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Institute
- Wirtschaftswissenschaften (1921) (remove)
Cross-predictability denotes the fact that some assets can predict other assets' returns. I propose a novel performance-based measure that disentangles the economic value of cross-predictability into two components: the predictive power of one asset's signal for other assets' returns (cross-predictive signals) and the amount of an asset's return explained by other assets' signals (cross-predicted returns). Empirically, the latter component dominates the former in the overall cross-prediction effects. In the crosssection, cross-predictability gravitates towards small firms that are strongly mispriced and difficult to arbitrage, while it becomes more difficult to cross-predict returns when market capitalization and book-to-market ratio rise.
This paper examines the dynamic relationship between firm leverage and risktaking. We embed the traditional agency problem of asset substitution within a multi-period model, revealing a U-shaped relationship between leverage and risktaking, evident in data from both the U.S. and Europe. Firms with medium leverage avoid risk to preserve the option of issuing safe debt in the future. This option is valuable because safe debt does not incur the expected cost of bankruptcy, anticipated by debt-holders due to future risk-taking incentives. Our model offers new insights on the interaction between companies' debt financing and their risk profiles.
If service providers can identify reasons users are in favor of or against a service, they have insightful information that can help them understand user behavior and what they need to do to change such behavior. This article argues that the novel text-mining technique referred to as information-seeking argument mining (IS-AM) can identify these reasons. The empirical study applies IS-AM to news articles and reviews about electric scooter-sharing systems (i.e., a service enabling the short-term rentals of electric motorized scooters). Its results point to IS-AM as a promising technique to improve service; the data enable the authors to identify 40 reasons to use or not use electric scooter-sharing systems, as well as their importance to users. Furthermore, the results show that news articles are better data sources than reviews because they are longer and contain more arguments and, thus, reasons.
Libra — a global virtual currency project initiated by Facebook — has been the subject of many controversial discussions since its announcement in June 2019. This paper provides a differentiated view on Libra, recognising that different development scenarios of Libra are conceivable. Libra could serve purely as an alternative payment system in combination with a dedicated payment token, the Libra coin. Alternatively, the Libra project could develop into a broader financial infrastructure for advanced financial services such as savings and loan products operating on the Libra Blockchain. Based on a comparison of the Libra architecture with other cryptocurrencies, the opportunities and challenges for the development of the respective Libra ecosystems are investigated from a commercial, regulatory and monetary policy perspective.
The importance of agile methods has increased in recent years, not only to manage IT projects 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 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.
The financial sector plays an important role in financing the green transformation. Various regulatory initiatives in the EU aim to improve transparency in relation to the sustainability of financial products and the sustainability of economic activities of non-financial and financial undertakings. For credit institutions, the Green Asset Ratio (GAR) has been established by the European regulatory authorities as a key performance indicator (KPI) for measuring the proportion of Taxonomy-aligned on-balance-sheet exposure in relation to the total assets. The breakdown of the total GAR by type of counterparty, environmental objective and type of asset provides in-depth information about the sustainability profile of a credit institution. This information, which has not been available to date, may also initiate discussions between management and shareholders or other stakeholders regarding the future sustainability strategy of credit institutions. This paper provides an overview of the regulatory background and the method of calculating the GAR along different dimensions. Finally, the potential benefits and limitations of the GAR are discussed.
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.
The financial sector plays an important role in supporting the green transformation of the European economy. A critical assessment of the current regulatory framework for sustainable finance in Europe leads to ambiguous results. Although the level of transparency on environmental, social and governance aspects of financial products has improved significantly, it is questionable whether the complex, mainly disclosure-oriented architecture is sufficient to mobilise more private capital into sustainable investments. It should be discussed whether a minimum taxonomy ratio or Green Asset Ratio has to be fulfilled to market a financial product as “green”. Furthermore, because of the high complexity of the regulation, it could be helpful for private investors to establish a simplified green rating, based on the taxonomy ratio, to facilitate the selection of green financial products.
With a notional amount outstanding of more than USD 500 trillion, the market for OTC derivatives is of vital importance for global financial stability. A growing proportion of these contracts are cleared via central counterparties (CCPs), which means that CCPs are gaining in importance as critical financial market infrastructures. At the same time, there is growing concern that a new „too big to fail" problem could arise, as the CCP industry is highly concentrated due to economies of scale. From a European perspective, it should be noted that the clearing of euro-denominated OTC derivatives mainly takes place in London, hence outside the EU in the foreseeable future. For some time there has been a controversial discussion as to whether this can remain the case post Brexit. CCPs, which clear a significant proportion of euro OTC derivatives and are systemically relevant from an EU perspective, should be subject to direct supervision by EU authorities and should be established in the EU. This would represent an important building block for a future Capital Markets Union in Europe, as regulatory or supervisory arbitrage in favour of systemically important third-country CCPs could be prevented. In addition, if a systemically relevant CCP handling a considerable portion of the euro OTC derivatives business were to run into serious difficulties, this may impact ECB monetary policy. This applies both to demand for central bank money and to the transmission of monetary policy measures, which can be significantly impaired, particularly in the event that the repo market or payment systems are disrupted. It is therefore essential for the ECB to be closely involved in the supervision of CCPs. Against this background, the draft amendment of EMIR (European Market Infrastructure Regulation) presented on 13 June 2017 is a step in the right direction. In addition, there is an urgent need to introduce a recovery and resolution mechanism for CCPs in the EU to complement the existing single resolution mechanism (SRM) for banks in the eurozone. Only then can the diverse interdependencies between banks and CCPs be adequately taken into account in the recovery and resolution programmes required in a financial crisis.
Ad blockers allow users to browse websites without viewing ads. Online news publishers that rely on advertising income tend to perceive users’ adoption of ad blockers purely as a threat to revenue. Yet, this perception ignores the possibility that avoiding ads—which users presumably dislike—may affect users’ online news consumption behavior in positive ways. Using 3.1 million visits from 79,856 registered users on a news website, this research finds that ad blocker adoption has robust positive effects on the quantity and variety of articles users consume. Specifically, ad blocker adoption increases the number of articles that users read by 21.0%–43.2%, and it increases the number of content categories that users consume by 13.4%–29.1%. These effects are stronger for less-experienced users of the website. The increase in news consumption stems from increases in repeat visits to the news website, rather than in the number of page impressions per visit. These postadoption visits tend to start from direct navigation to the news website, rather than from referral sources. The authors discuss how news publishers could benefit from these findings, including exploring revenue models that consider users’ desire to avoid ads.
A common element of market structure analysis is the spatial representation of firms’ competitive positions on maps. Such maps typically capture static snapshots in time. Yet, competitive positions tend to change. Embedded in such changes are firms’ trajectories, that is, the series of changes in firms’ positions over time relative to all other firms in a market. Identifying these trajectories contributes to market structure analysis by providing a forward-looking perspective on competition, revealing firms’ (re)positioning strategies and indicating strategy effectiveness. To unlock these insights, we propose EvoMap, a novel dynamic mapping framework that identifies firms’ trajectories from high-frequency and potentially noisy data. We validate EvoMap via extensive simulations and apply it empirically to study the trajectories of more than 1,000 publicly listed firms over 20 years. We find substantial changes in several firms’ positioning strategies, including Apple, Walmart, and Capital One. Because EvoMap accommodates a wide range of mapping methods, analysts can easily apply it in other empirical settings and to data from various sources.
Regulators worldwide have been implementing different privacy laws. They vary in their impact on the value for advertisers, publishers and users, but not much is known about these differences. This article focuses on three important privacy laws (i.e., General Data Protection Regulation [GDPR], California Consumer Privacy Act [CCPA] and Personal Information Protection Law [PIPL]) and compares their impact on the value for the three primary actors of the online advertising market, namely, advertisers, publishers and users. This article first compares these three privacy laws by developing a legal strictness score. It then uses the existing literature to derive the effects of the legal strictness of each privacy law on each actor’s value. Finally, it quantifies the three privacy laws’ impact on each actor’s value. The results show that GDPR and PIPL are similar and stricter than CCPA. Stricter privacy laws bring larger negative changes to the value for actors. As a result, both GDPR and PIPL decrease the actors’ value more substantially than CCPA. These value declines are the largest for publishers and are rather similar for users and advertisers. Scholars and practitioners can use our findings to explore ways to create value for multiple actors under various privacy laws.
For many services, consumers can choose among a range of optional tariffs that differ in their access and usage prices. Recent studies indicate that tariff-specific preferences may lead consumers to choose a tariff that does not minimize their expected billing rate. This study analyzes how tariff-specific preferences influence the responsiveness of consumers’ usage and tariff choice to changes in price. We show that consumer heterogeneity in tariff-specific preferences leads to heterogeneity in their sensitivity to price changes. Specifically, consumers with tariff-specific preferences are less sensitive to price increases of their preferred tariff than other consumers. Our results provide an additional reason why firms should offer multiple tariffs rather than a uniform nonlinear pricing plan to extract maximum consumer surplus.
We use a structural VAR model to study the German natural gas market and investigate the impact of the 2022 Russian supply stop on the German economy. Combining conventional and narrative sign restrictions, we find that gas supply and demand shocks have large and persistent price effects, while output effects tend to be moderate. The 2022 natural gas price spike was driven by adverse supply
shocks and positive storage demand shocks, as Germany filled its inventories before the winter. Counterfactual simulations of an embargo on natural gas imports from Russia indicate similar positive price and negative output effects compared to what we observe in the data.
Highlights
• The 1986 Immigration Reform and Control Act legalized millions of Hispanic migrants.
• The IRCA receive significantly increases state-to-county fiscal transfers.
• Electoral incentives of the state governor drive the fiscal response of the IRCA.
• Legalization increases Hispanic turnout and political engagement.
Abstract
We study the impact of immigrant legalization on fiscal transfers from state to local governments in the United States, exploiting variation in legal status from the 1986 Immigration Reform and Control Act (IRCA). State governments allocate more resources to IRCA counties, an allocation that is responsive to the electoral incentives of the governor. Importantly, the effect emerges prior to the enfranchisement of the IRCA migrants and we argue it is driven by the IRCA’s capacity to politically empower already legal Hispanic migrants in mixed legal status communities. The IRCA increases turnout in large Hispanic communities as well as Hispanic political engagement, without detectably triggering anti-migrant sentiment.
With adequate support for the learner, errors can have high learning potential. This study investigates rather unsuitable action patterns of teachers in dealing with errors. Teachers rarely investigate the causes that evoke the occurrence of individual students’ errors, but instead often change addressees immediately after an error occurs. Such behavior is frequent in the classroom, leaving unexploited, yet important potential to learn from errors. It has remained unexplained why teachers act the way they do in error situations. Using video-stimulated recalls, I investigate the reasons for teachers’ behavior in students’ error situations by confronting them with recorded episodes from their own teaching. Error situations are analyzed (within-case) and teachers’ beliefs are classified in an explanatory model (cross-case) to illustrate patterns across teachers. Results show that teachers refer to an interaction of student attributes, their own attributes, and error attributes when reasoning their own behavior. I find that reference to specific attributes varies depending on the situation, and so do the described reasons that led to a particular behavior as a spontaneous or more reflective decision.
The crowdfunding of altruism
(2022)
This paper introduces a machine learning approach to quantify altruism from the linguistic style of textual documents. We apply our method to a central question in (social) entrepreneurship: How does altruism impact entrepreneurial success? Specifically, we examine the effects of altruism on crowdfunding outcomes in Initial Coin Offerings (ICOs). The main result suggests that altruism and ICO firm valuation are negatively related. We, then, explore several channels to shed some light on whether the negative altruism-valuation relation is causal. Our findings suggest that it is not altruism that causes lower firm valuation; rather, low-quality entrepreneurs select into altruistic projects, while the marginal effect of altruism on high-quality entrepreneurs is actually positive. Altruism increases the funding amount in ICOs in the presence of high-quality projects, low asymmetric information, and strong corporate governance.
Experiments are an important tool in economic research. However, it is unclear to which extent the control of experiments extends to the perceptions subjects form of such experimental decision situations. This paper is the first to explicitly elicit perceptions of the dictator and trust game and shows that there is substantial heterogeneity in how subjects perceive the same game. Moreover, game perceptions depend not only on the game itself but also on the order of games (i.e., the broader experimental context in which the game is embedded) and the subject herself. This highlights that the control of experiments does not necessarily extend to game perceptions. The paper also demonstrates that perceptions are correlated with game behavior and moderate the relationship between game behavior and field behavior, thereby underscoring the importance and relevance of game perceptions for economic research.
Detailed feedback on exercises helps learners become proficient but is time-consuming for educators and, thus, hardly scalable. This manuscript evaluates how well Generative Artificial Intelligence (AI) provides automated feedback on complex multimodal exercises requiring coding, statistics, and economic reasoning. Besides providing this technology through an easily accessible web application, this article evaluates the technology’s performance by comparing the quantitative feedback (i.e., points achieved) from Generative AI models with human expert feedback for 4,349 solutions to marketing analytics exercises. The results show that automated feedback produced by Generative AI (GPT-4) provides almost unbiased evaluations while correlating highly with (r = 0.94) and deviating only 6 % from human evaluations. GPT-4 performs best among seven Generative AI models, albeit at the highest cost. Comparing the models’ performance with costs shows that GPT-4, Mistral Large, Claude 3 Opus, and Gemini 1.0 Pro dominate three other Generative AI models (Claude 3 Sonnet, GPT-3.5, and Gemini 1.5 Pro). Expert assessment of the qualitative feedback (i.e., the AI’s textual response) indicates that it is mostly correct, sufficient, and appropriate for learners. A survey of marketing analytics learners shows that they highly recommend the app and its Generative AI feedback. An advantage of the app is its subject-agnosticism—it does not require any subject- or exercise-specific training. Thus, it is immediately usable for new exercises in marketing analytics and other subjects.
This paper shows that support for climate action is high across survey participants from all EU countries in three dimensions: (1) Participants are willing to contribute personally to combating climate change, (2) they approve of pro-climate social norms, and (3) they demand government action. In addition, there is a significant perception gap where individuals underestimate others' willingness to contribute to climate action by over 10 percentage points, influencing their own willingness to act. Policymakers should recognize the broad support for climate action among European citizens and communicate this effectively to counteract the vocal minority opposed to it.
In recent decades, biodiversity has declined significantly, threatening ecosystem services that are vital to society and the economy. Despite the growing recognition of biodiversity risks, the private sector response remains limited, leaving a significant financing gap. The paper therefore describes market-based solutions to bridge the financing gap, which can follow a risk assessment approach and an impact-oriented perspective. Key obstacles to mobilising private capital for biodiversity conservation are related to pricing biodiversity due to its local dimension, the lack of standardized metrics for valuation and still insufficient data reporting by companies hindering informed investment decisions. Financing biodiversity projects poses another challenge, mainly due to a mismatch between investor needs and available projects, for example in terms of project timeframes and their additionality.
The development of China’s exports – is there a decoupling from the EU and the United States?
(2024)
Some observers warn that a high level of economic dependence on China could negatively affect the economic resilience of Western economies and therefore recommend reducing such dependence by gradually decoupling from China. On the other hand, industry leaders emphasise the economic importance of China and warn against any kind of trade conflicts.
Against this background, we briefly analyse the development of China’s export strategy. We find that the export intensity of the Chinese economy is diminishing and that exports are becoming more diversified overall. In addition, the relative importance of the United States and the European Union as export markets has been reduced, indicating a gradual decoupling of China from Western economies. Conversely, we find that exports to China have become more important, both for the EU and the United States. Although the figures remain at a non-critical level, Europe’s export activities could be more diversified as well.
How does the design of debt repayment schedules affect household borrowing? To answer this question, we exploit a Swedish policy reform that eliminated interest-only mortgages for loan-to-value ratios above 50%. We document substantial bunching at the threshold, leading to 5% lower borrowing. Wealthy borrowers drive the results, challenging credit constraints as the primary explanation. We develop a model to evaluate the mechanisms driving household behavior and find that much of the effect comes from households experiencing ongoing flow disutility to amortization payments. Our results indicate that mortgage contracts with low initial payments substantially increase household borrowing and lifetime interest costs.
We educate investors with significant dividend holdings about the benefits of dividend reinvestment and the costs of misperceiving dividends as additional, free income. The intervention increases planned dividend reinvestment in survey responses. Using trading records, we observe a corresponding causal increase in dividend reinvestment in the field of roughly 50 cents for every euro received. This holds relative to their prior behavior and a placebo sample. Investors who learned the most from the intervention update their trading by the largest extent. The results suggest the free dividends fallacy is a significant source of dividend demand. Our study demonstrates that simple, targeted, and focused educational interventions can affect investment behavior.
Inflation and trading
(2024)
We study how investors respond to inflation combining a customized survey experiment with trading data at a time of historically high inflation. Investors' beliefs about the stock return-inflation relation are very heterogeneous in the cross section and on average too optimistic. Moreover, many investors appear unaware of inflation-hedging strategies despite being otherwise well-informed about inflation and asset returns. Consequently, whereas exogenous shifts in inflation expectations do not impact return expectations, information on past returns during periods of high inflation leads to negative updating about the perceived stock-return impact of inflation, which feeds into return expectations and subsequent actual trading behavior.
This paper contributes a multivariate forecasting comparison between structural models and Machine-Learning-based tools. Specifically, a fully connected feed forward non-linear autoregressive neural network (ANN) is contrasted to a well established dynamic stochastic general equilibrium (DSGE) model, a Bayesian vector autoregression (BVAR) using optimized priors as well as Greenbook and SPF forecasts. Model estimation and forecasting is based on an expanding window scheme using quarterly U.S. real-time data (1964Q2:2020Q3) for 8 macroeconomic time series (GDP, inflation, federal funds rate, spread, consumption, investment, wage, hours worked), allowing for up to 8 quarter ahead forecasts. The results show that the BVAR improves forecasts compared to the DSGE model, however there is evidence for an overall improvement of predictions when relying on ANN, or including them in a weighted average. Especially, ANN-based inflation forecasts improve other predictions by up to 50%. These results indicate that nonlinear data-driven ANNs are a useful method when it comes to macroeconomic forecasting.
Central bank intervention in the form of quantitative easing (QE) during times of low interest rates is a controversial topic. The author introduces a novel approach to study the effectiveness of such unconventional measures. Using U.S. data on six key financial and macroeconomic variables between 1990 and 2015, the economy is estimated by artificial neural networks. Historical counterfactual analyses show that real effects are less pronounced than yield effects.
Disentangling the effects of the individual asset purchase programs, impulse response functions provide evidence for QE being less effective the more the crisis is overcome. The peak effects of all QE interventions during the Financial Crisis only amounts to 1.3 pp for GDP growth and 0.6 pp for inflation respectively. Hence, the time as well as the volume of the interventions should be deliberated.
We create an alternative version of the present utility value formula to explicitly show that every store-of-value in the economy bears utility-interest (non-pecuniary income) for ist holder regardless of possible interest earnings from financial markets. In addition, we generalize the well-known welfare measures of consumer and producer surplus as present value concepts and apply them not only for the production and usage of consumer goods and durables but also for money and other financial assets. This helps us, inter alia, to formalize the circumstances under which even a producer of legal tender might become insolvent. We also develop a new measure of seigniorage and demonstrate why the well-established concept of monetary seigniorage is flawed. Our framework also allows us to formulate the conditions for liability-issued money such as inside money and financial instruments such as debt certificates to become – somewhat paradoxically – net wealth of the society.
This paper studies discrete time finite horizon life-cycle models with arbitrary discount functions and iso-elastic per period power utility with concavity parameter θ. We distinguish between the savings behavior of a sophisticated versus a naive agent. Although both agent types have identical preferences, they solve different utility maximization problems whenever the model is dynamically inconsistent. Pollak (1968) shows that the savings behavior of both agent types is nevertheless identical for logarithmic utility (θ = 1). We generalize this result by showing that the sophisticated agent saves in every period a greater fraction of her wealth than the naive agent if and only if θ ≥ 1. While this result goes through for model extensions that preserve linearity of the consumption policy function, it breaks down for non-linear model extensions.
Almost ten years after the European Commission action plan on building a capital markets union (CMU) and despite incremental progress, e.g. in the form of the EU Listing Act, the picture looks dire. Stock exchanges, securities markets, and supervisory authorities remain largely national, and, in many cases, European companies have decided to exclusively list overseas. Notwithstanding the economic and financial benefits of market integration, CMU has become a geopolitical necessity. A unified capital market can bolster resilience, strategic autonomy, and economic sovereignty, reduce dependence on external funding, and may foster economic cooperation between member states.
The reason for the persistent stand-still in Europe’s CMU development is not so much the conflict between market- and state-based integration, but rather the hesitancy of national regulatory and supervisory bodies to relinquish powers. If EU member states wanted to get real about CMU (as they say, and as they should), they need to openly accept the loss of sovereignty that follows from a true unified capital market. Building on economic as well as historical evidence, the paper offers viable proposals on how to design competent institutions within the current European framework.
This note outlines the case for speedy capital market integration and for the adoption of a common regulatory framework and single supervisory authority from a political economy perspective. We also show the alternative case for harmonization and centralization via regulatory competition, elaborating how competition between EU jurisdictions by way of full mutual recognition may lead to a (cost-)efficient and standardized legal framework for capital markets. Lastly, the note addresses the political economy conflict that underpins the implementation of both models for integrating capital markets. We point out that, in both cases, national authorities experience a loss of legislative and jurisdictional competence at the national level. We predict that any plan to foster a stronger capital market union, following an institution based or a market-based strategy, will face opposition from powerful national stakeholders.
This study analyses potential consequences of exiting the Targeted Long-Term Refinancing Operations (TLTRO) of the European Central Bank (ECB). Thanks to its asset purchase programs, the Eurosystem still holds plenty of reserves even with a full exit from the TLTROs. This explains why voluntary and mandatory repayments of TLTRO III borrowing went smoothly. Nevertheless, the more liquidity is drained from the banking system, the more important becomes interbank market borrowing and lending, ideally between euro area member states. Right now, the usual fault lines of the euro area show up. The German banking system has plenty of reserves while there are first signs of aggregate scarcity in the Italian banking system. This does not need to be a source of concern if the interbank market can be sufficiently reactivated. Moreover, the ECB has several tools to address possible future liquidity shortages.
This document was provided/prepared by the Economic Governance and EMU scrutiny Unit at the request of the ECON Committee.
Homeownership rates differ widely across European countries. We document that part of this variation is driven by differences in the fraction of adults co-residing with their parents. Comparing Germany and Italy, we show that in contrast to homeownership rates per household, homeownership rates per individual are very similar during the first part of the life cycle. To understand these patterns, we build an overlapping-generations model where individuals face uninsurable income risk and make consumption-saving and housing tenure decisions. We embed an explicit intergenerational link between children and parents to capture the three-way trade-off between owning, renting, and co-residing. Calibrating the model to Germany we explore the role of income profiles, housing policies, and the taste for independence and show that a combination of these factors goes a long way in explaining the differential life-cycle patterns of living arrangements between the two countries.
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.
A stochastic forward-looking model to assess the profitability and solvency of European insurers
(2016)
In this paper, we develop an analytical framework for conducting forward-looking assessments of profitability and solvency of the main euro area insurance sectors. We model the balance sheet of an insurance company encompassing both life and non-life business and we calibrate it using country level data to make it representative of the major euro area insurance markets. Then, we project this representative balance sheet forward under stochastic capital markets, stochastic mortality developments and stochastic claims. The model highlights the potential threats to insurers solvency and profitability stemming from a sustained period of low interest rates particularly in those markets which are largely exposed to reinvestment risks due to the relatively high guarantees and generous profit participation schemes. The model also proves how the resilience of insurers to adverse financial developments heavily depends on the diversification of their business mix. Finally, the model identifies potential negative spillovers between life and non-life business thorugh the redistribution of capital within groups.
The economic rise of China has changed the global economy. The authors explore China’s transformation from a low-cost manufacturing hub to an increasingly innovation- and service-driven economy. Major growth drivers for the period 2010-2025 are analysed, including the paradigms of “Made in China” and the “Dual Circulation Strategy”. The export intensity of China’s economy is declining overall, with a tendency towards greater regional diversification and a gradual decoupling from North America and the European Union. At the same time, trade and investment activities are increasingly geared to the Belt and Road Initiative. Furthermore, labour and energy cost advantages for manufacturing operations in China are likely to diminish in the coming years, calling into question China’s attractiveness as a global manufacturing hub. In this regard, the further development of regional and industrial clusters is pivotal for China to enhance its global competitiveness and remain an attractive destination for foreign direct investment (FDI) in the medium term. On the other hand, high productivity in science and technology and rich deposits of critical minerals put China in a favourable position in advanced industries. Important challenges include the still wide development gap between rural and urban areas, the structural mismatch in the labour market, with persistently high youth unemployment, and the race to achieve carbon neutrality by 2060.
This paper studies whether Eurosystem collateral eligibility played a role in the portfolio choices of euro area asset managers during the “dash-for-cash” episode of 2020. We find that asset managers reduced their allocation to ECB-eligible corporate bonds, selling them in order to finance redemptions, while simultaneously increasing their cash holdings. These findings add nuance to previous studies of liquidity strains and price dislocations in the corporate bond market during the onset of the Covid-19 pandemic, indicating a greater willingness of dealers to increase their inventories of corporate bonds pledgeable with the ECB. Analysing the price impact of these portfolio choices, we also find evidence pointing to price pressure for both ECB-eligible and ineligible corporate bonds. Bonds that were held to a larger extent by investment funds in our sample experienced higher price pressure, although the impact was lower for ECB-eligible bonds. We also discuss broader implications for the related policy debate about how central banks could mitigate similar types of liquidity 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.
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.