Refine
Year of publication
- 2021 (238) (remove)
Document Type
- Working Paper (113)
- Part of Periodical (71)
- Article (43)
- Book (5)
- Contribution to a Periodical (2)
- Review (2)
- Bachelor Thesis (1)
- Report (1)
Has Fulltext
- yes (238)
Is part of the Bibliography
- no (238)
Keywords
- COVID-19 (8)
- Covid-19 (6)
- ESG (6)
- monetary policy (6)
- Green Finance (4)
- Artificial intelligence (3)
- Machine learning (3)
- Sustainability (3)
- climate change (3)
- corporate governance (3)
- volatility (3)
- BRRD (2)
- Bank Capitalization (2)
- Bank Resolution (2)
- Bayesian inference (2)
- China (2)
- Climate Change (2)
- DSGE (2)
- Diseases (2)
- ETFs (2)
- Elasticity (2)
- Equity Crowdfunding (2)
- Expectations (2)
- Forbearance (2)
- Health care (2)
- Idiosyncratic Risk (2)
- Innovation (2)
- Medical research (2)
- Non-performing Loans (2)
- Pathogenesis (2)
- Portfolio optimization (2)
- Risk aggregation (2)
- Sustainable Finance (2)
- Taxonomy (2)
- ambiguity (2)
- asset pricing (2)
- bubbles (2)
- credit risk (2)
- globalization (2)
- green finance (2)
- household finance (2)
- inequality (2)
- intergenerational persistence (2)
- oil price (2)
- recovery (2)
- school closures (2)
- 401(k) plan (1)
- AI fairness (1)
- Activism (1)
- Activist Hedge Fund (1)
- Adoption (1)
- Agent-based modeling (1)
- Agile Methods (1)
- Aging (1)
- Algorithmic fairness (1)
- Algorithmic transparency (1)
- Altersversorgung (1)
- Antitrust (1)
- Applied immunology (1)
- Asset Concentration Risk (1)
- Asset Management Companies (1)
- Asymmetric response (1)
- Audit partner style (1)
- Augmented reality (1)
- BaFin (1)
- Bailout (1)
- Bank Bailout (1)
- Bank Recapitalization (1)
- Bank Supervision (1)
- Bankenunion (1)
- Banking (1)
- Banking Union (1)
- Bayesian estimation (1)
- Behavioral Agency Model (1)
- Belief up-dating (1)
- Beliefs (1)
- Bitcoin (1)
- Blockchain (1)
- Blue Chip (1)
- Board Appointments (1)
- Bond risk premia (1)
- Brand focus (1)
- Brexit (1)
- C corporations (1)
- CDS spreads (1)
- CO2 emissions intensity (1)
- COVID-19 pandemic (1)
- CSPP (1)
- Capital Purchase Program (1)
- Capital allocation (1)
- Centrality (1)
- Changes in labor markets (1)
- Choquet (1)
- Classification (1)
- Coin tossing (1)
- Collaboration network (1)
- Collaboration types (1)
- Commercial real estate (1)
- Complementary mobility services (1)
- Computational Methods (1)
- Concordance (1)
- Consumer Welfare (1)
- Content analysis (1)
- Contractarian Model of Corporate Law (1)
- Core-component reuse (1)
- Corona (1)
- Corporate Bonds (1)
- Corporate Finance (1)
- Corporate Social Responsibility (1)
- Corporate quantitative easing (1)
- Correlated risk (1)
- Correlated risks (1)
- Costs (1)
- Covid pandemic (1)
- Covid-19 Pandemic (1)
- Credibility of Inflation Targets (1)
- Credit Risk (1)
- Crime (1)
- Crisis Management (1)
- Crowdfunding (1)
- Cryptocurrency (1)
- Curse of dimensionality (1)
- Customer focus (1)
- Cyclical Income Risk (1)
- DCC-GARCH (1)
- DSGE model (1)
- DSGE models (1)
- Delaware Incorporation (1)
- Delphic forward guidance (1)
- Deposit Insurance (1)
- Derivatives (1)
- Dictionary (1)
- Digitalisierung (1)
- Digitalized Markets (1)
- Disclosure (1)
- Discordance (1)
- Discount Functions (1)
- Discrete choice experiment (1)
- Discrete time dynamic programming (1)
- Disinflation (1)
- Disposition Effect (1)
- Dividend Payments (1)
- Dual response (1)
- Dynamic Inconsistency (1)
- Dynamic portfolio choice (1)
- ECB (1)
- ESG Rating Agencies (1)
- EU Bonds (1)
- Earnings call (1)
- Ecology (1)
- Economic Governance (1)
- Effective Lower Bound (1)
- Electric vehicles (1)
- Emerging economies (1)
- Endocrinology (1)
- Entrepreneurial Exit Intentions (1)
- Entrepreneurial finance (1)
- Entry mode (1)
- Environmental (1)
- Environmental sciences (1)
- Environmental social sciences (1)
- Environmental stringency (1)
- Epstein-Weil-Zin Preferences (1)
- Equity Premium (1)
- European Monetary Fund (1)
- European Stability Mechanism (1)
- Exchange rate regime (1)
- Expectation Formation (1)
- Expected Utility Preferences (1)
- Experiences (1)
- Explainable machine learning (1)
- Fair AI (1)
- Federal Reserve (1)
- FinTechs (1)
- Financial Crises (1)
- Financial Crisis (1)
- Financial Frictions (1)
- Financial Harvest Exit Strategy (1)
- Financial Market Cycles (1)
- Financial Reporting (1)
- Financial Stability (1)
- Financial advice (1)
- Financial center (1)
- Financial literacy (1)
- Financial management (1)
- Finanzstabilität (1)
- Fintech (1)
- Fire Sales (1)
- Fiscal Capacity (1)
- Fiscal theory of the price level (1)
- Flash crash (1)
- Foreign direct investment (1)
- Formative experiences (1)
- Forward Guidance (1)
- Fund Flows (1)
- Future of work (1)
- Gatekeeper position (1)
- Gender Gap (1)
- Governance (1)
- Government debt (1)
- Gradient-based optimization (1)
- Granger Causality (1)
- Green Bonds (1)
- Green bonds (1)
- Greenium (1)
- Growth (1)
- Health occupations (1)
- Hierarchical B-splines (1)
- High Frequency Data (1)
- High-frequency event study (1)
- Homeownership (1)
- Hong test (1)
- Household Finance (1)
- Household Inflation Expectations (1)
- Human-enhancing technologies (1)
- Idiosyncratic Income Risk (1)
- Immunology (1)
- Imperfect competition (1)
- Index Funds (1)
- Infection (1)
- Infectious diseases (1)
- Information processing (1)
- Information systems (1)
- Innate immune cells (1)
- Innate immunity (1)
- Insurance (1)
- Intelligence augmentation (1)
- Interest Rates (1)
- Internalization of externalities (1)
- International Finance (1)
- International Monetary Fund (1)
- Investor Protection (1)
- Investor sentiment (1)
- Kapitalallokation (1)
- Kapitalmarktunion (1)
- Klimawandel (1)
- Knowledge (1)
- Kreditrisiko (1)
- LSTM neural networks (1)
- Labor cost adjustments (1)
- Lebensversicherung (1)
- Life Insurance (1)
- Life-Cycle Model (1)
- LifeCycle Model (1)
- Liquidity (1)
- Liquidity Risk (1)
- Liquidity provision (1)
- Liquiditätsrisiko (1)
- Lobbying (1)
- Local projection (1)
- Location-based games (1)
- Longitudinal data (1)
- Machine Learning (1)
- Macroeconomic risks (1)
- Mandatory Law (1)
- Market Efficiency (1)
- Market Manipulation (1)
- Market efficiency (1)
- Market engineering (1)
- Market fragility (1)
- Markov-switching DSGE (1)
- Markups (1)
- Maximum length of association (1)
- Merchandise trade (1)
- Microprudential Insurance Regulation (1)
- Mikroprudenzielle Versicherungsregulierung (1)
- Mobile games (1)
- Monetary Policy Surprises (1)
- Monetary-fiscal interaction (1)
- Mutuality principle (1)
- NLP (1)
- Nachhaltigkeit (1)
- Narrative disclosures (1)
- Network theory (1)
- New vehicles (1)
- Next Generation EU (1)
- Nonlinear solution methods (1)
- Norway (1)
- Notverkäufe (1)
- Numerical accuracy (1)
- Obfuscation (1)
- Occasionally Binding Constraints (1)
- Offenlegungspflichten (1)
- Oil market (1)
- Online Surveys (1)
- Optimal redistribution (1)
- Options (1)
- Overfunding (1)
- Overlapping Generations (1)
- PCAOB (1)
- Patents (1)
- Pecuniary Externalities (1)
- Perceptions (1)
- Phillips Curve (1)
- Pigouvian tax (1)
- Plaintiff Lawyers (1)
- Pollution haven hypothesis (1)
- Portfolio Rebalancing (1)
- Portfolio choice (1)
- Portfoliooptimierung (1)
- Precautionary Saving (1)
- Price Competition (1)
- Price Pressures (1)
- Prior (1)
- Private Equity (1)
- Product life cycle (1)
- Production of disclosures (1)
- Production-based asset pricing (1)
- Productivity growth (1)
- Produktivitätsunterschiede (1)
- Public Housing (1)
- Public financial news (1)
- Public procurement (1)
- Quantitative easing (1)
- Quid-pro-quo Mechanism (1)
- Rational Inattention (1)
- Real Effects (1)
- Regional Entrepreneurship (1)
- Regulation (1)
- Regulatory Capture (1)
- Regulierung (1)
- Resolution (1)
- Responsible investment (1)
- Retail Investor (1)
- Risikoaggregation (1)
- Risk factors (1)
- Risk taking (1)
- S corporations (1)
- S&P 500 (1)
- Sample-based longitudinal study (1)
- Scenario (1)
- Scrum (1)
- Secondary Loan Markets (1)
- Sectoral Asset Diversification (1)
- Securities Regulation (1)
- Slow-moving capital (1)
- Small businesses (1)
- Social Conditioning (1)
- Social and Governance (ESG) (1)
- Social media (1)
- Socially responsible investing (1)
- Solution methods (1)
- Sovereign Risk (1)
- Soziale Marktwirtschaft (1)
- Spatial econometrics (1)
- Spatially adaptive sparse grids (1)
- Stewardship Exit Strategy (1)
- Stock market (1)
- Structural policies (1)
- Such-Matching- Sortierung (1)
- Supervisory Relief Measures (1)
- Surveillance (1)
- Sustainable Investing (1)
- Sustainable Investments (1)
- Systematic Risk (1)
- Systemic Risk (1)
- Systemic risk (1)
- TARP (1)
- Tail correlation (1)
- Tax Cuts and Jobs Act (1)
- Taxation (1)
- Taxation of Capital (1)
- Temperature variability (1)
- Text analysis (1)
- Textual similarity (1)
- Theory of Planned Behavior (1)
- Trading (1)
- Transparency (1)
- Twitter (1)
- Unemployment volatility (1)
- University-industry linkages (1)
- Unknown probabilities (1)
- Unternehmensanleihen (1)
- Unternehmensfinanzierung (1)
- Vehicle registration tax (1)
- Vermögenskonzentrationsrisiko (1)
- Versicherungen (1)
- Virtual reality (1)
- Volatility (1)
- Wage inertia (1)
- Welfare (1)
- Wirecard (1)
- XAI (1)
- Zero Lower Bound (1)
- Zinsrisiko der Lebensversicherung (1)
- Zinssätze (1)
- absolute loss (1)
- age (1)
- ambiguity premium (1)
- anomalies (1)
- asset management (1)
- asset purchases (1)
- attack scenarios (1)
- attention (1)
- audit industry (1)
- audit partners (1)
- audit quality (1)
- auditor rotation (1)
- automatic enrollment (1)
- automotive sector (1)
- bank (1)
- bank lending (1)
- banknotes (1)
- banks (1)
- base stations (1)
- batteries (1)
- behavioral economics (1)
- belief effect (1)
- belief estimation (1)
- belief updating (1)
- benchmarks (1)
- biased beliefs (1)
- bid-ask spread (1)
- bilateral investment treaties (1)
- bond markets (1)
- call auctions (1)
- capital markets (1)
- career development (1)
- careers (1)
- cash (1)
- catastrophe risk transfer (1)
- central banks (1)
- childcare (1)
- cliff effect (1)
- climate risk (1)
- climate-economy models (1)
- collateral (1)
- comparison (1)
- compliance behavior (1)
- confirmatory biases (1)
- conjoint analysis (1)
- consumer behavior (1)
- consumer protection (1)
- consumption (1)
- container (1)
- core (1)
- corporate bond market (1)
- corporate credit risk (1)
- corporate debt (1)
- corporate taxation (1)
- counterfactual analysis (1)
- credence goods (1)
- crises (1)
- cross-border institutions (1)
- cross-regional mobility (1)
- de-identification (1)
- default effect (1)
- default premium (1)
- delay of gratification (1)
- demographischer Wandel (1)
- designated market makers (1)
- device-to-device communication (1)
- discrimination (1)
- distance (1)
- earnings management (1)
- education (1)
- effective lower bound (1)
- employees (1)
- employment (1)
- endogenous growth (1)
- endogenous information acquisition (1)
- endorsement effect (1)
- equilibrium interest rate (1)
- erm structure of interest rates (1)
- euro area (1)
- euro crisis (1)
- executive labor market (1)
- expectation (1)
- explainability (1)
- factor timing (1)
- financial advice (1)
- financial literacy (1)
- financial market (1)
- financial risk-taking (1)
- financial well-being (1)
- financing (1)
- fintech (1)
- forecasts (1)
- forward guidance (1)
- gasoline price (1)
- global real activity (1)
- government finance (1)
- health (1)
- heterogeneous agents (1)
- high-tech (1)
- honesty (1)
- household survey (1)
- household finance (1)
- idiosynkratisches Risiko (1)
- impulse response (1)
- income distribution (1)
- inflation (1)
- influencing factors (1)
- innovation (1)
- institutional investors (1)
- interest rate risk (1)
- internet (1)
- interpretability (1)
- interregionale Mobilitätsinkongruenz (1)
- investment biases (1)
- investor behavior (1)
- investor preferences (1)
- investor segmentation (1)
- joint inference (1)
- labels (1)
- labor market entry (1)
- laboratory experiment (1)
- laboratory experiments (1)
- lending (1)
- life cycle saving (1)
- life insurance (1)
- liquidity (1)
- liquidity premium (1)
- loan guarantees (1)
- local investors (1)
- longer run (1)
- loss function (1)
- lottery-type assets (1)
- machine learning (1)
- make-up strategies (1)
- mandatory disclosure (1)
- manufacturing (1)
- marginal propensity to consume (1)
- market discipline (1)
- market price (1)
- market-based (1)
- maternal labor supply (1)
- measure of ambiguity (1)
- media polarization (1)
- median (1)
- mismatch (1)
- mobile communication (1)
- moderator (1)
- motivated beliefs (1)
- multiple equilibria (1)
- nance premium (1)
- net zero transition (1)
- news (1)
- nominal rigidity (1)
- nominee account (1)
- numerical solution method (1)
- oil inventories (1)
- opportunity (1)
- option prices (1)
- output hysteresis (1)
- pandemic (1)
- pandemic insurance (1)
- pandemics (1)
- patents (1)
- pension (1)
- performance evaluation (1)
- persistence (1)
- portfolio allocation (1)
- posterior (1)
- privacy preference (1)
- privacy setting (1)
- private Vermögensbildung (1)
- private–public partnerships (1)
- productivity differentials (1)
- productivity growth (1)
- propagation of inequality (1)
- protected values (1)
- quarter of birth (1)
- racial inequality (1)
- rare disasters (1)
- reale Auswirkungen (1)
- receivers (1)
- recession (1)
- refugees (1)
- requirements analysis (1)
- resilience (1)
- retail investors (1)
- retirement (1)
- saving (1)
- search and matching (1)
- search-matching (1)
- sektorale Vermögensdiversifizierung (1)
- sentiment (1)
- shareholder activism (1)
- shipping (1)
- skewness (1)
- social distance (1)
- sorting (1)
- source dependence (1)
- sovereign credit rating (1)
- sovereign debt (1)
- sovereign rating (1)
- spillover effects (1)
- staatliche Sozialversicherung (1)
- stochastic volatility (1)
- stock market crisis (1)
- structural VAR (1)
- structural equation modeling (1)
- substitution (1)
- supervision (1)
- supply chain (1)
- survey (1)
- sustainability (1)
- sustainable finance (1)
- synchronization (1)
- systematisches Risiko (1)
- systemisches Risiko (1)
- tax cut (1)
- tax intervention (1)
- tax policy (1)
- taxonomies (1)
- technological growth (1)
- technology diffusion (1)
- time series momentum (1)
- time-varying risk premia (1)
- trading activity (1)
- trend chasing (1)
- trend-extrapolation (1)
- unemployment (1)
- user preferences (1)
- user study (1)
- valuation ratios (1)
- wealth distribution (1)
- wealth effects (1)
- wealth inequality (1)
- willingness to forward (1)
- wireless communication (1)
- wireless networks (1)
- workforce (1)
- working hours (1)
- yield curve (1)
- yields (1)
- “Macro-regions” (1)
- financial literacy (1)
Institute
- Wirtschaftswissenschaften (238) (remove)
Advances in distributed ledger technology are leading to a growing decentralisation of financial services (“decentralised finance”) that can be offered largely without intermediation by financial institutions. An important driver for this development is the ongoing tokenisation of assets, payments and rights, which enables the digital encryption of “crypto assets” on distributed ledgers. This article elaborates the foundations and fields of application of decentralised financial services with crypto assets that could challenge the established business models of financial institutions. This trend not only affects payment systems based on controversial crypto currencies such as Bitcoin, but also exchange platforms, capital markets solutions and corporate financing. A rapidly growing ecosystem of start-ups, tech companies and financial institutions is emerging, yet this ecosystem lacks a consistent regulatory framework. The European initiative MiCA (Markets in Crypto Assets) points in the right direction but needs to be adopted soon to ensure the future competitiveness of the European financial sector.
We extend the canonical income process with persistent and transitory risk to cyclical shock distributions with left-skewness and excess kurtosis. We estimate our income process by GMM for US household data. We find countercyclical variance and procyclical skewness of persistent shocks. All shock distributions are highly leptokurtic. The tax and transfer system reduces dispersion and left-skewness. We then show that in a standard incomplete-markets life-cycle model, first, higherorder risk has sizable welfare implications, which depend on risk attitudes; second, it matters quantitatively for the welfare costs of cyclical idiosyncratic risk; third, it has non-trivial implications for self-insurance against shocks.
We consider an additively time-separable life-cycle model for the family of power period utility functions u such that u0(c) = c−θ for resistance to inter-temporal substitution of θ > 0. The utility maximization problem over life-time consumption is dynamically inconsistent for almost all specifications of effective discount factors. Pollak (1968) shows that the savings behavior of a sophisticated agent and her naive counterpart is always identical for a logarithmic utility function (i.e., for θ = 1). As an extension of Pollak’s result we show that the sophisticated agent saves a greater (smaller) fraction of her wealth in every period than her naive counterpart whenever θ > 1 (θ < 1) irrespective of the specification of discount factors. We further show that this finding extends to an environment with risky returns and dynamically inconsistent Epstein-Zin-Weil preferences.
Using a structural life-cycle model and data on school visits from Safegraph and school closures from Burbio, we quantify the heterogeneous impact of school closures during the Corona crisis on children affected at different ages and coming from households with different parental characteristics. Our data suggests that secondary schools were closed for in-person learning for longer periods than elementary schools (implying that younger children experienced less school closures than older children), and that private schools experienced shorter closures than public schools, and schools in poorer U.S. counties experienced shorter school closures. We then extend the structural life cycle model of private and public schooling investments studied in Fuchs-Schündeln, Krueger, Ludwig, and Popova (2021) to include the choice of parents whether to send their children to private schools, empirically discipline it with data on parental investments from the PSID, and then feed into the model the school closure measures from our empirical analysis to quantify the long-run consequences of the Covid-19 school closures on the cohorts of children currently in school. Future earnings- and welfare losses are largest for children that started public secondary schools at the onset of the Covid-19 crisis. Comparing children from the topto children from the bottom quartile of the income distribution, welfare losses are ca. 0.8 percentage points larger for the poorer children if school closures were unrelated to income. Accounting for the longer school closures in richer counties reduces this gap by about 1/3. A policy intervention that extends schools by 3 months (6 weeks in the next two summers) generates significant welfare gains for the children and raises future tax revenues approximately sufficient to pay for the cost of this schooling expansion.
Using a structural life-cycle model, we quantify the heterogeneous impact of school closures during the Corona crisis on children affected at different ages and coming from households with different parental characteristics. In the model, public investment through schooling is combined with parental time and resource investments in the production of child human capital at different stages in the children’s development process. We quantitatively characterize the long-term consequences from a Covid-19 induced loss of schooling, and find average losses in the present discounted value of lifetime earnings of the affected children of close to 1%, as well as welfare losses equivalent to about 0.6% of permanent consumption. Due to self-productivity in the human capital production function, skill attainment at a younger stage of the life cycle raises skill attainment at later stages, and thus younger children are hurt more by the school closures than older children. We find that parental reactions reduce the negative impact of the school closures, but do not fully offset it. The negative impact of the crisis on children’s welfare is especially severe for those with parents with low educational attainment and low assets. The school closures themselves are primarily responsible for the negative impact of the Covid-19 shock on the long-run welfare of the children, with the pandemic-induced income shock to parents playing a secondary role.
We characterize the optimal linear tax on capital in an Overlapping Generations model with two period lived households facing uninsurable idiosyncratic labor income risk. The Ramsey government internalizes the general equilibrium effects of private precautionary saving on factor prices and taxes capital unless the weight on future generations in the social welfare function is sufficiently high. For logarithmic utility a complete analytical solution of the Ramsey problem exhibits an optimal aggregate saving rate that is independent of income risk, whereas the optimal time-invariant tax on capital implementing this saving rate is increasing in income risk. The optimal saving rate is constant along the transition and its sign depends on the magnitude of risk and on the Pareto weight of future generations. If the Ramsey tax rate that maximizes steady state utility is positive, then implementing this tax rate permanently induces a Pareto-improving transition even if the initial equilibrium capital stock is below the golden rule.
Market risks account for an integral part of life insurers' risk profiles. This paper explores the market risk sensitivities of insurers in two large life insurance markets, namely the U.S. and Europe. Based on panel regression models and daily market data from 2012 to 2018, we analyze the reaction of insurers' stock returns to changes in interest rates and CDS spreads of sovereign counterparties. We find that the influence of interest rate movements on stock returns is more than 50% larger for U.S. than for European life insurers. Falling interest rates reduce stock returns in particular for less solvent firms, insurers with a high share of life insurance reserves and unit-linked insurers. Moreover, life insurers' sensitivity to interest rate changes is seven times larger than their sensitivity towards CDS spreads. Only European insurers significantly suffer from rising CDS spreads, whereas U.S. insurers are immunized against increasing sovereign default probabilities.
Life insurance convexity
(2021)
Life insurers massively sell savings contracts with surrender options which allow policyholders to withdraw a guaranteed amount before maturity. These options move toward the money when interest rates rise. Using data on German life insurers, we estimate that a 1 percentage point increase in interest rates raises surrender rates by 17 basis points. We quantify the resulting liquidity risk in a calibrated model of surrender decisions and insurance cash flows. Simulations predict that surrender options can force insurers to sell up to 3% of their assets, depressing asset prices by 90 basis points. The effect is amplified by the duration of insurers' investments, and its impact on the term structure of interest rates depends on life insurers' investment strategy.
Tail-correlation matrices are an important tool for aggregating risk measurements across risk categories, asset classes and/or business segments. This paper demonstrates that traditional tail-correlation matrices—which are conventionally assumed to have ones on the diagonal—can lead to substantial biases of the aggregate risk measurement’s sensitivities with respect to risk exposures. Due to these biases, decision-makers receive an odd view of the effects of portfolio changes and may be unable to identify the optimal portfolio from a risk-return perspective. To overcome these issues, we introduce the “sensitivity-implied tail-correlation matrix”. The proposed tail-correlation matrix allows for a simple deterministic risk aggregation approach which reasonably approximates the true aggregate risk measurement according to the complete multivariate risk distribution. Numerical examples demonstrate that our approach is a better basis for portfolio optimization than the Value-at-Risk implied tail-correlation matrix, especially if the calibration portfolio (or current portfolio) deviates from the optimal portfolio.
Historical evidence like the global financial crisis from 2007-09 highlights that sector concentration risk can play an important role for the solvency of insurers. However, current microprudential frameworks like the US RBC framework and Solvency II consider only name concentration risk explicitly in their solvency capital requirements for asset concentration risk and neglect sector concentration risk. We show by means of US insurers’ asset holdings from 2009 to 2018 that substantial sectoral asset concentrations exist in the financial, public and real estate sector, and find indicative evidence for a sectoral search for yield behavior. Based on a theoretical solvency capital allocation scheme, we demonstrate that the current regulatory approaches can lead to inappropriate and biased levels of solvency capital for asset concentration risk, and should be revised. Our findings have also important implications on the ongoing discussion of asset concentration risk in the context of macroprudential insurance regulation.
This paper documents that the bond investments of insurance companies transmit shocks from insurance markets to the real economy. Liquidity windfalls from household insurance purchases increase insurers’ demand for corporate bonds. Exploiting the fact that insurers persistently invest in a small subset of firms for identification, I show that these increases in bond demand raise bond prices and lower firms’ funding costs. In response, firms issue more bonds, especially when their bond underwriters are well connected with investors. Firms use the proceeds to raise investment rather than equity payouts. The results emphasize the significant impact of investor demand on firms’ financing and investment activities.
I measure the effects of workers’ mobility across regions of different productivity through the lens of a search and matching model with heterogeneous workers and firms estimated with administrative data. In an application to Italy, I find that reallocation of workers to the most productive region boosts productivity at the country level but amplifies differentials across regions. Employment rates decline as migrants foster job competition, and inequality between workers doubles in less productive areas since displacement is particularly severe for low-skill workers. Migration does affect mismatch: mobility favors co-location of agents with similar productivity but within-region rank correlation declines in the most productive region. I show that worker-firm complementarities in production account for 33% of the productivity gains. Place-based programs directed to firms, like incentives for hiring unemployed or creating high productivity jobs, raise employment rates and reduce the gaps in productivity across regions. In contrast, subsidies to attract high-skill workers in the South have limited effects.
Nations are imposing unprecedented measures at a large scale to contain the spread of the COVID-19 pandemic. While recent studies show that non-pharmaceutical intervention measures such as lockdowns may have mitigated the spread of COVID-19, those measures also lead to substantial economic and social costs, and might limit exposure to ultraviolet-B radiation (UVB). Emerging observational evidence indicates the protective role of UVB and vitamin D in reducing the severity and mortality of COVID-19 deaths. This observational study empirically outlines the protective roles of lockdown and UVB exposure as measured by the ultraviolet index (UVI). Specifically, we examine whether the severity of lockdown is associated with a reduction in the protective role of UVB exposure. We use a log-linear fixed-effects model on a panel dataset of secondary data of 155 countries from 22 January 2020 until 7 October 2020 (n = 29,327). We use the cumulative number of COVID-19 deaths as the dependent variable and isolate the mitigating influence of lockdown severity on the association between UVI and growth rates of COVID-19 deaths from time-constant country-specific and time-varying country-specific potentially confounding factors. After controlling for time-constant and time-varying factors, we find that a unit increase in UVI and lockdown severity are independently associated with − 0.85 percentage points (p.p) and − 4.7 p.p decline in COVID-19 deaths growth rate, indicating their respective protective roles. The change of UVI over time is typically large (e.g., on average, UVI in New York City increases up to 6 units between January until June), indicating that the protective role of UVI might be substantial. However, the widely utilized and least severe lockdown (governmental recommendation to not leave the house) is associated with the mitigation of the protective role of UVI by 81% (0.76 p.p), which indicates a downside risk associated with its widespread use. We find that lockdown severity and UVI are independently associated with a slowdown in the daily growth rates of cumulative COVID-19 deaths. However, we find evidence that an increase in lockdown severity is associated with significant mitigation in the protective role of UVI in reducing COVID-19 deaths. Our results suggest that lockdowns in conjunction with adequate exposure to UVB radiation might have even reduced the number of COVID-19 deaths more strongly than lockdowns alone. For example, we estimate that there would be 11% fewer deaths on average with sufficient UVB exposure during the period people were recommended not to leave their house. Therefore, our study outlines the importance of considering UVB exposure, especially while implementing lockdowns, and could inspire further clinical studies that may support policy decision-making in countries imposing such measures.
By computing a volatility index (CVX) from cryptocurrency option prices, we analyze this market’s expectation of future volatility. Our method addresses the challenging liquidity environment of this young asset class and allows us to extract stable market implied volatilities. Two alternative methods are considered to compute volatilities from granular intra-day cryptocurrency options data, which spans over the COVID-19 pandemic period. CVX data therefore capture ‘normal’ market dynamics as well as distress and recovery periods. The methods yield two cointegrated index series, where the corresponding error correction model can be used as an indicator for market implied tail-risk. Comparing our CVX to existing volatility benchmarks for traditional asset classes, such as VIX (equity) or GVX (gold), confirms that cryptocurrency volatility dynamics are often disconnected from traditional markets, yet, share common shocks.
We study the role mutual funds play in the recovery from fast intraday crashes based on data from the National Stock Exchange of India for a single large stock. During normal times, trading activity and liquidity provision by mutual funds is negligible compared to other traders at around 4% of overall activity. Nevertheless, for the two intraday market-wide crashes in our sample, price recovery took place only after mutual funds moved in. Market stability may require the presence of well-capitalized standby liquidity providers for recovery from fast crashes.
This paper explores entrepreneurs’ initially intended exit strategies and compares them to their final exit paths using an inductive approach that builds on the grounded theory methodology. Our data shows that initially intended and final exit strategies differ among entrepreneurs. Two groups of entrepreneurs emerged from our data. The first group comprises entrepreneurs who financed their firms through equity investors. The second group is made up of entrepreneurs who financed their businesses solely with their own equities. Our data shows that the first group originally intended a financial harvest exit strategy and settled with this harvest exit strategy. The second group initially intended a stewardship exit strategy but did not succeed. We used the theory of planned behavior and the behavioral agency model to analyze our data. By examining our results from these two theoretical perspectives, our study explains how entrepreneurs’ exit intentions lead to their actual exit strategies.
This article uses information from two data sources, Compustat and Nexis Uni, and textual analysis to measure and validate the brand focus and customer focus of 109 U.S. listed retailers. The results from an analysis of their 853 earnings calls in 2010 and 2018 outline that on average, both foci increased over time. Although both foci vary substantially, brand focus varies more widely across retailers than their customer focus. Both foci are independent of each other. Specialty retailers have the highest brand focus, and internet & direct marketing retailers have the highest customer focus. A positive correlation exists between a retailer’s customer focus and its profitability, but not between a retailer’s brand focus and its profitability. The authors use the results to generate a research agenda that can direct future research in further systematically exploring firms’ brand and customer focus.
Small businesses face major challenges to becoming more innovative. These challenges are particularly prevalent in emerging economies where high uncertainties are a barrier to innovation. We know from previous studies that linkages to universities, on the one hand, and public procurement, on the other, support large and innovative firms in their efforts to become more innovative. However, we do not know whether these positive effects also hold true for small businesses. In this paper, we focus on how policy strategies reducing information, market and financial uncertainties shape small businesses’ innovation in China. Based on a sample of 926 small businesses derived from the World Bank Enterprises Survey in China (2012), we find that university-industry linkages enhance innovation, though only when it comes to minor forms of innovation. In line with the resource-based view of the firm, this effect is stronger for small businesses with higher capabilities. Moreover, we show that bidding for or delivering contracts to public sector clients has a positive effect on innovation, and in particular of major forms of innovation. In the bidding selection process, private firms and firms with higher capabilities are selected. Our findings show that both policy strategies have enhanced innovation, though with different effects on the degree of novelty. We attribute this finding to the different degrees of uncertainties they address.
Vulnerability comes, according to Orio Giarini, with two risks: human-made risks, also called entrepreneurial risks, and natural or pure risks such as accidents and earthquakes. Both types of risk are growing in dimension and are increasingly interrelated. To control the vulnerability, sophisticated insurance products are called for. Here, mutual insurance is relevant, in particular when risks are large, probabilities uncertain or unknown, and events interrelated or correlated. In this paper the following three examples are discussed and the advantages of mutual insurance are shown: unknown probabilities connected with unforeseeable events, correlated risks and macroeconomic or demographic risks.
This study explores the implications of rising markups for optimal Mirrleesian income and profit taxation. Using a stylized model with two individuals, the main forces shaping welfare-optimal policies are analytically characterized. Although a higher profit tax has redistributive benefits, it adversely affects market competition, leading to a greater equilibrium cost-of-living. Rising markups directly contribute to a decline in optimal marginal taxes on labor income. The optimal policy response to higher markups includes increasingly relying on the profit tax to fund redistribution. Declining optimal marginal income taxes assists the redistributive function of the profit tax by contributing to the expansion of the profit tax base. This response alone considerably increases the equilibrium cost-of-living. Nevertheless, a majority of the individuals become better off with the optimal policy. If it is not possible to tax profits optimally, due, for example, to profit shifting, increasing redistribution via income taxes is not optimal; every individual is worse off relative to the scenario with optimal profit taxation.
Nowadays, digitalization has an immense impact on the landscape of jobs. This technological revolution creates new industries and professions, promises greater efficiency and improves the quality of working life. However, emerging technologies such as robotics and artificial intelligence (AI) are reducing human intervention, thus advancing automation and eliminating thousands of jobs and whole occupational images. To prepare employees for the changing demands of work, adequate and timely training of the workforce and real-time support of workers in new positions is necessary. Therefore, it is investigated whether user-oriented technologies, such as augmented reality (AR) and virtual reality (VR) can be applied “on-the-job” for such training and support—also known as intelligence augmentation (IA). To address this problem, this work synthesizes results of a systematic literature review as well as a practically oriented search on augmented reality and virtual reality use cases within the IA context. A total of 150 papers and use cases are analyzed to identify suitable areas of application in which it is possible to enhance employees' capabilities. The results of both, theoretical and practical work, show that VR is primarily used to train employees without prior knowledge, whereas AR is used to expand the scope of competence of individuals in their field of expertise while on the job. Based on these results, a framework is derived which provides practitioners with guidelines as to how AR or VR can support workers at their job so that they can keep up with anticipated skill demands. Furthermore, it shows for which application areas AR or VR can provide workers with sufficient training to learn new job tasks. By that, this research provides practical recommendations in order to accompany the imminent distortions caused by AI and similar technologies and to alleviate associated negative effects on the German labor market.
We investigate how financial literacy shapes older Americans’ demand for financial advice. Using an experimental module fielded in the Health and Retirement Study, we show that financial literacy strongly improves the quality but not the quantity of financial advice sought. In particular, more financially literate people seek financial help from professionals. This effect is more pronounced among older people and those with more wealth and more complex financial positions. Our analysis result implies that financial literacy and financial advisory services are complementary with, rather than substitutes for, each other.
Artificial Intelligence (AI) and Machine Learning (ML) are currently hot topics in industry and business practice, while management-oriented research disciplines seem reluctant to adopt these sophisticated data analytics methods as research instruments. Even the Information Systems (IS) discipline with its close connections to Computer Science seems to be conservative when conducting empirical research endeavors. To assess the magnitude of the problem and to understand its causes, we conducted a bibliographic review on publications in high-level IS journals. We reviewed 1,838 articles that matched corresponding keyword-queries in journals from the AIS senior scholar basket, Electronic Markets and Decision Support Systems (Ranked B). In addition, we conducted a survey among IS researchers (N = 110). Based on the findings from our sample we evaluate different potential causes that could explain why ML methods are rather underrepresented in top-tier journals and discuss how the IS discipline could successfully incorporate ML methods in research undertakings.
Tail-correlation matrices are an important tool for aggregating risk measurements across risk categories, asset classes and/or business segments. This paper demonstrates that traditional tail-correlation matrices—which are conventionally assumed to have ones on the diagonal—can lead to substantial biases of the aggregate risk measurement’s sensitivities with respect to risk exposures. Due to these biases, decision-makers receive an odd view of the effects of portfolio changes and may be unable to identify the optimal portfolio from a risk-return perspective. To overcome these issues, we introduce the “sensitivity-implied tail-correlation matrix”. The proposed tail-correlation matrix allows for a simple deterministic risk aggregation approach which reasonably approximates the true aggregate risk measurement according to the complete multivariate risk distribution. Numerical examples demonstrate that our approach is a better basis for portfolio optimization than the Value-at-Risk implied tail-correlation matrix, especially if the calibration portfolio (or current portfolio) deviates from the optimal portfolio.
We empirically examine how systemic risk in the banking sector leads to correlated risk in office markets of global financial centers. In so doing, we compute an aggregated measure of systemic risk in financial centers as the cumulated expected capital shortfall of local financial institutions. Our identification strategy is based on a double counterfactual approach by comparing normal with financial distress periods as well as office with retail markets. We find that office market interconnectedness arises from systemic risk during financial turmoil periods. Office market performance in a financial center is affected by returns of systemically linked financial center office markets only during a systemic banking crisis. In contrast, there is no evidence of correlated risk during normal times and among the within-city counterfactual retail sector. The decline in office market returns during a banking crisis is larger in financial centers compared to non-financial centers.
Having a gatekeeper position in a collaborative network offers firms great potential to gain competitive advantages. However, it is not well understood what kind of collaborations are associated with such a position. Conceptually grounded in social network theory, this study draws on the resource-based view and the relational factors view to investigate which types of collaboration characterize firms that are in a gatekeeper position, which ultimately could improve firm performance in subsequent periods. The empirical analysis utilizes a unique longitudinal data set to examine dynamic network formation. We used a data crawling approach to reconstruct collaboration networks among the 500 largest companies in Germany over nine years and matched these networks with performance data. The results indicate that firms in gatekeeper positions often engage in medium-intensity collaborations and less likely weak-intensity collaborations. Strong-intensity collaborations are not related to the likelihood of being a gatekeeper. Our study further reveals that a firm's knowledge base is an important moderator and that this knowledge base can increase the benefits of having a gatekeeper position in terms of firm performance.
This paper analyzes the scope of the private market for pandemic insurance. We develop a framework that explains theoretically how the equilibrium price of pandemic insurance depends on accumulation risk, covariance between pandemic claims and other claims, and covariance between pandemic claims and the stock market performance. Using the natural catastrophe (NatCat) insurance market as a laboratory, we estimate the relationship between the insurance price markup and the tail characteristics of the loss distribution. Then, by using the high-frequency data tracking the economic impact of the COVID-19 pandemic in the United States, we calibrate the loss distribution of a hypothetical insurance contract designed to alleviate the impact of the pandemic on small businesses. The pandemic insurance contract price markup corresponds to the top 20% markup observed in the NatCat insurance market. Then we analyze an intertemporal risk-sharing scheme that can reduce the expected shortfall of the loss distribution by 50%.
The current economic landscape is complex and globalized, and it imposes on individuals the responsibility for their own financial security. This situation has been intensified by the COVID-19 crisis, since short-time work and layoffs significantly limit the availability of financial resources for individuals. Due to the long duration of the lockdown, these challenges will have a long-term impact and affect the financial well-being of many citizens. Moreover, it can be assumed that the consequences of this crisis will once again particularly affect groups of people who have already frequently been identified as having low financial literacy. Financial literacy is therefore an important target for educational measures and interventions. However, it cannot be considered in isolation but must take into account the many potential factors that influence financial literacy alone or in combination. These include personality traits and socio-demographic factors as well as the (in)ability to defer gratification. Against this background, individualized support offers can be made. With this in mind, in the first step of this study, we analyze the complex interaction of personality traits, socio-demographic factors, the (in-)ability to delay gratification, and financial literacy. In the second step, we differentiate the identified effects regarding different groups to identify moderating effects, which, in turn, allow conclusions to be drawn about the need for individualized interventions. The results show that gender and educational background moderate the effects occurring between self-reported financial literacy, financial learning opportunities, delay of gratification, and financial literacy.
Sample-based longitudinal discrete choice experiments: preferences for electric vehicles over time
(2021)
Discrete choice experiments have emerged as the state-of-the-art method for measuring preferences, but they are mostly used in cross-sectional studies. In seeking to make them applicable for longitudinal studies, our study addresses two common challenges: working with different respondents and handling altering attributes. We propose a sample-based longitudinal discrete choice experiment in combination with a covariate-extended hierarchical Bayes logit estimator that allows one to test the statistical significance of changes. We showcase this method’s use in studies about preferences for electric vehicles over six years and empirically observe that preferences develop in an unpredictable, non-monotonous way. We also find that inspecting only the absolute differences in preferences between samples may result in misleading inferences. Moreover, surveying a new sample produced similar results as asking the same sample of respondents over time. Finally, we experimentally test how adding or removing an attribute affects preferences for the other attributes.
Crowdfunding platforms offer project initiators the opportunity to acquire funds from the Internet crowd and, therefore, have become a valuable alternative to traditional sources of funding. However, some processes on crowdfunding platforms cause undesirable external effects that influence the funding success of projects. In this context, we focus on the phenomenon of project overfunding. Massively overfunded projects have been discussed to overshadow other crowdfunding projects which in turn receive less funding. We propose a funding redistribution mechanism to internalize these overfunding externalities and to improve overall funding results. To evaluate this concept, we develop and deploy an agent-based model (ABM). This ABM is based on a multi-attribute decision-making approach and is suitable to simulate the dynamic funding processes on a crowdfunding platform. Our evaluation provides evidence that possible modifications of the crowdfunding mechanisms bear the chance to optimize funding results and to alleviate existing flaws.
Correction to: Computational Economics https://doi.org/10.1007/s10614-020-10061-x
The original publication has been updated. In the original publication of this article, under the Introduction heading section, the corrections to the second paragraph’s inline equation were not incorporated. The author’s additional corrections have also been incorporated. The publisher apologizes for the error made during production.
India has recorded 142,186 deaths over 36 administrative regions placing India third in the world after the US and Brazil for COVID-19 deaths as of 12 December 2020. Studies indicate that south-west monsoon season plays a role in the dynamics of contagious diseases, which tend to peak post-monsoon season. Recent studies show that vitamin D and its primary source Ultraviolet-B (UVB) radiation may play a protective role in mitigating COVID-19 deaths. However, the combined roles of the monsoon season and UVB radiation in COVID-19 in India remain still unclear. In this observational study, we empirically study the respective roles of monsoon season and UVB radiation, whilst further exploring, whether the monsoon season negatively impacts the protective role of UVB radiation in COVID-19 deaths in India. We use a log-linear Mundlak model to a panel dataset of 36 administrative regions in India from 14 March 2020–19 November 2020 (n = 6751). We use the cumulative COVID-19 deaths as the dependent variable. We isolate the association of monsoon season and UVB radiation as measured by Ultraviolet Index (UVI) from other confounding time-constant and time-varying region-specific factors. After controlling for various confounding factors, we observe that a unit increase in UVI and the monsoon season are separately associated with 1.2 percentage points and 7.5 percentage points decline in growth rates of COVID-19 deaths in the long run. These associations translate into substantial relative changes. For example, a permanent unit increase of UVI is associated with a decrease of growth rates of COVID-19 deaths by 33% (= − 1.2 percentage points) However, the monsoon season, mitigates the protective role of UVI by 77% (0.92 percentage points). Our results indicate a protective role of UVB radiation in mitigating COVID-19 deaths in India. Furthermore, we find evidence that the monsoon season is associated with a significant reduction in the protective role of UVB radiation. Our study outlines the roles of the monsoon season and UVB radiation in COVID-19 in India and supports health-related policy decision making in India.
Consider two independent random walks. By chance, there will be spells of association between them where the two processes move in the same direction, or in opposite direction. We compute the probabilities of the length of the longest spell of such random association for a given sample size, and discuss measures like mean and mode of the exact distributions. We observe that long spells (relative to small sample sizes) of random association occur frequently, which explains why nonsense correlation between short independent random walks is the rule rather than the exception. The exact figures are compared with approximations. Our finite sample analysis as well as the approximations rely on two older results popularized by Révész (Stat Pap 31:95–101, 1990, Statistical Papers). Moreover, we consider spells of association between correlated random walks. Approximate probabilities are compared with finite sample Monte Carlo results.
Vehicle registrations have been shown to strongly react to tax reforms aimed at reducing CO2 emissions from passengers’ cars, but are the effects equally strong for positive and negative tax changes? The literature on asymmetric reactions to price and tax changes has documented asymmetries for everyday goods but has not yet considered durables. We leverage multiple vehicle registration tax (VRT) reforms in Norway and estimate their impact on within car-model substitutions. We estimate stronger effects for cars receiving tax cuts and rebates than for those affected by tax increases. The corresponding estimated elasticity is − 1.99 for VRT decreases and 0.77 for increases. As consumers may also substitute across car models, our estimates represent a lower bound.
This paper uses historical monthly temperature level data for a panel of 114 countries to identify the effects of within year temperature level variability on productivity growth in five different macro regions, i.e., (1) Africa, (2) Asia, (3) Europe, (4) North America and (5) South America. We find two primary results. First, higher intra-annual temperature variability reduces (increases) productivity in Europe and North America (Asia). Second, higher intra-annual temperature variability has no significant effects on productivity in Africa and South America. Additional empirical tests indicate also the following: (1) rising intra-annual temperature variability reduces productivity (even thought less significantly)in both tropical and non-tropical regions, (2) inter-annual temperature variability reduces (increases) productivity in North America (Europe) and (3) winter and summer inter-annual temperature variability generates a drop in productivity in both Europe and North America. Taken together, these findings indicate that temperature variability shocks tend to have stronger adverse economic effects among richer economies. In a production economy featuring long-run productivity and temperature volatility shocks, we quantify these negative impacts and find welfare losses of 2.9% (1%) in Europe (North America).
Solving High-Dimensional Dynamic Portfolio Choice Models with Hierarchical B-Splines on Sparse Grids
(2021)
Discrete time dynamic programming to solve dynamic portfolio choice models has three immanent issues: firstly, the curse of dimensionality prohibits more than a handful of continuous states. Secondly, in higher dimensions, even regular sparse grid discretizations need too many grid points for sufficiently accurate approximations of the value function. Thirdly, the models usually require continuous control variables, and hence gradient-based optimization with smooth approximations of the value function is necessary to obtain accurate solutions to the optimization problem. For the first time, we enable accurate and fast numerical solutions with gradient-based optimization while still allowing for spatial adaptivity using hierarchical B-splines on sparse grids. When compared to the standard linear bases on sparse grids or finite difference approximations of the gradient, our approach saves an order of magnitude in total computational complexity for a representative dynamic portfolio choice model with varying state space dimensionality, stochastic sample space, and choice variables.
The mobile games business is an ever-increasing sub-sector of the entertainment industry. Due to its high profitability but also high risk and competitive atmosphere, game publishers need to develop strategies that allow them to release new products at a high rate, but without compromising the already short lifespan of the firms' existing games. Successful game publishers must enlarge their user base by continually releasing new and entertaining games, while simultaneously motivating the current user base of existing games to remain active for more extended periods. Since the core-component reuse strategy has proven successful in other software products, this study investigates the advantages and drawbacks of this strategy in mobile games. Drawing on the widely accepted Product Life Cycle concept, the study investigates whether the introduction of a new mobile game built with core-components of an existing mobile game curtails the incumbent's product life cycle. Based on real and granular data on the gaming activity of a popular mobile game, the authors find that by promoting multi-homing (i.e., by smartly interlinking the incumbent and new product with each other so that users start consuming both games in parallel), the core-component reuse strategy can prolong the lifespan of the incumbent game.
Digital wealth and its necessary regulation have gained prominence in recent years. The European Commission has published several documents and policy proposals relating, directly or indirectly, to the data economy. A data economy can be defined as an ecosystem of different types of market players collaborating to ensure that data is accessible and usable in order to extract value from data through, for example, creating a variety of applications with great potential to improve daily life. The value of data can increase from EUR 257 billion (1.85 of EU Gross Domestic Product (GDP)) to EUR 643 billion by 2020 (3.17% of EU GDP), according to the EU Commission. The legal implications of the increasing value of the data economy are clear; hence the need to address the challenges presented by its legal regulation.
The health and genetic data of deceased people are a particularly important asset in the field of biomedical research. However, in practice, using them is compli- cated, as the legal framework that should regulate their use has not been fully developed yet. The General Data Protection Regulation (GDPR) is not applicable to such data and the Member States have not been able to agree on an alternative regulation. Recently, normative models have been proposed in an attempt to face this issue. The most well- known of these is posthumous medical data donation (PMDD). This proposal supports an opt-in donation system of health data for research purposes. In this article, we argue that PMDD is not a useful model for addressing the issue at hand, as it does not consider that some of these data (the genetic data) may be the personal data of the living relatives of the deceased. Furthermore, we find the reasons supporting an opt-in model less convincing than those that vouch for alternative systems. Indeed, we propose a normative framework that is based on the opt-out system for non-personal data combined with the application of the GDPR to the relatives’ personal data.
The quality of life: protecting non-personal interests and non-personal data in the age of big data
(2021)
Under the current legal paradigm, the rights to privacy and data protection provide natural persons with subjective rights to protect their private interests, such as related to human dignity, individual autonomy and personal freedom. In principle, when data processing is based on non-personal or aggregated data or when such data pro- cesses have an impact on societal, rather than individual interests, citizens cannot rely on these rights. Although this legal paradigm has worked well for decades, it is increasingly put under pressure because Big Data processes are typically based indis- criminate rather than targeted data collection, because the high volumes of data are processed on an aggregated rather than a personal level and because the policies and decisions based on the statistical correlations found through algorithmic analytics are mostly addressed at large groups or society as a whole rather than specific individuals. This means that large parts of the data-driven environment are currently left unregu- lated and that individuals are often unable to rely on their fundamental rights when addressing the more systemic effects of Big Data processes. This article will discuss how this tension might be relieved by turning to the notion ‘quality of life’, which has the potential of becoming the new standard for the European Court of Human Rights (ECtHR) when dealing with privacy related cases.
Ownership of databases: personal data protection and intellectual property rights on databases
(2021)
When we think on initiatives on access to and reuse of data, we must consider both the European Intellectual Property Law and the General Data Protection Regulation (GDPR). The first one provides a special intellectual property (IP) right – the sui generis right – for those makers that made a substantial investment when creating the database, whether it contains personal or non-personal data. That substantial investment can be made by just one person, but, in many cases, it is the result of the activities of many people and/or some undertakings processing and aggregating data. In the modern digital economy, data are being dubbed the ‘new oil’ and the sui generis right might be con- sidered a right to control any access to the database, thus having an undeniable relevance. Besides, there are still important inconsistences between IP Law and the GDPR, which must be removed by the European legislator. The genuine and free consent of the data subject for the use of his/her data must remain the first step of the legal analysis.
Commercialization of consumers’ personal data in the digital economy poses serious, both conceptual and practical, challenges to the traditional approach of European Union (EU) Consumer Law. This article argues that mass-spread, automated, algorithmic decision-making casts doubt on the foundational paradigm of EU consumer law: consent and autonomy. Moreover, it poses threats of discrimination and under- mining of consumer privacy. It is argued that the recent legislative reaction by the EU Commission, in the form of the ‘New Deal for Consumers’, was a step in the right direction, but fell short due to its continued reliance on consent, autonomy and failure to adequately protect consumers from indirect discrimination. It is posited that a focus on creating a contracting landscape where the consumer may be properly informed in material respects is required, which in turn necessitates blending the approaches of competition, consumer protection and data protection laws.
Public kindergarten, maternal labor supply, and earnings in the longer run: too little too late?
(2021)
By facilitating early re-entry to the labor market after childbirth, public kindergarten might positively affect maternal human capital and labor market outcomes: Are such effects long-lasting? Can we rely on between-individuals differences in quarter of birth to identify them? I isolate the effects of interest from spurious associations through difference-in-difference, exploiting across-states and over-time variation in public kindergarten eligibility regulations in the United States. The estimates suggest a very limited impact in the first year, and no longer-run impacts. Even in states where it does not affect kindergarten eligibility, quarter of birth is strongly and significantly correlated with maternal outcomes.
The term structure of interest rates is crucial for the transmission of monetary policy to financial markets and the macroeconomy. Disentangling the impact of monetary policy on the components of interest rates, expected short rates, and term premia is essential to understanding this channel. To accomplish this, we provide a quantitative structural model with endogenous, time-varying term premia that are consistent with empirical findings. News about future policy, in contrast to unexpected policy shocks, has quantitatively significant effects on term premia along the entire term structure. This provides a plausible explanation for partly contradictory estimates in the empirical literature.
Contemporary information systems make widespread use of artificial intelligence (AI). While AI offers various benefits, it can also be subject to systematic errors, whereby people from certain groups (defined by gender, age, or other sensitive attributes) experience disparate outcomes. In many AI applications, disparate outcomes confront businesses and organizations with legal and reputational risks. To address these, technologies for so-called “AI fairness” have been developed, by which AI is adapted such that mathematical constraints for fairness are fulfilled. However, the financial costs of AI fairness are unclear. Therefore, the authors develop AI fairness for a real-world use case from e-commerce, where coupons are allocated according to clickstream sessions. In their setting, the authors find that AI fairness successfully manages to adhere to fairness requirements, while reducing the overall prediction performance only slightly. However, they find that AI fairness also results in an increase in financial cost. Thus, in this way the paper’s findings contribute to designing information systems on the basis of AI fairness.
Strict environmental regulation may deter foreign direct investment (FDI). The paper develops the hypothesis that regulation predominantly discourages FDI that is conducted as Greenfield investment rather than mergers and acquisitions (M&A). The hypothesis is tested with German firm-level FDI data. Empirically, stricter regulation reduces new Greenfield projects in polluting industries, but indeed has a much smaller impact on the number of M&As. This significant difference is compatible with the fact that existing operations often benefit from grandfathering rules, which provide softer regulation for pre-exisiting plants, and with the expectation that for M&As part of the regulation is capitalized in the purchase price. The heterogeneous effects help explaining mixed results in previous studies that have neglected the mode of entry.
Master of science in international economics and economic policy : guidelines winter term 2021/22
(2021)
We examine how often and why some audit partners rotate off client engagements before the end of the maximum five-year cycle period. Specifically, we investigate whether audit quality issues play a role for engagement partners and clients to separate prematurely. For a sample of about 4,000 within-audit firm partner rotations for Big 6 clients over the 2008 to 2014 period, we find that client characteristics such as financial leverage or performance have little explanatory power. In contrast, severe audit quality issues such as financial restatements or PCAOB inspection findings are associated with early partner rotations. These associations are more pronounced for early rotations that are not explained by scheduled retirements, promotions, or temporary leaves as well as for large clients and when partners are less experienced. We also find that female partners have a higher likelihood of early rotation for audit quality reasons. Early rotations have career consequences. Partners are assigned to fewer SEC issuer clients, manage fewer audit hours, receive lower partner ratings, and are more likely to be internally inspected after being rotated early. Our results suggest that audit quality concerns are an important factor for early partner rotations with ensuing negative career consequences for partners’ client assignments and management responsibilities.
We investigate the impact of reporting regulation on corporate innovation. Exploiting thresholds in Europe’s regulation and a major enforcement reform in Germany, we find that forcing firms to publicly disclose their financial statements discourages innovative activities. Our evidence suggests that reporting regulation has significant real effects by imposing proprietary costs on innovative firms, which in turn diminish their incentives to innovate. At the industry level, positive information spillovers (e.g., to competitors, suppliers, and customers) appear insufficient to compensate the negative direct effect on the prevalence of innovative activity. The spillovers instead appear to concentrate innovation among a few large firms in a given industry. Thus, financial reporting regulation has important aggregate and distributional effects on corporate innovation.
This paper studies the consumption response to an increase in the domestic value of foreign currency household debt during a large depreciation. We use detailed consumption survey data that follows households for four years around Hungary’s 2008 currency crisis. We find that, relative to similar local currency debtors, foreign currency debtors reduce consumption approximately one-for-one with increased debt service, suggesting a role for liquidity constraints. We document a variety of margins of adjustment to the shock. Foreign currency debtors reduce both the quantity and quality of expenditures, consistent with nonhomothetic preferences and “flight from quality.” We find no effect on overall household labor supply, consistent with a weak wealth effect on labor supply. However, a small subset of households adjusts labor supply toward foreign income streams. Affected households also boost home pro- duction, suggesting a shift in consumption from money-intensive to time-intensive goods.
We show that the COVID-19 pandemic triggered a surge in the elasticity of non-financial corporate to sovereign credit default swaps in core EU countries, characterized by strong fiscal capacity. For peripheral countries with lower budgetary slackness, the pandemic had essentially no impact on such elasticity. This evidence is consistent with the disaster-induced repricing of government support, which we model through a rare-disaster asset pricing framework with bailout guarantees and defaultable public debt. The model implies that risk-adjusted guarantees in the core were 2.6 times those in the periphery, suggesting that fiscal capacity buffers provide relief to firms’ financing costs.
We analyze the impact of decreases in available lending resources on quantitative and qualita- tive dimensions of firms’ patenting activities. We thereby make use of the European Banking Authority?s capital exercise to carve out the causal effect of bank lending on firm innovation. In order to do so we combine various datasets to derive information on firms’ financials, their patenting behaviors, as well as their relationships with their lenders. Building on this self- generated dataset, we provide support for the “less finance, less innovation” view. At the same time, we show that lower available financial resources for firms lead to improvement in the qualitative dimensions of their patents. Hence, we carve out a “less finance, less but better innovation” pattern.
We investigate the differential effect of the COVID-19 shock to the stock market shock on the share prices of firms with different levels of ESG (Environmental, Social and Governance) scores. Thereby, we analyse whether and to what extent better ESG ratings provided insurance for investors in the stocks of those firms during this shock. We focus our analysis on the European market in which ESG investment plays a particularly important role. Using a broad sample of listed firms we provide mixed evidence. On the one hand, we show that immediately after the start of the shock firms with a higher ESG score outperformed their peers. On the other hand, this effect faded less than six weeks later. Given the quick recovery of the market our finding supports the idea that ESG stocks provide limited insurance in severe crises.
Predictions of oil prices reaching $100 per barrel during the winter of 2021/22 have raised fears of persistently high inflation and rising inflation expectations for years to come. We show that these concerns have been overstated. A $100 oil scenario of the type discussed by many observers, would only briefly raise monthly headline inflation, before fading rather quickly. However, the short-run effects on headline inflation would be sizable. For example, on a yearover- year basis, headline PCE inflation would increase by 1.8 percentage points at the end of 2021 under this scenario, and by 0.4 percentage points at the end of 2022. In contrast, the impact on measures of core inflation such as trimmed mean PCE inflation is only 0.4 and 0.3 percentage points in 2021 and 2022, respectively. These estimates already account for any increases in inflation expectations under the scenario. The peak response of the 1-year household inflation expectation would be 1.2 percentage points, while that of the 5-year expectation would be 0.2 percentage points.
Retail investors pay over twice as much attention to local companies than non-local ones, based on Google searches. News volume and volatility amplify this attention gap. Attention appears causally related to perceived proximity: first, acquisition by a nonlocal company is associated with less attention by locals, and more by nonlocals close to the acquirer; second, COVID-19 travel restrictions correlate with a drop in relative attention to nonlocal companies, especially in locations with fewer fights after the outbreak. Finally, local attention predicts volatility, bid-ask spreads and nonlocal attention, not viceversa. These findings are consistent with local investors having an information-processing advantage.
Die BaFin hat im August 2021 eine Richtlinie für nachhaltige Investmentvermögen vorgelegt. Diese soll regeln, unter welchen Voraussetzungen ein Fonds als „nachhaltig“, „grün“ o.ä. bezeichnet und vermarktet werden darf. Zwar sind aufsichtsrechtliche Maßnahmen, die darauf abzielen, die Qualität von Informationen zu Nachhaltigkeitscharakteristika von Finanzprodukten zu erhöhen, grundsätzlich zu begrüßen. Der Erlass der konsultierten Richtlinie ist jedoch nicht zu befürworten. Im Lichte der einschlägigen unionsrechtlichen Regelwerke und Initiativen ist unklar, welchen informationellen Mehrwert diese rein nationale Maßnahme schaffen soll. Ferner bleibt auf Grundlage des Entwurfs unklar, anhand welcher Maßstäbe die „Nachhaltigkeit“ eines Investmentvermögens beurteilt werden soll, sodass das primäre Regelungsziel einer verbesserten Anlegerinformation nicht erreicht würde.
Careers in finance
(2021)
The finance wage premium since the 1990s has arguably lured talent away from other industries. However, the allocation of talent is likely to respond to differences in career paths, not in wages at a given date. We use resume data to reconstruct the careers of 11,255 professionals in finance, high-tech and services from 1980 to 2017, and find that careers mostly develop within sectors. Careers in asset management feature higher and steeper pay profiles than those of employees in banking, insurance and non-finance, yet this career premium cannot be explained by higher risk. Labor market entry responds positively to career premia in asset management and high-tech, and these sectors are regarded as substitutes by potential entrants, consistently with high-tech competing with asset management in attracting talent.
Using the pandemic as a laboratory, we show that asset markets assign a time- varying price to firms' disaster risk exposure. In 2020 the cross-section of realized and expected stock returns reflected firms' different exposure to the pandemic, as measured by their vulnerability to social distancing. Realized and expected return differentials initially widened and then narrowed, but disaster exposure still commanded a risk premium in December 2020. When inferred from market outcomes, resilience correlates not only with social distancing, but also with cash and environmental ratings. However, vulnerability to social distancing is the only characteristic that identifies persistently scarred firms.
We investigate whether government credit guarantee schemes, extensively used at the onset of the Covid-19 pandemic, led to substitution of non-guaranteed with guaranteed credit rather than fully adding to the supply of lending. We study this issue using a unique euro-area credit register data, matched with supervisory bank data, and establish two main findings. First, guaranteed loans were mostly extended to small but comparatively creditworthy firms in sectors severely affected by the pandemic, borrowing from large, liquid and well-capitalized banks. Second, guaranteed loans partially substitute pre-existing non-guaranteed debt. For firms borrowing from multiple banks, the substitution mainly arises from the lending behavior of the bank extending guaranteed loans. Substitution was highest for funding granted to riskier and smaller firms in sectors more affected by the pandemic, and borrowing from larger and stronger banks. Overall, the evidence indicates that government guarantees contributed to the continued extension of credit to relatively creditworthy firms hit by the pandemic, but also benefited banks’ balance sheets to some extent.
The US Tax Cuts and Jobs Act (TCJA) led to a drastic reduction in the corporate tax and improved the treatment of C corporations compared to S corporations. We study the differential effect of the TCJA on these types of corporations using key economic variables of US banks, such as the number of employees, average salaries and benefits, profit/loss before taxes, and net income. Our analysis suggests that the TCJA increased the net-of-tax profits of C corporation banks compared to S corporations and, to a lesser extent, their pre-tax profits. At the same time, the reform triggered no significantly differential effect on the employment and average wages.
Historically Central Bank Independence (CBI) was anything but the norm. CBI seems to contradict core principles of democracy. Most economists were also against CBI. After the Great Inflation of the 1970ies many empirical studies demonstrated that there is a strong negative correlation between the degree of CBI and the rate of inflation. In 1990 most major countries had endowed their central bank with the status of independence. Overburdening with elevated expectations and additional competences are threatening the reputation of central banks and undermining the case for CBI.
COVID-19 brought about a shift in entrepreneurial opportunities and in the United States. In this paper, we proxy entrepreneurial processes by examining housing prices in different regions of the United States. Housing prices capture the movement in people, tax dynamics, and behavioral preferences for equity ownership in different regions and over time, all of which were drastically impacted by COVID-19. We examine all U.S. equity crowdfunding offerings starting with the very first offerings in 2016 Q2 until 2021 Q1 based on data from the Securities and Exchange Commission. The data indicate that regional housing prices post-COVID-19 are a strong predictor of the number of equity crowdfunding campaigns and the amount of capital raised. The impact of housing price changes on crowdfunding is more pronounced among more prosperous regions. The housing price effect is robust to numerous controls and consideration of outliers.
Leveraging data from a leading FinTech peer-to-peer lending platform in the United States, allowing us to capture both individuals’ successful and unsuccessful loan applications, we test the effect of FinTech loans on subsequent employment choice and future financial performance of serial borrowers, those repeatedly soliciting loans on the platform. An analysis of 198,984 loan requests made by 92,382 individuals shows that a failed loan application increases the probability of switching employment status. Self-employed individuals are 22% more likely to switch to becoming an employee following an unsuccessful loan application. This probability increases to 31% for those in the lowest income decile and decreases to 13% for those in the highest income decile. We document an improvement in monthly income and credit access following a successful loan application. However, this enhancement is asymmetric. Monthly income enhancement is 3.11 times larger for self-employed individuals in the lowest income decile relative to individuals in the highest income decile. Access to credit enhancement is 1.85 times larger for self-employed individuals in the lowest credit access decile relative to individuals in the second highest credit access decile.
We consider whether traders are more likely to commit securities violations when trading at home, a new form of working induced by the Covid pandemic. We examine data pre- and post-Covid, during which some traders were unexpectedly forced to work at home. The data indicate the presence of both a treatment and a selection effect, where work at home exhibits fewer misconduct cases. Work at home is associated with fewer cases of trading misconduct, although no difference in communications misconduct. The economic significance of working from home on trading misconduct is large for both the treatment and selection effects.
The nominee approach to equity crowdfunding pools all crowd investors into one (nominee) account where typically the platform acts as the legal owner but the crowd retains beneficial ownership. The platform plays an active digital corporate governance role that simultaneously enfranchises crowd investors with voting and ownership rights but removes the administrative burden on startups of having to deal with several hundred shareholders. Through an inter-platform and intra-platform analysis of a large sample of 1,018 initial equity crowdfunding campaigns, this paper assesses both the short-term and the long-term impact of nominee versus direct ownership. It finds that nominee initial campaigns are on average more successful than direct ownership campaigns in that they are more likely to succeed, raise more funds, attract overfunding and enjoy greater long run success in terms of successful seasoned equity crowdfunded offerings, numbers of such offerings, and probability of survival. These results hold inter-platform between the two main UK equity crowdfunding platforms (Seedrs and Crowdcube) as well as intra-platform, using the post-2015 quasi-natural experiment when the nominee approach became an option for startups raising capital on Crowdcube.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
The importance of agile methods has increased in recent years, not only to manage software development processes but also to establish flexible and adaptive organisational structures, which are essential to deal with disruptive changes and build successful digital business strategies. This paper takes an industry-specific perspective by analysing the dissemination, objectives and relative popularity of agile frameworks in the German banking sector. The data provides insights into expectations and experiences associated with agile methods and indicates possible implementation hurdles and success factors. Our research provides the first comprehensive analysis of agile methods in the German banking sector. The comparison with a selected number of fintechs has revealed some differences between banks and fintechs. We found that almost all banks and fintechs apply agile methods in IT-related projects. However, fintechs have relatively more experience with agile methods than banks and use them more intensively. Scrum is the most relevant framework used in practice. Scaled agile frameworks are so far negligible in the German banking sector. Acceleration of projects is apparently the most important objective of deploying agile methods. In addition, agile methods can contribute to cost savings and lead to improved quality and innovation performance, though for banks it is evidently more challenging to reach their respective targets than for fintechs. Overall our findings suggest that German banks are still in a maturing process of becoming more agile and that there is room for an accelerated adoption of agile methods in general and scaled agile frameworks in particular.
We propose three governance mechanisms pertinent to equity crowdfunding and campaign success through mitigating pronounced information asymmetries and agency problems. First, unlike IPOs for which the effect of Delaware incorporation has declined or disappeared over time, we propose Delaware incorporation matters a great deal for success in the new setting of equity crowdfunding. Second, we propose that security design is a critical tool for equity crowdfunding success and even more important than the limited 2-year financial statement disclosure. Third, we propose that platforms as intermediaries between entrepreneurs and investors play an important role in mitigating and sometimes exacerbating information asymmetries and agency problems. The population of equity crowdfunding campaigns from market inception in May 2016 to Q2, 2021 in the United States provides strong support for these propositions.
As part of the Next Generation EU (NGEU) program, the European Commission has pledged to issue up to EUR 250 billion of the NGEU bonds as green bonds, in order to confirm their commitment to sustainable finance and to support the transition towards a greener Europe. Thereby, the EU is not only entering the green bond market, but also set to become one of the biggest green bond issuers. Consequently, financial market participants are eager to know what to expect from the EU as a new green bond issuer and whether a negative green bond premium, a so-called Greenium, can be expected for the NGEU green bonds. This research paper formulates an expectation in regards to a potential Greenium for the NGEU green bonds, by conducting an interview with 15 sustainable finance experts and analyzing the public green bond market from September 2014 until June 2021, with respect to a potential green bond premium and its underlying drivers. The regression results confirm the existence of a significant Greenium (-0.7 bps) in the public green bond market and that the Greenium increases for supranational issuers with AAA rating, such as the EU. Moreover, the green bond premium is influenced by issuer sector and credit rating, but issue size and modified duration have no significant effect. Overall, the evaluated expert interviews and regression analysis lead to an expected Greenium for the NGEU green bonds of up to -4 bps, with the potential to further increase in the secondary market.
Target date funds in corporate retirement plans grew from $5B in 2000 to $734B in 2018, partly because federal regulation sanctioned these as default investments in automatic enrollment plans. We show that adopters delegated pension investment decisions to fund managers selected by plan sponsors. Including these funds in retirement saving menus raised equity shares, boosted bond exposures, curtailed cash/company stock holdings, and reduced idiosyncratic risk. The adoption of low-cost target date funds may enhance retirement wealth by as much as 50 percent over a 30-year horizon.