Estimating the uncertainty of relative risk aversion

This note reports estimates of the coefficient of relative risk aversion, using a method recently proposed by Azar (2006). In contrast to his work, the complete information of US stock return data over the period 1926 to 2002 is utilized. Moreover, a bootstrap procedure is applied to estimate the associated uncertainty. Point estimates close to 3.5 are obtained. However, ranging from 1.4 to 7.1, the 95% confidence interval is wide.

A Gas Chromatography Mass Spectrometry-Based Method for the Quantification of Short Chain Fatty Acids

Short Chain Fatty Acids (SCFAs) are produced by the gut microbiota and are present in varying concentrations in the intestinal lumen, in feces but also in the circulatory system. By interacting with different cell types in the body, they have a great impact on host metabolism and their exact quantification is indispensable. Here, we present a derivatization-free method for the gas chromatography mass spectrometry (GC-MS) based quantification of SCFAs in plasma, feces, cecum, liver and adipose tissue. SCFAs were extracted using ethanol and concentrated by alkaline vacuum centrifugation. To allow volatility for separation by GC, samples were acidified with succinic acid. Analytes were detected in selected ion monitoring (SIM) mode and quantified using deuterated internal standards and external calibration curves. Method validation rendered excellent linearity (R2 > 0.99 for most analytes), good recovery rates (95–117%), and good reproducibility (RSD: 1–4.5%). Matrix effects were ruled out in plasma, feces, cecum, liver and fat tissues where most abundant SCFAs were detected and accurately quantified. Finally, applicability of the method was assessed using samples derived from conventionally raised versus germ-free mice or mice treated with antibiotics. Altogether, a reliable, fast, derivatization-free GC-MS method for the quantification of SCFAs in different biological matrices was developed allowing for the study of the (patho)physiological role of SCFAs in metabolic health

An econometric analysis of the main components of M3 in the Euro area

C22, C32, E41,

Das IMM – Ein makroökonometrisches Mehrländermodell

In diesem Beitrag wird ein internationales makroökonometrisches Modell präsentiert, das Deutschland, Großbritannien, Frankreich und Italien als separate Ländermodule enthält (Big4-Modell). Die Modellstruktur basiert auf dem volkswirtschaftlichen Kreislaufschema. Die Verhaltensbeziehungen sind in Fehlerkorrekturform für das Angebot und die Nachfrage auf den Güter- und Faktormärkten, die Einkommensverteilung sowie für die Preis-, Zins- und Wechselkursentwicklung spezifiziert. Zudem wird der öffentliche Sektor berücksichtigt, der insbesondere für Deutschland detailliert dargestellt ist. Das Modell liegt den kurz- und mittelfristigen Prognosen der gesamtwirtschaftlichen Entwicklung zugrunde, die das DIW Berlin kontinuierlich durchführt. Darüber hinaus wird das Modell zur Simulation der Effekte alternativer wirtschaftspolitischer Maßnahmen eingesetzt. Abstract We present a macroeconometric model for the large EU economies, i.e. Germany, the UK, France and Italy (Big4 model). The general model structure is based on the system of national accounts. Behavioural relationships are specified in error correction form for the supply and demand side at product and factor markets, income distribution, and the evolution of prices, interest and exchange rates. In addition, the public sector is discussed in detail especially for the German economy. The model provides a consistent framework for the regular short and medium term forecasts at DIW Berlin. Moreover, the model is used to simulate the effects of alternative economic policy options. JEL Code: C3, C5, F0