Monthly Archives: novembre 2012

CHANGE IN THE DISTIBUTION OF HOUSE PRICES ACROSS SPANISH CITIES

The database used in this study include a total of 21.517 homes sold during the period2004-2007 by a real estate agency for for which the details concerning the characteristics of the transactions and the location of these are known. Empirical models used in this analysis are, in one hand, hedonic regression, and secondly, decomposition quantílica. The first model determines when the change in the distribution of property prices can be explained by the size, quality and location of the house sold, whether as if there are systematic differences between different cities within the same country . The second model helps answer questions like the evolving distribution of house prices over time or similar. This model examines the effect of covariates on various quantiles of the logistic function of price. Using this model the authors can decompose quantile decomposition changes in the distribution of property prices in the distribution originated by the explanatory variable, on one side, and on the changes induced by the quantilic regression coefficients.n of property prices over time in several Spanish regions. Traditional literature provides very few results and studies on this topic.The aim of this paper is to present a quantilic estimation of housing price index between 2004 and 2007 in several Spanish cities. To perform this analysis, the authors proceed to decompose the change in property prices in parts due to changes in explanatory variables and parts due to coefficients change over time. During the period 2004-2009, the Spanish property price growth of approximately 31.91%. This period can be divided into two smaller sub-sequences: while during 2004-2007 price indices increased approximately 44.31%, in 2007 these prices entered a downward dynamic in which fell about 8.60%. Note that this greater appreciation in the price indices did not occur equally in all Spanish cities. Based on this evidence, the aim of this paper is to understand more satisfactorily the evolution of the distributio

The distribution of prices for homes for sale in Spain in 2007 adopted a less sesgad distribution, with a tendency to move to the right and a smaller kurtosis distribution compared to 2004. All the Spanish cities experienced a change in the distribution of their housing prices, although this change was greater in smaller cities like Valencia or Bilbao compared to Madrid or Barcelona. The difference is greatest in low and high percentiles. We can also determine how much of the difference in the distribution of property prices between 2004 and 2007 is explained by it’s coefficients. The final results suggest that a single price index is not an appropriate measure to measure changes in prices, as the variance of the price index increases over time. Allow assessment ratios vary across quantiles can help us to obtain a more realistic picture of the change in the overall distribution of property prices than an estimator that focuses only on the mean or median. This result comes reinforced by the fact that the variation of the ratio quantile assessment and its components is different between the cities that make up the index.

 

WHICH ARE THE REAL DETERMINANTS OF TENURE? A COMPARATIVE ANALYSIS OF DIFFERENT MODELS OF THE TENURE CHOICE OF A HOUSE

 

The choice concerning the method of acquisition of the property (either owned or rented) is closely linked to other individual choices of great importance not only for consumers but also for the country where these consumers live. The article “What are the determinants of the mode of housing tenure?” aims to make a comparison of the various types of approaches that have been used in the economic literature on the analysis of the decision of individual housing tenure . The models used in economics are different and vary from binary choice models to model duration. In this aspect, the determinants of tenure are unclear because depending on the definition of the dependent variable and the estimation method, the determinants of tenure vary.

The study conducted in this study examines the various models that have been used in economic theory to model correctly the analysis of housing tenure. In short, the list of models to consider are: the classical model of tenure (classical model), which describes the probability that an individual homeowner is, at any given time, the model estimated only for those individuals who have made a transition and therefore have already opted for a form of tenure (model recent migrants), sequential bivariate probit model, which estimates the tenure decision and the status of migrants together, the duration model, which reflects the decision to do a transition from an specific state tenure (rental or ownership) to another state at any given moment of time, and finally the transition model, which uses a sample based in the tenure decision, giving this more weight in the sample. The data for this analysis was obtained from the European Community Household Pamel (ECHP), in particular the periods from 1994 to 2001. The ECHP is a standardized survey that is conducted in the European Union. This database contains information about housing characteristics and its inhabitants. From these data, we conducted a sampling on Spanish owners who had been on the panel for more than one period. This estimation had data for about 6778 households, nearly 82% of which were proprietary. In addition, a 40.36% of those had perfomed at least one movement  during the five periods observed. The definition of the dependent variable for all the models in which the dependent variable is the decision between the decision to rent or buy property is as follows: the status of tenure, (variable that has value 1 if the consumer owns or 0 if not), “move”, (in the equation used in the model selection of recent migrants), “stayer” (the second equation for the sequential model), transition (this variable takes values ​​1 for those individuals who make the transition of ownership to property, taking 0 in any other cases), income (estimated permanent income and transitory income based on the current monetary income’s  owner of the of the household head), gender (This dichotomous variable takes values ​​1 if the person providing the main source of income is a man and 0 otherwise) and age, property size (how many people are in the house), marital status, work and education, relative price (this is the price relation-tenant) duration (for those owners who have made a transition) and finally the number of rooms.

The results of this model are obtained by grouping the various models analyzed in terms of the dependent variable and analyzing these based on your top 6 formats. The first group, in which the dependent variable is the state of holding together the neoclassical models, the model of recent migrants and the sequential model. The second group, in which the dependent variable is the transition from rental to home ownership, includes duration and transition models. Overall, the results provide evidence of a better performance in models in which the dependent variable is the transition between renting and home ownership. This higher performance is not only explained by the results observed in terms of goals but also the ability to provide predictive and marginal effects closer than previously predicted. In terms of predictive ability, both models (duration and transition models) show relatively high success rates. To summarize, we conclude that, if we want to describe the profile of consumers who are home owners, permanent income, age, marital status and level of education are the main explanatory variables. All these variables can be considered life cycle, with marital status with a greater impact. On the contrary, if we want to answer the question about what are the determinants of the transition to rental property, we conclude that, in addition to life-cycle variables, variables related to prices and transaction costs are also important determinants. In conclusion, the results underline that the model in which the dependent variable is the fact of owning or not a house underestimate the effects of prices and transaction costs.

 

 

VALUING TOURISTM DESTINATIONS: AN OAXACA-BLINDER APPROACH

A brand is a name, symbol or any other type of marker that distinguishes a product or service from the competition. The territorial branding, such as the so-called “Marca España”, influences the selection of destination by tourists and their future behavior. However, a measurement of the power and influence of this concept in the decision making

The empirical framework developed in this study is an estimation based on linear equations determining the price per room. Different equations are estimated for the different study areas, ie, the resorts of Catalonia, Valencia, the Balearic Islands and Languedoc-Roussillon. The aim of the equation is to analyzed to obtain the price of a hotel room based on their characteristics and the analyzed week in order to control the temporal effect. It applies the conventional Oaxaca-Blinder decomposition to decompose the average gap between the variable outcome between French and Spanish resorts. This type of breakdown is called double decomposition because the difference in the output is divided into two parts. As discussed above, the data from this study was obtained from the price of hotels in coastal towns of the Pyrenees and the Mediterranean area of ​​the Euro Area and the community of Valencia. The chosen regions were: Lloret de Mar and Alto Maresme (Catalonia), Denia and Calpe (Valencia) and Alcudia Calvià (Balearic Islands) and finally Argeles-Sur-Mer and Collioure (Languedoc-Roussillon). They were chosen because they are all located on the coast, have a minimum population and can be considered homogeneous from the point of view of tourism specialization index, ie the ratio of second homes between primary residences. For all selected municipalities, we had a total of 11,910 observations, 11,032 of them being Spanish hotels and the remaining 878 of French hotels. The dependent variable of the study, of course, is the price in euros per night for a room in their logarithmic function. The exploratory variables are: hotel area, it’s category and finally type of hotel.

The results of the study are clear. These highlight the importance of the territorial brand promotion as an explanatory variable for much of the differences in the prices of the services provided to tourists in the resorts analyzed. The estimation obtained in this analysis shows that almost 55% of the gap in prices of hotels between Spanish and French resorts can be attributed to territorial development policies, while only the remaining 45% is explained by differences in the characteristics analyzed. These results can be interpreted as an additional motivation for both public and private authorities to enhance the promotion of the major tourist localities.