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Type 2 diabetes mellitus (T2DM) is a major risk factor for advanced liver disease. The aim of this prospective cohort study was to assess the prevalence and associated risk factors of liver fibrosis and cirrhosis in primary care centers participating in the diabetes disease management program (DMP) in Germany. A total of 175 participants with the diagnosis of T2DM were enrolled in two primary care centers. Steatotic liver disease (SLD; hepatic steatosis, ≥275 dB/m), fibrosis (≥8 kPa), and cirrhosis (≥15 kPa) were assessed non‐invasively using vibration‐controlled transient elastography. Multivariable logistic regression analysis was performed to identify clinical predictors of fibrosis and cirrhosis. The AUDIT questionnaire was used to screen for alcohol consumption, and a score ≥8 was considered harmful alcohol consumption. The majority of participants were male (62%), and the median age was 66 years (interquartile range 59; 71). The median body mass index was 31.1 kg/m2, with 58.9% of the participants being obese. Harmful alcohol consumption was prevalent in 8.0% and 20.0% of the entire cohort and in those with cirrhosis, respectively. The prevalence of SLD, fibrosis, and cirrhosis was 77.1%, 42.3%, and 12.0%, respectively. In multivariable logistic regression analysis, obesity, and harmful alcohol consumption were associated with the highest odds of fibrosis (odds ratio [OR] 5.198, 95% confidence interval [CI] 2.269–11.908) and cirrhosis (OR 5.615, 95% CI 1.274–24.756), respectively. The prevalence of fibrosis and cirrhosis in patients seen in the diabetes DMP in Germany is high. Obesity and harmful alcohol consumption increase the risk of fibrosis and cirrhosis in people with T2DM. Screening for advanced liver disease and associated risk factors within the DMP program may reduce the liver disease burden in this high‐risk population.

We predict university dropout using random forests based on conditional inference trees and on a broad German data set covering a wide range of aspects of student life and study courses. We model the dropout decision as a binary classification (graduate or dropout) and focus on very early prediction of student dropout by stepwise modeling students’ transition from school (pre-study) over the study-decision phase (decision phase) to the first semesters at university (early study phase). We evaluate how predictive performance changes over the three models, and observe a substantially increased performance when including variables from the first study experiences, resulting in an AUC (area under the curve) of 0.86. Important predictors are the final grade at secondary school, and also determinants associated with student satisfaction and their subjective academic self-concept and self-assessment. A direct outcome of this research is the provision of information to universities wishing to implement early warning systems and more personalized counseling services to support students at risk of dropping out during an early stage of study.

Globally, health expenditure as a percentage of GDP has increased in recent years, so evaluating the health care systems used in different countries is an important tool for identifying best practices and improving inefficient health care systems. We investigate health system efficiency at the country level based on OECD health data. We focus on several aspects of health care systems to identify specific inefficiencies within them. This information hints at potential policy interventions that could improve specific parts of a country’s health care system. A discussion is provided of ideal-typical evaluations of health systems, ignoring data restrictions, which provide the theoretical basis for an analysis performed under factual data restrictions. This investigation includes health care systems in 34 countries and is based on OECD health data. Health care system efficiency scores are obtained using data envelopment analysis (DEA). Relative productivity measures are calculated based on average DEA prices. Given the severe data limitations involved, instead of performing an all-encompassing analysis of each health care system, we focus on several aspects of each system, performing five partial analyses. For each country, the efficiencies yielded by the five partial analyses varied considerably, resulting in an ambiguous picture of the efficiencies of the various health care systems considered. A synopsis providing comprehensive rankings of the analyzed countries is provided. Analysis of several aspects of the health care systems considered here highlights potential improvements in specific areas of these systems, thereby providing information for policymakers on where to focus when aiming to improve a country’s health care system.

The article discusses the declaration of neutrality by Fribourg and the Swiss Confederation of the 13 cantons in 1674. Topics include the factors behind the declaration, including economic and political pressure, with a particular focus on micro-economic actions, the lack of perspectives, and private interests of the parties involved. Information is offered on the historical background of the declaration of neutrality, such as the role of Swiss soldiers in Spanish duty, the importance of salt from an economic, cultural, and political perspective, as well as Freiburg's relations to France and Spain.

Since attrition in the European Community Household Panel (ECHP) has cumulated to a considerable extent, there is concern that attrition biases empirical analysis. In this paper we compare the performance of four different strategies for estimating an earnings equation in the presence of panel attrition. By splitting the completely observed sample in one wave according to the response behavior of the following wave, we assess empirically the bias of an un-weighted, an inverse probability weighted, a Heckman and a matching estimator through bootstrap methods. Our findings lead us to several conclusions. First, for the example of Mincerian earnings equations, attrition is no matter of great concern when using the ECHP data. Second, the three estimation strategies, which correct for attrition based on estimated response probabilities, reduce the number of significantly biased parameters. Third, the correction strategies strongly increase the variance of the estimates through relying on estimated response probabilities and increase the relative bias. Hence, the reduction of significant biases is rather due to increased variance than due to lower biases. This result is confirmed when comparing the mean square error of the different estimation techniques. Therefore, for the estimation of income equations the uncorrected estimation based on respondents is suggested as the superior estimation strategy.

We analyse the investment behaviour of German firms within the framework of the Q-theory. Because we use anonymous individual firm balance sheet data, no stock market measure of Q is available. The data set contains 1,342 manufacturing firms covering the period 1987 to 1998. Using the approach of Abel&Blanchard and Gilchrist&Himmelberg, a measure of Q is derived through a vector-autoregressive-model to forecast future profits directly.

In dem Beitrag wird das in Deutschland beobachtbare Phänomen der im Vergleich zur Realvermögensbildung überproportionalen Geldvermögensbildung untersucht. Grundlage ist die Finanzierungsrechnung der Deutschen Bundesbank, die eine sektorale Analyse des Vermögensbildungsprozesses erlaubt. Es zeigt sich, daß zu dem gesamtwirtschaftlich beobachtbaren Anstieg der Relation von Geld- und Realvermögensbildung insbesondere die finanziellen Sektoren beitragen, aber auch bei den Produktionsunternehmen eine relativ gestiegene Geldvermögensbildung festzustellen ist. Mittels einer Komponentenanalyse läßt sich bei den Produktionsunternehmen der Anstieg der Relation insbesondere dem starken Anstieg der Kassenhaltung zurechnen. Ergebnisse einer Regressionsanalyse zeigen, daß der Quotient aus Sach- und Geldvermögensrendite (Tobins q) und die Veränderung der Inflationsrate einen signifikant negativen Einfluß auf das Verhältnis von Geld- zu Realvermögensbildung aufweisen.

In verschiedenen empirischen Arbeiten wird für a priori als nicht liquiditätsrestringiert klassifizierte Unternehmen ein signifikant geringerer Einfluß des Cash Flow auf die Investitionstätigkeit festgestellt. In diesem Artikel wird der Frage nach der Sensitivität dieser Befunde in verschiedener Hinsicht nachgegangen. Es werden drei unterschiedliche Operationalisierungen von Tobins Q vorgenommen sowie vier alternative a priori-Klassifikationsvariablen als Indikatoren zur Messung der Liquiditätsrestringiertheit berücksichtigt. Zudem wird die Sensitivität der Ergebnisse bezüglich der verwendeten Klassengrenzen untersucht. Für drei der vier untersuchten Klassifikationsvariablen zeigt sich, daß die als a priori nicht liquiditätsrestringiert eingestuften Sektorjahre einen signifikant geringeren Einfluß des Cash Flow auf die Investitionstätigkeit aufweisen. Zudem zeigt sich eine relativ geringe Sensitivität der Ergebnisse bezüglich der gewählten Klassifikationsgrenzen. Die Operationalisierung von Tobins Q als Renditequotient führt - im Vergleich zu der auf Bestandsgrößen beruhenden - zu weniger signifikanten Ergebnissen.