Sobre aquest BlocEn este blog pretendemos dar difusión de todos los resultados de la investigación científica elaborada dentro del Grupo de Investigación Emergente Reconocido por AGAUR GRABET (Grup de Recerca Aplicada en Benestar Econòmic i Turisme). En este sentido, se resumirán los principales resultados de los papers publicados, las ponencias presentadas en Conferencias Internacionales, las tesis dirigidas, los proyectos de investigación acabados, etc.
Dra. Natividad Juaneda Doctora en Economía, es profesora (y Vicerectora) de la Universitat de les Illes Balears. Es especialista en Economia del Turismo. Ha participado en diversos proyectos competitivos y ha publicado artículos científicos en revistas como Tourism Economics o Annals of Tourism Research.
Dra. Catia Nicodemo Catia Nicodemo received her Ph.D. in Economics from Tor Vergata University and Pompeu Fabra University. Her main research interests include labor economics and applied microeconometrics.
Dra. Dolors Celma i Benaiges Doctora en Organitzación de Empreses por la Universitat de Girona (2011). Es profesora titular de la Escola UNiversitaria del Maresme (Universitat Pompeu Fabra). Sus campos de investigación son la Responsabilidad Corporativa y Los Recursos Humanos.
Dr. Carlos Pestana Barros Professor Carlos Pestana is a researcher from the U.T.L. - Technical University of Lisbon. His main research interests include transportation, energy, finance, tourism and sport economics. He has an extense number of publications in the best Journals of these fields.
Dra. Esther Martinez Profesora Titular de Economía Aplicada de la Universidad de Girona, es doctora en Economía por la Universidad de Barcelona. Ha publicado en revistas científicas del JCR en economía del turismo y de la salud.
Dr. Josep Maria Raya Dr.Josep Maria Raya es profesor titular de la Escola Universitaria del Maresme (Universitat Pompeu Fabra). Su investigación se centra en economía de la vivienda y economía del turismo.
Dr. Montserrat Vilalta-Bufí Montse holds a PhD degree in Economics from the International Doctorate in Economic Analysis at Universitat Autònoma de Barcelona. She is a lecturer of economics in the Department of Economic Theory at Universitat de Barcelona. Her research interests concentrate on labor economics, intergenerational mobility and economic growth.
Dr. Montse Vilalta-Ferrer Montse is PhD in Economics by Universitat Abat-Oliba and holds a position of Director of Maresme University College. Her research spans from efficiency of universities, through university-business linkages to female entrepreneurship. Currently her research agenda concentrates strictly on female entrepreneurship in comparative perspective.
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Monthly Archives: octubre 2012
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.
DETERMINANTES DE LA DEMANDA TEMPORAL DE TURISMO: UNA APROXIMACIÓN MICROECONÓMICA CON UN MODELO DE DURACIÓN
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.
The article entitled “Local Public Expenditures and housing prices” takes a comprehensiveeconometric analysis of the effect of local public investment in dwelling prices in the city of Barcelona during the period 1998-2001. According to the Spanish Ministry of Development, the Spanish property prices in this period increased an average of 53%. The importance of this analysis is that never before has any project of its kind in Spain been done, as well as providing new interpretations for the classic explanations that analyzed the evolution of real estate prices, such as demographic changes . The authors say that, apriori, it is expected that an increase in government spending in a particular area of Barcelona has a positive effect on the price of nearby properties.
The econometric model used in this case was a classic two-stage hedonic price. Recall that the basic methodology of this model provides a hedonic price equation that captures the effect of different individual attributes of a property in determining its market value through a generic function of type P = f (I, V, U , Z, S, E, W). In the first stage the authors calculate the prices in each geographic area in which is divided the sample of properties, in a total of 244 statistical areas, after controlling the effect of the physical dwelling’s characteristics. In the second stage it is analyzed, once the dummies variables were introduced, the effects of public spending per capita again in the property prices.
The results show a positive effect, although it is small, of the public expenditure per capita (approximately 10%) on property prices in the geographical area where the investment takes place. This result can draw two main conclusions. The first one, that the public sector could be partly responsible, through its local investment policy, of the increase in housing prices in the area where the investment takes place. And second, the estimation of the effect of local spending in real estate prices can derive a first estimation of the willingness of property owners to pay for increasing government spending in their local area.
The article “Length of stay for low-cost tourism” aims to analyze, using an appropriate econometric study, the time spent at the destination among tourists who fly mostly with “low cost” companies. Through this analysis, it may be possible to obtain new data and information that could be used in tourist destination areas and which will help to clarify which sociodemographic aspects influence this process. Note that Spain is one of three countries in the world that attracts larger volume of tourists, highlighting the community of Catalonia as the region of Spain that attracts larger number of people visiting it, mostly from other European countries.
The literature on this topic is relatively limited. Previous studies were conducted by Alegre and Pou (2007), Gokovali, Bahar and Kozak (2007) and Fleischer and Pizam (2002). They all find interesting results which will be latter completed with the study performed in this article by Martinez-Garcia and Ray.
The model used is mainly based on the economic theory about demand functions based on consumer utility as well as their budget and temporary restrictions. The dependent variable of this model is the time spent at the place of destination by the people visiting it. The authors finally choose to use duration model, also known as survival or hazard models. This model allows obtaining estimations when the duration is correlated with the explanatory variables of the model. Within all duration models which the econometric science provides, the authors use a log-logistic scheme, as this model is the one showing the highest value for the log-likelihood function and a lower value in the AIC criterion.
The database used for this study was drawn from a survey that was given to tourists flying to the Girona-Costa Brava’s Airport during the spring and summer of 2005, being only asked European tourists. The dependent variable, as discussed above, is continuous and takes values from 1 to 31. The explanatory variables are varied and were chosen according to the economic model used. They are classified into: socio-demographic variables (age, sex, education level, occupation level), nationality, place of destination (Girona, Barcelona or seaside locations), the main reason for travelling, type of accommodation closed, whether the trip was organized or not, and also asking if they were travelling during high season and finally whether it was a family trip, or not.
The results were clear. The following variables have a positive effect: Irish, Dutch or Belgian, and to a lesser extent French nationalities, to be over 50 and having only primary education, travelling during summer time to coastal towns, as well as sojourn in a camping site and rented properties. By contrast, certain values show a negative effect on the dependent variable, such as: to be autonomous or a worker of a low middle class. The remaining variables seem to have no clear effect in the regression.