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This paper uses unique administrative data and a quasi-field experiment of exogenous allocation in Sweden to estimate medium- and longer-run effects on financial behavior from exposure to financially literate neighbors. It contributes evidence of causal impact of exposure and of a social multiplier of financial knowledge, but also of unfavorable distributional aspects of externalities. Exposure promotes saving in private retirement accounts and stockholding, especially when neighbors have economics or business education, but only for educated households and when interaction possibilities are substantial. Findings point to transfer of knowledge rather than mere imitation or effects through labor, education, or mobility channels.
The recent sovereign debt crisis in the Eurozone was characterized by a monetary policy, which has been constrained by the zero lower bound (ZLB) on nominal interest rates, and several countries, which faced high risk spreads on their sovereign bonds. How is the government spending multiplier affected by such an economic environment?While prominent results in the academic literature point to high government spending multipliers at the ZLB, higher public indebtedness is often associated with small government spending multipliers. I develop a DSGE model with leverage constrained banks that captures both features of this economic environment, the ZLB and fiscal stress. In this model, I analyze the effects of government spending shocks. I find that not only are multipliers large at the ZLB, the presence of fiscal stress can even increase their size. For longer durations of the ZLB,multipliers in this model can be considerably larger than one.
JEL Classification: E32, E 44, E62
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.
Editorial : economic competence and financial literacy of young adults – status and challenges
(2016)
In modern society, the ability to deal with financial and economic matters is becoming increasingly important. This is true for both professionals – e.g., in the investment and banking sectors – and for individuals responsible for managing their financial and economic affairs in everyday life (Aprea et al., in press). This ability is generally described as economic competence, economic literacy or financial literacy. Despite the importance of these constructs, there is still a lack of clarity regarding the exact definitions, and specifically, which components they cover in detail. Furthermore, the terms economic competence and financial literacy are only loosely coupled. Economic competence is usually considered to be more comprehensive than financial literacy. However, recent research on financial literacy has followed a broader approach as well. ...
The necessity for well-founded teacher education in economics – findings from curriculum analyses
(2016)
Everybody has to make daily decisions requiring a good understanding of political and economic systems to manage and design our life but also to react on changes in these systems. Already in the early stages of adulthood, individuals need to decide on which job to choose, which party to vote for or on what money to spend on. For all these activities economical knowledge is necessary, which usually derives from economic education taught in schools in several subjects. ...
The authors take a detailed look at the economic competence and financial literacy of young adults, especially of those who start an apprenticeship or who take up their studies at an university. Economic competence and financial literacy are of special interest within this group, because these young people are – mostly for the first time in their lives – responsible for autonomously managing their own financial affairs and deal with economic challenges.
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.
SAFE Newsletter : 2018, Q4
(2018)
Higher capital ratios are believed to improve system-wide financial stability through three main channels: (i) higher loss-absorption capacity, (ii) lower moral hazard, (iii) stabilization of the financial cycle if capital ratios are increased during good times. We examine these mechanisms in a laboratory asset market experiment with indebted participants. We find support for the loss-absorption channel: higher capital ratios reduce the bankruptcy rate. However, we do not find support for the moral hazard channel. Higher capital ratios (insignificantly) increase asset price bubbles, an aggregate measure of excessive risk-taking. Additional evidence suggests that bankruptcy aversion explains this surprising result. Finally, the evidence supports the idea that higher capital ratios in good times stabilize the financial cycle.
Distributed ledger technologies rely on consensus protocols confronting traders with random waiting times until the transfer of ownership is accomplished. This time consuming settlement process exposes arbitrageurs to price risk and imposes limits to arbitrage. We derive theoretical arbitrage boundaries under general assumptions and show that they increase with expected latency, latency uncertainty, spot volatility, and risk aversion. Using high-frequency data from the Bitcoin network, we estimate arbitrage boundaries due to settlement latency of on average 124 basis points, covering 88% of the observed cross-exchange price differences. Settlement through decentralized systems thus induces non-trivial frictions affecting market efficiency and price formation.
Zum ersten Mal wurde in Deutschland eine groß angelegte wissenschaftliche Studie zur Machbarkeit und zum Nutzen einer säulenübergreifenden Renteninformationsplattform durchgeführt, unter realen Bedingungen und mit mehreren tausend Teilnehmern. Die beiden zentralen Ergebnisse sind, dass ein elektronisches Rentencockpit auch in Deutschland technisch machbar ist und beträchtlichen individuellen Zusatznutzen für die Bürgerinnen und Bürger stiften würde. Die Langfristanalysen der Pilotstudie zeigen, dass selbst die einmalige Schaffung von Rententransparenz für viele Teilnehmer Anlass genug ist, ihren Rentenplan zu überdenken und sich aktiv mit ihrer Altersvorsorge auseinanderzusetzen und ihr Verhalten zu ändern. Teilnehmer mit Zugang zu einem elektronischen Rentencockpit fühlen sich nach der Studie deutlich besser informiert und neigen dazu ihr Sparverhalten stärker anzupassen als Personen ohne Zugang. Die außerordentlich hohe Bereitschaft zur Teilnahme und die Antworten in den Online-Befragungen sind zudem Beleg für den großen Bedarf an systemgestützter, individueller Rententransparenz. Soll ein Rentencockpit Verbreitung in Deutschland finden, scheint eine automatisierte, elektronische Bereitstellung von Vertragsdaten von Seiten der Rententräger jedoch unabdingbar, da die eigenständige Suche und teilmanuelle Bereitstellung von Standmitteilungen für die meisten Studienteilnehmer ein großes Hindernis darstellt.