Measuring intergenerational earnings mobility in Spain: a selection-bias-free approach

This paper analyses intergenerational earnings mobility in Spain correcting for different selection biases. We address the co-residence selection problem by combining information from two samples and using the two-sample two-stage least square estimator. We find a small decrease in elasticity when we move to younger cohorts. Furthermore, we find a higher correlation in the case of daughters than in the case of sons; however, when we consider the employment selection in the case of daughters, by adopting a Heckman-type correction method, the diference between sons and daughters disappears. By decomposing the sources of earnings elasticity across generations, we find that the correlation between child's and father's occupation is the most important component. Finally, quantile regressions estimates show that the influence of the father's earnings is greater when we move to the lower tail of the offspring's earnings distribution, especially in the case of daughters' earnings.

Agronomic and commercial performance of four Spanish carob cultivars

The carob tree (Ceratonia siliqua) shows interesting prospects for some coastal Mediterranean growing areas and is widely used for industrial, agricultural, and ornamental purposes. It can be an alternative crop adapted to part-time farming and can also be used to regenerate vegetation in areas with a mild climate and erosion problems. Four Spanish carob cultivars were examined (Banya de Cabra, Duraio, Matalafera, and Rojal) to determine the one that performed the best for planting new orchards in northeastern Spain (Catalonia). The trees in this rain-fed trial (average rainfall of 500 mm) were planted in 1986 using seedling rootstocks that were budded in 1987. The trees were trained using the free-vase system and were spaced 8 x 9 m (138 trees/ha including 12% pollinators). The results showed that ‘Rojal’ was the earliest bearing cultivar. However, no significant differences were observed for cumulative pod production 18 years after budding. With respect to cumulative seed yield, ‘Duraio’ had the highest production (95 kg/tree). The lowest tree vigor (trunk cross-section) was observed in ‘Matalafera’. ‘Rojal’ trees produced the largest pods (average fruit weight of 18.9 g) and lowest seed content (11.8%), while ‘Banya de Cabra’ and ‘Duraio’ produced the smallest fruit (weighing 15.3 and 16.2 g, respectively) with the highest seed content (15.2% and 17.3%, respectively). Gum content, expressed as a percentage of the dry weight, was highest in ‘Duraio’ (56.9%) and was lowest in ‘Rojal’ (54.1%). Thus, in terms of kernel and pod production, ‘Duraio’ appeared to be the best-performing female cultivar for planting new carob orchards

System GMM estimation with a small sample

Properties of GMM estimators for panel data, which have become very popular in the empirical economic growth literature, are not well known when the number of individuals is small. This paper analyses through Monte Carlo simulations the properties of various GMM and other estimators when the number of individuals is the one typically available in country growth studies. It is found that, provided that some persistency is present in the series, the system GMM estimator has a lower bias and higher efficiency than all the other estimators analysed, including the standard first-differences GMM estimator.

Series enlazadas de algunos agregados económicos nacionales y regionales, 1955-2007 Versión 2.1

I construct "homogeneous" series of GVA at current and constant prices, employment and population for the Spain and its regions covering the period 1955-2007. The series are obtained by linking the Regional Accounts of the National Statistical Institute with the series constructed by Julio Alcaide and his team for the BBVA Foundation. The "switching point" at which this last source stops being used as a reference to construct the linked series is determined using a procedure that allows me to estimate which of the two competing series would produce an estimator with the lowest MSE when it is used as dependent variable in a regression on an arbitrary independent variable. To the extent that it is possible, the difference between the two series found at the point of linkage is distributed between the initial levels of the older series and its subsequent growth using external estimates of the relevant variables at the beginning of the sample period.

A Data mining approach to indirect inference

Consider a model with parameter phi, and an auxiliary model with parameter theta. Let phi be a randomly sampled from a given density over the known parameter space. Monte Carlo methods can be used to draw simulated data and compute the corresponding estimate of theta, say theta_tilde. A large set of tuples (phi, theta_tilde) can be generated in this manner. Nonparametric methods may be use to fit the function E(phi|theta_tilde=a), using these tuples. It is proposed to estimate phi using the fitted E(phi|theta_tilde=theta_hat), where theta_hat is the auxiliary estimate, using the real sample data. This is a consistent and asymptotically normally distributed estimator, under certain assumptions. Monte Carlo results for dynamic panel data and vector autoregressions show that this estimator can have very attractive small sample properties. Confidence intervals can be constructed using the quantiles of the phi for which theta_tilde is close to theta_hat. Such confidence intervals are found to have very accurate coverage.

Avantpassats de plata

Treball de recerca realitzat per una alumna d'ensenyament secundari i guardonat amb un Premi CIRIT per fomentar l'esperit científic del Jovent l'any 2009. El treball es centra en conèixer la complexitat d’un estudi fotogràfic del s. XIX: l’estudi Napoleón. Per entendre tots els aspectes que implicava fer una fotografia en aquest estudi comença explicant com es van desenvolupar i descobrir les diferents tècniques fotogràfiques, després presenta l’estat de la fotografia a la Catalunya del s. XIX. El nucli del treball té diferents aspectes: per una banda s’investiga la història dels fundadors d’un dels estudis més importants a la Barcelona del s. XIX, per l’altra presenta com eren les sales, els decorats, els clients, la tipografia, les càmeres .... i per últim, porta a la pràctica tot allò necessari per a transformar un paper blanc en una fotografia fent servir els mètodes de l’època. Podríem dir que el treball es desenvolupa en tres àmbits: el primer sobre els fonaments tècnics i històrics de la fotografia, les fonts utilitzades per realitzar aquest apartat han estat fonamentalment bibliogràfiques; el segon fa referència a l’estudi fotogràfic dels Napoleón, en aquest cas, a part de les fonts bibliogràfiques, també ha estat de vital importància la informació aportada per un descendent de la família i finalment s’explica els procediments que es van fer servir per obtenir imatges durant el segle s.XIX i les reaccions químiques en les quals es fonamenten. Aporta també una part experimental que dóna un caire artístic i novedós al treball.

An Introduction to parametric and non-parametric models for bivariate positive insurance claim severity distributions

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.

SNM Guide

This is a guide that explains how to use software that implements the simulated nonparametric moments (SNM) estimator proposed by Creel and Kristensen (2009). The guide shows how results of that paper may easily be replicated, and explains how to install and use the software for estimation of simulable econometric models.

Tritordeum, wheat and triticale yield components under multi-local mediterranean drought conditions

The species x location interaction was of great importance in explaining the behaviour of genetic material. The study presented here shows, for the first time, the performance, under field conditions of the new tritordeum species, compared to wheat and triticale in a wide range of Mediterranean countries (Spain, Lebanon and Tunisia). The results obtained revealed that despite the diversity of environmental conditions, the main differences in yield were due to genotypes, especially to differences between species. The multi-local study with different growth conditions revealed important information about the water availability effect on yield. In the lowest yielding environments (Tunisia rainfed), Tritordeum and triticale yields were equivalent. However under better growth conditions (Spain), tritordeum yield was shown to be lower than wheat and triticale. Interestingly, when water limitation was extended during the pre-anthesis period, differences in tritordeum versus wheat-triticale yield rate were larger than when water stress occurred during anthesis. These variations were explained by the fact that kernel weight has been found as the limiting factor for yield determination in tritordeum, and a delay in the anthesis date may have been the cause for the low kernel weight and low yield under Mediterranean drought conditions. Such differences in yield between tritordeum and wheat or triticale could be explained by the fact that tritordeum is a relatively new species and far fewer resources have been devoted to its improvement when compared to wheat and triticale. Our results suggest that breeding efforts should be directed to an earlier anthesis date and a longer grain filling period. tritordeum proved to have possibilities to be grown under drought environments as a new crop, since its performance was quite close to wheat and triticale. Besides, it has qualitative added values that may improve farmers' income per unit land.

Desarrollo de software para el procesado numérico en tarjetas gráficas

Debido al gran número de transistores por mm2 que hoy en día podemos encontrar en las GPU convencionales, en los últimos años éstas se vienen utilizando para propósitos generales gracias a que ofrecen un mayor rendimiento para computación paralela. Este proyecto implementa el producto sparse matrix-vector sobre OpenCL. En los primeros capítulos hacemos una revisión de la base teórica necesaria para comprender el problema. Después veremos los fundamentos de OpenCL y del hardware sobre el que se ejecutarán las librerías desarrolladas. En el siguiente capítulo seguiremos con una descripción del código de los kernels y de su flujo de datos. Finalmente, el software es evaluado basándose en comparativas con la CPU.

An empirical analysis of a merger between a network and low-cost airlines

We use a difference-in-difference estimator to examine the effects of a merger involving three airlines. The novelty lies in the examination of this operation in two distinct scenarios: (1) on routes where two low-cost carriers and (2) on routes where a network and one of the low-cost airlines had previously been competing. We report a reduction in frequencies but no substantial effect on prices in the first scenario, while in the second we report an increase in prices but no substantial effect on frequencies. These results may be attributed to the differences in passenger types flying on these routes.

Estimation of parametric and nonparametric models for univariate claim severity distributions - an approach using R

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

How does monetary policy change? evidence on inflation targeting countries

We examine the evolution of monetary policy rules in a group of inflation targeting countries (Australia, Canada, New Zealand, Sweden and the United Kingdom) applying moment- based estimator at time-varying parameter model with endogenous regressors. Using this novel flexible framework, our main findings are threefold. First, monetary policy rules change gradually pointing to the importance of applying time-varying estimation framework. Second, the interest rate smoothing parameter is much lower that what previous time-invariant estimates of policy rules typically report. External factors matter for all countries, albeit the importance of exchange rate diminishes after the adoption of inflation targeting. Third, the response of interest rates on inflation is particularly strong during the periods, when central bankers want to break the record of high inflation such as in the U.K. or in Australia at the beginning of 1980s. Contrary to common wisdom, the response becomes less aggressive after the adoption of inflation targeting suggesting the positive effect of this regime on anchoring inflation expectations. This result is supported by our finding that inflation persistence as well as policy neutral rate typically decreased after the adoption of inflation targeting.

Indirect likelihood inference

Given a sample from a fully specified parametric model, let Zn be a given finite-dimensional statistic - for example, an initial estimator or a set of sample moments. We propose to (re-)estimate the parameters of the model by maximizing the likelihood of Zn. We call this the maximum indirect likelihood (MIL) estimator. We also propose a computationally tractable Bayesian version of the estimator which we refer to as a Bayesian Indirect Likelihood (BIL) estimator. In most cases, the density of the statistic will be of unknown form, and we develop simulated versions of the MIL and BIL estimators. We show that the indirect likelihood estimators are consistent and asymptotically normally distributed, with the same asymptotic variance as that of the corresponding efficient two-step GMM estimator based on the same statistic. However, our likelihood-based estimators, by taking into account the full finite-sample distribution of the statistic, are higher order efficient relative to GMM-type estimators. Furthermore, in many cases they enjoy a bias reduction property similar to that of the indirect inference estimator. Monte Carlo results for a number of applications including dynamic and nonlinear panel data models, a structural auction model and two DSGE models show that the proposed estimators indeed have attractive finite sample properties.

The determinants of YIc's R&D activity

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.