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The authors embed human capital-based endogenous growth into a New-Keynesian model with search and matching frictions in the labor market and skill obsolescence from long-term unemployment. The model can account for key features of the Great Recession: a decline in productivity growth, the relative stability of inflation despite a pronounced fall in output (the "missing disinflation puzzle"), and a permanent gap between output and the pre-crisis trend output.
In the model, lower aggregate demand raises unemployment and the training costs associated with skill obsolescence. Lower employment hinders learning-by-doing, which slows down human capital accumulation, feeding back into even fewer vacancies than justified by the demand shock alone. These feedback channels mitigate the disinflationary effect of the demand shock while amplifying its contractionary effect on output. The temporary growth slowdown translates into output hysteresis (permanently lower output and labor productivity).
Occasionally binding constraints have become an important part of economic modelling, especially since western central banks see themselves (again) constraint by the so-called zero lower bound (ZLB) of the nominal interest rate. A binding ZLB constraint poses a major problem for a quantitative-structural analysis: Linear solution methods do no work in the presence of a non-linearity such as the ZLB and existing alternatives tend to be computationally demanding. The urge to study macroeconomic questions related to the Great Recession and the Covid-19 crisis in a quantitative-structural framework requires algorithms that are not only accurate, but that are also robust, fast, and computationally efficient.
A particularly important application where efficient and fast methods for occasionally binding constraints (OBCs) are needed is the Bayesian estimation of macroeconomic models. This paper shows that a linear dynamic rational expectations system with OBCs, depending on the expected duration of the constraint, can be represented in closed form. Combined with a set of simple equilibrium conditions, this can be exploited to avoid matrix inversions and simulations at runtime for signifcant gains in computational speed.
Central banks sometimes evaluate their own policies. To assess the inherent conflict of interest, the authors compare the research findings of central bank researchers and academic economists regarding the macroeconomic effects of quantitative easing (QE). They find that central bank papers report larger effects of QE on output and inflation. Central bankers are also more likely to report significant effects of QE on output and to use more positive language in the abstract. Central bankers who report larger QE effects on output experience more favorable career outcomes. A survey of central banks reveals substantial involvement of bank management in research production.
Empirical estimates of equilibrium real interest rates are so far mostly limited to advanced economies, since no statistical procedure suitable for a large set of countries is available. This is surprising, as equilibrium rates have strong policy implications in emerging markets and developing economies as well; current estimates of the global equilibrium rate rely on only a few countries; and estimates for a more diverse set of countries can improve understanding of the drivers. The authors propose a model and estimation strategy that decompose ex ante real interest rates into a permanent and transitory component even with short samples and high volatility. This is done with an unobserved component local level stochastic volatility model, which is used to estimate equilibrium rates for 50 countries with Bayesian methods.
Equilibrium rates were lower in emerging markets and developing economies than in advanced economies in the 1980s, similar in the 1990s, and have been higher since 2000. In line with economic integration and rising global capital markets, synchronization has been rising over time and is higher among advanced economies. Equilibrium rates of countries with stronger trade linkages and similar demographic and economic trends are more synchronized.
With the second wave of the Covid-19 pandemic in full swing, banks face a challenging environment. They will need to address disappointing results and adverse balance sheet restatements, the intensity of which depends on the evolution of the euro area economies. At the same time, vulnerable banks reinforce real economy deficiencies. The contribution of this paper is to provide a comparative assessment of the various policy responses to address a looming banking crisis. Such a crisis will fully materialize when non-performing assets drag down banks simultaneously, raising the specter of a full-blown systemic crisis. The policy responses available range from forbearance, recapitalization (with public or private resources), asset separation (bad banks, at national or EU level), to debt conversion schemes. We evaluate these responses according to a set of five criteria that define the efficacy of each. These responses are not mutually exclusive, in practice, as they have never been. They may also go hand in hand with other restructuring initiatives, including potential consolidation in the banking sector. Although we do not make a specific recommendation, we provide a framework for policymakers to guide them in their decision making.
Following the financial crash and the subsequent recession, European policymakers have undertaken major reforms regarding the European Economic and Monetary Union (EMU). Yet, the success rate is mixed. Several reform proposals have either completely failed due to opposition forces or are still pending, sometimes for years. This article provides an overview of reforms in four major policy fields: financial stabilisation, economic governance, fiscal solidarity, and cooperative dissolution. Building on the conceptual foundation of policy analysis, it distinguishes between policy outputs and outcomes. Policy output refers to legislation being adopted or agreement on treaty changes, while policy outcomes depict the result from the implementation process.
This policy white paper shows, using data on European Commission (EC) lobby meetings, that financial institutions and finance trade associations have substantial access to EC policymakers. While lobbying could transfer policy-relevant information and expertise to policymakers, it could also result in the capture of policymakers by the industry, which could harm consumers and taxpayers. How could policymakers prevent regulatory capture, but retain the benefits of the sector expertise in policy decisions? Awareness of regulatory capture by policymakers is one of the most important remedies. This paper provides an overview of the origins of the regulatory capture theory and recent academic evidence. The paper shows that regulatory capture could emerge in a variety of institutions and policy areas but is not ubiquitous and depends on the incentives of policymakers and the policy environment. Subsequently, the paper discusses various measures to prevent regulatory capture, such as more transparency, diverse expert groups, and cooling-off periods.
“Right to Buy” (RTB), a large-scale natural experiment by which incumbent tenants in public housing could buy properties at heavily-subsidised prices, increased the UK homeownership rate by over 10 percentage points between 1980 and the late 1990s. This paper studies its impact on crime, showing that RTB generated significant reductions in property and violent crime that persist up to today. The behavioural changes of incumbent tenants and the renovation of public properties were the main drivers of the crime reduction. This is evidence of a novel means by which subsidised homeownership and housing policy may contribute to reduce criminality.
We derive the Bayes estimator of vectors of structural VAR impulse responses under a range of alternative loss functions. We also derive joint credible regions for vectors of impulse responses as the lowest posterior risk region under the same loss functions. We show that conventional impulse response estimators such as the posterior median response function or the posterior mean response function are not in general the Bayes estimator of the impulse response vector obtained by stacking the impulse responses of interest. We show that such pointwise estimators may imply response function shapes that are incompatible with any possible parameterization of the underlying model. Moreover, conventional pointwise quantile error bands are not a valid measure of the estimation uncertainty about the impulse response vector because they ignore the mutual dependence of the responses. In practice, they tend to understate substantially the estimation uncertainty about the impulse response vector.
This paper examines the advantages and drawbacks of alternative methods of estimating oil supply and oil demand elasticities and of incorporating this information into structural VAR models. I not only summarize the state of the literature, but also draw attention to a number of econometric problems that have been overlooked in this literature. Once these problems are recognized, seemingly conflicting conclusions in the recent literature can be resolved. My analysis reaffirms the conclusion that the one-month oil supply elasticity is close to zero, which implies that oil demand shocks are the dominant driver of the real price of oil. The focus of this paper is not only on correcting some misunderstandings in the recent literature, but on the substantive and methodological insights generated by this exchange, which are of broader interest to applied researchers.
Using a novel dataset, we develop a structural model of the Very Large Crude Carrier (VLCC) market between the Arabian Gulf and the Far East. We study how fluctuations in oil tanker rates, oil exports, shipowner profits, and bunker fuel prices are determined by shocks to the supply and demand for oil tankers, to the utilization of tankers, and to the cost of operating tankers, including bunker fuel costs. Our analysis shows that time charter rates are largely unresponsive to tanker cost shocks. In response to higher costs, voyage profits decline, as cost shocks are only partially passed on to round-trip voyage rates. Oil exports from the Arabian Gulf also decline, reflecting lower demand for VLCCs. Positive utilization shocks are associated with higher profits, a slight increase in time charter rates and lower fuel prices and oil export volumes. Tanker supply and tanker demand shocks have persistent effects on time charter rates, round-trip voyage rates, the volume of oil exports, fuel prices, and profits with the expected sign.
Optimal investment decisions by institutional investors require accurate predictions with respect to the development of stock markets. Motivated by previous research that revealed the unsatisfactory performance of existing stock market prediction models, this study proposes a novel prediction approach. Our proposed system combines Artificial Intelligence (AI) with data from Virtual Investment Communities (VICs) and leverages VICs’ ability to support the process of predicting stock markets. An empirical study with two different models using real data shows the potential of the AI-based system with VICs information as an instrument for stock market predictions. VICs can be a valuable addition but our results indicate that this type of data is only helpful in certain market phases.
Participation in further education is a central success factor for economic growth and societal as well as individual development. This is especially true today because in most industrialized countries, labor markets and work processes are changing rapidly. Data on further education, however, show that not everybody participates and that different social groups participate to different degrees. Activities in continuous vocational education and training (CVET) are mainly differentiated as formal, non-formal and informal CVET, whereby further differences between offers of non-formal and informal CVET are seldom elaborated. Furthermore, reasons for participation or non-participation are often neglected. In this study, we therefore analyze and compare predictors for participation in both forms of CVET, namely, non-formal and informal. To learn more about the reasons for participation, we focus on the individual perspective of employees (invidual factors, job-related factors, and learning biography) and additionally integrate institutional characteristics (workplace and company-based characteristics). The results mainly show that non-formal CVET is still strongly influenced by institutional settings. In the case of informal CVET, on the other hand, the learning biography plays a central role.
Learning to fly through informational turbulence: critical thinking and the case of the minimum wage
(2020)
The paper addresses online reasoning and information processing with respect to a much debated issue: the pros and cons of the minimum wage. Like with all controversial issues, one can easily remain in a self-reinforcing bubble, once one has taken sides, and immunize oneself against criticism. Paradoxically, the more information we have at our disposal, the easier this gets (Roetzel, 2019). The only (and possibly universal) antidote seems to be “critical thinking” (Ennis, 1987, 2011). However, critical thinking is a very broad concept, purported to include diverse kinds of information processing, and it is also thought to be content-specific. Therefore, we aim at addressing both understanding of content knowledge and reasoning processes. We pursue three goals with this paper: First, we conduct a conceptual analysis of the learning content and of reasoning patterns for and against the minimum wage. Second, we explicate an inferential framework that can be applied for processes of critical thinking. Third, teaching strategies are discussed to support reasoning processes and to promote critical thinking skills.