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The Capital Markets Union-project of the European Commission aims for an increase of marketbased debt financing of small and medium-sized enterprises (SMEs), complementing bank lending. In this essay we argue that rather than focussing on pure non-bank lending, a reasonable mix of bankand market-based financing should be considered. Banks are said to have a comparative advantage in critical lending functions such as credit screening, debtor monitoring and debt renegotiation. All forms of lending require a persistent skin-in-the-game of critical players in order to be effective. The regulator should insist on full disclosure of skin-in-the-game, thereby improving capital allocation and reducing systemic risks.
We establish a benchmark result for the relationship between the loanable funds and the money-creation approach to banking. In particular, we show that both processes yield the same allocations when there is no uncertainty and thus no bank default. In such cases, using the much simpler loanable funds approach as a shortcut does not imply any loss of generality.
Fleckenstein et al. (2014) document that nominal Treasuries trade at higher prices than inflation-swapped indexed bonds, which exactly replicate the nominal cash flows. We study whether this mispricing arises from liquidity premiums in inflation-indexed bonds (TIPS) and inflation swaps. Using US data, we show that the level of liquidity affects TIPS, whereas swap yields include a liquidity risk premium. We also allow for liquidity effects in nominal bonds. These results are based on a model with a systematic liquidity risk factor and asset-specific liquidity characteristics. We show that these liquidity (risk) premiums explain a substantial part of the TIPS underpricing.
This paper examines the welfare implications of rising temperatures. Using a standard VAR, we empirically show that a temperature shock has a sizable, negative and statistically significant impact on TFP, output, and labor productivity. We rationalize these findings within a production economy featuring long-run temperature risk. In the model, macro-aggregates drop in response to a temperature shock, consistent with the novel evidence in the data. Such adverse effects are long-lasting. Over a 50-year horizon, a one-standard deviation temperature shock lowers both cumulative output and labor productivity growth by 1.4 percentage points. Based on the model, we also show that temperature risk is associated with non-negligible welfare costs which amount to 18.4% of the agent's lifetime utility and grow exponentially with the size of the impact of temperature on TFP. Finally, we show that faster adaptation to temperature shocks results in lower welfare costs. These welfare benefits become substantially higher in the presence of permanent improvements in the speed of adaptation.
We shed new light on the macroeconomic effects of rising temperatures. In the data, a shock to global temperature dampens expenditures in research and development (R&D). We rationalize this empirical evidence within a stochastic endogenous growth model, featuring temperature risk and growth sustained through innovations. In line with the novel evidence in the data, temperature shocks undermine economic growth via a drop in R&D. Moreover, in our endogenous growth setting temperature risk generates non-negligible welfare costs (i.e., 11% of lifetime utility). An active government, which is committed to a zero fiscal deficit policy, can offset the welfare costs of global temperature risk by subsidizing the aggregate capital investment with one-fifth of total public spending.
We study the general equilibrium implications of different fiscal policies on macroeconomic quantities, asset prices, and welfare by utilizing two endogenous growth models. The expanding variety model features only homogeneous innovations by entrants. The Schumpeterian growth model features heterogeneous innovations: "incremental" innovations by incumbents and "radical" innovations by entrants. The government levies taxes on labor income and corporate profits and supplies subsidies to consumption, capital investment, and investments in research and development by entrants and, if applicable, incumbents. With these models at hand, we provide new insights on the interplay of innovation dynamics and fiscal policy.
Recent work has analyzed the forecasting performance of standard dynamic stochastic general equilibrium (DSGE) models, but little attention has been given to DSGE models that incorporate nonlinearities in exogenous driving processes. Against that background, we explore whether incorporating stochastic volatility improves DSGE forecasts (point, interval, and density). We examine real-time forecast accuracy for key macroeconomic variables including output growth, inflation, and the policy rate. We find that incorporating stochastic volatility in DSGE models of macroeconomic fundamentals markedly improves their density forecasts, just as incorporating stochastic volatility in models of financial asset returns improves their density forecasts.
Commodity connectedness
(2017)
We use variance decompositions from high-dimensional vector autoregressions to characterize connectedness in 19 key commodity return volatilities, 2011-2016. We study both static (full-sample) and dynamic (rolling-sample) connectedness. We summarize and visualize the results using tools from network analysis. The results reveal clear clustering of commodities into groups that match traditional industry groupings, but with some notable differences. The energy sector is most important in terms of sending shocks to others, and energy, industrial metals, and precious metals are themselves tightly connected.
The international diffusion of technology plays a key role in stimulating global growth and explaining co-movements of international equity returns. Existing empirical evidence suggests that countries are heterogeneous in their attitude toward innovation: Some countries rely more on technology adoption while other countries rely more on internal technology production. European countries that rely more on adoption are also typically characterized by lower fiscal policy exibility and higher labor market rigidity. We develop a two-country model – where both countries rely on R&D and adoption – to study the short-run and long-run effects of aggregate technology and adoption probability shocks on economic growth in the presence of the aforementioned asymmetries. Our framework suggests that an increase in the ability to adopt technology from abroad stimulates economic growth in the country that benefits from higher adoption rates but the beneficial effects also spread to the foreign country. Moreover, it helps explaining the differences in macro quantities and equity returns observed in the international data.
We propose a 2-country asset-pricing model where agents' preferences change endogenously as a function of the popularity of internationally traded goods. We determine the effect of the time-variation of preferences on equity markets, consumption and portfolio choices. When agents are more sensitive to the popularity of domestic consumption goods, the local stock market reacts more strongly to the preferences of local agents than to the preferences of foreign agents. Therefore, home bias arises because home-country stock represents a better investment opportunity for hedging against future fluctuations in preferences. We test our model and find that preference evolution is a plausible driver of key macroeconomic variables and stock returns.
Monetary policy communication is particularly important during unconventional times, because high uncertainty about the economy, the introduction of new policy tools and possible limits to the central bank’s toolkit could hamper the predictability of policy actions. We study how monetary policy communication should and has worked under such circumstances. Our main results relate to announcements of asset purchase programmes and the use of forward guidance. We show that announcements of asset purchase programmes have lowered market uncertainty, particularly when accompanied by a contextual release of implementation details such as the envisaged size of the programme. We also show that forward guidance reduces uncertainty more effectively when it is state‐contingent or when it provides guidance about a long horizon than when it is open‐ended or covers only a short horizon, and that the credibility of forward guidance is strengthened if the central bank also has embarked on an asset purchase programme.
Asymmetric social norms
(2017)
Studies of cooperation in infinitely repeated matching games focus on homogeneous economies, where full cooperation is efficient and any defection is collectively sanctioned. Here we study heterogeneous economies where occasional defections are part of efficient play, and show how to support those outcomes through contagious punishments.
The level of capital tax gains has high explanatory power regarding the question of what drives economic inequality. On this basis, the authors develop a simple, yet micro-founded portfolio selection model to explain the dynamics of wealth inequality given empirical tax series in the US. The results emphasize that the level and the transition of speed of wealth inequality depend crucially on the degree of capital taxation. The projections predict that – continuing on the present path of capital taxation in the US – the gap between rich and poor is expected to shrink whereas “massive” tax cuts will further increase the degree of wealth concentration.
Financial market interactions can lead to large and persistent booms and recessions. Instability is an inherent threat to economies with speculative financial markets. A central bank’s interest rate setting can amplify the expectation feedback in the financial market and this can lead to unstable dynamics and excess volatility. The paper suggests that policy institutions may be well-advised to handle tools like asset price targeting with care since such instruments might add a structural link between asset prices and macroeconomic aggregates. Neither stock prices nor indices are a good indicator to base decisions on.
Das Clearing von Euro-OTC-Derivaten post Brexit – eine Analyse der vorliegenden Kostenschätzungen
(2017)
Im Zusammenhang mit dem Brexit wird über die Kosten einer Relokation des Clearing des Euro-OTC-Derivate-Geschäftes auf ein EU-CCP diskutiert. Das vorliegende Papier zeigt, dass die bislang vorliegenden Kostenschätzungen, die von Kosten in Höhe von bis zu USD 100 Mrd. für einen Zeitraum von fünf Jahren ausgehen, viel zu hoch sind. Die erwarteten Kosten einer Relokation liegen vielmehr bei ca. USD 0,6 Mrd. p.a. bzw. ca. USD 3,2 Mrd. für eine Übergangsphase von fünf Jahren. Angesichts der hohen Bedeutung von systemrelevanten CCPs für die Stabilität der Eurozone sollten diese Kosten nicht entscheidungsrelevant für eine Relokation sein.
In the context of the upcoming Brexit, a relocation of the clearing of euro-OTC derivatives for EU-based firms is the subject of controversial discussion. The opponents of a relocation argue that a relocation would cause additional costs for market participants of up to USD 100 bn over a period of 5 years. This paper shows that this cost estimate is fairly unrealistic and that relocation costs would amount to approximately USD 0.6 bn p.a., which translates to cumulative costs of around USD 3.2 bn for a transition period of 5 years. In light of the strategic importance of systemically relevant CCPs for the financial stability of the eurozone, the potential relocation costs should not be a decision criterion.
We propose a long-run risk model with stochastic volatility, a time-varying mean reversion level of volatility, and jumps in the state variables. The special feature of our model is that the jump intensity is not affine in the conditional variance but driven by a separate process. We show that this separation of jump risk from volatility risk is needed to match the empirically weak link between the level and the slope of the implied volatility smile for S&P 500 options.
Causality is a widely-used concept in theoretical and empirical economics. The recent financial economics literature has used Granger causality to detect the presence of contemporaneous links between financial institutions and, in turn, to obtain a network structure. Subsequent studies combined the estimated networks with traditional pricing or risk measurement models to improve their fit to empirical data. In this paper, we provide two contributions: we show how to use a linear factor model as a device for estimating a combination of several networks that monitor the links across variables from different viewpoints; and we demonstrate that Granger causality should be combined with quantile-based causality when the focus is on risk propagation. The empirical evidence supports the latter claim.
For some time now, structural macroeconomic models used at central banks have been predominantly New Keynesian DSGE models featuring nominal rigidities and forwardlooking decision-making. While these features are widely deemed crucial for policy evaluation exercises, most central banks have added more detailed characterizations of the financial sector to these models following the Great Recession in order to improve their fit to the data and their forecasting performance. We employ a comparative approach to investigate the characteristics of this new generation of New Keynesian DSGE models and document an elevated degree of model uncertainty relative to earlier model generations. Policy transmission is highly heterogeneous across types of financial frictions and monetary policy causes larger effects, on average. The New Keynesian DSGE models we analyze suggest that a simple policy rule robust to model uncertainty involves a weaker response to inflation and the output gap in the presence of financial frictions as compared to earlier generations of such models. Leaning-against-the-wind policies in models of this class estimated for the Euro Area do not lead to substantial gains. With regard to forecasting performance, the inclusion of financial frictions can generate improvements, if conditioned on appropriate data. Looking forward, we argue that model-averaging and embracing alternative modelling paradigms is likely to yield a more robust framework for the conduct of monetary policy.
The impact of network connectivity on factor exposures, asset pricing and portfolio diversification
(2017)
This paper extends the classic factor-based asset pricing model by including network linkages in linear factor models. We assume that the network linkages are exogenously provided. This extension of the model allows a better understanding of the causes of systematic risk and shows that (i) network exposures act as an inflating factor for systematic exposure to common factors and (ii) the power of diversification is reduced by the presence of network connections. Moreover, we show that in the presence of network links a misspecified traditional linear factor model presents residuals that are correlated and heteroskedastic. We support our claims with an extensive simulation experiment.