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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]

Most “wage curve” studies ignore the geography of local labor markets. However, when a local labor market is in close proximity of other labor markets, a local shock that increases unemployment may not lead to lower pay rates if employers fear outward migration of their workers. Hence, the unemployment elasticity of pay will be greater, the more isolated the local labor market is. Wages are also expected to be higher in regions that interact strongly with other regions. These hypotheses are confirmed by means of an estimation of wage curves with data for 327 regions of western Germany over the period 1990–1997. [ABSTRACT FROM AUTHOR]

There is a growing interest in the academic and policy making communities in understanding the effects of sectoral specialisation on labour market performance. The existing empirical evidence, mainly based on US data, generally finds a positive correlation between sectoral specialisation and labour market indicators such as wages and unemployment. The policy implication one can draw from these results is that fostering sectoral diversification may reduce unemployment. However, this lesson may not hold for all countries. In particular, in the case of Europe, the diversity of labour market institutions may play a distinct role in shaping the relationship between sectoral specialisation and labour market performance. In this paper, we investigate the relationship between regional sectoral specialisation and regional unemployment rate in the context of different collective bargaining institutions in the EU countries. We find that collective bargaining institutions do play a role in shaping the unemployment rate differentials across regions belonging to the same country. Furthermore, the relationship between regional specialisation and the regional unemployment rate is stronger in countries with intermediate and decentralised collective bargaining institutions in comparison to countries with centralised collective bargaining institutions. Our results suggest that labour market institutions are likely to influence the outcome of policies aiming at fostering regional diversification. While such policies may result in reducing regional unemployment in countries with decentralised and intermediate levels of collective bargaining, they may not make a big difference in countries with centralised collective bargaining institutions. [ABSTRACT FROM AUTHOR]

Self-Organised Criticality (SOC) is a concept developed over the last decade from dynamic systems analysis that aims to investigate the transition trajectories of evolutionary systems. The main emphasis in SOC is on the analysis of the impact of slow exogenous forces in combination with strong localised interactions between single elements or components of the systems concerned, with particular regard to the attainment of a critical state at the macro-level. Against this background, SOC serves to identify the critical conditions from the internal dynamics of the systems that lead to major and significant transformations of their behaviour. The present paper aims to offer insights and reflections originating from the SOC concept, as well as to explore its potential contribution to understanding the evolution of regional economic patterns, in particular the functioning of regional labour markets. In our study, the evolutionary dynamics of employment at a district level in West Germany as well as in the combined West and East German setting will be investigated, in order to detect the possible existence of a power law distribution of growth rates, which may be seen as an indication for SOC at the macro-economic level. In this context, SOC may help to explain the presence of large socio-economic regional fluctuations in a country, and, in general, the dynamics inherent to regional development. [ABSTRACT FROM AUTHOR]

Focuses on cyclical and regional variations in vacancy dynamics in Dutch labor markets with persistent imbalances between demand and supply. Developments in Dutch regional labor markets from 1980 to 1993; Regional variations in vacancy dynamics; Shift-share analysis of average vacancy duration from 1989 to 1993; Investigation of the differences in the effectiveness to match demand and supply on the labor market across regions; Conclusions.

Purpose An interest in social transmission as a source of welfare and income inequality in a society has re-emerged recently with new vigour in leading economic research (see Piketty, 2014). This paper presents a mixed Bourdieu-Mincer (B-M) type micro-economic model which provides a testable mechanism for culturally biased socio-economic inter-generational transmission. In particular, the operationalisation of this mixed B-M type model seeks to find evidence for individual and local cultural capital effects on the economic achievements, in addition to the human capital effect, for both migrants and locals in the Netherlands. The purpose of this paper is to examine two sources of wage differential in the local labour market, namely: individual cultural capital (approximated by immigrant background), which affects schooling results; and the local cultural capital (approximated with the cultural milieu), which directly biases the selection of employees.Design/methodology/approach The study utilises the 2007-2009 data set for higher professional education (in Dutch termed HBO) graduates registered in the Maastricht database. The Mincer-type equation is augmented with a control variable for the local cultural milieu. The authors cope with this model empirically by means of 2SLS and 3SLS methods.Findings The authors find convincing evidence for the existence of both an individual cultural capital and a local cultural capital effect on schooling and wage differentials. This can be interpreted as a migrant background effect leading to a disadvantaged position on the labour market due to less frequently attending high-quality secondary schools.Originality/value More importantly, the authors find evidence for a classical Myrdalian effect of self-fulfilling prophecy, in which graduates with second-generation migrant background have a disadvantaged position due to access only to poorer quality of schooling. [ABSTRACT FROM AUTHOR]

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]

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]

(Spatial) panel data are routinely modeled in discrete time ( DT). However, compelling arguments exist for continuous-time ( CT) modeling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an incomplete representation of reality, and may lead to misinterpretation of estimation results. The most compelling reason for a CT approach is that, in contrast to DT modeling, it allows adequate modeling of dynamic adjustment processes. This article introduces spatial dependence in a CT modeling framework. We propose a nonlinear structural equation model ( SEM) with latent variables for estimation of the exact discrete model ( EDM), which links CT model parameters to DT observations. The use of a SEM with latent variables enables a specification that accounts for measurement errors in the variables, leading to a reduction of attenuation bias (i.e., disattenuation). The SEM-CT model with spatial dependence developed here is the first dynamic SEM with spatial dependence. A simple regional labor market model for Germany, comprising changes in unemployment and population as endogenous state variables, and changes in regional average wages and in the structure of the manufacturing sector as exogenous input variables, illustrates this spatial econometric SEM-CT framework. El modelamiento de datos panel espaciales se realiza habitualmente utilizando una conceptualización del tiempo discreto (TD). Sin embargo, existen argumentos de peso para conceptualizar el tiempo de manera continua (TC). En concreto, la mayoría de procesos sociales se desarrolla en TC, por lo que el análisis estadístico en DT trae como consecuencia una simplificación excesiva de los procesos, da una representación incompleta de la realidad, y puede conducir a una interpretación errónea de los resultados de la estimación. La razón más convincente para el uso de un enfoque CT es que a diferencia de modelos DT, una conceptualización CT permite el modelado adecuado de los procesos de ajuste dinámico ( dynamic adjustment). Este artículo incorpora la dependencia espacial en un marco de modelamiento con CT. Los autores proponen un modelo de ecuaciones estructurales no lineal ( nonlinear structural equation model -SEM) con variables latentes para la estimación del modelo discreto exacto ( exact discrete model-EDM), que vincula los parámetros del modelo CT a las observaciones de DT. El uso de un SEM con variables latentes permite una especificación que da cuenta de los errores de medición en las variables, dando lugar a una reducción del sesgo de atenuación (es decir, 'desatenuacion'). El modelo SEM-CT con dependencia espacial desarrollado en el presente estudio es el primer SEM dinámico con dependencia espacial. Para ilustrar el marco conceptual SEM-CT los autores presentan un modelo simple del mercado laboral regional de Alemania. El modelo está compuesto por los cambios en el desempleo y la población como variables endógenas de estado, y los cambios en los salarios regionales promedio y en la estructura del sector manufacturero como variables de entrada exógenas. （空间）面板数据通常基于离散时间（DT）进行建模。然而更令人信服的观点是基于连续时间（CT）进行（空间）面板数据建模。特别是多数社会过程均在连续时间中演化，基于离散时间的统计分析可能过度简化，使得对现实状况的表达不完备，并可能导致对估计结果的错误解释。相比于离散时间（DT）建模，连续时间（CT）建模最具说服力的原因在于在建模过程中允许足够多的动态调整。本文介绍了CT模型框架中的空间依赖性。把CT模型参数链接到DT观察值中，我们提出了用于估计精确离散模型（EDM）的包含潜变量的非线性结构方程模型（SEM）。包含潜在变量的SEM提供了变量测量误差的计算方案，使得衰减偏差（如反衰减性）减小。本文了提出的空间相关SEM-CT模型是第一个动态空间相关的SEM模型，并以德国一个简单的区域劳动力市场模型为例，以失业和人口构成变化为内生状态变量，以区域平均工资和制造业结构部门变化为外生输入变量，阐述了该空间计量SEM- CT模型的框架。 [ABSTRACT FROM AUTHOR]

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]

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]