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
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)
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.
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.
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)
PhD graduates hold the highest education degree, are trained to conduct research and can be considered a key element in the creation, commercialization and diffusion of innovations. The impact of PhDs on innovation and economic development takes place through several channels such as the accumulation of scientific capital stock, the enhancement of technology transfers and the promotion of cooperation relationships in innovation processes. Although the placement of PhDs in industry provides a very important mechanism for transmitting knowledge from universities to firms, information about the characteristics of the firms that employ PhDs is very scarce. The goal of this paper is to improve understanding of the determinants of the demand for PhDs in the private sector. Three main potential determinants of the demand for PhDs are considered: cooperation between firms and universities, R&D activities of firms and several characteristics of firms, size, sector, productivity and age. The results from the econometric analysis show that cooperation between firms and universities encourages firms to recruit PhDs and point to the existence of accumulative effects in the hiring of PhD graduates.
García-Quevedo, J. (IEB), Mas-Verdú, F. (IEB), Polo-Otero, J. (IEB)
We present a real data set of claims amounts where costs related to damage are recorded separately from those related to medical expenses. Only claims with positive costs are considered here. Two approaches to density estimation are presented: a classical parametric and a semi-parametric method, based on transformation kernel density estimation. We explore the data set with standard univariate methods. We also propose ways to select the bandwidth and transformation parameters in the univariate case based on Bayesian methods. We indicate how to compare the results of alternative methods both looking at the shape of the overall density domain and exploring the density estimates in the right tail.
When actuaries face with the problem of pricing an insurance contract that contains different types of coverage, such as a motor insurance or homeowner’s insurance policy, they usually assume that types of claim are independent. However, this assumption may not be realistic: several studies have shown that there is a positive correlation between types of claim. Here we introduce di®erent multivariate Poisson regression models in order to relax the independence assumption, including zero-in°ated models to account for excess of zeros and overdispersion. These models have been largely ignored to date, mainly because of their computational di±culties. Bayesian inference based on MCMC helps to solve this problem (and also lets us derive, for several quantities of interest, posterior summaries to account for uncertainty). Finally, these models are applied to an automobile insurance claims database with three different types of claims. We analyse the consequences for pure and loaded premiums when the independence assumption is relaxed by using different multivariate Poisson regression models and their zero-inflated versions.
Drawing on data contained in the 2005 EU-SILC, this paper investigates the disparities in educational opportunities in Italy and Spain. Its main objective is to analyse the predicted probabilities of successfully completing upper-secondary and tertiary education for individuals with different parental backgrounds, and the changes in these probabilities across birth cohorts extending from 1940 to 1980. The results suggest that the disparities in tertiary education opportunities in Italy tend to increase over time. By contrast, the gap in educational opportunity in Spain shows a marked decrease across the cohorts. Moreover, by using an intuitive decomposition strategy, the paper shows that a large part of the educational gap between individuals of different backgrounds is “composed” of the difference in the endowment of family characteristics. Specifically, it seems that more highly educated parents are more able to endow their children with a better composition of family characteristics, which accounts for a significant proportion of the disparities in educational opportunity.
Di Paolo, A. (GEAP & IEB) Published in Revista de Economía Aplicada, forthcoming
Esta investigación analiza la movilidad ocupacional de los inmigrantes entre sus países de origen y España, así como sus principales determinantes. La misma se basa en los microdatos de la Encuesta Nacional de Inmigrantes y el uso de una escala de estatus ocupacional de carácter internacional (ISEI). La evidencia muestra que, por lo general, los inmigrantes sufren una fuerte degradación ocupacional en España con respecto a sus países de origen. Ésta se explica en buena medida por la intensa degradación que suelen experimentar al incorporarse al mercado de trabajo español, puesto que la mejora ocupacional asociada a su estancia en nuestro país es limitada. La degradación ocupacional al llegar es mayor para las mujeres, los inmigrantes de mayor nivel educativo y los procedentes de países en desarrollo. La recuperación posterior confirma la hipótesis de una movilidad ocupacional en forma de U profunda para los dos últimos colectivos, mientras que las mujeres padecen mayores dificultades para progresar ocupacionalmente. Residir en España, convalidar estudios extranjeros, aprender castellano y regularizar la situación documental mejoran el estatus ocupacional, pero, excepto en el último caso, de forma lenta. Acceder al primer empleo en España a través de redes informales tiene un efecto negativo sobre el logro ocupacional. Por último, mayor tiempo buscando empleo y una búsqueda de trabajo que incluya la movilidad geográfica se traducen en una mejora ocupacional mayor, mientras que el desempleo tiene un efecto negativo.
Simón, H. (IEB), Ramos, R. (AQR-IREA), Sanromá, E. (IEB)