Spatial dependence and the representation of space in empirical models

A well-formed spatial model should most likely not produce spatial autocorrelation at all. From this perspective spatial autocorrelation is not (pure) statistical nuisance but a sign of that a model lacks a representation of an important economic phenomenon. In a Knowledge Production Function (KPF) context, this paper shows that a representation of space reflecting the potential of physical interaction between localities by means of accessibility variables on the “right-hand-side”—a simple alternative to spatial lag and spatial error which can be estimated by OLS—captures substantive spatial dependence. Results are verified with Monte Carlo simulations based on Anselin’s (Int Reg Sci Rev 26(2):153–166, 2003) taxonomy of modelled and unmodelled effects. The analysis demonstrates that an accessibility representation of explanatory variables depict the network nature of spatial interaction, such that spatial dependence is actually modelled.     

Measuring self-sustainability of economic development at the county level

Factors that affect self-sustainability of regional economic development are defined and analyzed in this paper. Extensive empirical testing shows that at the county level, the size of the regional economy and agglomeration effects are less important than its regional multiplier and its export base. Because the classic export-base model fails specification tests when estimated at the county level, a modified export-base model accounting for spatial effects is developed and analyzed. To validate the proposed spatial export-base model, a practical procedure for estimating parameters of the model is also developed and utilized in an empirical study. The paper concludes with a brief review of the applicability of the modified export-base model to the analysis of the self-sustainability of regional economies, its limitations, and its policy implications. In particular, it is suggested that regional economic development policies should focus on promoting patterns of self-reinforcing regional growth rather than on maintaining unsustainable economic initiatives. It is also demonstrated that the size of a county's economy is not directly related to its self-sustainability and growth rates. Received: May 2000/Accepted: March 2002 Many thanks to Roger Stough and Alena Smirnova for their helpful comments. The research was supported in part by Grant CO-12884F from the Appalachian Regional Commission. An earlier version of the paper was presented at the 39th Annual Meeting of the Southern Regional Science Association in Miami Beach, FL, April 13–15, 2000.     

Modelling regional labour market dynamics in space and time

This paper extends the seminal Blanchard and Katz regional labour market model to include interaction effects using a dynamic spatial panel data approach. Three key contributions of this extended model are: (i) the unrealistic assumption that regions are independent of one another no longer has to be made, (ii) the magnitude and significance of so‐called spillover effects can be empirically assessed, and (iii) both the temporal and spatial propagation of labour demand shocks can be investigated. Using annual data from 1986–2010 for 112 regions across eight EU countries, both the non‐spatial and spatial models are estimated. It is found that the majority of the spillover effects are highly significant. Consistent with economic theory, the impact of a region‐specific demand shock is largest in the region where the shock instigates. The shock also propagates to other regions, especially impacting the first and second‐order neighbours.     

Crime and regional economic growth in Mexico: A spatial perspective

The aim of this paper is to examine the effects of crime on regional economic growth in Mexico. We estimate a growth model using a spatial panel data model and test for the presence and type of spatial interaction, as proposed by Elhorst. Our results suggest that a two‐way spatial Durbin model best fits the data, crime exerts a negative total effect on economic growth across Mexican states, particularly homicides and robbery, and significant spillover effects seem to reinforce the negative impact on regional growth.     

A multi-scale, multi-model approach for analyzing the future dynamics of European land use

Europe’s rural areas are expected to witness massive and rapid changes in land use due to changes in demography, global trade, technology and enlargement of the European Union. Changes in demand for agricultural products and agrarian production structure are likely to have a large impact on landscape quality and the value of natural areas. Most studies address these changes either from a macro-economic perspective focusing on changes in the agricultural sector or from a local perspective by analyzing recent changes in landscapes for small case studies. This paper describes a methodology in which a series of models has been used to link global level developments influencing land use to local level impacts. It is argued that such an approach is needed to properly address the processes at different scales that give rise to the land use dynamics in Europe. An extended version of the global economic model (GTAP) and an integrated assessment model (IMAGE) are used to calculate changes in demand for agricultural areas at the country level while a spatially explicit land use change model (CLUE-s) was used to translate these demands to land use patterns at 1 km² resolution. The global economic model ensures an appropriate treatment of macro-economic, demographic and technology developments and changes in agricultural and trade policies influencing the demand and supply for land use related products while the integrated assessment model accounts for changes in productivity as result of climate change and global land allocation. The land use change simulations at a high spatial resolution make use of country specific driving factors that influence the spatial patterns of land use, accounting for the spatial variation in the biophysical and socio-economic environment. Results indicate the large impact abandonment of agricultural land and urbanization may have on future European landscapes. Such results have the potential to support discussions on the future of the rural area and identify hot-spots of landscape change that need specific consideration. The high spatial and thematic resolution of the results allows the assessment of impacts of these changes on different environmental indicators, such as carbon sequestration and biodiversity. The global assessment allows, at the same time, to account for the tradeoffs between impacts in Europe and effects outside Europe.     

Measuring the spillover effects: Some Chinese evidence

Based on recently developed methods of exploratory spatial data analysis, this article seeks to prove the desired spread effects in the Chinese space economy from a core-periphery perspective. Recently developed methods of exploratory spatial data analysis provide new insights on the spatial pattern of the interaction of Chinese provincial output growth rates over the 1978–1994 period. Findings indicate that the economic spillover effects are most evident at the first order of province contiguity from Guangdong, where the two coastal provinces of Hainan and Guangxi are identified with a significant spread pattern, while non-coastal provinces Hunan and Jiangxi are observed with a strong polarization pattern. A further analysis indicates that the state preferential policies favoring the coastal region are the fundamental force in determining the direction of spread-polarization processes in the Chinese space economy. This finding confirms Friedmann's hypothesis on spatial interaction, namely, that the spread process is a successful diffusion of the core's existing institutions into the periphery. Received 14 August 1997 / Accepted 12 July 1999     

Neoclassical theory versus new economic geography: competing explanations of cross-regional variation in economic development

This paper uses data for 255 NUTS-2 European regions over the period 1995–2003 to test the relative explanatory performance of two important rival theories seeking to explain variations in the level of economic development across regions, namely the neoclassical model originating from the work of Solow (Q J Econ 70:65–94, 1956) and the so-called Wage equation, which is one of a set of simultaneous equations consistent with the short-run equilibrium of new economic geography (NEG) theory, as described by Fujita et al. (The spatial economy. Cities, regions, and international trade. The MIT Press, Cambridge, 1999). The rivals are non-nested, so that testing is accomplished both by fitting the reduced form models individually and by simply combining the two rivals to create a composite model in an attempt to identify the dominant theory. We use different estimators for the resulting panel data model to account variously for interregional heterogeneity, endogeneity, and temporal and spatial dependence, including maximum likelihood with and without fixed effects, two stage least squares and feasible generalised spatial two stage least squares plus GMM; also most of these models embody a spatial autoregressive error process. These show that the estimated NEG model parameters correspond to theoretical expectation, whereas the parameter estimates derived from the neoclassical model reduced form are sometimes insignificant or take on counterintuitive signs. This casts doubt on the appropriateness of neoclassical theory as a basis for explaining cross-regional variation in economic development in Europe, whereas NEG theory seems to hold in the face of competition from its rival.     

From physical to general spaces: A spatial econometric analysis of cross-country economic growth and institutions

In this paper I extend the use of space as the organizing framework from the physical space to a socio-economic one and, based on an established institutional space, I conduct a cross-country analysis of institutions and economic performance from a spatial econometric perspective. While my results corroborate previous findings on the institutional dimensions of economic development, I am able to provide precise insights as to the spatial dimensions of national per capita GDP growth rates as well as new evidence on the role of spatial effects in the formal econometric analysis of cross-country growth performance. This paper is important in that it represents the first detailed evidence in the two aspects aforementioned. I would like to thank Arthur Getis for his invaluable help throughout my research period. I would also like to thank Tschangho John Kim and anonymous referees for their very constructive critiques and valuable comments on earlier drafts of this article. I do, however, retain responsibility for any remaining errors and misrepresentations. This research is financially supported by the National Natural Science Foundation of China. Received: December 2003/Accepted: April 2004     

RHOMOLO: A dynamic spatial general equilibrium model for assessing the impact of cohesion policy

The paper presents the newly developed dynamic spatial general equilibrium model of European Commission, RHOMOLO, and proposes its future extensions. The model incorporates several elements from economic geography in a novel and theoretically consistent way. It describes the location choice of different types of agents and captures the interplay between agglomeration and dispersion forces in determining the spatial equilibrium. The model is also dynamic as it allows for the accumulation of factors of production, human capital and technology. This makes RHOMOLO particularly suited for simulating policy scenario related to the EU cohesion policy and for the analysis of its impact on the regions and the Member States of the union.     

Study on Spatial Spillover Effects of Infrastructures Investment: A Case Study on Cities along Shanghai-Kunming Railway Line

Using the economic development of regions and cities along the Shanghai-Kunming railway line as an example, the paper carries out an empirical study on the spatial spillover effects of infrastructure investment in China. It has been found that the infrastructure investment along Shang-Kunming line not only produces positive spatial spillover effects, such as promoting the region’s transportation capacity, expanding trading volume, adjusting industrial structure, and facilitating economic development, but also leads to certain negative spatial spillover effects like unbalanced flow of production elements among the region, and unbalanced economic growth.     

Modelling the geography of economic activities on a continuous space

In the present article we propose a spatial micro econometric approach for studying the geographical concentration of economic activities. We analyse the incentives to use this approach rather than the traditional one based on regional aggregates. As an example, we present our prototypical theoretic model – to be seen as a continuous space version of Krugman's concentration model – that includes birth, survival and growth components. We present a numerical estimation of the birth model for a set of data referring to the concentration of the manufacturing industries in the San Marino Republic. Received: 18 May 1998 / Accepted: 12 March 2001     

Economic shocks and growth: Spatio‐temporal perspectives on Europe's economies in a time of crisis

The response by regional and national economies to exogenous impulses has a well‐established literature in both spatial econometrics and in mainstream econometrics and is of considerable importance given the post‐2007 economic crisis, which is characterized by a period of severe global instability resulting from unprecedented economic shocks. This paper focuses on dynamic counterfactual predictions and impulse‐response functions derived from appropriate econometric models. These provide insight regarding the question of whether responses to economic shocks are transitory or whether they have a permanent effect. Analysis shows that output shocks have had permanent effects on productivity so that economies have tended not to return to the pre‐shock path but rather adjust to new levels. This suggests that the current recession will be embodied permanently within the memory of some of Europe's leading economies as a hysteretic effect.     

A Bayesian approach to hedonic price analysis

Two important objectives in hedonic price analysis are to predict sale prices and delineate submarkets based on geographical and functional considerations. In this paper, we applied Bayesian models with spatially varying coefficients in an analysis of housing sale prices in the city of Toronto, Ontario to address these objectives. We evaluated model performance and identified patterns of submarkets indicated by the spatial coefficient processes. Our results show that Bayesian spatial process models predict housing sale prices well, provide useful inference regarding heterogeneity in prices within a market, and may be specified to include expert market opinions.     

Urban spatial structure,agglomeration economies,and economic growth in Barcelona: An intra‐metropolitan perspective*

This paper presents an intra‐metropolitan approach to analyse the impact of urban spatial structure on local economic growth. Focusing on the Barcelona metropolitan region (BMR) between 1986 and 2001, we estimate a municipal employment growth model in which dynamic agglomeration economies related to urban spatial structure are considered using distance to employment centres, to assess metropolitan effects, and distance‐weighted variables, to measure neighbourhood effects. The results obtained show the existence of neighbourhood specialization economies and metropolitan urbanization‐localization economies fostering local growth. All of this leads to the paper's main conclusion: urban spatial structure is important for economic growth in an intra‐metropolitan context.     

Statistical and mathematical sources of regional science theory: Map pattern analysis as an example

Krugman states that “Regional science is not a unified subject. It is best described as a collection of tools.” Unfortunately such a perspective fails to fully acknowledge theoretical dimensions of the accompanying refocusing on geographic expressions of economic linkages, such as those highlighted in spatial externalities specifications. Such promulgated aspects of the spatial economic landscape relate to map pattern, and certainly the spatial statistics and spatial econometrics theory that accompanies it, as well as the underlying substantive theory garnered from a variety of sources. The principal implication is other than “loose- jointed, do-the-best-you-can theorizing”. Received: 22 November 1997 / Accepted: 10 March 1998     

Target search of burglars: A revised economic model

Abstract. This article investigates home attributes that attract residential burglars in choosing a target. These attributes are the location of the home, its physical appearance, demographic characteristics of the residents, and the security precautions present. The theoretical foundation of the empirical model is the criminal utility maximization behavior that considers costs and benefits as formulated by Becker. However, this article introduces to the model the spatial dimension of the burglar's search for a target. The incidence of burglary is the dependent variable and is measured in a dichotomy scale. The empirical analysis utilizes a survey database of burgled and non-burgled homes that was conducted by the researchers. A logit model is used for the investigation, and the effects of the explanatory variables are calculated as probabilities. The database is unique in the wealth of attributes of individual homes that are relevant to burglars'decision process.     

Testing and explaining economic resilience with an application to Italian regions

This paper studies regional economic resilience by exploiting the properties of the non‐linear smooth‐transition autoregressive model. A testing procedure to distinguish between engineering and ecological resilience is presented, and a measurement of economic resilience is provided. Regional differences in economic resilience are explained by the presence of spatial interactions and by adopting a set of determinants like economic diversity, export performance, financial constraints, and human and social capital. An empirical investigation is conducted for analysing regional employment evolution in Italy from 1992 to 2012. Some concluding suggestions propose possible future areas of research.     

Non‐linearities in regional growth: A non‐parametric approach

This paper analyses the determinants of regional economic growth in the European Union adopting a non‐parametric approach. Although the local‐linear kernel estimator applied does not explicitly take into account the spatial dimension of the data, it is found to be consistent in our context. In addition, the geographically weighted regression turns out to be less efficient. We obtain evidence of a non‐linear relationship between regional growth and its determinants in the form of parameter heterogeneity and threshold effects. These non‐linearities mainly affect the initial productivity of labour, the human capital endowment and, as a novelty, the level of infrastructures.     

Specification of spatial models: A simulation study on weights matrices

The correct specification of spatial models, and especially the choice of the spatial weights matrix, represents a crucial decision for researchers using georeferenced data. However, few guidelines exist on which weights matrix is most appropriate in certain cases. This paper therefore (1) studies the sensitivity of testing and estimating spatial models with different weights matrix specifications and (2) formulates recommendations for researchers applying spatial models regarding model selection and weights matrix specification. The research is based on Monte Carlo simulations with synthetic data.

Resumen

La correcta especificación de modelos espaciales, y especialmente la elección de la matriz de pesos espaciales, representa una decisión crucial para investigadores que estén utilizando datos georreferenciados. Sin embargo, existen pocas recomendaciones acerca de que matriz de pesos es la más apropiada en ciertos casos. Por tanto este artículo (1) estudia la sensitividad de los ensayos y la estimación de modelos espaciales con especificaciones diferentes de la matriz de pesos y (2) formula recomendaciones para investigadores que estén aplicando modelos espaciales en relación con la elección del modelo y las especificaciones de la matriz de pesos. La investigación está basada en simulaciones de Monte Carlo con datos sintéticos.

     

Determinants of international tourist choices in Italian provinces: A joint demand–supply approach with spatial effects

Only recently is research merging demand and supply approaches in explaining tourist market equilibria. This paper innovates in three ways. One: we jointly consider demand and supply explanatory variables and spillover effects originating from contiguous areas by designing a unilateral gravity model augmented with spatial effects (spatial Durbin model). Two: we raise the economic profile by prioritizing an expenditure variable over flow variables (arrivals, overnight stays, length of stay) and taking into account travel costs (via the origin–destination distance). Three: we differentiate spatial contexts by focusing on international tourist origins and on local (NUTS3) destinations. Results confirm previous literature only in part.