Yearly Archives: 2012


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.




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.




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.



Sporting events are a very important promotional tool for many cities, given its national and international impact. Many of these cities already have long supported these events as a way to internationally promote their brand. The economic impact of these sporting events not only depends on the number of participants but also, among other factors, on the duration of their stay in the city that hosts the event. The aim of this study, therefore, is to analyze the determinants that determine the length of stay of these athletes in the venue that hosts the event studied, the International Triathlon Challenge Barcelona-Maresme. This event took place on October 3, 2009. More than 2000 participants from 30 countries attended the competition. The model also quantifies the likelihood that an athlete had been in the venue for “t” days (known as hazard function) depending on “t” conditioned to completing the trip.

The method used is a duration model, also known as hazard  or survival model. Thesemodels estimate the length of time spent in a particular state before transitioning to another state. These regression models allow us to estimate when the duration of a state is correlated with the explanatory variables in the observed period. Given that in our model the proportionality assumption holds, the author decides to use a proportional duration model. Among these selected models, the model chosen is the Weibull. The choice of this model is based, first, on the lack of evidence to reject the proportional hypothesis, as seen in the graph of the survival function, and second, from the proportional duration model, the author must choose the better model in order to avoid problems arising from lack of specification. In this case, when the models are nested, the Wald test rejects the null hypothesis of the exponential model. Once the model used is choose, we proceed to perform the data collection. The model uses information extracted from a survey conducted by the Maresme City Council in 2009 to several participants of the International Triathlon Challenge Barcelona-Maresme. The survey was administered to participants during the days prior to the competition and the day of the competition. A total of 346 valid responses were obtained. The model evaluates the destination, spending, type of accommodation used and type of competitors correlated with the duration of the event.

Of all the variables studied, neither age, or the fact that the participants had visited the city hosting the event seem to have a significant effect. Quantitatively, being a foreign participant, expenditure and evaluation of fate, in this order, emerged as aspects that increase the duration of the event analyzed. The dummy variable “foreign participant” seems to capture the fact that participants from another country travel greater distances than the average Spanish participant and having made the decision to travel a far distance des stay lengthens. The results obtained in this study confirm the hypothesis that the participants in sporting events cannot be considered equal in terms of the effects of different factors in their decisions regarding the duration of the event. In summary, the results of the duration model used in this paper shows that the greatest impact of these sporting events is conditioned on the ability to attract foreign athletes.



Tourists travelling on low –cost airlines (LLCs) in Europe have increased sharply, in contrast to the stagnation of traditional companies.  Local governments and tourists destinations supporting what it is known as LLCs are nowadays really interested in knowing what type of tourists those companies are attracting and so on which kind ofbehavior they have. From those things which want to be known, one aspects that is receiving attention by policy makers involves the determinants of tourist’s length of stay at the chosen destination.

Economic analysis of tourism demand is usually grounded in neoclassical theories involving consumers choice with demand measured as a quantitative variable. Due to the characteristics of the duration choice used in this model, a time restriction is also included. The way tourism demand it’s calculated here does not differ in it’s specification from the demand for other goods and services. But, when using a more stylized formulation of this model, tourists demand is the result of a standard maximization process by the tourist/consumer, of a utility function, the arguments for which are the consumption of tourism and other goods, using a budgetary and time restriction. The data used in this study have been obtained from traffic passengers traffic at Girona-Costa Brava airport. The information for our duration model are taken from a survey conducted during spring and summer of 2005. This survey was given to tourists who stayed in Catalonia and who used low-cost airlines to travel. The dependent variable, number of days stayed is considered to be continuous and takes values from 1 to 31 days. The explanatory variables are sociodemographic characteristics of the tourist, the type of accommodation chosen, the main reason for travel, whether or not the trip was done during summer destination and whether or not it was and organized trip. One of the categories for each variable acts as a reference category. The results of the model estimations will show the effect of each category of the explanatory variable on the likelihood of length of stay with regard to the reference category.

The expected results from the estimation of the empirical model show values according to what could be expected from the theoretical model used: heterogeneity in preferences among LLC users is observed, and so time and income constraints are relevant for duration, and finally the effects of each explanatory variable can differ among tourists according to their country of origin. The conclusions of this study show that, in general, time and income restrictions are relevant factors and the authors found that there was individual heterogeneity. The model also shows that the tourist group with a longer trip duration are non-senior, married, British tourist who travel in summer to a coastal destinations and stay in campsites. The French travel to sun and sand locations in the summer and stay at campsites. German tourist, as well as, also travel to sun and sand locations in summer time, they are senior, and choose to stay at campsite as well. To end, regarding to Italian tourist, longer stays are positively and significantly associated to not being employed, travelling in summer to a sun and sand locations and staying at campsite.



The aim of the article entitled “The Effet of time on Hotel Pricing Strategy”, by Professor Josep Maria Raya, is to present an empirical model of the dynamics in the room rates in hotels and tourist resorts on the Catalan coast. The increase in Internet distribution of products for tourists is encouraging many companies to implement dynamic pricing policies, price indices changing depending on last minute bookings.

The model used in this case is a hedonic pricing model. This type of model shows howheterogeneous products are composed of various features and the implicit marginal price can be obtained by estimating a model that represents the price of the product in terms of its characteristics. Specifically, this hedonic price model is modeled by estimating a discrete duration model for the probability of occurrence of a change in prices in a particular time and by another model that takes into account the number of times the given price change during the study period. The sample consists of 111 hotels in 3 resorts in the Catalan coast: Calella, Santa Susanna and Lloret de Mar. In each of these hotels, they monitored the price of a double room in the first week of August during the period between the second week of January to the last of July. The dependent variables of the model are the dummy on price changes (changes) and the number of changes. The explanatory variables are the quota of rooms in each hotel in the city’s total, the city where it is located, the category, the week in which the observed price and the initial price.

Model results analyzed show that higher initial price (indicator of a policy of aggressive price discrimination) increases the number of times this price varies during the period (and therefore the likelihood that this price may vary at any time given). Although a larger market share increases the probability of a price change at any given time, this variable does not affect the number of times the price undergoes a change. Finally, as the weeks go by without causing any change in price, the probability of a change in these increases.



The increase in interest expense of pharmaceuticals is one of the main factors behind the increase in public health spending in developed countries. This increase is largely explained by demographic factors, such as increasing average age and life expectancy of the population, and, in general, a greater demand for health care. Due to this increase, many leading health authorities in several countries have introduced numerous regulatory actions that have affected the market system, especially on the supply side. These measures are many and varied, as are to set reference prices or lower profits of producers and distributors.

The objective of this study is to quantify the impact of regulatory measures implemented by Spanish healthcare system between 1995 and 2006. The impact is analyzed in three main categories: expenditure per capita, prescriptions per capita, and average prices of health products financed by the Catalan public sector. The authors of this article implement an integrated autoregressive moving time series model (ARIMA for its acronym in English) using dummy variables to represent the various cost containment measures which have been implemented. The data used are the monthly totals charged by pharmacies in prescriptions between January 1995 and December 2006. Data were supplied by the Catalan Health Service.

The results of the regression performed indicate that a large part of the measures implemented to contain health care costs have not been effective in reducing expenditure per capita, the average prices of prescriptions or the number of prescriptions per patient. Especially, the results show that four of the interventions examined, from a total of 16, had a significant negative impact on per capita expenditure, eight interventions had a significant impact on prices (only one with positive impact) and three more had a positive impact on the number of prescriptions per capita (with only one resulting in a reduction). In short, all the interventions reviewed, only four were effective in controlling total spending.




En el presente trabajo se analiza la demanda de turismo en el extranjero, canalizada a través del turismo que se sirve de las actualmente muy conocidas compañías aéreas debajo coste. Mediante el correspondiente análisis, se estudiaran los determinantes microeconómicos de la duración de la estancia en destino de un conjunto de turistas españoles que vuelan en compañías aéreas de bajo coste hacia destinos extranjeros. Con ello se contribuirá al conocimiento que se dispone sobre la demanda de turismo español en el exterior, muy escaso hasta el momento. El turismo emisor español se caracteriza por generar un gasto por persona y día muy superior al del turismo interno. El medio de transporte más utilizado por estos es el avión (aproximadamente el 50,5% de los viajes para el conjunto del turismo español) y el tipo de alojamiento más elegido es el hotel. En el caso de Catalunya, de dónde proceden la mayoría de turistas cuya demanda es objeto de análisis en el presente artículo presentan ciertas características propias. En el caso de esta comunidad la tasa de población viajera es del 65,5%, cuatro puntos por encima de la media española y representan el 27,2% del total de los viajeros españoles que lo hacen en el extranjero.

La estimación del modelo de demanda temporal que se realiza en este trabajo utiliza información procedente de una muestra de turistas que viajaron en vuelos de bajo coste en el aeropuerto de Girona en 2005. Este aeropuerto transportó 3,5 millones de pasajeros, lo que representa un 1,95% del total transporte por conjunto de aeropuertos españoles. Con ello se situaba en el décimo lugar del conjunto de aeropuertos españoles por volumen de tráfico. Este análisis adopta una modelización neoclásica de elección del consumidor, según la cual la demanda de turismo no difiere en su especificación de la demanda para el resto de sectores. En este modelo, la demanda turística es el resultado de un proceso estándar de maximización por parte del consumidor, de una función de utilidad condicionada por una restricción presupuestaria y una restricción temporal. De acuerdo a esta formulación neoclásica, el consumidor elige n = (n1,n2), el número de días de estancia conjuntamente con q, el consumo del conjunto del resto de bienes, como resultado de un proceso de maximización. Teniendo en cuenta que en nuestro caso se incumplen la hipótesis de proporcionalidad, se rechazan los modelos proporcionales en favor de los de aceleración (MA). La encuesta de donde procede la información empleada en este estudio, se realizó en el momento de partida del turista hacia destinos europeos, eligiendo a los entrevistados aleatoriamente entre los diferentes vuelos y destinos, en el edificio propio del aeropuerto, una vez pasado el control de pasajeros. Las encuestas se realizaron en dos períodos: durante la primavera de 2005, período que no incluía ningún período vacacional, y el segundo en verano del mismo año 2005, en pleno período vacacional. La variable dependiente, días de duración de la estancia, se considera continua y toma valores de entre 1 y 31 días. Las variables explicativas hacen referencia a la restricción monetaria y temporal y a las características personales del turista que modelan sus preferencias. Las variables que recogen la información socio-económico-demográfica del turista son la edad, el género, el estado civil, el nivel de estudios y el tipo de ocupación laboral. A estas se suman, como modeladoras de preferencias, el motivo principal del viaje, la forma de organizar el viaje, y si el turista viaja acompañado o no.

Los resultados de la estimación del modelo han demostrado que la duración media esperada del viaje al extranjero es corta (5,5 días), pero con diferencias significativas según determinadas características del turista y su viaje. Así, son determinantes de la duración del viaje, el destino y el motivo del viaje, el nivel de estudios del turista, el tipo de alojamiento elegido, el hecho de viajar en temporada vacacional y la zona de residencia. Resultan significativos y con efecto positivo, que el  turista tenga o no estudios no universitarios, que viaje por motivo estudios, en periodo vacacional  y que se aloje en una vivienda gratuita o en una vivienda en alquiler. En cambio afecta negativamente el hecho de viajar a Francia y en menor medida, a Italia, y que proceda de las provincias de Barcelona o Girona. Ni la edad, ni el género, ni tampoco la ocupación, el estado civil o el haber contratado un viaje organizado parecen tener ninguna incidencia significativa.



The paper about to read presents a comparative analysis of the price component of the physical characteristics and location of both apartments and hotels in order to compare their effect on the final price of both types of accommodation. Nowadays, new forms of accommodation have strongly emerged among tourist demands, having all of those news accommodations a certain degree of substitutability. This substitutability can be broken down by comparing the price component of shared characteristics. To compare it, this paper sets out prices them using a hedonic price method, distinguishing between two basic forms of accommodation: hotels and apartments. To sum up, a hedonic price analysis will be conducted of the price of hotels (rooms) and apartments (units) in certain coastal sun and sand resorts in the Pyrenean-Mediterranean and coastal Mediterranean Euro region.

The hedonic price model us basically used on econometrics studies to explain the price of heterogeneous products made up of different characteristics, because the implicit marginal price of these characteristics can be ascertained by estimating a model that explains the price of a product based on its characteristics. The data are taken from hotel and apartment prices among those municipalities: Lloret de Mar and Alt Maresme (Catalonia), Dénia and Calp (Alicante), Calvià and Alcúdia (Balearic Islands) and Argelès-sur-Mer and Collioure (Languedoc-Roussillon). All of them are on the coast and they can be considered homogeneous from the point of view of truism specialization index. Once the municipalities had been selected, a search was made in tour operators’ paper travel brochures and exhaustive data were compiled from their website. The database contained the prices and characteristics of tourist apartments and hotel rooms from May to October 2007.  The dependent variable was the price per night in euros of a room in the case of hotels and of an entire unit in the case of apartments. The explanatory variables were varied, being all of them dummy variables: the resort, the category, the type of board (only for hotels), type of room (hotels only), number of rooms, the presence of swimming pool, car park, garden or terrace and weeks.

The main findings of this paper was to price3 the locations of the different kind of accommodations analyzed and the time of the demand for hotels and apartments. Pricing location provided indirect evidence of the destination’s quality. The authors concluded that greater differences in the quality of the chosen destinations as perceived by tourists staying in hotels in relation to differences in the quality of these destinations as perceived by tourists staying in apartments. In the case of hotels, the lower quality of the destinations as perceived by the tourists to these resorts is the result of a policy based heavily on prices aimed at tourists of low socio economic level who base decisions on this variable alone. In the case of apartments, the price policy for these resorts does not seem so visibly aggressive. Results suggest similar and strongly seasonal evolution for both types of accommodations, although there are few differences. To conclude, knowing the estimated price components of accommodation it’s a key factor in the development of destinations management strategies.



The aim of the article we are about to read is to make an estimation of both the price and income elasticity of demand for housing characteristics using information of properties appraised in the city of Barcelona during the period 1998 to 2001. For this case, thedifferences between indirect and direct aid on public sector budget measures for housing must be taken into account. Direct aid takes the form of interest rates subsidies, as well as access to qualified loans and personal grants. On the other hand, indirect aid is that derived from the tax treatment given to the usual home in the Spanish tax system. In Spain, 87% of budget aid for housing is allocated to indirect aid to subsidize home purchases, whereas in the Euro Zone this percentage ranges from 10 to 25%. The authors estimate the price and income elasticity of demand for a series of basic housing characteristics (quantity, quality and location), in order to make policy recommendations about the type of housing units that are the most desirable to be subsidized.

The method finally chosen to use is a hedonic price models. This regression makes it possible to estimate constant quality prices. So, following this model, the methodological approach will be divided into two parts: the modeling of the hedonic price regression and the modeling of the demand equation. The dependent variable is the total value of the property, while the explanatory variable uses about eleven characteristics for each house analyzed.

Once the regression was made, it was observed that the compensated price elasticity indicated inelastic demands. So, keeping expenditure and the rest of the prices constants, an increase in the price of one of the characteristics results in a less proportional decrease in the quantity demanded of that characteristic. Obviously, if citizens can keep their utility constant, an increase in the price of floor area will also lead to a less than proportional decrease in the quantity of demanded floor. In conclusion, a policy of small subsidized housing units is justified, although with certain minimum standards of quality and in no event in marginal areas.