Search

While considerable attention has been directed to the national‐level impacts of global value chains, far less attention has been focused on the way in which global production fragmentation has affected regional economies. Using some measures derived from a multiregional, multisectoral input–output model, this paper analyzes the position and share of EU regions in Global Value Chains (GVC). The spatial determinants of these two dimensions are explored using spatial econometric methods to capture the influence of neighboring regions on these outcomes. Empirically, the focus is on a set of NUTS2 European regions for the most recent year (2010) of the EUREGIO database. Our results confirm the hypothesis of spatial dependence between regions conditioning the engagement and position GVCs, suggesting that global production processes are influenced by regional and local factors. In particular, spatial spillover effects play a significant role conditioned by both geographical proximity and similarity of production structures. The results show that sharing certain characteristics, some of them associated to their degree of proximity and the neighbouring situation of regions condition their specialization, participation and positioning in GVC, generating some important insights informative for the formulation of regional development policies. [ABSTRACT FROM AUTHOR]

Spatial interactions among regional units may influence the geographical distribution of economic activities. Many traditional measures of geographical concentration fail in capturing this aspect, being insensitive to permutations of the spatial position of regions. This paper proposes an approach to the measurement of geographical concentration of economic activities that accounts for spatial interactions among regions. The locational Gini is split into spatial and non‐spatial components, so that a new interpretation of the index is presented. The measure is applied to evaluate the geographical concentration of different economic sectors for 1,323 NUTS 3 regions in the European Union over the period 2001–2018. [ABSTRACT FROM AUTHOR]

This study attempts to identify the causal and/or direct effects of sociocultural determinants of infant mortality in Turkey within a regional context using causal graph analysis and global and local spatial models. The conceptual framework, combined with the data, shows that fertility and consanguinity have direct effects on infant mortality rates, and that female illiteracy, as a proxy for maternal education, is the main cause of rising infant mortality even in the presence of latent confounding. The surface of estimates further shows that the local effects of female illiteracy and consanguinity are non‐stationary across space, calling for location‐specific policies. [ABSTRACT FROM AUTHOR]

The relationship between labour force participation and the business cycle is a common topic in economic literature. However, few studies have examined if the cyclical sensitivity of labour force participation is influenced by social effects. In this paper, we construct a theoretical model defining a relatively new hypothesis, the bandwagon worker effect (BWE). We use spatial econometrics techniques to test the existence of the BWE in the local labour markets in Spain. Our results reveal a positive spatial dependence in the cyclical sensitivity of labour force participation that decreases as we fix a laxer neighbourhood criterion, which verifies the existence of the BWE. [ABSTRACT FROM AUTHOR]

Gibrat's law asserts that the growth of a city is independent of its initial size, but the populations of cities display a pattern of systematic agglomeration. This pattern may emerge because some cities are more attractive than others. We analyse the relationship between the growth and size of 1,188 cities in the South Region of Brazil using municipal data between 2000 and 2010. The selected model is the spatial Durbin model (SDM) that controls for temporal and spatial dependence, relevant omitted variables, economic factors, local amenities and externalities. The results indicate that Gibrat's law is not robust when cities interact. [ABSTRACT FROM AUTHOR]

Stochastic dominance tests are used to measure whether distributions are directionally‐distinct. Using stochastic dominance measures, an income distribution can be measured to be more favorable for its members at all income levels than another distribution. This contrasts with conventional σ and β‐convergence approaches that compare distributions at a set of predetermined income levels. Given this comprehensiveness, stochastic dominance measures can yield novel insight into the relationship between income distributions, and thus to the relative economic welfare of inhabitants of different societies. However, stochastic dominance measures used in the analysis of regional income convergence have ignored the complications of geography. In this paper we examine the properties of common tests for stochastic dominance using various descriptive models of geographically‐realistic income growth processes. We find that the false positive rate of stochastic dominance tests increases significantly when comparing spatially‐informed income distributions growing over time. Further, this over‐eager rejection rate requires only that one distribution be spatially‐dependent, unlike some other bivariate statistics. We demonstrate that both the parametric and non‐parametric spatial filtering procedures are effective at resolving these issues in restricted circumstances for higher‐order dominance tests. Overall, while providing a novel and useful perspective on income distribution dynamics, stochastic dominance measures are demonstrated to have undesirable properties when used in geographically‐realistic scenarios and they resist one common method to address these issues. Solutions to the concerns expressed here remain open. [ABSTRACT FROM AUTHOR]

Drawing upon a panel dataset on China's state‐owned construction land supply at the prefecture level, this paper adopts the spatial panel data model to investigate the existence of spatial dependence in the mechanisms behind China's urban land expansion from 2004 to 2014. The empirical results show that China's urban land expansion has been mainly influenced by a quadruple process of urbanization, industrialization, globalization and decentralization. The strong existence of spatial dependence in China's urban land expansion can be reflected by the significant coefficient estimates of the spatial lags of both the dependent variable and independent variables. [ABSTRACT FROM AUTHOR]

Abstract: This study presents novel evidence regarding the role of regional internet infrastructure in reducing regional per capita income disparities. We base our study on the assumptions that (1) the diffusion of information homogenizes regional economies through reducing the dissimilarities in institutions and culture, and (2) the telecommunication capacity, represented by the internet infrastructure of a region, facilitates this flow of information. Using the data from the 26 statistical NUTS‐2 regions of Turkey for the period 1999–2011, we find evidence that internet infrastructure increases the speed of regional convergence. [ABSTRACT FROM AUTHOR]

This paper examines the growth rate volatility of European regions' per capita GDP from 1992 to 2008. We measure the regional volatility using a new methodology based on Markov matrices, and investigate its main determinants. Volatility displays a geographical pattern and a significant spatial dependence. Output composition appears one of the main drivers of volatility; among the other determinants we find a negative impact of the size of regional economies and of labour market flexibility, and a positive impact of sectoral concentration, financialization of the economy, and, occasionally, of participation in EMU. [ABSTRACT FROM AUTHOR]

This paper estimates a conditional β-convergence model of labour productivity growth in Italy's manufacturing industry during 1871-1911, accounting for spatial dependence. The empirical evidence is based on a recent set of data at provincial (NUTS 3) level on manufacturing value added at 1911 prices, and a new set of data on human and social capital, political participation, and infrastructures. By focusing on a country and a time when the agglomeration forces and spillover effects advocated by the new economic geography were only starting to operate, we can investigate a particularly interesting case study. Our results suggest that human capital, a cooperative culture, and initial productivity in neighbouring provinces can explain much of the geographical variability of productivity growth in manufacturing in nineteenth-century Italy. [ABSTRACT FROM AUTHOR]

Drawing upon township-level data on high-tech firms of Nanjing, China, this paper adopts a spatial econometric approach to examining the existence of spatial dependence and heterogeneity in the location processes of high-tech firms. The results show that some locational determinants of neighbouring townships exert significant impacts on the attractiveness of a certain township for high-tech firms. Besides, the marginal effects of some locational determinants are found to vary across space. In general, these results point to the need to account for both inter-territorial spillovers and cross-spatial variance in the investigation of factors that influence high-tech firm location. [ABSTRACT FROM AUTHOR]

We explore the estimation of origin-destination (OD), city-pair, air passenger flows. Our dataset contains 279 cities, worldwide, over 2010-2012. Allowing for two gravity model specifications (log-normal and Poisson), we compare non-spatial and spatial models. We are the first to apply spatial econometric flow models and eigenfunction spatial filtering approaches to air transport. Distinguishing between origin, destination and network effects, we determine the impact and significance of a change in a variable in a given city, on flows originating from and going to that city and originating from a different city and going to an alternative city. Finally, we compare models based on different specifications of the spatial weight matrix. [ABSTRACT FROM AUTHOR]

The paper analyses the impact of domestic and international tourism on the economic growth process for 179 European regions. The econometric analysis is based on a spatial growth regression framework where the rate of GDP per capita growth at the regional level for the period 1999-2009 depends on tourism flows, in addition to the traditional growth variables. Besides controlling for initial conditions, we also include a wide set of covariates to account for the endowment of human and technological capital and for the geographical, social and institutional features of the regions. The results, confirmed by several robustness checks, demonstrate that regional growth is positively affected by domestic and international tourism. [ABSTRACT FROM AUTHOR]

A statistical test procedure is proposed to check a polynomial relationship of the non-parametric component in partially linear spatial autoregressive models, in which a residual-based bootstrap procedure is used to derive the p-value of the test. Some simulations are conducted to assess the performance of the test and the results show that the bootstrap approximation to the null distribution of the test statistic is valid and the test is powerful in identifying a polynomial relationship of the non-parametric component. Furthermore, a real-world example is given to demonstrate the usefulness of the proposed test. [ABSTRACT FROM AUTHOR]

This paper employs a spatial Durbin growth model to estimate the impact of trade openness on regional per capita income in Brazil using a data set of 469 Brazilian micro-regions over the period 2004-2007. We calculate the direct, indirect and cumulative impact on per capita income of trade openness and human capital in these micro-regions. Results indicate that greater trade openness in a region promotes economic development locally, while exerting negative influence on per capita income of the neighbouring regions. Our findings also show that human capital has a positive - direct and indirect - impact on the economic development of Brazilian micro-regions. [ABSTRACT FROM AUTHOR]

Studies on governance generally ignore spatial dependence among the observations. Employing spatial econometric methods, we find that governance in one country exhibits a positive relationship with governance in neighbouring countries. Consequently, a change in a single explanatory variable in a particular country not only affects the level of governance in that country itself, but also in neighbouring countries. Using maximum likelihood function values and Bayesian posterior model probabilities, we also find that the spatial arrangement of the countries in the sample is best described by a spatial weights matrix based on the 10 nearest neighbours of every country in the sample. [ABSTRACT FROM AUTHOR]

The objective of this paper is to advance in the discussion of the topic of heterogeneity in a spatial econometric model. The proposal is not a novelty as there is a great deal of experience accumulated on the same subject. What differentiates this work is that we use a broad notion of the term heterogeneity, in association with different symptoms of stability in the elements of the equation. That is, we deal with problems ( i) in the coefficients of regression, ( ii) in the variance of the random term and ( iii) in the mechanisms of spatial dependence. With this purpose, we develop several tests through which we tackle the problem of heterogeneity from various perspectives. We assess their performance through a Monte Carlo experiment. Resumen El objetivo de este artículo es avanzar en la discusión sobre el tema de la heterogeneidad existente en un modelo econométrico espacial. La propuesta no es novedosa por cuanto ya existe mucha experiencia acumulada sobre el mismo tema. Lo que distingue a este trabajo es que utilizamos una lectura amplia del término heterogeneidad, asociado a diversos síntomas de estabilidad en los elementos de la ecuación. Esto es, tratamos con problemas ( i) en los coeficientes de regresión, ( ii) en la varianza del término aleatorio y ( iii) en los mecanismos de dependencia espacial. Con este propósito, desarrollamos varias pruebas mediante las cuales abordamos el problema de la heterogeneidad desde perspectivas diferentes. Evaluamos su rendimiento mediante un experimento de Monte Carlo. [ABSTRACT FROM AUTHOR]

This paper studies the evolution of regional income disparities in Europe. Besides using a more complete data set that offers a more detailed look at the evolution of regional incomes in Western Europe than previous studies, it is the first to shed empirical light on regional income differences and their evolution in Eastern Europe during the transition phase from communism towards EU membership by means of a (spatial) Markov chain analysis. Regional income disparities in Western Europe are found to be decreasing over time and less persistent than reported in earlier studies. In the case of Eastern Europe some regions are likely to fall behind in terms of GDP per capita whereas a substantial number of other regions will be able to (slowly) catch up with their Western neighbours. Moreover in Western Europe localized regional conditions appear to be a main determinant of the observed income differences, whereas in Eastern Europe country-specific factors are of bigger importance. [ABSTRACT FROM AUTHOR]

In this article a semiparametric spatial Durbin model is employed to analyse the growth behaviour of 155 European regions in the period 1988–2000. This specification combines the semiparametric approach with the usual parametric spatial econometric technique to accommodate both spatial dependence and nonlinearities as suggested by recent neoclassical growth models with spatial technological interdependence. The results provide evidence of nonlinearities in the effect of initial per capita incomes and human capital investments. Moreover, the specification used allows identifying the effect of the interaction between the characteristics (initial conditions and structural variables) of each region and those of its neighbours. Finally, it shows some indication of global spillovers across-country and local spatial spillovers from domestic neighbours. Resumen En este artículo se emplea un modelo semiparamétrico espacial de Durbin para analizar el comportamiento del crecimiento de 155 regiones europeas durante el periodo 1988–2000. Esta especificación combina el enfoque semiparamétrico con técnicas econométricas espaciales paramétricas habituales para reconciliar la dependencia espacial y las no linealidades, tal y como sugieren los modelos de crecimiento neoclásicos recientes con interdependencia tecnológica espacial. Los resultados ofrecen pruebas de no linealidades en el efecto de ingresos per capita iniciales e inversiones en capital humano. Además, la especificación utilizada permite utilizar el efecto de la interacción entre las características (condiciones iniciales y variables estructurales) de cada región y las de sus vecinos. Finalmente, da una idea de spillovers (efectos de derrame) globales entre países y spillovers espaciales locales de regiones vecinas dentro del país. [ABSTRACT FROM AUTHOR]

This article develops a growth-based regionalisation of the United States using both principal components and cluster analyses to endogenously sort states into regional transition clubs with somewhat uniform annual rates of per capita real GSP growth in the period 1977–2004. I correlate the principal components with annual growth in per capita real GDP and assess spatial dependencies in the identified transition clubs. Growth variability in the transition clubs is compared with growth variability in BEA and Census regions. Results show a large Coastal transition club that contains most of the New England, Middle Atlantic, and South Atlantic census regions. California, Minnesota, and Arizona belong to this grouping. A second growth transition club titled Eastern Interior groups most of the states in the East North Central and the East South Central census regions. A Western Interior region groups states in the southern Great Plains. Coefficients of variation show that these three large interstate groupings grow more uniformly compared with associated census and BEA regions. Growth in western states is idiosyncratic. Most western states group with one or two related states, California and Arizona associate with the Coastal club, Nevada does not pigeonhole well with other states, and Alaska's annual growth trajectory is unique. Este artículo desarrolla una regionalización de los Estados Unidos basada en crecimiento usando componentes principales y análisis de cluster para agrupar los estados en grupos de transición regional según tasas anuales de crecimiento más o menos uniformes en el producto estatal bruto (GSP) real per capita en el periodo 1977–2004. Correlaciono los componentes principales con el crecimiento anual en el producto interior bruto (GDP) real per capita y evalúo dependencias espaciales en los grupos de transición identificados. La variabilidad de crecimiento en los grupos de transición se compara con la variabilidad de crecimiento en regiones BEA (Bureau of Economic Analysis) y Censuales. Los resultados muestran un grupo de transición grande en la Costa que contiene la mayoría de regiones censuales de New England, Atlántico Medio, y Atlántico Sur. California, Minnesota, y Arizona pertenecen a este grupo. Un Segundo grupo de transición de crecimiento llamado Interior Este aglutina la mayoría de estados de las regiones censuales Central Norte Oriental y Central Sur Oriental. Una región Interior Occidental agrupa los estados de las Grandes Llanuras del Sur. Los coeficientes de variación muestran que estos tres grandes grupos interestatales crecen más uniformemente en comparación con las regiones censuales y BEA asociadas. El crecimiento en los estados occidentales es idiosincrásico. La mayoría de los estados occidentales se agrupan con uno o dos estados relacionados, California y Arizona se asocian con el grupo de la Costa, Nevada no se clasifica bien con ningún otro estado, y la trayectoria de crecimiento anual de Alaska es única. [ABSTRACT FROM AUTHOR]

In this note we provide evidence on the importance of location for the growth of per capita income of Brazilian states over the period 1985–2001. The study presents strong evidence of spatial dependence, and that regional inequality reduction occurred simultaneously with increasing spatial autocorrelation. The analysis of local indicators of spatial association confirmed that conclusion, showing the existence of two geographical clusters, one of low income states in the Northeast and North regions, and another of rich states in the Southeast and South regions. The low value for the convergence coefficient, in conjunction with the strong influence of shocks in the residuals, indicate the existence of a very sensible dynamic pattern of convergence across Brazilian states, which helps explaining the well documented persistence in regional income disparities in Brazil. After conditioning on other important variables that could affect growth, however, spatial dependence disappears. We have thus identified two potential channels through which the strong spatial dependence in the process of convergence of per capita income of Brazilian states occurs. [ABSTRACT FROM AUTHOR]

This paper explores the implications that spatial effects can hold for the application of measures of σ-convergence. The bias of a common indicator of σ-convergence is examined for a family of spatial process models including: [a] spatial lag, [b] spatial error, and [c] spatial moving average. We show that the measure of σ-convergence is sensitive to a number of distinct influences including global dispersion, spatial dependence, and a variety of forms of spatial heterogeneity. We suggest a decomposition of the convergence indicator into two components: one reflecting global dispersion, and one reflecting the influence of spatial effects. We then illustrate this approach with a case study of the U.S. states over the 1929–2000 period. [ABSTRACT FROM AUTHOR]

This article analyses the consequences of spatial interdependence for convergence in a Solow-type growth model. In such a model a region's speed of convergence depends on its location and it can be decomposed into: (i) the speed of convergence proper, (ii) the remoteness effect, and (iii) the impact of the initial gap. Also σ-convergence is affected by spatial interaction and we propose a decomposition to isolate the impact of spatial spillovers. Using GDP per capita of European regions, we calibrate a numerical model with parameters typically found in spatial convergence studies. We find that the remoteness effect leads to considerable variation in the speed of convergence while it marginally affects σ-convergence. [ABSTRACT FROM AUTHOR]

The article examines the extent to which foreign manufacturing firms in the UK promote productivity growth in the domestically owned manufacturing sector through their buying and supplying relationships. Evidence for intra- and inter-regional externalities from the presence of foreign manufacturing, and intra- and inter-industry effects is brought to light. Externalities in the domestic sector are most noticeable where foreign manufacturing sells to domestic manufacturing. These externalities are, however, not wholly robust to different specifications of spatial dependence. The findings are positioned in a debate, which has tended to view backward (as opposed to forward) linkages from multinationals to domestically owned supply bases as a critical driver of indirect economic benefits. [ABSTRACT FROM AUTHOR]

We examine the relationship between county per capita income and toxic pollutants using a comprehensive model of the Environmental Kuznets Curve. The model incorporates ethnic diversity, spatial effects and most independent variables used in previous studies. Initial results suggest that the relationship follows an inverted-U-shape. However, incorporation of a cubic term for income reveals that toxic pollution eventually increases again as income continues to rise. Ethnic diversity and spatial effects are found to be important in understanding toxic pollution in US counties. We also detect an EKC-type relationship with respect to income inequality. [ABSTRACT FROM AUTHOR]