Alternative regional specification and convergence of U.S. regional growth rates

We apply absolute beta convergence techniques to cross sectional per capita income data for alternative specifications of U.S. regions in order to detect whether U.S. regional growth rates are converging over relatively recent time periods. We also explore whether estimates of convergence differ between economic and political region specifications. We show that convergence of growth rates across regions of the U.S. has continued in modern times (1969–1997) for almost any regional specification and for all time frames considered. We do find, however, some difference in convergence rates between economic and political regions. Convergence coefficients, however, are remarkably similar across alternative economic region specifications. An earlier version of this paper was presented in February 2003 at the 42nd annual meetings of the Western Regional Science Association in Rio Rico, Arizona. We would like to thank our session participants in Rio Rico and three anonymous referees for helpful comments. Any remaining errors or oversights, however, are entirely our responsibility.     

The regional distribution of Spanish unemployment: A spatial analysis

In this article we propose a set of tools for analysing the regional distribution of unemployment. As we are interested in the characteristics of the distribution as a whole, results from a traditional regression analysis are complemented with those obtained by estimating its external shape before and after being conditioned to factors underlying regional unemployment. In addition, we specifically consider the spatial characteristics of the distribution, and the empirical model we develop to determine explanatory factors includes spatial effects. This framework is applied to the study of the provincial distribution of unemployment rates in Spain. Results point to increasing spatial dependence in the distribution of regional unemployment rates, and a change in the factors causing regional differentials over the last decade.     

Spatial markets and the potential for economic integration between Canadian and U.S. regions

The potential for further economic integration among Canadian and American regions is measured by comparing province-to-state trade with state-to-state trade, where the latter is used as a benchmark of integration. To accomplish this, an attraction constrained gravity model is derived from micro foundations and estimated. The analysis demonstrates that after controlling for variations in output, distance, wages, productivity, and localization economies, the border remains a significant barrier to trade, although much less than previous estimates of the border effect using internal Canadian trade as a benchmark. The model's results also indicate that the border's influence varies across sectors, and the influence appears to be, in part, related to the presence of tariff and non-tariff barriers. Received: 1 February 1999 / Accepted: 8 August 2000     

A test strategy for spurious spatial regression, spatial nonstationarity, and spatial cointegration

Abstract.  A test strategy consisting of a two-step Lagrange Multiplier test is suggested as a device to reveal spatial nonstationarity and spurious spatial regression. It is further illustrated how the test strategy can be used as a diagnostic for presence of a spatial cointegrating relationship between two variables. Using Monte Carlo simulations it is shown that the small-sample behaviour of the test strategy is as desired in these cases.     

Welfare reform and spatial matchingbetween clients and jobs

The recent Welfare Reform Act requires several categories of public assistance recipients to transition to the work force. In most metropolitan areas public assistance clients reside great distances from areas of entry-level jobs. Any program designed to provide access to these jobs, for those previously on public aid, needs relevant transportation services when the job search process begins. Therefore it is essential that the latent demand for commuting among public aid clients be assessed in developing public transportation services. The location of entry-level jobs must also be known or, as in this article, estimated using numerous data sources. This article reports on such a demand estimation effort, focusing primarily on the use of Regional Science methods. Received: 5 January 1998 / Accepted: 25 November 1998     

Beyond neoclassical orthodoxy: A view based on the new economic geography and UK regional wage data

Abstract.  The article examines the performance of two competing non-nested models of regional wage variations in Great Britain, one motivated by the Solow-Swann neoclassical growth model which assumes constant returns to scale, the other by new economic geography theory, which assumes internal and external increasing returns. Both models also include controls for labour efficiency variations across regions. The empirical analysis, which is based on the bootstrap J test, shows that the neoclassical model does not reject the new economic geography specification, but the converse is not true and the model with a basis in new economic geography has significantly superior explanatory power. This adds support to the notion that in order to correctly understand differential regional economic development, we should move beyond neoclassical orthodoxy and that an increasing returns stance is more appropriate. However, the article also highlights some limitations of new economic geography theory.     

Sectors associations and similarities in input-output systems: An application of dual scaling and fuzzy logic to Canada and the United States

Various authors addressed interindustry linkages in the context of input-output systems, however many focused on the identification of key sectors in the economy. Sonis et al. (1996) offered as a field of influence theory an alternative approach focusing on the analytical importance of elements and combinations of elements. In an attempt to further the understanding of the linkages in an input-output system, the objective of this paper is to examine the cluster structure of sales and purchases profiles when the principle of excluded middle is violated by the use of fuzzy sets. The identification of fuzzy clusters is based on an analysis to derive an alternative decomposition ofinterindustry flows (Dridi and Hewings 2002), it is a complementary approach to the so-called Matrioshka principal (Sonis and Hewings 1990) and will be presented first; the approach looks into the hierarchy of the statistical dependence between supply and demand in input-output systems. The analysis on the cluster structure and the interindustry flows is conducted using the data analysis technique known as dual scaling (Nishisato 1980, 1994). Results of the analysis will be illustrated using input-output tables of the US and Canada. An earlier draft of this paper was presented at the 41st Annual Meeting of the Western Regional Science Association-Monterey, California (February 17–20, 2002), comments from conference participants, J. Le Gallo, and two anonymous referees are acknowledged. The usual disclaimer applies.     

Regional science: From crisis to opportunity

This essay reacts to the idea of crisis implied in earlier reviews of regional science and suggests that ongoing methodological debates in the fields of geography and economics provide many opportunities for regional scientists. The recent shift away from spatial analysis to social theory in geography has not found much support in regional science, but it is the implications of postmodernism that should be of most concern. Recent trends in economics have shown that lively debates can occur without embracing every new intellectual fashion. Regional science has much to gain from engagements in such debates as we approach the fin de millennium. Received: 16 October 1998 / Accepted: 26 October 1998     

Consumer choice and optimal locations models: Formulations and heuristics

A new direction of research in competitive location theory incorporates theories of consumer choice behavior in its models. Following this direction, the present article studies the importance of consumer behavior with respect to distance or transportation costs in the optimality of locations obtained by traditional competitive location models. We consider various ways of defining a key parameter in the basic maximum capture model (MAXCAP). This parameter will indicate a number of ways to take distance into account based on several consumer choice behavior theories. The optimal locations and the deviation in demand – captured when the optimal locations of the other models are used instead of the true ones – are computed for each model. We present a metaheuristic based on GRASP and the tabu search procedure to solve all the models. Computational experience and an application to a 55-node network are also presented. Received: 12 June 1998 / Accepted: 29 July 1999     

Spatial autoregressively distributed lag models: equivalent forms, estimation, and an illustrative commuting model

A spatial generalization of the (well-known special case from times series) Autoregressively Distributed lag model is defined. Equivalent forms—a Spatial Error Correction model, a Spatial Bewley model, and a Spatial Baardsen model—are considered. As none of these are consistently estimated by Ordinary Least Squares, an Instrument Variable estimation procedure is investigated using Monte Carlo simulation. It is found that there is a tendency to biased estimation results if the spatial autoregression is extremely low or extremely high. Finally, an empirical case illustrates the concepts discussed.     

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.     

Urban and regional distinctions for aggregating time series data

Abstract.  This article argues that using either the SIC or NAICS one-digit classifications as a method of aggregating two- and three-digit time series data can ignore important regional characteristics. We present a pairwise cointegration approach of aggregation where the aggregated sectors can vary widely across regions. By systematically constructing region-specific sectors from more detailed industries, we find that the level of agglomeration across rural and urban areas can affect the composition and number of local sectors in a region. We use the results pointing to rural/urban geographic distinctiveness to further consider the Carlino and Defina (1998, 1999 ) finding that monetary policy has disparate effects across regions in the U.S.     

The confusing relationship between environmental policy and location behaviour of firms: A methodological review of selected case studies

The literature on the effects of environmental policy on the location behaviour of firms has so far failed to draw any firm conclusions. Different studies have shown that the effects may be zero, negative or positive. They always tend to be small. This paper argues that methodological issues form a major explanation for the contradictory results. It discusses the methodological strengths and weaknesses of data collection and secondary data analysis. Moreover, several typical studies are reviewed both in terms of methodology and findings. The paper finds that methodological issues tend to affect the results. The main substantive result is that at the present intensity of environmental policy plant closing is most likely to result, followed by reduced location of new firms whereas relocation is the least likely response. The results have to be interpreted with caution, however, because of methodological problems inherent to most studies.     

Regional valuation of infrastructure and transport attributes for Swedish road freight

Is it possible to identify regional differences among shippers in their valuation of infrastructure improvements? In this study, the question is analysed using a random utility approach, where parameters are estimated by a logit model. Data consist of a Swedish stated-preference study from 1992. The results indicate that regional differences exist, but that a considerable heterogeneity in the empirical data means that in some cases the results are not robust. However, when industrial mix, shipping distance, and goods values are held constant, the analysis still indicates the existence of regional differences. Independently of the limitations in the results, the study has implications for any infrastructure benefit analysis where parameters from spatial averages are used. The results are based on short-term decisions, and one should recognise that parameters may vary in the mid- and long-term. Received: May 1999/Accepted: March 2001     

Integrated regional econometric+input-output modeling: Issues and opportunities

Recent research on integrated econometric+input-output modeling for regional economies is reviewed. The motivations for and the alternative methodological approaches to this type of analysis are examined. Particular attention is given to the issues arising from multiregional linkages and spatial effects in the implementation of these frameworks at the sub-national scale. The linkages between integrated modeling and spatial econometrics are outlined. Directions for future research on integrated econometric and input-output modeling are identified. Received: 20 January 1999 / Accepted: 26 June 1999     

Highway infrastructure and state-level employment: A causal spatial analysis

This paper analyses the causal relationship between highway infrastructure and employment within the U.S. We estimate dynamic panel models in a vector autoregressive framework using time-series cross-sectional data on lane miles of roadway capacity and private sector employment for the 48 contiguous states over the period 1984–1997. The issue of spatial dependence is explicitly taken into account by means of a spatial filtering technique. Our analysis reveals evidence of employment growth temporally influenced by annual growth in the provision of major highways within the same state and all other states, as well as the other way around. However, the results show that the existence and direction of these temporal and spatial effects depend on the type of highways and time lags considered.

Resumen

país comercial este artículo analiza la relación causal entre la infraestructura de autopistas y el empleo en los EE.UU. Estimamos modelos dinámico de datos de panel dentro de un marco autorregresivo vectorial utilizando datos transversales de series temporales en de capacidad de carretera en millas de carril y de empleo del sector privado para los 48 estados contiguos durante el periodo 1984–1997. Nuestro análisis revela pruebas de crecimiento del empleo influido temporalmente por el crecimiento anual en la provisión de autopistas principales dentro del mismo estado y el resto de estados, y a la inversa. Sin embargo, los resultados muestran que la existencia y dirección de estos efectos temporales y espaciales dependen del tipo de autopistas y los lapsos de tiempo considerados.

     

A global search procedure for parameter estimation in neural spatial interaction modelling

Parameter estimation is one of the central issues in neural spatial interaction modelling. Current practice is dominated by gradient based local minimization techniques. They find local minima efficiently and work best in unimodal minimization problems, but can get trapped in multimodal problems. Global search procedures provide an alternative optimization scheme that allows to escape from local minima. Differential evolution has been recently introduced as an efficient direct search method for optimizing real-valued multi-modal objective functions (Storn and Price 1997). The method is conceptually simple and attractive, but little is known about its behavior in real world applications. This article explores this method as an alternative to current practice for solving the parameter estimation task, and attempts to assess its robustness, measured in terms of in-sample and out-of-sample performance. A benchmark comparison against backpropagation of conjugate gradients is based on Austrian interregional telecommunication traffic data. Received: 11 November 1998 / Accepted: 14 January 1999     

A typology of community opportunity and vulnerability in metropolitan Australia

A multivariate model using hierarchical clustering and discriminant analysis is used to identify clusters of community opportunity and community vulnerability across Australia's mega metropolitan regions. Variables used in the model measure aspects of structural economic change, occupational change, human capital, income, unemployment, family/household disadvantage, and housing stress. A nine-cluster solution is used to categorise communities across metropolitan space. Significant between -city variations in the incidence of these clusters of opportunity and vulnerability are apparent, suggesting the emergence of marked differentiation between Australia's mega metropolitan regions in their adjustments to changing economic and social conditions. Received: 15 October 1999 / Accepted: 21 June 2000     

Ecological inference and spatial heterogeneity: an entropy-based distributionally weighted regression approach*

Abstract. In this article we compare two competing approaches to ecological modelling using test data. The first approach is based on the “traditional” method of Ordinary Least Squares (OLS), assuming constancy of parameters across disaggregated spatial units (spatial homogeneity). The second (new) approach is based on the method of Generalised Cross-Entropy (GCE), assuming varying parameters (spatial heterogeneity). The latter approach is designated as entropy-based “distributionally weighted regression” (DWR). The two approaches are tested in a real-world application, using data on per-capita GDP for the 17 regions and some covariates for the 50 provinces of Spain. Specifically, the performances of the two approaches are assessed by examining their capability in tracking the actual per-capita GDP data for the provinces (while treating them as if they were not observed by the econometrician), and in showing evidence of spatial heterogeneity. Our findings indicate that the GCE varying-parameter approach outperforms the OLS approach in terms of predictive power. Specifically, we find that the GCE predictions make efficient use of the lower-level information that is available. In addition, it is shown that entropy-based DWR has some potential as a useful technique for investigating spatially heterogeneous relationships at the lower level of analysis that might otherwise be overlooked.