Regional public stock reductions in Spain: estimations from a multiregional spatial vector autorregressive model

The estimation of the impact of public investment on regional economic growth requires consideration of the spatio-temporal dynamics among the state variables of each region. Recent austerity policies in Spain that feature temporary decreases in the accumulation of regional public capital should thus be evaluated in terms of their impact on the economy as a whole, on specific regions together with the spillovers effects from one region to the rest of the regional system. Applying a multiregional integrated specification to model interdependencies across regions, our results indicate that, while global decreases in public investment have a homogenously negative effect on the output of all the regions, the Spanish regions portray heterogeneous responses from localized public capital stock reductions over the simulation period considered

Health Inequalities Across The European Union Regions: A Beta-Convergence Approach

This work is devoted to the study of the variations of health status (measured by life expectancy) across the EU regions of NUTS II level. We apply existing tools developed in economic growth literature to study a mortality convergence. Using the idea of unconditional convergence model developed for economic growth, we can confirm a decrease or increase of regional health inequalities. The main research hypothesis is as follows: whether regions with lower initial life expectancies have experienced the largest increases in life expectancies. To verify the hypothesis of beta-convergence we use spatial econometric models which additionally allow to take the geographic dependence among the surveyed regions into consideration. Due to the heterogeneity of the surveyed spatial units we also verify the hypothesis of the club beta-convergence

The countryside in urbanized Flanders: towards a flexible definition for a dynamic policy

The countryside, the rural area, the open space, … many definitions are used for rural Flanders. Everyone makes its own interpretation of the countryside, considering it as a place for living, working or recreating. The countryside is more than just a geographical area: it is an aggregate of physical, social, economic and cultural functions, strongly interrelated with each other. According to international and European definitions of rural areas there would be almost no rural area in Flanders. These international definitions are all developed to be used for analysis and policy within their specific context. They are not really applicable to Flanders because of the historical specificity of its spatial structure. Flanders is characterized by a giant urbanization pressure on its countryside while internationally rural depopulation is a point of interest. To date, for every single rural policy initiative – like the implementation of the European Rural Development Policy – Flanders used a specifically adapted definition, based on existing data or previously made delineations. To overcome this oversupply of definitions and delineations, the Flemish government funded a research project to obtain a clear and flexible definition of the Flemish countryside and a dynamic method to support Flemish rural policy aims. First, an analysis of the currently used definitions of the countryside in Flanders was made. It is clear that, depending on the perspective or the policy context, another definition of the countryside comes into view. The comparative study showed that, according to the used criteria, the area percentage of Flanders that is rural, varies between 9 and 93 per cent. Second, dynamic sets of criteria were developed, facilitating a flexible definition of the countryside, according to the policy aims concerned. This research part was focused on 6 policy themes, like ‘construction, maintenance and management of local (transport) infrastructures’ and ‘provision of (minimum) services (education, culture, health care, …)’. For each theme a dynamic set of criteria or indicators was constructed. These indicators make it possible to show where a policy theme manifests itself and/or where policy interventions are possible or needed. In this way every set of criteria makes up a new definition of rural Flanders. This method is dynamic; new data or insights can easily be incorporated and new criteria sets can be developed if other policy aims come into view. The developed method can contribute to a more region-oriented and theme-specific rural policy and funding mechanism

How effective has the Spanish lockdown been to battle COVID-19? A spatial analysis of the coronavirus propagation across provinces

This paper examines the propagation of COVID-19 across the Spanish provinces and assesses the effectiveness of the Spanish lockdown of the population implemented on March 14, 2020 in order to battle this pandemic. To achieve these objectives, a standard spatial econometric model used in economics is adapted to resemble the popular reproduction models employed in the epidemiological literature. In addition, we introduce a counterfactual exercise that allows us to examine the Gross domestic product (GDP) gains of bringing forward the date of the Spanish Lockdown. We find that the number of COVID-19 cases would have been reduced by 70.4% in the absence of spatial propagation between the Spanish provinces. We also determine that the lockdown prevented the propagation of the virus within and between provinces. As such, the Spanish lockdown reduced the number of potential COVID-19 cases by 82.8%. However, the number of coronavirus cases would have been reduced by an additional 11.6% if the lockdown had been brought forward to March 7, 2020. Finally, an earlier lockdown would have saved approximately 26,900,000,000 eurosMinisterio de Ciencia, Innovación y Universidades, Grant/Award Number: PRX19/00596, PRX19/00589 INNJOBMAD-CM, Grant/Award Number: H2019/HUM-5761 Ministry of Science and Innovation, Grant/Award Number: PID2020-113076GB-I0

GEOGRAPHIC AND INSTITUTIONAL DETERMINANTS OF REAL INCOME:A SPATIO-TEMPORAL SIMULTANEOUS EQUATION APPROACH

This paper tests a series of prominent hypotheses regarding the determinants of per-capita income using a novel spatial econometric approach to control for spillovers among neighboring countries and for spatially correlated omitted variables. We use simultaneous equations to identify alternative channels through which country characteristics might affect income, and then test the robustness of those effects. We find support for both “institutionalist” and “geographic” determinants of income. A time-varying index of institutional quality has a strong independent effect on current income, but there is also a persistent effect of geographic factors such as seasonal frost, malaria transmission, and coastal location, which influence income through their links to agricultural output, health, urbanization and trade. The data cover 95 countries across the world from 1960 through 2002, which we use to construct a pooled dataset of nine 5-year averages centered on 1960, 1965, and so on through 2000. We use both limited and full information estimators, partly based on a generalized moments (GM) estimator for spatial autoregressive coefficients, allowing for spatial error correlation, correlation across equations, and the presence of spatially lagged dependent variableseconomic growth, geography, institutions, spatial econometrics, simultaneous equations

Geographical competition-complementarity relationships between Greek regional economies

This paper examines the nature of interregional competition and complementarity in Greece. Covering the 1975-2002 period, the analysis provides a picture of the interregional interactions by focusing on derived linkages between the regional economies. The adopted methodology combines previous approaches based on the Dendrinos-Sonis model (e.g. Nazara et al 2002, Bonet 2003) and a cointegration modeling framework (Marquez and Hewings, 2003). A sensitivity analysis of the model coefficients that designate competition or complementarity, with respect to time, is undertaken as well.

Do more trucks lead to more motor vehicle fatalities in European roads? Evaluating the impact of specific safety strategies.

Truck operations have recently become an important focus of academic research not only because road freight transport is a key part of logistics, but because trucks are usually associated with negative externalities including pollution, congestion and traffic accidents. While the negative environmental impacts of truck activities have been extensively analyzed, comparatively little attention has been paid to the role of trucks in road accidents. A review of the literature identifies various truck-traffic safety related issues: frequency of accidents and their determinants; risk factors associated with truck driver behavior (including cell phone use, fatigue, alcohol and drugs consumption); truck characteristics and facilities (roadway types, specific lanes and electronic stability programs) to improve performance of vehiclemaneuvering; and the safety characteristics of heavy and large trucks. However, to date, there seems to have been developed few studies evaluating the complex coexistence of trucks and cars on roads and that may support the implementation of differential road safety strategies applied to them. This paper focuses on the impact on the traffic fatalities rate of the interaction between trucks and cars on roads. We also assess the efficiency of two stricter road safety regulations for trucks, as yet not harmonized in the European Union; namely, speed limits and maximum blood alcohol concentration rates. For this, econometric models have been developed from a panel data set for European Union during the years 1999–2010. Our findings show that rising motorization rates for trucks lead to higher traffic fatalities, while rising motorization rates for cars do not. These effects remain constant across Europe, even in the most highly developed countries boasting the best highway networks. Furthermore, we also find that lower maximum speed limits for trucks are effective and maximum blood alcohol concentration rates for professional drivers are only effective when they are strictly set to zero. Therefore, our results point to that the differential treatment of trucks is not only adequate for mitigating an important source of congestion and pollution, but that the implementation of stricter road safety measures in European countries for the case of trucks also contributes significantly to reducing fatalities. In summary, and as a counterpoint to the negative impact of trucks on road traffic accidents, we conclude the effectiveness of efforts made in road safety policy (based on specific traffic regulations by vehicle type imposed by member States) to counteract the safety externalities of freight transportation in the European Union. In certain sense, our study might provide indirect support to public policies implemented at the macro European level to promote multimodal transport corridors. In this respect, there is an increasing focus at the European level on how freight transport can be moved from trucks on roads to more environmentally-sustainable modes, such as rail and ship.Dirección General de Tráfico SPIP2014127

On Diffusion of Ideas in the Academic World: the Case of Spatial Econometrics

Spatial econometrics is a fast-growing field in the series of quantitative disciplines, auxiliaries of economics and related social sciences. Space, friction, interdependence, spatiotemporal components, externalities and many other aspects interact and should be treated adequately in this field. The publication of the Paelinck and Klaassen book in the late 1970s generated virtually the field spatial econometrics This article studies the diffusion of spatial econometrics, through experienced history on the one hand, on the other through bibliometric methods. Although this field was an “Invisible College” up to 2006 (absence of any organization in form of association, conference, journal, etc.), the databases depict a fast diffusion in the past and strong prospects for the future.

Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions

In any economic analysis, regions or municipalities should not be regarded as isolated spatial units, but rather as highly interrelated small open economies. These spatial interrelations must be considered also when the aim is to forecast economic variables. For example, policy makers need accurate forecasts of the unemployment evolution in order to design short- or long-run local welfare policies. These predictions should then consider the spatial interrelations and dynamics of regional unemployment. In addition, a number of papers have demonstrated the improvement in the reliability of long-run forecasts when spatial dependence is accounted for. We estimate a heterogeneouscoefficients dynamic panel model employing a spatial filter in order to account for spatial heterogeneity and/or spatial autocorrelation in both the levels and the dynamics of unemployment, as well as a spatial vector-autoregressive (SVAR) model. We compare the short-run forecasting performance of these methods, and in particular, we carry out a sensitivity analysis in order to investigate if different number and size of the administrative regions influence their relative forecasting performance. We compute short-run unemployment forecasts in two countries with different administrative territorial divisions and data frequency: Switzerland (26 regions, monthly data for 34 years) and Spain (47 regions, quarterly data for 32 years)