This paper examines competition between generic and brand-name drugs in the regulated Spanish pharmaceutical market. A nested logit demand model is specified for the three most consumed therapeutic subgroups in Spain: statins (anticholesterol), selective serotonin reuptake inhibitors (antidepressants) and proton pump inhibitors (antiulcers). The model is estimated with instrumental variables from a panel of monthly prescription data from 1999 to 2005. The dataset distinguishes between three different levels of patients’ copayments within the prescriptions and the results show that the greater the level of insurance that the patient has (and therefore the lower the patient’s copayment), the lower the proportion of generic prescriptions made by physicians. It seems that the low level of copayment has delayed the penetration of generics into the Spanish market. Additionally, the estimation of the demand model suggests that the substitution rules and promotional efforts associated with the reference pricing system have increased generic market share, and that being among the first generic entrants has an additional positive effect.
This paper examines the determinants of young innovative companies’ (YICs) R&D activities taking into account the autoregressive nature of innovation. Using a large longitudinal dataset comprising Spanish manufacturing firms over the period 1990-2008, we find that previous R&D experience is a fundamental determinant for mature and young firms, albeit to a smaller extent in the case of the YICs, suggesting that their innovation behaviour is less persistent and more erratic. Moreover, our results suggest that firm and market characteristics play a distinct role in boosting the innovation activity of firms of different age. In particular, while market concentration and the degree of product diversification are found to be important in boosting R&D activities in the sub-sample of mature firms only, YICs’ spending on R&D appears to be more sensitive to demand-pull variables, suggesting the presence of credit constraints. These results have been obtained using a recently proposed dynamic type-2 tobit estimator, which accounts for individual effects and efficiently handles the initial conditions problem.
García-Quevedo, J. (IEB); Pellegrino, G. (IEB); Vivarelli, M.
Distintos trabajos han analizado la relevancia del desajuste educativo y de sus consecuencias sobre los trabajadores que la padecen. Dicho análisis es especialmente importante en el caso de España, ya que presenta uno de los porcentajes de sobreeducación más elevado de los países de la OCDE. Un aspecto que, sin embargo, no ha sido estudiado hasta el momento y que tiene un claro interés en el contexto de la economía de la educación es el posible efecto intergeneracional del desajuste educativo. El objetivo del trabajo consiste en analizar si el desajuste educativo de los padres genera algún efecto desincentivador sobre la educación de sus hijos. En concreto, se analiza si el desajuste educativo de los padres afecta a los resultados educativos de los hijos. A partir de los microdatos de la encuesta PISA para España referidos al año 2009. Dicha encuesta facilita información detallada sobre la formación de los alumnos de 15 años en las materias de matemáticas, ciencia y lengua, sus características personales y la de su entorno escolar y familiar lo que la hace idónea para llevar a cabo el estudio planteado. Los resultados obtenidos muestran que los estudiantes con progenitores sobreeducados tienen una penalización en su rendimiento académico en las tres materias analizadas, siendo ésta más intensa para los estudiantes con peores resultados educativos.
This article analyzes empirically the main existing theories on income and population city growth: increasing returns to scale, locational fundamentals and random growth. To do this we implement a threshold nonlinearity test that extends standard linear growth regression models to a dataset on urban, climatological and macroeconomic variables on 1,175 U.S. cities. Our analysis reveals the existence of increasing returns when per-capita income levels are beyond $19; 264. Despite this, income growth is mostly explained by social and locational fundamentals. Population growth also exhibits two distinct equilibria determined by a threshold value of 116,300 inhabitants beyond which city population grows at a higher rate. Income and population growth do not go hand in hand, implying an optimal level of population beyond which income growth stagnates or deteriorates
We present a methodology that allows to calculate the impact of a given Long-Term Care (LTC) insurance protection system on the risk of incurring extremely large individual lifetime costs. Our proposed methodology is illustrated with a case study. According to our risk measure, the current Spanish public LTC system mitigates individual risk by more than 30% compared to the situation where no public protection were available. We show that our method can be used to compare risk reduction of alternative LTC insurance plans.
This paper analyses whether a firm’s absorptive capacity and its distance from the technological frontier affect the choice between innovation and imitation in innovative Spanish firms. From an extensive survey of 5,575 firms during the 2004-2009 period, we found two significant results. With regard to the role of absorptive capacity, the empirical evidence shows that when innovative firms have difficulties in accessing external information and hire skilled workers, their innovative capacity is reduced. Meanwhile, with regard to distance from the technological frontier, the firms that reduce this gap manage to increase their innovative capacity at the expense of imitation. To summarise, when we studied firms’ absorptive capacity and their relative position to the technological frontier in tandem, we found that the two factors directly affected firms’ ability to innovate or imitate.
This paper presents an analysis of motor vehicle insurance claims relating to vehicle damage and to associated medical expenses. We use univariate severity distributions estimated with parametric and non-parametric methods. The methods are implemented using the statistical package R. Parametric analysis is limited to estimation of normal and lognormal distributions for each of the two claim types. The nonparametric analysis presented involves kernel density estimation. We illustrate the benefits of applying transformations to data prior to employing kernel based methods. We use a log-transformation and an optimal transformation amongst a class of transformations that produces symmetry in the data. The central aim of this paper is to provide educators with material that can be used in the classroom to teach statistical estimation methods, goodness of fit analysis and importantly statistical computing in the context of insurance and risk management. To this end, we have included in the Appendix of this paper all the R code that has been used in the analysis so that readers, both students and educators, can fully explore the techniques described.
Pitt, D.; Guillén, M. (RFA-IREA); Bolancé, C. (RFA-IREA)
Our objective is to analyse fraud as an operational risk for the insurance company. We study the effect of a fraud detection policy on the insurer’s results account, quantifying the loss risk from the perspective of claims auditing. From the point of view of operational risk, the study aims to analyse the effect of failing to detect fraudulent claims after investigation. We have chosen VAR as the risk measure with a non-parametric estimation of the loss risk involved in the detection or non-detection of fraudulent claims. The most relevant conclusion is that auditing claims reduces loss risk in the insurance company.
Ayuso, M. (RFA-IREA); Guillén, M. (RFA-IREA); Bolancé, C. (RFA-IREA)
The effectiveness of R&D subsidies can vary substantially depending on their characteristics. Specifically, the amount and intensity of such subsidies are crucial issues in the design of public schemes supporting private R&D. Public agencies determine the intensities of R&D subsidies for firms in line with their eligibility criteria, although assessing the effects of R&D projects accurately is far from straightforward. The main aim of this paper is to examine whether there is an optimal intensity for R&D subsidies through an analysis of their impact on private R&D effort. We examine the decisions of a public agency to grant subsidies taking into account not only the characteristics of the firms but also, as few previous studies have done to date, those of the R&D projects. In determining the optimal subsidy we use both parametric and nonparametric techniques. The results show a non-linear relationship between the percentage of subsidy received and the firms’ R&D effort. These results have implications for technology policy, particularly for the design of R&D subsidies that ensure enhanced effectiveness.
Duch-Brown, N. (IEB); García-Quevedo, J. (IEB); Montolio, D. (IEB)
In a recent paper Bermúdez [2009] used bivariate Poisson regression models for ratemaking in car insurance, and included zero-inflated models to account for the excess of zeros and the overdispersion in the data set. In the present paper, we revisit this model in order to consider alternatives. We propose a 2-finite mixture of bivariate Poisson regression models to demonstrate that the overdispersion in the data requires more structure if it is to be taken into account, and that a simple zero-inflated bivariate Poisson model does not suffice. At the same time, we show that a finite mixture of bivariate Poisson regression models embraces zero-inflated bivariate Poisson regression models as a special case. Additionally, we describe a model in which the mixing proportions are dependent on covariates when modelling the way in which each individual belongs to a separate cluster. Finally, an EM algorithm is provided in order to ensure the models’ ease-of-fit. These models are applied to the same automobile insurance claims data set as used in Bermúdez [2009] and it is shown that the modelling of the data set can be improved considerably.