This paper models the competition of user networks as a continuous-time Markov process. It presents a dynamic version of the Discrete Choice Analysis with state-dependent choice probabilities. Among other things, we show that the network competition can be characterized by the coexistence of...

This paper presents theoretical models and their empirical results for the return and variance dynamics of German stocks. A factor structure is used in order to allow for a parsimonious modeling of the first two moments of returns. Dynamic factor models with GARCH dynamics (GARCH(1,1)-M,...

Problems related to labor migration on a large scale in South-North as well as in East-West direction are high on the agenda. This papers presents an endogenous growth model for two regions with human capital formation as the engine of growth. The model is used to analyze the growth (rate)...

This paper investigates the Information content of daily trading volume with respect to the long-run or high persistent and the short-run or transitory components of the volatility of daily stock market returns using bivariate mixture models. For this purpose, the Standard bivariate mixture...

In this paper we examine small sample properties of a generalized method of moments (GMM) estimation using Monte Carlo simulations. We assume that the generated time series describe the stochastic variance rate of a stock index. We use a mean reverting square-root prooess to simulate the...

The cost-effectiveness of unilateral emission abatement can be seriously hampered by emission leakage. We assess three widely-discussed proposals for leakage reduction targeted at energy-intensive and trade-exposed industries: border tax adjustments, output-based allocation and industry...

We develop and test a model of social comparison in which individuals gain status through pro-social behavior (competitive altruism) and in which they endogenously choose the reference group and associated reference standard involved in signaling status (reference group selection). In our...