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The IMFS Interdisciplinary Study 2/2013 contains speeches of Michael Burda (Humboldt University ), Benoît Coeuré (European Central Bank), Stefan Gerlach (Bank of Ireland and former IMFS Professor), Patrick Honohan (Bank of Ireland), Sabine Lautenschläger (Deutsche Bundesbank), Athanasios Orphanides (MIT) and Helmut Siekmann as well as Volker Wieland.
This study contains articles based on speeches and presentations at the 14th CFS-IMFS Conference "The ECB and its Watchers" on June 15, 2012 by Mario Draghi, John Vickers, Peter Praet, Lucrezia Reichlin, Vitor Gaspar, Lucio Pench and Stefan Gerlach and a post-conference outlook by Helmut Siekmann and Volker Wieland.
Is wider access to stockholding opportunities related to reduced wealth inequality, given that it creates challenges for small and less sophisticated investors? Counterfactual analysis is used to study the influence of changes in the US stockholder pool and economic environment, on the distribution of stock and net household wealth during a period of dramatic increase in stock market participation. We uncover substantial shifts in stockholder pool composition, favoring smaller holdings during the 1990s upswing but larger holdings around the burst of the Internet bubble. We find no evidence that widening access to stocks was associated with reduced net wealth inequality.
Using fiscal reaction functions for 3a panel of actual euro-area countries the paper investigates whether euro membership has reduced the responsiveness of countries to increases in the level of inherited debt compared to the period prior to succession to the euro. While we find some evidence for such a loss in prudence, the results are not robust to changes in the specification, as for example an exclusion of Greece from the panel. This suggests that the current debt problems may result to a large extent from pre-existing debt levels prior to entry or from a larger need for fiscal prudence in a common currency, while an adverse change in the fiscal reaction functions for most countries does not apply.
This note proposes a new set-up for the fund backing the Single Resolution Mechanism (SRM). The proposed fund is a Multi-Tier Resolution Fund (MTRF), restricting the joint and several supranational liability to a limited range of losses, bounded by national liability at the upper and the lower end. The layers are, in ascending order: a national fund (first losses), a European fund (second losses), the national budget (third losses), the ESM (fourth losses, as a backup for sovereigns). The system works like a reinsurance scheme, providing clear limits to European-level joint liability, and therefore confining moral hazard. At the same time, it allows for some degree of risk sharing, which is important for financial stability if shocks to the financial system are exogenous (e.g., of a supranational macroeconomic nature). The text has four parts. Section A describes the operation of the Multi-Tier Resolution Fund, assuming the fund capital to be fully paid-in (“Steady State“). Section B deals with the build-up phase of the fund capital (“Build up“). Section C discusses how the proposal deals with the apparent incentive conflicts. The final Section D summarizes open questions which need further thought (“Open Questions“).
This policy letter provides an overview of the strengths, weaknesses, risks and opportunities of the upcoming comprehensive risk assessment, a euro area-wide evaluation of bank balance sheets and business models. If carried out properly, the 2014 comprehensive assessment will lead the euro area into a new era of banking supervision. Policy makers in euro area countries are now under severe pressure to define a credible backstop framework for banks. This framework, as the author argues, needs to be a broad, quasi-European system of mutually reinforcing backstops.
SAFE Newsletter : 2013, Q4
(2013)
Sovereign bond risk premiums
(2013)
Credit risk has become an important factor driving government bond returns. We therefore introduce an asset pricing model which exploits information contained in both forward interest rates and forward CDS spreads. Our empirical analysis covers euro-zone countries with German government bonds as credit risk-free assets. We construct a market factor from the first three principal components of the German forward curve as well as a common and a country-specific credit factor from the principal components of the forward CDS curves. We find that predictability of risk premiums of sovereign euro-zone bonds improves substantially if the market factor is augmented by a common and an orthogonal country-specific credit factor. While the common credit factor is significant for most countries in the sample, the country-specific factor is significant mainly for peripheral euro-zone countries. Finally, we find that during the current crisis period, market and credit risk premiums of government bonds are negative over long subintervals, a finding that we attribute to the presence of financial repression in euro-zone countries.
This paper takes a novel approach to estimating bankruptcy costs by inference from market prices of equity and put options using a dynamic structural model of capital structure. This approach avoids the selection bias of looking at firms in or near default and therefore permits theories of ex ante capital structure determination to be tested. We identify significant cross sectional variation in bankruptcy costs across industries and relate these to specific firm characteristics. We find that asset volatility and growth options have significant positive impacts, while tangibility and size have negative impacts. Our bankruptcy cost variable estimate significantly negatively impacts leverage ratios. This negative impact is in addition to that of other firm characteristics such as asset intangibility and asset volatility. The results provide strong support for the tradeoff theory of capital structure.
We study to what extent firms spread out their debt maturity dates across time, which we call "granularity of corporate debt." We consider the role of debt granularity using a simple model in which a firm's inability to roll over expiring debt causes inefficiencies, such as costly asset sales or underinvestment. Since multiple small asset sales are less costly than a single large one, firms may diversify debt rollovers across maturity dates. We construct granularity measures using data on corporate bond issuers for the 1991-2011 period and establish a number of novel findings. First, there is substantial variation in granularity in that many firms have either very concentrated or highly dispersed maturity structures. Second, our model's predictions are consistent with observed variation in granularity. Corporate debt maturities are more dispersed for larger and more mature firms, for firms with better investment opportunities, with higher leverage ratios, and with lower levels of current cash flows. We also show that during the recent financial crisis especially firms with valuable investment opportunities implemented more dispersed maturity structures. Finally, granularity plays an important role for bond issuances, because we document that newly issued corporate bond maturities complement pre-existing bond maturity profiles.
We consider an economy where individuals privately choose effort and trade competitively priced securities that pay off with effort-determined probability. We show that if insurance against a negative shock is sufficiently incomplete, then standard functional form restrictions ensure that individual objective functions are optimized by an effort and insurance combination that is unique and satisfies first- and second-order conditions. Modeling insurance incompleteness in terms of costly production of private insurance services, we characterize the constrained inefficiency arising in general equilibrium from competitive pricing of nonexclusive financial contracts.
We propose a new classification of consumption goods into nondurable goods, durable goods and a new class which we call “memorable” goods. A good is memorable if a consumer can draw current utility from its past consumption experience through memory. We construct a novel consumption-savings model in which a consumer has a well-defined preference ordering over both nondurable goods and memorable goods. Memorable goods consumption differs from nondurable goods consumption in that current memorable goods consumption may also impact future utility through the accumulation process of the stock of memory. In our model, households optimally choose a lumpy profile of memorable goods consumption even in a frictionless world. Using Consumer Expenditure Survey data, we then document levels and volatilities of different groups of consumption goods expenditures, as well as their expenditure patterns, and show that the expenditure patterns on memorable goods indeed differ significantly from those on nondurable and durable goods. Finally, we empirically evaluate our model’s predictions with respect to the welfare cost of consumption fluctuations and conduct an excess-sensitivity test of the consumption response to predictable income changes. We find that (i) the welfare cost of household-level consumption fluctuations may be overstated by 1.7 percentage points (11.9% points as opposed to 13.6% points of permanent consumption) if memorable goods are not appropriately accounted for; (ii) the finding of excess sensitivity of consumption documented in important papers of the literature might be entirely due to the presence of memorable goods.
There is mounting evidence that retail investors make predictable, costly investment mistakes, including underinvestment, naïve diversification, and payment of excessive fund fees. Over the past thirty-five years, however, participant-directed 401(k) plans have largely replaced professionally managed pension plans, requiring unsophisticated retail investors to navigate the financial markets themselves. Policy-makers have struggled with regulatory interventions designed to improve the quality of investment decisions without a clear understanding of the reasons for investor mistakes. Absent such an understanding, it is difficult to design effective regulatory responses. This article offers a first step in understanding the investor decision-making process. We use an internet-based experiment to disentangle possible explanations for inefficient investment decisions. The experiment employs a simplified construct of an employee’s allocation among the options in a retirement plan coupled with technology that enables us to collect data on the specific information that investors choose to view. In addition to collecting general information about the process by which investors choose among mutual fund options, we employ an experimental manipulation to test the effect of an instruction on the importance of mutual fund fees. Pairing this instruction with simplified fee disclosure allows us to distinguish between motivation-limits and cognition-limits as explanations for the widespread findings that investors ignore fees in their investment decisions. Our results offer partial but limited grounds for optimism. On the one hand, within our simplified experimental construct, our subjects allocated more money, on average, to higher-value funds. Furthermore, subjects who received the fees instruction paid closer attention to mutual fund fees and allocated their investments into funds with lower fees. On the other hand, the effects of even a blunt fees instruction were limited, and investors were unable to identify and avoid clearly inferior fund options. In addition, our results suggest that excessive, naïve diversification strategies are driving many investment decisions. Although our findings are preliminary, they suggest valuable avenues for future research and important implications for regulation of retail investing.
The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast monthly and quarterly oil prices. There also has been increased interest in the link between financial markets and oil markets, including the question of whether financial market information helps forecast the real price of oil in physical markets. An obvious advantage of financial data in forecasting oil prices is their availability in real time on a daily or weekly basis. We investigate whether mixed-frequency models may be used to take advantage of these rich data sets. We show that, among a range of alternative high-frequency predictors, especially changes in U.S. crude oil inventories produce substantial and statistically significant real-time improvements in forecast accuracy. The preferred MIDAS model reduces the MSPE by as much as 16 percent compared with the no-change forecast and has statistically significant directional accuracy as high as 82 percent. This MIDAS forecast also is more accurate than a mixed-frequency realtime VAR forecast, but not systematically more accurate than the corresponding forecast based on monthly inventories. We conclude that typically not much is lost by ignoring high-frequency financial data in forecasting the monthly real price of oil.
Model case procedures have some fundamentals in common with collective redress in civil law countries. This is particularly true in the field of investor protection which is highly regulated and marked by resulting enforcement failures, which led the German legislator to the enactment of the KapMuG and its recent amendment which highlight exemplary elements of model case procedure. A survey of the ongoing activities of the European Union in the area of collective redress and of its repercussions on the member state level therefore forms a suitable basis for the following analysis of the 2012 amendment of the KapMuG. It clearly brings into focus a shift from sector-specific regulation with an emphasis on the cross-border aspect of protecting consumers towards a “coherent approach” strengthening the enforcement of EU law. As a result, regulatory policy and collective redress are two sides of the same coin today. With respect to the KapMuG such a development brings about some tension between its aim to aggregate small individual claims as efficiently as possible and the dominant role of individual procedural rights in German civil procedure. This conflict can be illustrated by some specific rules of the KapMuG: its scope of application, the three-tier procedure of a model case procedure, the newly introduced notification of claims and the new opt-out settlement under the amended §§ 17-19.
We propose the realized systemic risk beta as a measure for financial companies’ contribution to systemic risk given network interdependence between firms’ tail risk exposures. Conditional on statistically pre-identified network spillover effects and market as well as balance sheet information, we define the realized systemic risk beta as the total time-varying marginal effect of a firm’s Value-at-risk (VaR) on the system’s VaR. Statistical inference reveals a multitude of relevant risk spillover channels and determines companies’ systemic importance in the U.S. financial system. Our approach can be used to monitor companies’ systemic importance allowing for a transparent macroprudential supervision.
We introduce a copula-based dynamic model for multivariate processes of (non-negative) high-frequency trading variables revealing time-varying conditional variances and correlations. Modeling the variables’ conditional mean processes using a multiplicative error model we map the resulting residuals into a Gaussian domain using a Gaussian copula. Based on high-frequency volatility, cumulative trading volumes, trade counts and market depth of various stocks traded at the NYSE, we show that the proposed copula-based transformation is supported by the data and allows capturing (multivariate) dynamics in higher order moments. The latter are modeled using a DCC-GARCH specification. We suggest estimating the model by composite maximum likelihood which is sufficiently flexible to be applicable in high dimensions. Strong empirical evidence for time-varying conditional (co-)variances in trading processes supports the usefulness of the approach. Taking these higher-order dynamics explicitly into account significantly improves the goodness-of-fit of the multiplicative error model and allows capturing time-varying liquidity risks.