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 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.

Italian and Spanish property markets have experienced a sustained period of growth since the mid-1990s until 2008 when both markets fell into rapid decline due to the worldwide Financial Economic Crisis (FEC). Although the economic impact of the FEC was similar, each country experienced different reactions in its respective real estate market, changes on house prices, building constructions or planning regulations. This paper presents a new supply equation for Italian and Spanish regional markets. A pool of EGLS/IV Two-Step GLS methods are used to account for cross-sectional heteroskedasticity with fixed effects in order to control space differences. The analysis has been developed at a regional level, and shows the variation in the responsiveness of the new housing supply to prices by region. The results show long-term price supply elasticity by regions, and the negative impact of exogenous shock. They also suggest that house markets follow similar patterns in several regions with elastics responses in most territories and stronger negative impact of credit crunch in Spanish than Italian housing development.Professor Taltavull acknowledges the support from the Spanish Ministry of Economy and Competitiveness (National R&D&I Plan) [grant number CSO2011-29943-C03-02]

Purpose: This paper aims to estimate the green premium effect of retrofitted apartments in Bucharest and draw comparisons with international examples.Design/methodology/approach: A geo-referenced transaction database including information on whether the property had been retrofitted is utilised. The paper uses two approaches to test the green premium. One is a hedonic model controlled by areas to estimate the price incentive of a green building. The second is a STAR GLS model evaluating the diffusion effect of house prices spatially by sub-market and assessment upon the pricing effect of green characteristics.Findings: The authors’ findings suggest a green premium in two Bucharest areas of between 2.2 per cent and 6.5 per cent. Spatial diffusion effects are shown to contribute positively to house prices, but the unobserved spatial component reduces this effect.Originality/value: This paper is the first to assess price impacts of green characteristics in Bucharest and one of the first analysing green premium using spatial techniques. The analysis is of significance to policymakers and real estate developers.

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.

Purpose: There is a lack of understanding in the literature on the spatial relationships between crime and house price. This paper aims to test the impact of spatial effects in the housing market, how these are related to the incidence of crime and whether effects vary by the type of crime. Design/methodology/approach: The analysis initially explores univariate and bivariate spatial patterns in crime and house price data for the Belfast Metropolitan Area using Moran’s I and Local Indicator Spatial Association (LISA) models, and secondly uses spatial autoregression models to estimate the role of crime on house prices. A spatially weighted two-stage least-squares model is specified to analyse the joint impact of crime variables. The analysis is cross sectional, based on a panel of data. Findings: The paper illustrates that the pricing impact of crime is complex and varies by type of crime, property type and location. It is shown that burglary and theft are associated with higher-income neighbourhoods, whereas violence against persons, criminal damage and drugs offences are mainly associated with lower-priced neighbourhoods. Spatial error effects are reduced in models based on specific crime variables. Originality/value: The originality of this paper is the application of spatial analysis in the study of the impact of crime upon house prices. Criticisms of hedonic price models are based on unexplained error effects; the significance of this paper is the reduction of spatial error effects achievable through the analysis of crime data.