The Annals of Regional Science

While prior econometric forecasting models focus on either macroeconomic or territorial aspects as drivers of regional growth, the fourth version of the MAcroeconomic, Sectoral, Social, Territorial (MASST4) model merges these two conceptual approaches to regional growth. Mechanisms of territorial complexity governing regional development theories, like agglomeration economies, or structural changes in innovation modes, are included into a formal model so that they simultaneously activate regional growth and mediate macroeconomic growth impacts. Moreover, a longer time series than in previous versions of the MASST model now allows to take account of the structural changes taking place in EU economies as a consequence of the recent crisis. The model now also models the effects of the decrease in EU integration stemming from populistic waves in politics taking place in EU countries. The paper also presents an application of the MASST model to a reference scenario.

This paper aims to contribute to the development of a general network theory for the social sciences. This ambition comprises an attempt to a) formulate, and illustrate with historical examples, a general hypothesis about the relation between a contiguity and a network principle for spatial development, and to b) use the concept of interaction costs to illuminate the genesis and shaping of networks, the interaction between and within them, and implications of the fact that networks have different durability and potential for change. An attempt is made to break interaction cost-generating factors down into groups according to their potential for change. The concept of affinity is viewed as a part of the aggregate relationship between homogeneity and heterogeneity in the nodes of the respective networks – a relationship which constitutes one component of the totality of factors underlying interaction costs. The paper points out certain theoretical research issues such as the relationship between networks and politically-controlled territories; links between various external networks; links and flows within complex nodes; relationships between internal, „intra-nodal” and external networks and the processes in which a one-function node bifurcates from one network to another; the generation of links for various flows by nodes but also the impact made by the flows on the internal structure of complex nodes. A more systematic application of network theory to these (and other) fields seems to have the potential of producing important contributions to the understanding of economic development.

Studies in the regional innovation literature have largely focused on the role of economic, structural, demographic, and institutional factors, but very few studies shed light on the role of amenities. This paper investigates this question by examining how amenities shape the geography of innovation in China. The empirical results based on city-level data suggest that both natural and consumer amenities are positively associated with regional innovation. Specifically, amenities related to air quality, sunshine, public transportation, educational resources, and healthcare services matter most. Further, the analysis suggests the influence of amenities on innovation is closely linked to city characteristics such as income, density, and human capital. Therefore, to formulate innovation-driven growth, these results suggest that more attention should be paid to the role of amenities and amenity-related strategies should be tailored to city characteristics.

Interindustry input-output (IO) relationships were incorporated into a local labor market forecasting model for the Toledo, OH MSA by Magura (1990); he found that the use of the IO information as a Bayesian prior reduced forecast errors. LeSage and Magura (1991) found similar results using national labor market data. This paper likewise uses IO information as a Bayesian prior in forecasting employment in four industries in five states but also adds spatial information. The purpose of adding the spatial information is to determine if it further reduces forecast errors. Using a mixture of a spatial weight matrix similar to that proposed by LeSage (1993) in addition to the IO information, it is found that forecast errors are reduced beyond that achieved with only the IO information.

In this study, I investigate the commuting behavior of workers in Germany. Using comprehensive geo-referenced administrative employee and firm data, I can calculate the exact commuting time and the distance between workers’ residence and workplace locations. Based on a behavioral economic approach (Simonson and Tveresky in J Mark Res 29:281–295, 1992), I show that individual commuting decisions are influenced by wages and individual heterogeneity as well as depending on the context individuals observed in the past. In particular, my results show that previously observed commutes have an impact on subsequent commuting behavior: workers choose longer commuting times in the region they recently moved to when the average commute in the region they left was longer. The results indicate that while selectivity and sorting do not influence the effect of the context, the inclusion of individual fixed effects is crucial.

Conventional demand based approaches to recreational economics are reviewed and found unsuitable for analyzing the effects of changes of the quality of recreation. An alternative approach using a simulation model is proposed, which allows the use of both quantitative data and subjective input on the qualitative effects. The critical economic variables are found to be fishing recreation visitor days and investment in recreational facilities at the Salton Sea, California. The model results are projected for 20 years and key parameters and assumptions are identified by parametric analysis. These parameters were then subjected to critical interaction by a group of specialists in the area, during a workshop session. Results of the final model are compared to a previous economic study of the region and found to be more pessimistic about the benefits of quality control. Verification of the model is performed by tests of deviation of the predictions of visitor days by the model from the actual visitor days recorded over eight years.