The Camp View of Inflation Forecasts

Analyzing sample moments of survey forecasts, we derive disagreement and un- certainty measures for the short- and medium term inflation outlook. The latter provide insights into the development of inflation forecast uncertainty in the context of a changing macroeconomic environment since the beginning of 2008. Motivated by the debate on the role of monetary aggregates and cyclical variables describing a Phillips-curve logic, we develop a macroeconomic indicator spread which is assumed to drive forecasters’ judgments. Empirical evidence suggests procyclical dynamics between disagreement among forecasters, individual forecast uncertainty and the macro-spread. We call this approach the camp view of inflation forecasts and show that camps form up whenever the spread widens.monetary policy, survey forecasts, inflation uncertainty, heterogenous beliefs and expectations, monetary aggregates

Dissipative Dynamics with Trapping in Dimers

The trapping of excitations in systems coupled to an environment allows to study the quantum to classical crossover by different means. We show how to combine the phenomenological description by a non-hermitian Liouville-von Neumann Equation (LvNE) approach with the numerically exact path integral Monte-Carlo (PIMC) method, and exemplify our results for a system of two coupled two-level systems. By varying the strength of the coupling to the environment we are able to estimate the parameter range in which the LvNE approach yields satisfactory results. Moreover, by matching the PIMC results with the LvNE calculations we have a powerful tool to extrapolate the numerically exact PIMC method to long times.Comment: 5 pages, 2 figure

A multivariate extension of the Lorenz curve based on copulas and a related multivariate Gini coefficient

We propose an extension of the univariate Lorenz curve and of the Gini coefficient to the multivariate case, i.e., to simultaneously measure inequality in more than one variable. Our extensions are based on copulas and measure inequality stemming from inequality in each single variable as well as inequality stemming from the dependence structure of the variables. We derive simple nonparametric estimators for both instruments and exemplary apply them to data of individual income and wealth for various countries

The virus of polarization:online debates about Covid-19 in Germany

To what extent do online debates display features of political polarization and in how far does polarization pose a problem for democracy? We zoom in on affective polarization: the formation of societal groups with hostile feelings towards each other, arguing that affective polarization is particularly problematic for democracy if it features elements of political intolerance, which undermines key tenets of even the most conflict-prone theories of democracy. While affective polarization has been on the rise in several countries, Germany has been considered to be a country with low, and even declining levels of affective polarization. But does this still hold true during the Covid-19 pandemic, which saw a rapid rise in conspiracy theories? Based on a qualitative discourse analysis of online debates about Covid-19 on the Facebook platforms of a mainstream and a non-mainstream German media outlet, we find strong traces of affective polarization on both platforms, involving clear indications of political intolerance. Our findings suggest that the democratic discourse is threatened by the nature of online debates about Covid-19, and it is threatened not only by anti-rationalist conspiracists at the ideological extremes but also by the intolerance of more moderate rationalists at the centre of the political spectrum.</p

A multivariate extension of the Lorenz curve based on copulas and a related multivariate Gini coefficient

We propose an extension of the univariate Lorenz curve and of the Gini coefficient to the multivariate case, i.e., to simultaneously measure inequality in more than one variable. Our extensions are based on copulas and measure inequality stemming from inequality in every single variable as well as inequality stemming from the dependence structure of the variables. We derive simple nonparametric estimators for both instruments and apply them exemplary to data of individual income and wealth for various countries

Role of CDOs in the Digital Transformation of SMEs and LSEs - An Empirical Analysis

In recent years, the economy and companies of all sizes operating within it have undergone a progressive transformation that implied increased market complexity and dominance of the buyer market. This development is the result of the third industrial revolution and has been fostered during the last 40 years by major innovations in digital computer technology. This first digital revolution resulted in the development of the first computers and the associated entry of new electronics and information and communication technology (ICT) in companies being able to automate production processes and make them more efficient. Digitalization means not only the change of individual processes rather the fundamental transformation of entire business areas or the entire business model. In order not only to master, but also to cope with, the challenges of digital transformation, companies need a member in the management board that provides specific expertise and encourages these digital changes. In the process, the position of Chief Digital Officer (CDO) has been created precisely to meet these challenges of the digital transformation of a business model. The present work is based on various case studies analyzing what role the CDO plays in the framework of digital transformation in various company sizes (SMEs and LSEs). In particular, the responsibility, specific obligations and rights and the role - namely, functions and tasks - and the change in the role have been examined since taking over the position

A multivariate extension of the Lorenz curve based on copulas and a related multivariate Gini coefficient

We propose an extension of the univariate Lorenz curve and of the Gini coefficient to the multivariate case, i.e., to simultaneously measure inequality in more than one variable. Our extensions are based on copulas and measure inequality stemming from inequality in every single variable as well as inequality stemming from the dependence structure of the variables. We derive simple nonparametric estimators for both instruments and apply them exemplary to data of individual income and wealth for various countries.Comment: 17 pages,5 figure