In Krisenzeiten wie der aktuellen Corona-Pandemie ist der Bedarf an statistischen Daten am aktuellen Rand (Nowcast) zur frühzeitigen Abschätzung der wirtschaftlichen Auswirkungen besonders hoch. Der neu entwickelte experimentelle Frühindikator zur Umsatzentwicklung aus den monatlichen...

In this paper we introduce four new learning models: impulse balance learning, impulse matching learning, action-sampling learning, and payoff-sampling learning. With this models and together with the models of self- tuning EWA learning and reinforcement learning, we conduct simulations over 12...

In this paper a statistical model combining duration of search for an ap­prentice vacancy and choice of entering a training programme aiming at help­ing students finding an vacancy is presented. Using conventional duration models yields a negative effect on durations of search from the...

Bayesian Model Averaging (BMA) provides a coherent mechanism to address the problem of model uncertainty. In this paper we extend the BMA framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited Information...

In this experimental study we examine behavior relating to voluntary contributions to reduce expected losses associated, for example, with the occurrence of natural disasters or major industrial accidents. We ask subjects to allocate tokens between a private investment and a public investment....

We study herd behavior in a laboratory financial market with financial market professionals. We compare two treatments, one in which the price adjusts to the order flow so that herding should never occur, and one in which event uncertainty makes herding possible. In the first treatment, subjects...

We propose using a Bayesian time-varying coefficient model estimated with Markov chain-Monte Carlo methods to measure contagion empirically. The proposed measure works in the joint presence of heteroskedasticity and omitted variables and does not require knowledge of the timing of the crisis. It...

This paper attempts to identify robust patterns of cross-country growth behavior in the world as a whole and Africa. It employs a novel methodology that incorporates a dynamic panel estimator, and Bayesian Model Averaging to explicitly account for model uncertainty. The findings indicate that:...

This paper examines linkages across North America by estimating the size of spillovers from the major regions of the world-the United States, euro area, Japan, and the rest of the world-to Canada and Mexico, and decomposing the impact of these spillovers into trade, commodity price, and...

This paper develops the theoretical background for the Limited Information Bayesian Model Averaging (LIBMA). The proposed approach accounts for model uncertainty by averaging over all possible combinations of predictors when making inferences about the variables of interest, and it...