquire fundamental information.
In this note, we first highlight different developments for banks under direct ECB supervision within the SSM that may prompt further investigation by supervisors. We find that banks that were weakly capitalized at the start of direct ECB supervision (1) still face elevated levels of non-performing loans, (2) are less cost-efficient and (3) reduced their share of subordinated debt financing over the last years. We then stress the importance of continuous and ongoing cost-benefit analysis regarding banking supervision in Europe. We also encourage processes to question existing supervisory practices to ensure a lean and efficient banking supervision. Finally, we underline the need of continuous and intensified coordination among regulatory bodies in the Banking Union since the efficacy of European bank supervision rests on its interplay with many different institutions.
This document was requested by the European Parliament's Committee on Economic and Monetary Affairs. It was originally published on the European Parliament’s webpage.
Nach der 2008 startenden Finanzmarktkrise sind Maßnahmen zur Regulierung und Stabilisierung der Finanzmärkte in das Zentrum der politischen und der gesellschaftlichen Aufmerksamkeit gerückt. Insbesondere die hohen fiskalischen Kosten der Staaten zur Stützung ihrer Bankensysteme sowie die volkswirtschaftlichen Kosten infolge des Einbruchs des Wirtschaftswachstums in den Jahren nach der Insolvenz der US Investmentbank Lehman Brothers hatten einen globalen Konsens über die Notwendigkeit neuer Regulierungsmaßnahmen zur Folge. Im Ergebnis wurden das internationale Regulierungswerk Basel III sowie weitere nationale Maßnahmen zur Stabilisierung des Finanzsektors neu konzipiert und in Europa im Wege einer in nationales Recht umzusetzenden Richtlinie (die Capital Require-ments Directive IV - CRD IV) sowie einer Verordnung (die Capital Requirements Regulation CRR, welche unmittelbar geltendes Recht darstellt) eingeführt.
Vor diesem Hintergrund analysiert das vorliegende interdisziplinäre Gutachten die Auswirkungen der Regulierungsmaßnahmen, die zwischen 2008 bis zu Beginn des Jahres 2018 umgesetzt wurden auf dem deutschen Finanzsektor.
In diesem explorativen Beitrag machen wir uns Gedanken über die Zukunft von Deutscher Bank und Commerzbank und entwickeln einen neuen Zugang zu dem Thema: Statt einer Fusion von DB und CB schlagen wir eine Teilfusion nur der Datenzentren vor – es entsteht auf diese Weise die Grundlage für eine Open Banking Plattform als „utility“, also als Betrieb im Eigentum der Nutzer, an der perspektivisch weitere Finanzinstitute teilnehmen können. Die über die Daten kooperierenden Institute bleiben mit Blick auf Produkte und Dienstleistungen unverändert Konkurrenten – „national champions“ entstehen auf diese Weise nicht. Aber es wird damit in Europa die Basis für einen erfolgversprechenden Wettbewerb mit den großen Datenplattformen aus USA und China (Facebook, Amazon, Alipay) gelegt, die früher oder später in den Finanzmarkt eindringen werden. Das von uns vorgeschlagene Modell einer offenen Datenplattform für Banken verhindert das Entstehen von „national champions“ und schützt damit auch das Kernanliegen der Bankenunion: Die Schaffung eines Finanzsystems, dessen Banken jede für sich ausscheiden können ohne eine systemische Krise auszulösen, und ohne den Steuerzahler zu einer Rettungsaktion zu zwingen
SAFE Newsletter : 2019, Q1
(2019)
Do competition and incentives offered to designated market makers (DMMs) improve market liquidity? Using data from NYSE Euronext Paris, we show that an exogenous increase in competition among DMMs leads to a significant decrease in quoted and effective spreads, mainly through a reduction in adverse selection costs. In contrast, changes in incentives, through small changes in rebates and requirements for DMMs, do not have any tangible effect on market liquidity. Our results are of relevance for designing optimal contracts between exchanges and DMMs and for regulatory market oversight.
We show that banks that are facing relatively high locally non-diversifiable risks in their home region expand more across states than banks that do not face such risks following branching deregulation in the 1990s and 2000s. These banks with high locally non-diversifiable risks also benefit relatively more from deregulation in terms of higher bank stability. Further, these banks expand more into counties where risks are relatively high and positively correlated with risks in their home region, suggesting that they do not only diversify but also build on their expertise in local risks when they expand into new regions.
Self-control failure is among the major pathologies (Baumeister et al. (1994)) affecting individual investment decisions which has hardly been measurable in empirical research. We use cigarette addiction identified from checking account transactions to proxy for low self-control and compare over 5,000 smokers to 14,000 nonsmokers. Smokers self-directing their investment trade more frequently, exhibit more biases and achieve lower portfolio returns. We also find that smokers, some of which might be aware of their limited levels of self-control, exhibit a higher propensity than nonsmokers to delegate decision making to professional advisors and fund managers. We document that such precommitments work successfully.
Distributed ledger technology especially in the form of publicly coordinated validation networks such as Ethereum and Bitcoin with their own monetary circles provide for a revealing litmus test for current financial regulatory schemes. The paper highlights the interrelation between distributed coordination and the emission of virtual currency to make sense of the function of the new monetary phenomenon. It then argues for the regulation of financial services on the ground of the technology to ensure integrity standards. In this respect, it is useful to gear the development of a regulatory scheme towards the existing financial regulatory principles. However, future measures of the regulators must take the distributed nature of the platforms into account by relying on a “regulated self-regulation” of the community. Finally, the article focuses on the shortcomings of the current EU regulatory regimes, especially the regulation frameworks regarding financial services, payment services and electronic money.
Recently, Fuest and Sinn (2018) have demanded a change of rules for the Eurozone’s Target 2 payment system, claiming it would violate the Statutes of the European System of Central Banks and of the European Central Bank. The authors present a stylized model based on a set of macro-economic assumptions, and show that Target 2 may lead to loss sharing among national central banks (NCBs), thus violating the no risk-sharing requirement laid out by the Eurosystem Statutes.
In this note, I present an augmented model that incorporates essential features of the micro- and macroprudential regulatory and supervisory regime that today is hard-wired into Europe’s banking system. The model shows that the original no-risk-sharing principle is not necessarily violated during a financial crisis of a member state. Moreover, it shows that under a banking union regime, financial crisis asset value losses at or below the 99.9th percentile are borne by private investors, not by taxpayers, and particularly not by central banks.
Therefore, policy conclusions from the micro-founded model differ significantly from those suggested by Fuest and Sinn (2018).
n der Literatur wird oftmals angeführt, dass die Grunderwerbsteuer weder aus Sicht des Äquivalenzprinzips noch aus Sicht des Leistungsfähigkeitsprinzips zu rechtfertigen ist und daher in einem modernen Steuersystem nichts verloren hätte. Das vorliegende Papier weist darauf hin, dass die Grunderwerbsteuer Parallelen zur Grundsteuer aufweist und sich, zumindest aus ökonomischer Sicht, in eine Grundsteuer umbauen ließe. Dies könnte insbesondere dann interessant sein, wenn die derzeitige deutsche Grundsteuer in eine reine Flächensteuer umgebaut wird, die den Wert der Bebauung unbesteuert lässt. Ein Umbau der Grunderwerbsteuer, bei der der Kaufpreis dynamisiert wird und dann einer jährlichen Steuer unterworfen wird, hat einige Vorteile. Diese resultieren daraus, dass der negative Effekt auf die Zahl der Immobilientransaktionen (Lock-in-Effekt) abgemildert würde. Könnte die Dynamisierung treffsicher an die regionale Immobilienpreisentwicklung angepasst werden, entfällt der Lock-in-Effekt für Immobilien, die bereits einmal der dynamisierten Grunderwerbsteuer unterworfen waren, sogar komplett. Dies hat nicht nur positive Effekte auf das Funktionieren des Wohnungs- und Arbeitsmarktes, sondern kann auch dem Problem der Share Deals entgegen wirken.
We propose a shrinkage and selection methodology specifically designed for network inference using high dimensional data through a regularised linear regression model with Spike-and-Slab prior on the parameters. The approach extends the case where the error terms are heteroscedastic, by adding an ARCH-type equation through an approximate Expectation-Maximisation algorithm. The proposed model accounts for two sets of covariates. The first set contains predetermined variables which are not penalised in the model (i.e., the autoregressive component and common factors) while the second set of variables contains all the (lagged) financial institutions in the system, included with a given probability. The financial linkages are expressed in terms of inclusion probabilities resulting in a weighted directed network where the adjacency matrix is built “row by row". In the empirical application, we estimate the network over time using a rolling window approach on 1248 world financial firms (banks, insurances, brokers and other financial services) both active and dead from 29 December 2000 to 6 October 2017 at a weekly frequency. Findings show that over time the shape of the out degree distribution exhibits the typical behavior of financial stress indicators and represents a significant predictor of market returns at the first lag (one week) and the fourth lag (one month).
Extending the data set used in Beyer (2009) to 2017, we estimate I(1) and I(2) money demand models for euro area M3. After including two broken trends and a few dummies to account for shifts in the variables following the global financial crisis and the ECB's non-standard monetary policy measures, we find that the money demand and the real wealth relations identified in Beyer (2009) have remained remarkably stable throughout the extended sample period. Testing for price homogeneity in the I(2) model we find that the nominal-to-real transformation is not rejected for the money relation whereas the wealth relation cannot be expressed in real terms.
This paper examines how networks of professional contacts contribute to the development of the careers of executives of North American and European companies. We build a dynamic model of career progression in which career moves may both depend upon existing networks and contribute to the development of future networks. We test the theory on an original dataset of nearly 73 000 executives in over 10 000 _rms. In principle professional networks could be relevant both because they are rewarded by the employer and because they facilitate job mobility. Our econometric analysis suggests that, although there is a substantial positive correlation between network size and executive compensation, with an elasticity of around 20%, almost all of this is due to unobserved individual characteristics. The true causal impact of networks on compensation is closer to an elasticity of 1 or 2% on average, all of this due to enhanced probability of moving to a higher-paid job. And there appear to be strongly diminishing returns to network size.
Using a unique confidential contract level dataset merged with firm-level asset price data, we find robust evidence that firms' stock market valuations and employment levels respond more to monetary policy announcements the higher the degree of wage rigidity. Data on the renegotiations of collective bargaining agreements allow us to construct an exogenous measure of wage rigidity. We also find that the amplification induced by wage rigidity is stronger for firms with high labor intensity and low profitability, providing evidence of distributional consequences of monetary policy. We rationalize the evidence through a model in which firms in different sectors feature different degrees of wage rigidity due to staggered renegotiations vis-a-vis unions.
This paper analyzes the effect of financial constraints on firms' corporate social responsibility. Exploiting heterogeneity in firms' exposure to a monetary policy shock in the U.S., which reduced financial constraints for some firms, I find that firms increase their environmental responsibility. I use facility-level data to account for unobservable time-varying influences on pollution and find that toxic emissions decrease when parent companies are more exposed to the monetary policy shock. I further find that these facilities are also more likely to implement pollution abatement activities. Examining within-parent company heterogeneity I find that pollution abatement investments center on facilities at greater risk of facing additional costs due to environmental regulation. The findings are consistent with the idea that a reduction in financial constraints reduces pollution as it allows firms to implement pollution abatement measures.
Households buy life insurance as part of their liquidity management. The option to surrender such a policy can serve as a buffer when a household faces a liquidity need. In this study, we investigate empirically which individual and household specific sociodemographic factors influence the surrender behavior of life insurance policyholders. Based on the Socio-Economic Panel (SOEP), an ongoing wide-ranging representative longitudinal study of around 11,000 private households in Germany, we construct a proxy to identify life insurance surrender in the data. We use this proxy to conduct fixed effect regressions and support the results with survival analyses. We find that life events that possibly impose a liquidity shock to the household, such as birth of a child and divorce increase the likelihood to surrender an existing life insurance policy for an average household in the panel. The acquisition of a dwelling and unemployment are further aspects that can foster life insurance surrender. Our results are robust with respect to different models and hold conditioning on region specific trends; they vary however for different age groups. Our analyses contribute to the existing literature supporting the emergency fund hypothesis. The findings obtained in this study can help life insurers and regulators to detect and understand industry specific challenges of the demographic change.
Big data, data mining, machine learning und predictive analytics – ein konzeptioneller Überblick
(2019)
Mit der fortschreitenden Digitalisierung von Wirtschaft und Gesellschaft wächst die Bedeutung von Big Data Analytics, maschinellem Lernen und Künstlicher Intelligenz für die Analyse und Pognose ökonomischer Trends. Allerdings werden in wirtschaftspolitischen Diskussionen diese Begriffe häufig verwendet, ohne dass jeweils klar zwischen den einzelnen Methoden und Disziplinen differenziert würde. Daher soll nachfolgend ein konzeptioneller Überblick über die Gemeinsamkeiten, Unterschiede und Interdependenzen der vielfältigen Begrifflichkeiten im Bereich Data Science gegeben werden. Denn gerade für Entscheidungsträger aus Wirtschaft und Politik kann eine grundlegende Einordnung der Konzepte eine sachgerechte Diskussion über politische Weichenstellungen erleichtern.