Thomas de Graaff

The Performance of Diagnostics for Spatial Dependence in Linear Regression Models: A Meta-Analysis of Simulation Studies

One of the reasons for A.D. Cliff and J.K. Ord’s 1973 book “Spatial Autocorrelation” achieving the status of a seminal work on spatial statistics and econometrics lies in their careful and lucid treatment of the autocorrelation problem in spatial data series. Cliff and Ord present test statistics for univariate spatial series of categorical (nominal and ordinal) and continuous (interval or ratio scale) data. They extend the use of autocorrelation statistics, specifically Moran’s I (Moran, 1948), to the analysis of regression residuals (see also Cliff and Ord, 1972). The detection of spatial autocorrelation among regression residuals implies either a nonlinear relationship between the dependent and independent variables, the omission of one or more spatially correlated regressors, or the appropriateness of an autoregressive error structure. Ignoring the presence of spatial autocorrelation among the population errors causes ordinary least squares (OLS) to be a biased variance estimator and an inefficient regression coefficient estimator. Anselin (1988b) shows that erroneously omitting the spatially lagged dependent variable from the set of explanatory variables causes the OLS estimator to be biased and inconsistent. Cliff and Ord (1981, p. 197) therefore urge the applied researcher to always apply “some check for autocorrelation,” and take remedial action when necessary.

Resilience: an evolutionary approach to spatial economic systems

The concept of resilience has received a great deal of attention in the past decades. Starting from the first fundamental definitions offered by Holling, Pimms and Perrings in an economic-ecological modeling context, the present paper explores the ‘evolution’ of the resilience concept—as well as related different measures—in both a continuous and discrete time setting.From this perspective, the paper explores the relevance of the resilience concept in socio-economic systems, by focussing the attention on the relationships among resilience, transition dynamics and lock-in effects, in particular in the light of the dynamics of technological innovation diffusion and adaptive behaviour of firms. In this framework we will describe an empirical application, in which the resilience and dynamics of the West-German labour market will be investigated. This empirical illustration is offered by making use of an algorithm constructed for detecting Lyapunov exponents, so as to classify the resilience among employment sectors in our case study.

A General Misspecification Test for Spatial Regression Models: Dependence, Heterogeneity, and Nonlinearity

There is an increasing awareness of the potentials of nonlinear modeling in regional science. This can be explained partly by the recognition of the limitations of conventional equilibrium models in complex situations, and also by the easy availability and accessibility of sophisticated computational techniques. Among the class of nonlinear models, dynamic variants based on, for example, chaos theory stand out as an interesting approach. However, the operational significance of such approaches is still rather limited and a rigorous statistical-econometric treatment of nonlinear dynamic modeling experiments is lacking. Against this background this paper is concerned with a methodological and empirical analysis of a general misspecification test for spatial regression models that is expected to have power against nonlinearity, spatial dependence, and heteroskedasticity. The paper seeks to break new research ground by linking the classical diagnostic tools developed in spatial econometrics to a misspecification test derived directly from chaos theory-the BDS test, developed by Brock, Dechert, and Scheinkman (1987). A spatial variant of the BDS test is introduced and applied in the context of two examples of spatial process models, one of which is concerned with the spatial distribution of regional investments in The Netherlands, the other with spatial crime patterns in Columbus, Ohio. Copyright 2001 BlackwellPublishersThere is an increasing awareness of the potential of nonlinear modeling in regional science, which can partly be explained by the recognition of the limitations of conventional equilibrium models in complex situationsand partly by the easy availability and accessibility of sophisticated computational techniques. Among the class of nonlinear models chaos theory stands out as an interesting approach, in which notable progress hasbeen made in economic research. However, the operational significance– in terms of solid empirical tests on chaos – has still been rather limited and a rigorous statistical-econometric treatment of chaos phenomena isstill lacking. This paper is concerned with a methodological and empirical analysis of chaos in spatial systems. It seeks to break new research ground by linking the classical diagnostic tools developed in spatial econometrics to nonlinearity tests for empirical data series, in particular the so-called BDS (Brock, Dechert, Scheinkman) test. A spatial variant of the BDS test is developed, and subsequently applied in the context of a shift-share model for Dutch regional labor markets.

Regional Population–Employment Dynamics Across Different Sectors of the Economy

A previous version of this paper was presented at the conference “Urban Development: Patterns, Causes, Foundations and Policy” organized by the Institute for Housing and Urban Development Studies (IHS), the Erasmus University Rotterdam, and Utrecht University (Department of Economics and Faculty of Geosciences), in Rotterdam, The Netherlands, 13–14 December 2010.

A Spatial Economic Perspective on Language Acquisition: Segregation, Networking, and Assimilation of Immigrants

Immigration and multiculturalism are at the heart of modern Western societies. The issue of language acquisition of immigrants is intrinsically linked to immigration. We formally link language acquisition of immigrants to the relative size of the immigrant stock, employing a microeconomic trading framework. Our model allows for spatial interaction going beyond the immigrants area of residence, and explicitly incorporates spatial segregation. In addition, behavioral differences of immigrants with respect to their level of assimilation into the host country, as well as differences in networking within their own ethnic community, are accounted for. We test our model for four non-Western immigrant groups in the Netherlands at two different spatial scale levels. The empirical results reveal that there is only ambiguous support for the inverse relationship between size of the immigrant community and language acquisition or language proficiency in The Netherlands. We find instead that there is strong support for language acquisition and understanding being positively influenced by assimilation to the host countrys culture.

ICT and Substitution Between Out-of-home and at Home Work: The Importance of Timing

This paper investigates the determinants of at-home and out-of-home labor supply in the Netherlands in the 1990s, focusing on the presence of information and computer technology (ICT) in households—in particular modem possession. To investigate these determinants, a sequential hurdle model is estimated in which people first decide to work and then decide to divide total labor supply in at-home and out-of-home labor supply. To correct for possible endogeneity, the modem variable is estimated by means of instrumental variables. When we consider only office hours, possession of ICT facilities at home stimulates both at-home and out-of-home labor supply. Thus, the two may be called complements from the ICT perspective. However, outside office hours, modem possession leads to less work out of home. During this part of the day the time worked less on the job is partly substituted by work at home. Thus, during this part of the week we find that substitution dominates. However, because labor supply during office hours dominates labor supply during the rest of the week we find complementarity as the main feature of overall labor supply. These results underline the importance of timing issues.

On Spatial Differences in the Attractiveness of Dutch Museums

Museums may serve as important amenities for inhabitants and act as magnets for attracting visitors to a city. For city planners it is important to understand what different types of museums there are in terms of attraction power, and how their attractiveness may depend on the presence of other museums. To this end, we propose a gravity model for all museums allowing for spatial dependence between museums to account for local competition or synergy effects. To address the likely heterogeneity in our sample of museums, we first adopt a spatial error component model. Thereafter, we model the variation between museums explicitly by segmenting the museums using a finite mixture approach. The application of this model uses a unique transaction database of the visiting behaviour of 80 821 persons to 108 Dutch museums. The results stress the large variation both in the spatial reach of museums and in their spatial context.

Cultural Diversity and Cultural Distance as Choice Determinants of Migration Destination

Abstract This study analyses the impact of cultural composition on regional attractiveness from the perspective of international migrant sorting behaviour on a European regional NUTS1 level. We use an attitudinal survey to quantify cultural distances between natives and immigrants in the region concerned, and estimate the migrants’ varying preferences for both cultural diversity and cultural distance. To account for regional unobserved heterogeneity, our econometric analysis employs artificial instrumental variables, as developed by Bayer et al., [2004a. An equilibrium model of sorting in an urban housing market. NBER no. 10865]. The main conclusions are twofold. On the one hand, cultural diversity increases regional attractiveness. On the other hand, average cultural distance greatly weakens regional attractiveness.

A European Cross-Country Comparison of the Impact of Homeownership and Transaction Costs on Job Tenure

De Graaff T. and van Leuvensteijn M. A European cross-country comparison of the impact of homeownership and transaction costs on job tenure, Regional Studies. This paper looks at the impacts across European countries of homeownership and transaction costs on job tenure. The analysis is based on a representative household sample of fourteen European countries covering the period 1994–2001. These data are merged with country-specific transaction tax data and aggregate homeownership rates. Similar to previous microeconomic studies, the results indicate that homeownership reduces job mobility as well as the probability of becoming unemployed or economically inactive. It is found, however, that this effect is severely mitigated by two factors. First, it decreases when aggregate homeownership rates are higher. Thus, homeowners have larger job tenures, but more so in countries with low homeownership rates. Second, transaction costs on the housing market are positively associated with the probability of becoming ...De Graaff T. and van Leuvensteijn M. A European cross-country comparison of the impact of homeownership and transaction costs on job tenure, Regional Studies. This paper looks at the impacts across European countries of homeownership and transaction costs on job tenure. The analysis is based on a representative household sample of fourteen European countries covering the period 1994–2001. These data are merged with country-specific transaction tax data and aggregate homeownership rates. Similar to previous microeconomic studies, the results indicate that homeownership reduces job mobility as well as the probability of becoming unemployed or economically inactive. It is found, however, that this effect is severely mitigated by two factors. First, it decreases when aggregate homeownership rates are higher. Thus, homeowners have larger job tenures, but more so in countries with low homeownership rates. Second, transaction costs on the housing market are positively associated with the probability of becoming unemployed.

Product Heterogeneity, Intangible Barriers and Distance Decay: The Effect of Multiple Dimensions of Distance on Trade Across Different Product Categories

Abstract We empirically examine the heterogeneity in the effects of multiple dimensions of distance on trade across detailed product groups. Using finite mixture modelling on bilateral trade data at the three-digit Standard International Trade Classification level, we endogenously group product categories into an a priori unknown number of segments based on estimated coefficients of multiple dimensions of distance in the gravity equation. We find that institutional distance, belonging to the same trade bloc and especially geographical distance are crucial and distinct factors for classifying commodities into homogeneous product groups.