Alonso's Theory of Movements: Developments in Spatial Interaction Modeling

 The Spatial Interaction Model proposed by Alonso as “Theory of Movements” offers an innovative specification of spatial origin-destination flow models. Equations for flows between regions, total outflow from and total inflow to a region are linked by balancing factors. This paper presents a consistent formulation of Spatial Interaction Models in the Wilson tradition and Alonso's Theory of Movements. The paper is intended as an introduction to the model and a review of␣the state of the art. Besides it is argued that simultaneous equation techniques are required to estimate the so-called systemic parameters. Received: 21 May 2000 / Accepted: 18 January 2001     

On container versus time based inspection policies in invasive species management

We study the problem of precluding biological invasions caused by ships transporting internationally traded goods in containers between different regions of the world. Using the long run expected net cost (LRENC) of inspections as the apposite managerial objective, we address the following important question: given that inspection is a cyclical activity, is the LRENC lower when a port manager’s inspector inspects cargo upon the arrival of a specified number of containers (container policy) or is this LRENC lower when this inspector inspects cargo at fixed points in time (temporal policy)? We construct a queuing theoretic model and show that in an inspection cycle, irrespective of whether the inspection policy choice is made on the basis of an explicit optimization exercise or on the basis of rules of thumb, the container policy is superior to the temporal policy because the container policy results in lower LRENC from inspection activities.     

The market value of cultural heritage in urban areas: an application of spatial hedonic pricing

The current literature often values intangible goods like cultural heritage by applying stated preference methods. In recent years, however, the increasing availability of large databases on real estate transactions and listed prices has opened up new research possibilities and has reduced various existing barriers to applications of conventional (spatial) hedonic analysis to the real estate market. The present paper provides one of the first applications using a spatial autoregressive model to investigate the impact of cultural heritage—in particular, listed buildings and historic–cultural sites (or historic landmarks)—on the value of real estate in cities. In addition, this paper suggests a novel way of specifying the spatial weight matrix—only prices of sold houses influence current price—in identifying the spatial dependency effects between sold properties. The empirical application in the present study concerns the Dutch urban area of Zaanstad, a historic area for which over a long period of more than 20 years detailed information on individual dwellings, and their market prices are available in a GIS context. In this paper, the effect of cultural heritage is analysed in three complementary ways. First, we measure the effect of a listed building on its market price in the relevant area concerned. Secondly, we investigate the value that listed heritage has on nearby property. And finally, we estimate the effect of historic–cultural sites on real estate prices. We find that, to purchase a listed building, buyers are willing to pay an additional 26.9 %, while surrounding houses are worth an extra 0.28 % for each additional listed building within a 50-m radius. Houses sold within a conservation area appear to gain a premium of 26.4 % which confirms the existence of a ‘historic ensemble’ effect.     

Multidimensional economic indicators and multivariate functional principal component analysis (MFPCA) in a comparative study of countries’ competitiveness

Journal of Geographical Systems - The multivariate pluriformity and complexity of economic-geographic space (e.g., cities or countries) are reflected in their empirical multidimensional data...     

Universities and knowledge-based economic growth: the case of Delft (NL)

Knowledge about new technology is a main determinant of the competitiveness of cities and regions nowadays. It reduces the amount of uncertainty of companies in their daily operations. In addition, it is a basis for the establishment of new companies and the restructuring of old ones. The availability and use of knowledge has thus a major influence on the development of urban and regional economies. An amazingly small amount of research has been done on the knowledge capacity of cities to date, i.e. urban potentials to generate, store, transfer and use knowledge. This article explores therefore, the urban knowledge capacity in a theoretical and empirical sense. Attention will be given to essential urban knowledge activities, and to the comprehensive and complex nature of the phenomena involved. In addition, various planning tools aimed at knowledge-based economic growth will be considered, with a focus on differences between the actors involved, and opportunities and constraints for success. In the empirical part, the city of Delft in the Netherlands will serve as an example, particularly regarding local policies for knowledge-based growth. Delft is an interesting case given the abundant availability of new technology and the relatively low level of local new firm formation.     

Neural networks for regional employment forecasts: are the parameters relevant?

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.     

Joint impacts of immigration on wages and employment: review and meta-analysis

A burgeoning literature has emerged during the last two decades to assess the economic impacts of immigration on host countries. In this paper, we outline the quantitative approaches presented in the literature to estimate the impact of immigration on the labour market, particularly at the regional level. We then revisit the joint impacts of immigration on wages and employment using a meta-analytic approach. As a novel contribution to previous meta-analyses on labour market impacts, we use a simultaneous equations approach to the meta-analysis of wage and employment effects. Using 129 effect sizes, we find that the observed local wage and employment effects are very small indeed. Generally, the employment impact is more pronounced in Europe than in the United States. Controls for endogeneity show a somewhat more negative impact. Wage rigidity increases the magnitude of the employment impact on the native born. The demarcation of the local labour market in terms of geography and skills matters also.