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This paper aims to identify the presence of energy poverty in Ecuador. Three indicators proposed by the European Union Energy Poverty Observatory (EPOV) are used to construct a multidimensional energy poverty index (MEPI) based on measure conditions associated with energy poverty, in areas related to delays in the payment of electricity bills, disproportionate expenses, hidden energy poverty, and the 10% Boardman (1991) rule. The information comes from the Ecuatorian Life Conditions Survey. The results show that energy poverty is present in Ecuadorian households, at the national level, and just as these indicators have restrictions, advantages and disadvantages, which demand decisions about the choice of their use.

Residential price levels in Spain vary broadly among markets. Real estate theory explains that prices depend on market characteristics such as vacancy level, land availability, construction supply elasticity to respond to high or low speed to changes on the demand, as well as potential for economic growth, industrial and services activities located inside urban areas, etc. An analysis of prices in Spanish main cities shows that tensions appear to exist in some of them where economic activity shows different dynamism and price level appears to be independent of it. This paper tries to find evidence of the existing relationship between residential prices and economic and demographic factors that are demand determinants such as wages, migrations and productive structure, among others, to explain price formation in Spanish cities. It uses panel data and GLS methodology applied to 71 main Spanish province capitals and cities with more than 100,000 inhabitants. The results show evidence of determinants of housing prices and how some relationships appear to exist between price levels and families' waged income as well as with population and productive structure in Spanish cities.

Theory and empirical research show how building cycles' behaviour has substantial differences within countries among its different geographical areas. There is evidence of the existence of specific area leadership regarding development activity and how this influence is transmitted to the rest of the country as a locomotive effect in residential construction. This means that the aggregate building cycle could strongly depend on cycles in specific areas. This paper follows this approach and investigates the relationship between geographic areas' intensity in housing construction, showing how activity development in some of these areas is influencing the rest of the country. This process is analysed in Spain during the 1990s, using information on house licenses of construction given by regional areas and applying cointegration methodology to identify leading areas in building activity. Some leadership effect is found in the Levante area attracting building activity from the rest of the country during this period.

Paper presented to the Pacific Rim Real Estate Society 15th Annual Conference, Sydney, 18-21 January 2009. ; Economic theory tends to classify all retirees as a homogeneous class of consumers. Using cluster analysis, we examine how housing preferences among international retiree migrants in Alicante, Spain vary. From the resulting clusters, we identify relationships between homeowner characteristics and housing preferences. Initial empirical results indicate that there are identifiable segments with different housing preferences. ; REVIcVAL Project. Valencia Government GV048-530.

PurposeThis paper analyzes how three major industrial stock indices related to South Korean real estate industries are affected by the exogenous shock of the measures taken to control COVID-19, coupled with investor sentiment, which has global impacts.Design/methodology/approachThe paper uses daily stock market indices on three major stock price indices: construction industry sector index, real estate operating company (REOC) industry index and the real estate investment trust (REIT) industry index of the Korea Stock Exchange (KRX), from January 8, 2020, when the World Health Organization (WHO) began to issue official indicators regarding COVID-19, to March 27, 2020, the last trading day of the week during which the South Korean government's stock market stabilisation fund was launched.FindingsResults indicate the REIT sector's stock rate of return to be relatively less sensitive to impacts of COVID-19 compared to those of the two other indices. Impulse response analysis also shows similar results. Impulse response estimations indicate that earlier information of REITs has prominent significance in explaining changes in the time series process itself. Similar to findings of prior studies that have been conducted with long-term perspectives, results of our short-term study indicate that the medium-risk, medium-return characteristic of the real estate industry has significance even in short-term perspectives.Practical implicationsREITs can be an investment vehicle that provides strong benefits of diversified investment for mutual fund investment managers even in the case of short-term exogenous market disruptions.Originality/valueThe analysis run in the empirical exercise is the first to consider the sensibility between international stock exchanges to the effects of measures taken to control COVID-19 impact.

COVID-19 (coronavirus disease 2019) has spread successfully worldwide in a matter of weeks. After the example of China, all the affected countries are taking hard-confinement measures to control the infection and to gain some time to reduce the significant amount of cases that arrive at the hospital. Although the measures in China reduced the percentages of new cases, this is not seen in other countries that have taken similar measures, such as Italy and Spain. After the first weeks, the worry was whether or not the healthcare system would collapse rather than its response to the patient's needs who are infected and require hospitalization. Using China as a mirror of what could happen in our countries and with the data available, we calculated a model that forecasts the peak of the curve of infection, hospitalization, and ICU bed numbers. We aimed to review the patterns of spread of the virus in the two countries and their regions, looking for similarities that reflect the existence of a typical path in this expansive virulence and the effects of the intervention of the authorities with drastic isolation measures, to contain the outbreak. A model based on Autorregressive and moving average models (ARMA) methodology and including Chinese disease pattern as a proxy, predicts the contagious pattern robustly. Based on the prediction, the hospitalization and intensive care unit (ICU) requirements were also calculated. Results suggest a reduction in the speed of contagion during April in both countries, earlier in Spain than in Italy. The forecast advanced a significant increase in the ICU needs for Spain surpassing 8,000 units by the end of April, but for Italy, ICU needs would decrease in the same period, according to the model. We present the following predictions to inform political leaders because they have the responsibility to maintain the national health systems away from collapsing. We are confident these data could help them into decision-taking and place the capitals (from hospital beds to human resources) into the right place.

COVID-19 (coronavirus disease 2019) has spread successfully worldwide in a matter of weeks. After the example of China, all the affected countries are taking hard-confinement measures to control the infection and to gain some time to reduce the significant amount of cases that arrive at the hospital. Although the measures in China reduced the percentages of new cases, this is not seen in other countries that have taken similar measures, such as Italy and Spain. After the first weeks, the worry was whether or not the healthcare system would collapse rather than its response to the patient's needs who are infected and require hospitalization. Using China as a mirror of what could happen in our countries and with the data available, we calculated a model that forecasts the peak of the curve of infection, hospitalization, and ICU bed numbers. We aimed to review the patterns of spread of the virus in the two countries and their regions, looking for similarities that reflect the existence of a typical path in this expansive virulence and the effects of the intervention of the authorities with drastic isolation measures, to contain the outbreak. A model based on Autorregressive and moving average models (ARMA) methodology and including Chinese disease pattern as a proxy, predicts the contagious pattern robustly. Based on the prediction, the hospitalization and intensive care unit (ICU) requirements were also calculated. Results suggest a reduction in the speed of contagion during April in both countries, earlier in Spain than in Italy. The forecast advanced a significant increase in the ICU needs for Spain surpassing 8,000 units by the end of April, but for Italy, ICU needs would decrease in the same period, according to the model. We present the following predictions to inform political leaders because they have the responsibility to maintain the national health systems away from collapsing. We are confident these data could help them into decision-taking and place the capitals (from hospital beds to human resources) ...

COVID-19 (coronavirus disease 2019) has spread successfully worldwide in a matter of weeks. After the example of China, all the affected countries are taking hard-confinement measures to control the infection and to gain some time to reduce the significant amount of cases that arrive at the hospital. Although the measures in China reduced the percentages of new cases, this is not seen in other countries that have taken similar measures, such as Italy and Spain. After the first weeks, the worry was whether or not the healthcare system would collapse rather than its response to the patient's needs who are infected and require hospitalization. Using China as a mirror of what could happen in our countries and with the data available, we calculated a model that forecasts the peak of the curve of infection, hospitalization, and ICU bed numbers. We aimed to review the patterns of spread of the virus in the two countries and their regions, looking for similarities that reflect the existence of a typical path in this expansive virulence and the effects of the intervention of the authorities with drastic isolation measures, to contain the outbreak. A model based on Autorregressive and moving average models (ARMA) methodology and including Chinese disease pattern as a proxy, predicts the contagious pattern robustly. Based on the prediction, the hospitalization and intensive care unit (ICU) requirements were also calculated. Results suggest a reduction in the speed of contagion during April in both countries, earlier in Spain than in Italy. The forecast advanced a significant increase in the ICU needs for Spain surpassing 8,000 units by the end of April, but for Italy, ICU needs would decrease in the same period, according to the model. We present the following predictions to inform political leaders because they have the responsibility to maintain the national health systems away from collapsing. We are confident these data could help them into decision-taking and place the capitals (from hospital beds to human resources) into the right place. ; PT acknowledges the institutional support given by the Generalitat Valenciana through the Catedra de Transformación del Modelo Económico Valenciano in the development of this paper.

This paper aims to identify the presence of energy poverty in Ecuador. Three indicators proposed by the European Union Energy Poverty Observatory (EPOV) are used to construct a multidimensional energy poverty index (MEPI) based on measure conditions associated with energy poverty, in areas related to delays in the payment of electricity bills, disproportionate expenses, hidden energy poverty, and the 10% Boardman (1991) rule. The information comes from the Ecuatorian Life Conditions Survey. The results show that energy poverty is present in Ecuadorian households, at the national level, and just as these indicators have restrictions, advantages and disadvantages, which demand decisions about the choice of their use.