A new model based analysis method for regional economic development effects

It is the aim of this paper to provide a new method for the estimation and evaluation of long time ago implemented transport infrastructure and policy measures. This requires before and after data on a small spatial aggregation level. The main problem consists in the separation of the overall economic development, from the spatial impact of the implemented measures. Therefore, timeseries data of economic growth seem to be necessary, at least for some selected variables. However, longterm data series are rather difficult to find, and data uncertainties may lead to fluctuations in the estimated growth rates. In addition, it is an empirical fact that the spatial development of a region, even without any specific infrastructure investment, is not homogeneous. In order to take into account the usual data restrictions and uncertainties as well as the further requirements mentioned above, the spatial dependency and the growth effect will be modeled. It seems to be reasonable, that the rate of change of the regional growth factor depends on the kind of the infrastructure investment implemented, as well as on the 'distances' of the zone is under consideration to different appropriate junction points (e.g. stops of a train, exits to a motorway,...) to the infrastructure. Furthermore, it is reasonable to assume, that the impact of the implemented infrastructure exhibits a strong distance dependence. Of course, a specific investment may have different impacts on the considered socioeconomic indicators. The different spatial growth factors and the parameters describing the spatial impact of the infrastructure investment will be estimated via a nonlinear optimization procedure. The method is applied to the determination and separation of the economic development effects of a light rail system and of a motorway in the Stuttgart Region.

A new model based analysis method for regional economic development effects

It is the aim of this paper to provide a new method for the estimation and evaluation of long time ago implemented transport infrastructure and policy measures. This requires before and after data on a small spatial aggregation level. The main problem consists in the separation of the overall economic development, from the spatial impact of the implemented measures. Therefore, timeseries data of economic growth seem to be necessary, at least for some selected variables. However, longterm data series are rather difficult to find, and data uncertainties may lead to fluctuations in the estimated growth rates. In addition, it is an empirical fact that the spatial development of a region, even without any specific infrastructure investment, is not homogeneous. In order to take into account the usual data restrictions and uncertainties as well as the further requirements mentioned above, the spatial dependency and the growth effect will be modeled. It seems to be reasonable, that the rate of change of the regional growth factor depends on the kind of the infrastructure investment implemented, as well as on the 'distances' of the zone is under consideration to different appropriate junction points (e.g. stops of a train, exits to a motorway,...) to the infrastructure. Furthermore, it is reasonable to assume, that the impact of the implemented infrastructure exhibits a strong distance dependence. Of course, a specific investment may have different impacts on the considered socioeconomic indicators. The different spatial growth factors and the parameters describing the spatial impact of the infrastructure investment will be estimated via a nonlinear optimization procedure. The method is applied to the determination and separation of the economic development effects of a light rail system and of a motorway in the Stuttgart Region

Balanced gain and loss in Bose-Einstein condensates without PT symmetry

Balanced gain and loss renders the mean-field description of Bose-Einstein condensates PT symmetric. However, any experimental realization has to deal with unbalancing in the gain and loss contributions breaking the PT symmetry. We will show that such an asymmetry does not necessarily lead to a system without a stable mean-field ground state. Indeed, by exploiting the nonlinear properties of the condensate, a small asymmetry can stabilize the system even further due to a self-regulation of the particle number.Comment: 7 pages, 6 figure