Suchergebnisse

In this paper, we propose an index to measure the quality of the most important European cities. Using collected data from 66 cities belonging to the 28 countries within the European Union and applying the principal components analysis method, we construct the European Cities Quality Index (ECQI) as a combination of eight dimensions: (1) Public health, (2) Education, (3) Employment and incomes, (4) Environment, (5) Gender equality, (6) Leisure and entertainment, (7) Housing and safety and (8) Transport and mobility, that are in turn made up of 40 distinct variables. We find that London, Aarhus, and Berlin are the cities with the highest scores in the index, with northern European cities performing the best. At the other end of the spectrum, Sofia, Plovdiv, and Bucharest, with severe deficiencies in every dimension, scored worst on the study. The comparisons with the Sustainable Cities Index (Arcadis), the Global Power City Index (Institute for Urban Strategies), Cities in Motion (IESE), the Cities Prosperity Index (UN), and Dynamic Cities (Savills) help us understand the potential use of this new index and its purpose as a tool for assessing public policy. The ECQI could be used to assist public policies designed to improve perception in regions where it is needed.

The purpose of this paper is to create an index to measure the reputation of countries that belong to the European Union. Data for 28 countries has been taken from the Eurostat database and the method used is principal component analysis. The index is a combination of five different dimensions: (1) Economy, (2) Social Welfare, (3) Environment, (4) Digitalization and (5) Sports and Health, along with thirty-two distinct factors. The top scores in this index are Germany, United Kingdom or Sweden with high values in Economy or Environment. On the other side, we find Greece, Croatia or Cyprus, with a low process of digitalization. The International Reputation Index could be used to assist public policies designed to improve reputation in countries where it is needed.

In this paper we propose an index to measure the state of health of the 28 countries of the European Union. Material and methods Using the Principal Components Analysis method, we construct the European Health Index as a combination of six dimensions: (1) Working conditions, (2) General state of health, (3) Health system, (4) Quality of Life, (5) Mental health and drug abuse, and (6) Risk health factors, that are in turn made up of 29 distinct variables. Results We find the Netherlands, Denmark, Sweden and Ireland in the first four positions, and Estonia, Lithuania, Poland and Bulgaria at the end of the ranking. Within the European Union, two blocks stand out above the rest, the ex-soviet countries and northern Europe. Conclusion The European Health Index could be used to assist public policies designed to improve health perception in regions where it is needed. = En este artículo proponemos un índice para medir el estado de salud de los 28 países de la Unión Europea. Material y métodos Usando el método de Análisis de Componentes Principales, construimos el Índice de Salud Europeo (ISE) como una combinación de 6 dimensiones: (1) Condiciones de trabajo, (2) Estado general de salud, (3) Sistema de salud, (4) Calidad de vida, (5) Salud mental y abuso de drogas, y (6) Factores de riesgo para la salud, que a su vez se componen de 29 variables distintas. Resultados Encontramos a los Países Bajos, Dinamarca, Suecia e Irlanda en las primeras 4 posiciones, y Estonia, Lituania, Polonia y Bulgaria al final del ranking. Dentro de la Unión Europea, 2 bloques destacan sobre el resto, los países exsoviéticos y el norte de Europa. Conclusión El Índice de Salud Europeo podría usarse para ayudar a las políticas públicas diseñadas para mejorar la percepción de la salud en las regiones donde se necesita.

We propose an index to measure the degree of ability or desire of the population in a given country to have children, via an analysis of certain factors that may have a positive or negative influence on the fertility rate of that country. Using data for the twenty-eight countries of the European Union, and Principal Components Analysis, we construct the International Multidimensional Fertility Index as a combination of four dimensions: (1) Economy and family, (2) Attitudes and habits, (3) Work–Life Balance, and (4) Policy, along with nineteen distinct variables. We find that Denmark, the Netherlands, and Luxembourg are among the countries with the highest value of the index, and they also have high fertility rates within the EU. At the other end of the spectrum, Latvia, Cyprus, and Greece, are ranked in the last positions according to our index, countries that also present low values in their fertility rates. We also find a positive correlation between the value of our index and country fertility rates, an indication that our index may be capturing country differences in the conditions for bearing children, with higher values of the index indicating better conditions for childbirth and childrearing. To the extent that international data becomes available, our methodology will allow for the construction of international rankings, helpful in identifying cross-country differences in the conditions for fertility.