Helmut Berrer

The Inner Regulation Optimum of the Notarial Profession

This paper introduces the concept of an optimal level of regulation to accomplish welfare maximization in the context of civil law notaries. Regulation is generally considered inevitable to ensure the quality of legal services due to the presence of information asymmetries and externalities in the market for legal services. On theoretical and empirical grounds, we find that complete deregulation does not necessarily lead to a welfare-maximizing outcome, nor does it result in increased competition in the long run. Moreover, we specify conditions for an inner solution to achieve the regulatory optimum in an informationally inefficient market.

Traffic Sensitivity of Long-term Regional Growth Forecasts

We estimate the sensitivity of the regional growth forecast in the year 2002 due to expected changes in the travel time (TT) matrix. We use a dynamic panel model with spatial effects where the spatial dimension enters the explanatory variables in different ways. The spatial dimension is based on geographical distance between 227 cells in central Europe and the travel time matrix based on average train travel times. The regressor variables are constructed by a) the average past growth rates, where the travel times are used as weights, b) the average travel times across all cells (made comparable by index construction), c) the gravity potential variables based on GDP per capita, employment, productivity and population and d) dummy variables and other socio-demographic variables. We find that for the majority of the cells the relative differences in growth for the year 2020 is rather small. But there are differences as how many regions will benefit from improved train networks: GDP, employment, and population forecasts respond differently.

Stochastic Ranking and the Volatility “Croissant”: A Sensitivity Analysis of Economic Rankings

Rankings of countries are calculated using I indicator variables. Clearly, any ranking based on an index depends on the weights used, and therefore we conduct a sensitivity analysis on the weights of the index to obtain a measure for the volatility of the performance rankings. The weights are simulated from uniform and beta distributions on the simplex. As a result we observe a volatility “croissant”: Countries in the top and the bottom of the ranking are less volatile than in the middle of the ranking. The methodology is shown for the standardized performance ranking (SPR) and the rank performance ranking (RPR).