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Manche Wissenschaftler haben die Gabe, andere zu inspirieren. Sie ziehen talentierte junge Menschen an, sind gut vernetzt und bringen wiederum erfolgreiche Forscher hervor. Heike Jüngst spürt dem Erfolgsrezept der Begründer wissenschaftlicher Schulen an einem historischen und einem zeitgenössischen Beispiel nach.
Als Rainer Forst, Professor für politische Theorie und Philosophie an der Frankfurter Universität, 2012 den Leibniz-Preis erhielt, hieß es in der Laudatio, er führe die »philosophische Tradition der Frankfurter Schule mit Jürgen Habermas und Axel Honneth auf höchstem Niveau« fort. In diesem Jahr wird das Frankfurter Institut für Sozialforschung 90 Jahre alt, und die Anfänge der »Frankfurter Schule« liegen ungefähr 85 Jahre zurück – Anlässe genug, um zu fragen: Wie hat sich die »Frankfurter Schule« gewandelt?
Advertising arbitrage
(2014)
Speculators often advertise arbitrage opportunities in order to persuade other investors and thus accelerate the correction of mispricing. We show that in order to minimize the risk and the cost of arbitrage an investor who identifies several mispriced assets optimally advertises only one of them, and overweights it in his portfolio; a risk-neutral arbitrageur invests only in this asset. The choice of the asset to be advertised depends not only on mispricing but also on its "advertisability" and accuracy of future news about it. When several arbitrageurs identify the same arbitrage opportunities, their decisions are strategic complements: they invest in the same asset and advertise it. Then, multiple equilibria may arise, some of which inefficient: arbitrageurs may correct small mispricings while failing to eliminate large ones. Finally, prices react more strongly to the ads of arbitrageurs with a successful track record, and reputation-building induces high-skill arbitrageurs to advertise more than others.
Has economic research been helpful in dealing with the financial crises of the early 2000s? On the whole, the answer is negative, although there are bright spots. Economists have largely failed to predict both crises, largely because most of them were not analytically equipped to understand them, in spite of their recurrence in the last 25 years. In the pre-crisis period, however, there have been important exceptions – theoretical and empirical strands of research that largely laid out the basis for our current thinking about financial crises. Since 2008, a flurry of new studies offered several different interpretations of the US crisis: to some extent, they point to potentially complementary factors, but disagree on their relative importance, and therefore on policy recommendations. Research on the euro debt crisis has so far been much more limited: even Europe-based researchers – including CEPR ones – have often directed their attention more to the US crisis than to that occurring on their doorstep. In terms of impact on policy and regulatory reform, the record is uneven. On the one hand, the swift and massive liquidity provision by central banks in the wake of both crises is, at least partly, to be credited to previous research on the role of central banks as lenders of last resort in crises and on the real effects of bank lending and monetary policy. On the other hand, economists have had limited impact on the reform of prudential and security market regulation. In part, this is due to their neglect of important regulatory choices, which policy-makers are therefore left to take without the guidance of academic research-based analysis.
Consumption-based asset pricing with rare disaster risk : a simulated method of moments approach
(2014)
The rare disaster hypothesis suggests that the extraordinarily high postwar U.S. equity premium resulted because investors ex ante demanded compensation for unlikely but calamitous risks that they happened not to incur. Although convincing in theory, empirical tests of the rare disaster explanation are scarce. We estimate a disaster-including consumption-based asset pricing model (CBM) using a combination of the simulated method of moments and bootstrapping. We consider several methodological alternatives that differ in the moment matches and the way to account for disasters in the simulated consumption growth and return series. Whichever specification is used, the estimated preference parameters are of an economically plausible size, and the estimation precision is much higher than in previous studies that use the canonical CBM. Our results thus provide empirical support for the rare disaster hypothesis, and help reconcile the nexus between real economy and financial markets implied by the consumption-based asset pricing paradigm.
The long-run consumption risk (LRR) model is a promising approach to resolve prominent asset pricing puzzles. The simulated method of moments (SMM) provides a natural framework to estimate its deep parameters, but caveats concern model solubility and weak identification. We propose a two-step estimation strategy that combines GMM and SMM, and for which we elicit informative macroeconomic and financial moment matches from the LRR model structure. In particular, we exploit the persistent serial correlation of consumption and dividend growth and the equilibrium conditions for market return and risk-free rate, as well as the model-implied predictability of the risk-free rate. We match analytical moments when possible and simulated moments when necessary and determine the crucial factors required for both identification and reasonable estimation precision. A simulation study – the first in the context of long-run risk modeling – delineates the pitfalls associated with SMM estimation of a non-linear dynamic asset pricing model. Our study provides a blueprint for successful estimation of the LRR model.
he predictive likelihood is of particular relevance in a Bayesian setting when the purpose is to rank models in a forecast comparison exercise. This paper discusses how the predictive likelihood can be estimated for any subset of the observable variables in linear Gaussian state-space models with Bayesian methods, and proposes to utilize a missing observations consistent Kalman filter in the process of achieving this objective. As an empirical application, we analyze euro area data and compare the density forecast performance of a DSGE model to DSGE-VARs and reduced-form linear Gaussian models.
We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semi-martingale log asset price process which is subject to noise and non-synchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance estimates. The latter originate from a local method of moments (LMM) which recently has been introduced by Bibinger et al. (2014). We extend the LMM estimator to allow for autocorrelated noise and propose a method to adaptively infer the autocorrelations from the data. We prove the consistency and asymptotic normality of the proposed spot covariance estimator. Based on extensive simulations we provide empirical guidance on the optimal implementation of the estimator and apply it to high-frequency data of a cross-section of NASDAQ blue chip stocks. Employing the estimator to estimate spot covariances, correlations and betas in normal but also extreme-event periods yields novel insights into intraday covariance and correlation dynamics. We show that intraday (co-)variations (i) follow underlying periodicity patterns, (ii) reveal substantial intraday variability associated with (co-)variation risk, (iii) are strongly serially correlated, and (iv) can increase strongly and nearly instantaneously if new information arrives.
This paper studies the use of performance pricing (PP) provisions in debt contracts and compares accounting-based with rating-based pricing designs. We find that rating-based provisions are used by volatile-growth borrowers and allow for stronger spread increases over the credit period. Accounting-based provisions are employed by opaque-growth borrowers and stipulate stronger spread reductions. Further, a higher spread-increase potential in rating-based contracts lowers the spread at the loan’s inception and improves the borrower’s performance later on. In contrast, a higher spread-decrease potential in accounting-based contracts lowers the initial spread and raises the borrower’s leverage afterwards. The evidence indicates that rating-based contracts are indeed employed for different reasons than accounting-based contracts: the former to signal a borrower’s quality, the latter to mitigate investment inefficiencies.
This paper examines the effect of imperfect labor market competition on the efficiency of compensation schemes in a setting with moral hazard, private information and risk-averse agents. Two vertically differentiated firrms compete for agents by offering contracts with fixed and variable payments. Vertical differentiation between firms leads to endogenous, type-dependent exit options for agents. In contrast to screening models with perfect competition, we find that existence of equilibria does not depend on whether the least-cost separating allocation is interim efficient. Rather, vertical differentiation allows the inferior firm to offer (cross-)subsidizing fixed payments even above the interim efficient level. We further show that the efficiency of variable pay depends on the degree of competition for agents: For small degrees of competition, low-ability agents are under-incentivized and exert too little effort. For large degrees of competition, high-ability agents are over-incentivized and bear too much risk. For intermediate degrees of competition, however, contracts are second-best despite private information.