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This paper offers an exploratory investigation of the effects of inbound commuter flows on employment in regional labour markets in Germany. For this purpose, the paper distinguishes three main channels that may transmit the effects concerned: a crowding-out mechanism and two labour demand effects—namely, an aggregate demand effect and a positive externality on vacancy creation. The results bring to light that, on the whole, commuter flows have a positive and robust effect on both employment and the number of jobs in the receiving labour market districts, but a distinctly negative effect on the share of jobs filled by resident workers. The implications of the results are interpreted and, finally, ways are suggested in which the analysis could be improved and expanded. [ABSTRACT FROM PUBLISHER]

In this paper, we present a review of various computational experiments concerning neural network (NN) models developed for regional employment forecasting. NNs are nowadays widely used in several fields because of their flexible specification structure. A series of NN experiments is presented in the paper, using two data sets on German NUTS-3 districts. Individual forecasts are computed by our models for each district in order to answer the following question: How relevant are NN parameters in comparison to NN structure? Comprehensive testing of these parameters is limited in the literature. Building on different specifications of NN models-in terms of explanatory variables and NN structures-we propose a systematic choice of NN learning parameters and internal functions by means of a sensitivity analysis. Our results show that different combinations of NN parameters provide significantly varying statistical performance and forecasting power. Finally, we note that the sets of parameters chosen for a given model specification cannot be light-heartedly applied to different or more complex models. [ABSTRACT FROM AUTHOR]

The spatial activity patterns of firms in a multi-regional system are closely connected with the structure and evolution of regional labour markets. Based on an extensive data set (cross-section) on commuting flows in Germany, this paper aims to identify the relationship between entrepreneurial activity and spatial labour markets, by employing in particular the concept of ‘entrepreneurial city’. A network connectivity model is adopted to assess connectivity patterns, using the power-law and exponential law as a statistical test framework, in order to detect the presence of economic activity hubs that may resemble the concept of entrepreneurial cities. Various results are presented and interpreted in the final part of the paper. [ABSTRACT FROM AUTHOR]

Using a panel of 439 German regions, we evaluate and compare the performance of various Neural Network (NN) models as forecasting tools for regional employment growth. Because of relevant differences in data availability between the former East and West Germany, the NN models are computed separately for the two parts of the country. The comparisons of the models and their ex post forecasts are carried out by means of a non-parametric test: viz. the Friedman statistic. The Friedman statistic tests the consistency of model results obtained in terms of their rank order. Since there is no normal distribution assumption, this methodology is an interesting substitute for a standard analysis of variance. [ABSTRACT FROM AUTHOR]

Because of heterogeneity across regions, economic policy measures are increasingly targeted at the regional level and, therefore, require regional forecasts. The data available to compute regional forecasts are usually a pseudo panel of a limited number of observations over time and a large number of regions strongly interacting with each other. Traditional time-series techniques applied to distinct time series of regional data are probably a suboptimal forecasting strategy. Although both linear and nonlinear models have been applied and evaluated to forecast socioeconomic variables, spatial interactions among regions are often ignored. This article evaluates the ability of spatial error and spatial lag models to correct for misspecifications due to neglected spatial autocorrelation in the data. The empirical application on short-term forecasts of employment in 326 West German regions shows that the superimposed spatial structure that is required for the estimation of spatial models improves the forecasting performance of nonspatial models. [ABSTRACT FROM AUTHOR]

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Abstract: Spatial labour markets are subjected to the forces of regional economic activity and competing network effects. Commuting is, therefore, an important equilibrating vehicle in a City Network constellation. Cities act as attractors of commuters, as most economic activity occurs in cities, thus providing a high share of attractive workplaces. Cities that are centrally connected in a network may act as both centripetal and centrifugal forces in the whole system. The present paper focuses on what is named the City Network (CN) approach. A central idea is the accessibility concept, which is interpreted here as the potential of opportunity for interaction, which has a positive impact on economic growth. In our paper, the accessibility concept and the CN concept are linked together by positioning accessibility in the CN system. Since accessibility measures give geographical insights into the distribution of economic activities and the related (dis)equilibrium of regional development patterns, the connection with the labour market is evident, and, therefore, a second focus of our analysis. In an applied setting, our paper aims to investigate spatial accessibility patterns in the main CN in Germany. The 17 districts which belong to the country’s CN were chosen from the 439 German labour market districts on the basis of three criteria: (a) their connection to the high speed railway network; (b) the most accessible districts according to previous results (2002); (c) relevant districts for the German economy. Our applied modelling research concerns home-to-work commuters travelling between the selected districts belonging to the German CN, for both 2003 and 2007. Here, a comparative analysis of the ranking of the most accessible districts – also for different intra-zonal travel times – is carried out in order to map out the changes in accessibility between 2003 and 2007, especially in the light of new high speed connections and commuting flow dynamics. [Copyright &y& Elsevier]