873 publications from this institution
Wasserstoff ist Grundstoff der Chemietechnik und wird in der chemischen Industrie seit Jahrzehnten großtechnisch sicher beherrscht. Herstellung, Speicherung, Transport und Nutzung von Wasserstoff sind dort im wesentlichen Routine.
Faced with the problem that conventional multidimensional fixed effects models only focus on unobserved heterogeneity, but ignore any potential cross-sectional dependence due to network interactions, we introduce a model of trade flows between countries over time that allows for network dependence in flows, based on sociocultural connectivity structures. We show that conventional multidimensional fixed effects model specifications exhibit cross-sectional dependence between countries that should be modeled to avoid simultaneity bias. Given that the source of network interaction is unknown, we propose a panel gravity model that examines multiplenetwork interaction structures, using Bayesian model probabilities to determine those most consistent with the sample data. This is accomplished with the use of computationally efficient Markov Chain Monte Carlo estimation methods that produce a Monte Carlo integration estimate of the log-marginal likelihood that can be used for model comparison. Application of the model to a panel of trade flows points to network spillover effects, suggesting the presence of network dependence and biased estimates from conventional trade flow specifications. The most important sources of network dependence were found to be membership in trade organizations, historical colonial ties, common currency, and spatial proximity of countries.
Information about the taxonomic and geographic scope of this Excursion Flora to be published soon and on significant features of vegetation and flora of this region is provided. Some characteristic endemic taxa are mentioned. – Problems of writing an excursion Flora are discussed with focus on hints for improving keys in order to produce a user-friendly book.
This paper presents a methodology for neural spatial interaction modelling. Particular emphasis is laid on design, estimation and performance issues in both cases, unconstrained and singly constrained spatial interaction. Families of classical neural network models, but also less classical ones such as product unit neural network models are considered. Some novel classes of product unit and summation unit models are presented for the case of origin or destination constrained spatial interaction flows. The models are based on a modular connectionist architecture that may be viewed as a linked collection of functionally independent neural modules with identical feedforward topologies, operating under supervised learning algorithms. Parameter estimation is viewed as Maximum Likelihood (ML) learning. The nonconvex nature of the loss function makes the Alopex procedure, a global search procedure, an attractive and appropriate optimising scheme for ML learning. A benchmark comparison against the classical gravity models illustrates the superiority of both, the unconstrained and the origin constrained, neural network model versions in terms of generalization performance measured by Kullback and Leibler`s information criterion. Hereby, the authors make use of the bootstrapping pairs approach to overcome the largely neglected problem of sensitivity to the specific splitting of the data into training, internal validation and testing data sets, and to get a better statistical picture of prediction variability of the models. Keywords: Neural spatial interaction models, origin constrained or destination constrained spatial interaction, product unit network, Alopex procedure, boostrapping, benchmark performance tests.
In the past decade the social sciences have seen an upsurge of interest in analysing multidimensional contingency tables using log-linear models. Two broad families of log-linear models may be distinguished: the family of conventional models and the family of unconventional models (that is, quasi-log-linear and hybrid models). In this paper a brief review of such models is presented and some linkage to the class of generalised linear models suggested by Nelder and Wedderburn is provided. The great potential of log-linear models for spatial analysis is illustrated in applying conventional and unconventional models in a migration context to identify intertemporal stability of migration patterns. The problem that the effective units migrating are households rather than individuals is coped with by postulating a compound Poisson sampling scheme.
The paper provides an explanation of the mechanisms underlying trade roots of the contagion effects emanating from the recent turmoils. It is argued that under demand uncertainty risk averse behavior of firms provides a basis for international trade. The paper shows by means of a simple two-country model that risk averse firms operating in perfectly competitive markets with uncertainty of demand tend to diversify markets what gives a basis for international trade in identical commodities even between identical countries. It is shown that such trade may be welfare improving despite efficiency losses due to cross-hauling and transportation costs. The analysis reveals that change of the expectations concerning market conditions caused by the turmoil in the neighbor country (i.e., shift in the perception of market conditions) may lead to macroeconomic destabilization (increase in price level and unemployment, worsening of terms of trade, and deterioration of trade balance).
No abstract is provided for this article.
This chapter attempts to assemble and systematise empirical observations of the diffusion of IT-applications to various sectors and locations in several countries. The notion IT refers to information technology, which comprises microprocessors and their electronic...
No abstract is provided for this article.
The focus of this study is on regional knowledge production activities in Europe, with special emphasis on the interplay between agglomeration and network effects. As increasingly considered in economic geography and regional science in the recent past, regional knowledge production activities, on the one hand, still remain geographically bounded; on the other hand, knowledge production activities have become increasingly interwoven and internationalized, emphasizing the crucial importance of region-external knowledge sources for a region’s knowledge production capacity. The objective of the study is to estimate to what extent agglomeration and network effects influence knowledge production activities at the level of European regions. We use an extended regional knowledge production function framework as basis for the study, and derive a spatial Durbin model (SDM) relationship that can be used for empirical testing. The European coverage is achieved using 241 NUTS-2 regions covering the EU-25 member states. The dependent variable, knowledge production activity, is measured in terms of patent counts at the regional level in the time period 1998-2008, using patents applied at the European Patent Office (EPO). The independent variables include an agglomeration index, measured in terms of population density, and the regional participation intensity in the European network of R&D cooperation, measured in terms of the number of participations of a region in R&D joint ventures funded by the European Commission under the heading of the EU Framework programs (FPs). By this we are able to estimate the distinct effects of network participation and agglomeration on regional knowledge production. In our modeling framework, we further control for total regional R&D expenditures as widely used in regional knowledge production function frameworks and its empirical applications. In estimating the effects, we implement a panel version of the standard SDM that controls for spatial autocorrelation as well as individual heterogeneity across regions. The specification incorporates a spatial lag of the dependent variable as well as spatial lags of the independent variables. This allows for the estimation of spatial spillovers of agglomeration and network effects from neighboring regions by calculating scalar summary measures of impacts. The estimation results are expected to provide sketches of policy implications in a European and regional policy context. JEL Classification: R11, O31, C21 Keywords: Regional knowledge production, Agglomerations effects, R&D networks, European Framework Programs, knowledge production function, panel spatial Durbin model
Spatial interaction models approximate mean interaction frequencies between origin and destination locations by using origin-specific, destination-specific and spatial separation information. The focus is on models that are based on the theory of feedforward neural...
The explosion of activities and requirements associated with the production, processing and transfer of information is increasingly being matched by a profileration and diversification of new telecommunication media for transmitting information, including text processing and transmission services such as facsimile transmission, videotex, teleconference services, electronic mail etc. Nevertheless, the telephone is still - by far - the most important telecommunication service. The paper results from ESF-research undertaken within the Network on European Communication and Transport Activity Research (NECTAR) and relates to telephone communication undertaken for the Netherlands by Rietveld and Jansen (1990) and Switzerland by Rossera (1990). The current study focuses on the Austrian case and relies on data measured by the Austrian PTT in 1991, in terms of erlangs, an internationally widely used and reliable measure of telecommunication contact intensity. The data refer to the total telecommunication traffic on the public network. Due to technical reasons oral communication can not be distinguished from other services such as data transmission, transfer of documents and text (facsimile) etc. But the demand for such new telecommunication services is still at a very modest level in Austria. The paper addresses two major issues. First an attempt is made to explore the factors influencing the spatial pattern of domestic telephone traffic in Austria. The econometric approach applied to this problem belongs to the class of spatial interaction models explaining a telephone communication flow from a region i to a region j by three types of factors, factors associated with the region of origin, factors associated with the region of destination and factors associated with origin-destination pairs (separation factors). In using the spatial interaction modelling approach in telephone traffic analysis various choices need to be made about how the above mentioned factors should be defined. To have confidence in the model results it is desirable that its interpretation is insensitive to the particular choices made. Whether this is so, will be investigated for several potential sources of variation in model performance.
Club-convergence analysis provides a more realistic and detailed picture about regional income growth than traditional convergence analysis. This paper presents a spatial econometric framework for club-convergence testing that relates the concept of club-convergence to the notion of spatial heterogeneity. The study provides evidence for the club-convergence hypothesis in cross-regional growth dynamics from a pan-European perspective. The conclusions are threefold. First, we reject the standard Barro-style regression model which underlies most empirical work on regional income convergence, in favour of a two regime [club] alternative in which different regional economies obey different linear regressions when grouped by means of Getis and Ord's (1992) local clustering technique. Second, the results point to a heterogeneous pattern in the pan-European convergence process. Heterogeneity appears in both the convergence rate and the steady-state level. But, third, the study also reveals that spatial error dependence introduces an important bias in our perception of the club-convergence and shows that neglection of this bias would give rise to misleading conclusions.
No abstract is provided for this article.
Spatial interaction models of the gravity type are used in conjunction with sample data on flows between origin and destination locations to analyse international and interregional trade, commodity, migration and commuting patterns. The focus is on the classical log-normal model version and spatial econometric extensions that have recently appeared in the literature. These new models replace the conventional assumption of independence between origin-destination flows with formal approaches that allow for spatial dependence in flow magnitudes. The paper also discusses problems that arise in applied practice when estimating (log-normal) spatial interaction models.
