Regional economic integration and factor mobility in unified Germany

The massive movement of capital and labor in opposite directions is the most striking characteristic of economic integration of Eastern and Western Germany. Beyond that, wage-setting behavior during the early years of unification and massive public social transfers have affected the transition path of the Eastern economy. In this paper, I set up a two-region open economy model with capital and labor mobility, wage-setting behavior, and public social transfers to explain major empirical trends of the German integration episode. I show that the model is able to replicate aggregate migration pattern in unified Germany and that wage-setting behavior has delayed labor productivity convergence between both German regions, whereas public social transfers have reduced the effect of wage setting on East-West net migration

Privacy Discrimination: What it is and why it matters

We argue that online companies are able to exploit users’ varying levels of privacy needs. We show that by employing data analytics methods on a comparatively small amount of data it is possible to predict how high information privacy concerns of specific users are. We argue that online companies might be able to introduce “privacy discrimination”, in the sense that they might apply varying levels of privacy protection to users, based on their privacy concerns. Users indifferent about privacy could be presented with limited privacy options, adjusted terms and conditions or might be driven to disclose more personal information

Business Model Innovation and Stakeholder: Exploring Mechanisms and Outcomes of Value Creation and Destruction

Given the objective of the focal firm to generate value for stakeholders, this research aims at assessing mechanisms and outcomes for value creation and destruction between business model innovation (BMI) and stakeholders. To achieve this goal, we conduct a systematic literature review and apply grounded theory as coding scheme. Taking frequent mechanisms and outcomes into account, we construct a conceptual framework and pioneer theory building. As main result, we identify BMI creating economic return for third parties and product/service access for customers. Both outcomes are based on the mechanism of altering resources and processes. In contrast, analyzing stakeholder’s main influence, we find management creating strategic orientation by providing know-how. Our research agenda emphasizes the design of BMI from an ecosystem perspective and the destructive consequences of BMI. While the ecosystem level of analysis provides new insights into the concept, investigating negative impacts contributes to a more holistic understanding of BMI

Does Public Education Expansion Lead to Trickle-Down Growth?

The paper revisits the debate on trickle-down growth in view of the widely discussed evolution of the earnings and income distribution that followed a massive expansion of higher education. We propose a dynamic general equilibrium model to dynamically evaluate whether economic growth triggered by an increase in public education expenditure on behalf of those with high learning ability eventually trickles down to low-ability workers and serves them better than redistributive transfers. Our results suggest that, in the shorter run, low-skilled workers lose. They are better off from promoting equally sized redistributive transfers. In the longer run, however, low-skilled workers eventually benefit more from the education policy. Interestingly, although the expansion of education leads to sustained increases in the skill premium, income inequality follows an inverted U-shaped evolution

Cosmic expansion history from SNe Ia data via information field theory -- the charm code

We present charm (cosmic history agnostic reconstruction method), a novel inference algorithm that reconstructs the cosmic expansion history as encoded in the Hubble parameter $H(z)$ from SNe Ia data. The novelty of the approach lies in the usage of information field theory, a statistical field theory that is very well suited for the construction of optimal signal recovery algorithms. The charm algorithm infers non-parametrically $s(a)=\ln(\rho(a)/\rho_{\mathrm{crit}0})$, the density evolution which determines $H(z)$, without assuming an analytical form of $\rho(a)$ but only its smoothness with the scale factor $a=(1+z)^{-1}$. The inference problem of recovering the signal $s(a)$ from the data is formulated in a fully Bayesian way. In detail, we have rewritten the signal as the sum of a background cosmology and a perturbation. This allows us to determine the maximum a posteriory estimate of the signal by an iterative Wiener filter method. Applying charm to the Union2.1 supernova compilation, we have recovered a cosmic expansion history that is fully compatible with the standard $\Lambda$CDM cosmological expansion history with parameter values consistent with the results of the Planck mission

Scientific publication activity during COVID-19 shutdown

(...