Analysing Perceived Downside Risk: the Component Value‐at‐Risk Framework

Multinational companies face increasing risks arising from external risk factors, e.g. exchange rates, interest rates and commodity prices, which they have learned to hedge using derivatives. However, despite increasing disclosure requirements, a firm's net risk profile may not be transparent to shareholders. We develop the ‘Component Value‐at‐Risk (VaR)’ framework for companies to identify the multi‐dimensional downside risk profile as perceived by shareholders. This framework allows for decomposing downside risk into components that are attributable to each of the underlying risk factors. The firm can compare this perceived VaR, including its composition and dynamics, to an internal VaR based on net exposures as it is known to the company. Any differences may lead to surprises at times of earnings announcements and thus constitute a litigation threat to the firm. It may reduce this information asymmetry through targeted communication efforts.     

Öffentliches und Geheimes

In the second half of 2009, the entire media agenda in Germany was dominated by the swine flu, next to the German Federal Parliament elections. Criticism was voiced in the media against the pharmaceutical industry for lobbying the nationwide swine flu vaccination, which was widely considered nothing but a product of the industry’s lobbying power. In order to avoid the usual interviews with lobbyists, we attempted to apply a new methodological framework approach in analysing lobbying processes and key stakeholders in the public sphere—and outside. Crucial to the diversified approach, which involves quantitative content analysis of media coverage and press releases, are interviews with journalists, lobbyists’ network analysis and internet research on biographies. Although a conspiracy could not be conclusively proven, the results do indicate associations that validate the criticism of the industry’s lobbying activities.     

Die reale Zahlungsbereitschaft für Klimaschutz

Der Klimawandel und das globale ?ffentliche Gut Klimaschutz genie?en gro?e Aufmerksamkeit in der ?ffentlichen Debatte. Klimaschutz verursacht jedoch Kosten und es stellt sich die Frage, was die Menschen in Deutschland tats?chlich für Klimaschutz bereit sind zu zahlen. Dieser Beitrag stellt eine neue Studie zur Ermittlung der realen Zahlungsbereitschaft für Klimaschutz vor und diskutiert die Ergebnisse aus der Perspektive der Klimapolitik.     

Zur Definition und Schätzung von Mittelwerten für zufällige Variable auf der Sphäre

Zusammenfassung Diese Arbeit ist die gekürzte Fassung einer Dissertation, die vom Autor 1968 unter gleichem Titel in Würzburg ver?ffentlicht wurde. Es ist nicht sinnovll, Mittelwerte für zuf?llige Variable auf der Sph?re in der üblichen Weise, wie z. B. für zuf?llige Variable auf der reellen Achse, zu definieren. W. Uhlmann [1964] bediente sich entscheidungstheoretischer Begriffe, um für zirkul?re zuf?llige Variable mittlere Winkel zu definieren, die ihre Richtung unabh?ngig von der Wahl der Null-Richtung beibehalten. Die analoge Invarianzeigenschaft wird für alle hier definierten Mittelwertbegriffe (mittlere Richtung, mittlerer Gro?kreis, Mittelachse, Mittelkreis) gesichert, indem einfache Forderungen an die zu verwendenden Verlustfunktionen gestellt werden. Da als Sch?tzungen für diese Mittelwerte stets die entsprechenden Mittelwerte der empirischen Verteilung auftreten, haben diese auch die gleiche Invarianzeigenschaft. Um die Diskrepanz zwischen einer solchen Sch?tzung und dem zu sch?tzenden Mittelwert zu messen, werden neue Verlustfunktionen eingeführt. Es wird gezeigt, da? alle eingeführten Sch?tzungen bezüglich mindestens einer Verlustfunktion unverf?lscht sind, d. h. der erwartete Verlust wird minimal, wenn wir aus allen in Frage kommenden Objekten gerade den betreffenden Mittelwert gesch?tzt werden lassen. Dieser minimale Verlust wird die Dispersion der Sch?tzung bezüglich dieser Verlustfunktion genannt. Es wird bewiesen, da? alle ermittelten Dispersionen mindestens wien ^−1/2 gegen Null gehen, wenn n gegen Unendlich strebt.

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Summary This paper is shortened from an equally entitled dissertation which has been published by the author in 1968 at Würzburg. For random variables on the sphere it would make no sense to define means in the usual way as it is done e. g. for random variables on the real line. Introducing concepts of decision theory,W. Uhlmann [1964] defined mean angles for circular random variables the direction of which does not depend on the choice of the zero direction. Setting up simple conditions for the loss functions to be used, we ensure that all the means defined in the paper (mean directions, mean great circles, mean axes, mean circles) have the analogous invariance property. The estimators of these means are always the corresponding means of the empirical distribution, defined with respect to the same loss function and therefore they have the invariance property too. To measure the discrepance between an estimator and the estimated mean, new loss functions are introduced. It is shown that all the established estimators are unbiased with respect to at least one loss function, i. e. the expected loss is a minimum, if we take just the mean from all the things in question to be estimated by the regarded estimator. This minimum loss is called the dispersion of the estimator with respect to this loss function. It is proved, that all the calculated dispersions go to zero at least asn ^−1/2, ifn tends to infinity.

     

Competition among hospitals

We examine competition in the hospital industry, in particular the effect of ownership type (for-profit, not-for-profit, government). We estimate a structural model of demand and pricing in the hospital industry in California, then use the estimates to simulate the effect of a merger. California hospitals in 1995 face an average price elasticity of demand of -4.85. Not-for-profit hospitals face less elastic demand and act as if they have lower marginal costs. Their prices are lower than those of for-profits, but markups are higher. We simulate the effects of the 1997 merger of two hospital chains. In San Luis Obispo County, where the merger creates a near monopoly, prices rise by up to 53%, and the predicted price increase would not be substantially smaller were the chains not-for-profit.     

Evolution of networks—an experimental analysis

It is the main aim of our paper to study network formation in experimental setups in discrete and continuous time. Our design is inspired by the theoretical model on network formation by Bala and Goyal (Econometrica, 68(5): 1181–1229, 2000) as well as the experiments by Callander and Plott (J. Public Econ., 89: 1469–1495, 2005) and Falk and Kosfeld (IEW Working Paper, University of Zürich, Zürich, Switzerland, No. 146, 2003). In particular, we analyze the role of star-shaped networks which are strict Nash-equilibria of the corresponding network formation game. Our experimental results show that strict Nash networks prove to be a good indicator for predicting network formation, particularly in continuous time. In explaining our results, it turns out that, among others, the complexity in coordinating on stars, the inequity aversion against unequal payoff distribution in the network, and the groups’ degrees of activity are the most important determinants for the formation of strict Nash networks.      

Flexible estimation of price response functions using retail scanner data

Kalyanam and Shively [1998. Estimating irregular pricing effects: a stochastic spline regression approach. Journal of Marketing Research 35 (1), 16–29] and van Heerde et al. [2001. Semiparametric analysis to estimate the deal effect curve. Journal of Marketing Research 38 (2), 197–215] have demonstrated the usefulness of nonparametric regression to estimate pricing effects flexibly. The empirical results of these two studies, however, also revealed that nonparametric regression may suffer from too much flexibility leading to nonmonotonic shapes for price effects. In this paper, we show how the problem of nonmonotonicity can be dealt with without losing the power of flexible estimation techniques. We propose a semiparametric approach based on Bayesian P-splines with monotonicity constraints imposed on own- and cross-price effects. In an empirical application, we illustrate that flexible estimation of own- and cross-price effects can improve the predictive validity of a sales response model substantially, even when price response curves were constrained to show a monotonic shape, as suggested by economic theory. We also discuss the consequences from an unconstrained estimation of price effects.