The effect of short-term changes in air pollution on respiratory and cardiovascular morbidity in Nicosia, Cyprus.

Presented at the 6th International Conference on Urban Air Quality, Limassol, March, 2007. Short-paper was submitted for peer-review and appears in proceedings of the conference.This study investigates the effect of daily changes in levels of PM10 on the daily volume of respiratory and cardiovascular admissions in Nicosia, Cyprus during 1995-2004. After controlling for long- (year and month) and short-term (day of the week) patterns as well as the effect of weather in Generalized Additive Poisson models, some positive associations were observed with all-cause and cause-specific admissions. Risk of hospitalization increased stepwise across quartiles of days with increasing levels of PM10 by 1.3% (-0.3, 2.8), 4.9% (3.3, 6.6), 5.6% (3.9, 7.3) as compared to days with the lowest concentrations. For every 10μg/m3 increase in daily average PM10 concentration, there was a 1.2% (-0.1%, 2.4%) increase in cardiovascular admissions. With respects to respiratory admissions, an effect was observed only in the warm season with a 1.8% (-0.22, 3.85) increase in admissions per 10μg/m3 increase in PM10. The effect on respiratory admissions seemed to be much stronger in women and, surprisingly, restricted to people of adult age

Efficiency measurement in the Spanish cadastral units through DEA

This paper proposes an approach to measure efficiency of a set of units operating in an administrative public service, namely real estate cadastral offices, which have not been analysed previously. This study has been made possible thanks to the database provided by the Directorate General of Real Estate Cadastral Assessment which includes information on the 52 local offices in Spain for the period between 2000 and 2005. Data Envelopment Analysis has been used to estimate the efficiency levels of these offices. Subsequently, a second stage model based on bootstrap techniques is applied in order to identify other potential factors (differences in management techniques, demographic and economic variables, etc.) that may affect the estimated efficiency measures

A Comparison of Machine-Learning Methods to Select Socioeconomic Indicators in Cultural Landscapes

Cultural landscapes are regarded to be complex socioecological systems that originated as a result of the interaction between humanity and nature across time. Cultural landscapes present complex-system properties, including nonlinear dynamics among their components. There is a close relationship between socioeconomy and landscape in cultural landscapes, so that changes in the socioeconomic dynamic have an effect on the structure and functionality of the landscape. Several numerical analyses have been carried out to study this relationship, with linear regression models being widely used. However, cultural landscapes comprise a considerable amount of elements and processes, whose interactions might not be properly captured by a linear model. In recent years, machine-learning techniques have increasingly been applied to the field of ecology to solve regression tasks. These techniques provide sound methods and algorithms for dealing with complex systems under uncertainty. The term ‘machine learning’ includes a wide variety of methods to learn models from data. In this paper, we study the relationship between socioeconomy and cultural landscape (in Andalusia, Spain) at two different spatial scales aiming at comparing different regression models from a predictive-accuracy point of view, including model trees and neural or Bayesian networks

Estimating the Personal Income Distribution in Spanish Municipalities Using Tax Micro-Data

Local income data is an important economic indicator, widely used in a broad range of studies related to regional convergence, urban economics, fiscal federalism, housing and spatial analysis. Despite its importance, there is a lack of official data on local incomes and, most importantly, on local income distributions. In this paper we use official data on personal income tax returns and a reweighting procedure to derive a representative income sample at the local level. Unlike previous attempts in the literature to acquire local income estimates, the results obtained allow us to derive not only an average value for income but also its local distribution, a valuable and informative tool for analysing distributional and income inequality. We apply this methodology to Spanish Personal Income Tax micro-data and illustrate its potential use in analysing income inequality by means of computed Gini, Atkinson indexes and top 0.01%, 0.5% and 0.01% income share measures for the most populated Spanish municipalities (those with over 160,000 inhabitants)

Cycle commuting in Belgium: Spatial determinants and ‘re-cycling’ strategies

This paper attempts to explain the spatial variation of the use of a bicycle for commuting to work at the level of the 589 municipalities in Belgium. Regression techniques were used and special attention was paid to autocorrelation, heterogeneity and multicollinearity. Spatial lag models were used to correct for the presence of spatial dependence and a disaggregated modelling strategy was adopted for the northern and southern parts of the country. The results show that much of the inter-municipality variation in bicycle use is related to environmental aspects such as the relief, traffic volumes and cycling accidents. Town size, distance travelled and demographic aspects also have some effect. In addition, there are regional differences in the effects of the structural covariates on bicycle use: the impact of variables such as traffic volume and cycling accidents differs substantially between the north and the south of the country. This paper also suggests that high rates of bicycle use in one municipality stimulate cycling in neighbouring municipalities, and hence that a mass effect can be initiated, i.e. more cycle commuting encourages even more commuters in the area to cycle. These findings provide some recommendations for decision-makers wishing to promote a shift from car to bicycle usecycling, commuting, spatial lag model, spatial regime, pro-cycling strategies

COLONIAL INSTITUTIONS AND LONG-RUN ECONOMIC PERFORMANCE IN COLOMBIA: IS THERE EVIDENCE OF PERSISTENCE?

A recent body of literature has claimed that differences in long-run economic performance within the Americas stem from the different institutional structures established during colonial times. This research tries to find evidence of institutional persistence in Colombia using direct measures of colonial institutions, particularly the intensity of encomiendas, slavery and State presence. The paper deals with the possible endogeneity of colonial institutions developing an instrumental variables strategy based upon colonial institutional design. We find evidence of institutional persistence of encomienda, slavery and State capacity on a series of current socioeconomic outcomes.Institutions, institutional persistence, colonial history, long run development

The use of satellite data, meteorology and land use data to define high resolution temperature exposure for the estimation of health effects in Italy

Introduction. Despite the mounting evidence on heat-related health risks, there is limited evidence in suburban and rural areas. The limited spatial resolution of temperature data also hinders the evidence of the differential heat effect within cities due to individual and area-based characteristics. Methods. Satellite land surface temperature (LST), observed meteorological and spatial and spatio-temporal land use data were combined in mixed-effects regression models to estimate daily mean air temperature with a 1x1km resolution for the period 2000-2010. For each day, random intercepts and slopes for LST were estimated to capture the day-to-day temporal variability of the Ta–LST relationship. The models were also nested by climate zones to better capture local climates and daily weather patterns across Italy. The daily exposure data was used to estimate the effects and impacts of heat on cause-specific mortality and hospital admissions in the Lazio region at municipal level in a time series framework. Furthermore, to address the differential effect of heat within an urban area and account for potential effect modifiers a case cross-over study was conducted in Rome. Mean temperature was attributed at the individual level to the Rome Population Cohort and the urban heat island (UHI) intensity using air temperature data was calculated for Rome. Results. Exposure model performance was very good: in the stage 1 model (only on grid cells with both LST and observed data) a mean R2 value of 0.96 and RMSPE of 1.1°C and R2 of 0.89 and 0.97 for the spatial and temporal domains respectively. The model was also validated with regional weather forecasting model data and gave excellent results (R2=0.95 RMSPE=1.8°C. The time series study showed significant effects and impacts on cause-specific mortality in suburban and rural areas of the Lazio region, with risk estimates comparable to those found in urban areas. High temperatures also had an effect on respiratory hospital admissions. Age, gender, pre-existing cardiovascular disease, marital status, education and occupation were found to be effect modifiers of the temperature-mortality association. No risk gradient was found by socio-economic position (SEP) in Rome. Considering the urban heat island (UHI) and SEP combined, differential effects of heat were observed by UHI among same SEP groupings. Impervious surfaces and high urban development were also effect modifiers of the heat-related mortality risk. Finally, the study found that high resolution gridded data provided more accurate effect estimates especially for extreme temperature intervals. Conclusions. Results will help improve heat adaptation and response measures and can be used predict the future heat-related burden under different climate change scenarios.Open Acces

A Bottom-Up Spatial (Frontier) Model with an Application to a Spanish Electricity Network

In December 2013 a new electricity law was approved in Spain as part of an electricity market reform including a new remuneration scheme for distribution companies. This remuneration scheme was updated in December 2019 and the new regulatory framework introduced a series of relevant modifications that aim to encourage the regulated firms to reduce their power supply interruptions using a benchmarking approach. While some managerial decisions can prevent electricity power supply interruptions, other managerial decisions are more oriented to mitigate the consequences of these interruptions. This paper examines the second type of decisions using a unique dataset on the power supply interruptions of a Spanish distribution company network between 2013 and 2019. We focus on the effect of grid automatization on the restoration times, the relative efficiency of the maintenance staff, and the importance of its location. We combine a bottom-up spatial model and a stochastic frontier model to examine respectively external and internal power supply interruptions at municipal level. This model resembles the conventional spatial autoregressive models but differs from them in several important aspects

Impacts on the social cohesion of mainland Spain’s future motorway and high-speed rail networks

Una gran expansión de la red de infraestructuras viarias y ferroviarias está prevista en el Plan de Infraestructuras, Transportes y Vivienda (PITVI), a fin de lograr una mayor cohesión social en 2024 en España. Por esta razón, el objetivo de este estudio es para clasificar e identificar a los municipios que van a mejorar o empeorar su cohesión social. Para lograr este objetivo, los municipios fueron clasificados según el grado de desarrollo socioeconómico, y sus niveles de accesibilidad se determinaron antes y después de la construcción de estas infraestructuras. En primer lugar, la clasificación socioeconómica demuestra que existe predominio en la mitad septentrional de la península en los municipios más desarrollados. En segundo lugar, los niveles de accesibilidad muestran que un centro-modelo periférico se va a mantener en el futuro. Por último, los patrones territoriales, mal definidos, se obtiene con respecto a los efectos positivos o negativos de las nuevas infraestructuras en el ámbito de la cohesión social. Por lo tanto, es posible afirmar que el plan de construcción va a cumplir su objetivo parcialmente, ya que una cuarta parte de la población va a ser afectada por un impacto negativo en el desarrollo socioeconómico. Como consecuencia, las personas que viven aquí van a tener grandes problemas para lograr la cohesión social.A great expansion of the road and rail network is contemplated in the Infrastructure, Transport and Housing Plan (PITVI in Spanish), in order to achieve greater social cohesion in 2024 in Spain. For this reason, the aim of this study is to classify and to identify those municipalities that are going to improve or worsen their social cohesion. To achieve this goal, the municipalities were classified according to the degree of socioeconomic development, and their accessibility levels were determined before and after the construction of these infrastructures. Firstly, the socioeconomic classification demonstrates that there is predominance in the northern half of the peninsula in the most developed municipalities. Secondly, the accessibility levels show that the same center-peripheral models are going to be kept in the future. Finally, poorly-defined territorial patterns are obtained with respect to the positive or negative effects of new infrastructures on social cohesion. Therefore, it is possible to state that the construction plan is going to partially fulfill its aim, since a quarter of the population is going to be affected by a negative impact on socioeconomic development. As a consequence, people who live here are going to have major problems in achieving social cohesion.Trabajo patrocinado por: Junta de Extremadura y Fondos FEDER. Ayuda GR15121peerReviewe