Suchergebnisse

This study estimates housing quality and features explaining energy poverty in Spain and its regions. By using the EU-SILC dataset for 2008-2019, it calculates the hidden links between energy poverty indicators and housing features, controlled by other variables such as type of household, poverty, and housing tenancy. Confirmatory factor analysis is used to identify the role of different dimensions in explaining energy poverty at the household level. The empirical evidence finds three hidden factors associating energy poverty with poverty, poor housing quality, and housing size and outskirts location. These three factors enable classifying households accordingly, revealing their distribution across Spain and three of its 17 Spanish regions: Madrid, Cataluña, and Valencian Community. Findings indicate how the impact of energy poverty differs by region, rejecting the general hypothesis that all households in poverty live in poor housing because they cannot afford the maintenance costs, thus causing energy poverty. Results suggest that energy poverty due to poor housing quality and location affects many households that are not necessarily poor, with different impacts depending on location. The association between energy poverty and larger houses located on the outskirts represents new evidence in the literature and is one of the contributions of this study, together with the methodology for classification. Results suggest that retrofitting investment would be crucial in reducing energy poverty problems in Spain.

Background: COVID-19 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 diminish the big amount of cases that arrive to 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. Now we are in the middle of a battle trying to prevent the healthcare system from collapsing while it effectively responds to the needs of patients who are infected and require hospitalization. Methods: Using China as a mirror of what could happen in our countries and with the data available, we calculated a model that forecasts when are the peak of the curve going to happen. We aim to review the patterns of spread of the virus in the three countries and their regions, looking for similarities that reflect the existence of a common pattern in this expansive virulence and the effects of the intervention of the authorities with drastic isolation measures, to contain the outbreak. Findings: A model based on ARMA methodology and including Chinese disease pattern as a proxy predicts a reduction of the speed of contagious during the last week of March in Italy and smooth reduction until the peak in the second week of April. In the case of Spain, the infections still will follow growing fast until the end of March. Interpretation: We present the following predictions to inform political leaders since they have the responsibility to maintain the national health systems away from collapsing. We are confident this data could help them into decision taking and place the capitals (from hospital beds to human resources) into the right place.

The existence of a green premium in house (asking) prices in Alicante province, Spain, are analyzed using circa 9000 property observations. In developing the sample, information from energy efficiency certificates was matched with two other databases. The model tests for green premium by climatic zones using pool Ordinary Least Squares (pool-OLS) and Instrumental Variables (IV) hedonic models, adds new knowledge concerning the existence of green premiums from Southern Europe, explores differences in their estimation by climatic zone, debates the nature of the estimated green parameters, and explains the role of endogeneity in hedonic green premium models. The empirical evidence assesses the sensitivity of asking price to either energy consumption (KWh) or carbon dioxide emissions (CO2) with an apparent premium of 3%, and captures an association with efficiency rating from G to F of 1.8% and from F to E of 1.1%. Significantly, the results relating to price responses show a distinct variation between the coast and the cooler climatic zone of the interior. The paper shows that energy efficiency incentive policies should discriminate by climatic areas, and provides a price reference by which to assess the amount of incentives needed to achieve European Union (EU) objectives. ; This work was supported by the project RentalCal (http://www.rentalcal.eu/) funded by the European Union within the framework of H2020-EE-2014-2015: H2020-EE-2014-3-MarketUptake.

The existence of a green premium in house (asking) prices in Alicante province, Spain, are analyzed using circa 9000 property observations. In developing the sample, information from energy efficiency certificates was matched with two other databases. The model tests for green premium by climatic zones using pool Ordinary Least Squares (pool-OLS) and Instrumental Variables (IV) hedonic models, adds new knowledge concerning the existence of green premiums from Southern Europe, explores differences in their estimation by climatic zone, debates the nature of the estimated green parameters, and explains the role of endogeneity in hedonic green premium models. The empirical evidence assesses the sensitivity of asking price to either energy consumption (KWh) or carbon dioxide emissions (CO 2 ) with an apparent premium of 3%, and captures an association with efficiency rating from G to F of 1.8% and from F to E of 1.1%. Significantly, the results relating to price responses show a distinct variation between the coast and the cooler climatic zone of the interior. The paper shows that energy efficiency incentive policies should discriminate by climatic areas, and provides a price reference by which to assess the amount of incentives needed to achieve European Union (EU) objectives. © 2019 by the authors.

Housing demand models based on individual consumer's utility function reflect preferences about the structure and lot, neighborhood, and location as related to socioeconomic characteristics of the occupants. As a growing proportion of aging residents in many countries are undertaking late life moves, their preferences will have an influence on destination housing markets. We examine the characteristics, attitudes and preferences about retirement housing among immigrant retirees currently living in traditional housing in a retirement destination in Alicante, Spain. Using results from a survey of German and British retirees living in the region, we find through logistic regression that preference for retirement housing is associated with aging and gaining access to in-home support services. ; REVIcVAL Project. Valencia Government GV048-530.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 785058.