Lyfe-cycle effects on household expenditures: A latent-variable approach

Using data from the Spanish household budget survey, we investigate life- cycle effects on several product expenditures. A latent-variable model approach is adopted to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household life-cycle typologies. The analysis discloses significant life-cycle effects on the mean levels of expenditures; it also detects significant life-cycle effects on the way expenditures are affected by income and family size. Asymptotic robust methods are used to account for possible non-normality of the data.Structural equations, multi-group analysis, life cycle effects, product expenditures

An Empirical Evaluation of Five Small Area Estimators

This paper compares five small area estimators. We use Monte Carlo simulation in the context of both artificial and real populations. In addition to the direct and indirect estimators, we consider the optimal composite estimator with population weights, and two composite estimators with estimated weights: one that assumes homogeneity of within area variance and squared bias and one that uses area-specific estimates of variance and squared bias. In the study with real population, we found that among the feasible estimators, the best choice is the one that uses area-specific estimates of variance and squared bias.Regional statistics, small areas, root mean square error, direct, indirect and composite estimators.

An empirical evaluation of small area estimators

This paper investigates the comparative performance of five small area estimators. We use Monte Carlo simulation in the context of both theoretical and empirical populations. In addition to the direct and indirect estimators, we consider the optimal composite estimator with population weights, and two composite estimators with estimated weights: one that assumes homogeneity of within area variance and square bias, and another one that uses area specific estimates of variance and square bias. It is found that among the feasible estimators, the best choice is the one that uses area specific estimates of variance and square bias.Regional statistics, small areas, root mean square error, direct, indirect and composite estimators

On the performance of small-area estimators: Fixed vs. random area parameters

Most methods for small-area estimation are based on composite estimators derived from design- or model-based methods. A composite estimator is a linear combination of a direct and an indirect estimator with weights that usually depend on unknown parameters which need to be estimated. Although model-based small-area estimators are usually based on random-effects models, the assumption of fixed effects is at face value more appropriate.Model-based estimators are justified by the assumption of random (interchangeable) area effects; in practice, however, areas are not interchangeable. In the present paper we empirically assess the quality of several small-area estimators in the setting in which the area effects are treated as fixed. We consider two settings: one that draws samples from a theoretical population, and another that draws samples from an empirical population of a labor force register maintained by the National Institute of Social Security (NISS) of Catalonia. We distinguish two types of composite estimators: a) those that use weights that involve area specific estimates of bias and variance; and, b) those that use weights that involve a common variance and a common squared bias estimate for all the areas. We assess their precision and discuss alternatives to optimizing composite estimation in applications.Small area estimation, composite estimator, Monte Carlo study, random effect model, BLUP, empirical BLUP

Improving small area estimation by combining surveys: new perspectives in regional statistics

A national survey designed for estimating a specific population quantity is sometimes used for estimation of this quantity also for a small area, such as a province. Budget constraints do not allow a greater sample size for the small area, and so other means of improving estimation have to be devised. We investigate such methods and assess them by a Monte Carlo study. We explore how a complementary survey can be exploited in small area estimation. We use the context of the Spanish Labour Force Survey (EPA) and the Barometer in Spain for our study.Composite estimator, complementary survey, mean squared error, official statistics, regional statistics, small area

Origin of the very metal poor stars in the disk of the Milky Way

Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2022, Tutora: Maria Teresa Antoja CastelltortThe stars with quasi-primordial chemistry are remnants of the early stages of formation of our Galaxy thus providing insights into its assembly. We use GARROTXA, a “Milky Way-like” high resolution zoom-in cosmological simulation, to show that even though these stars are commonly associated with the halo of the Galaxy, by setting geometrical and dynamical constraints we managed to detect 619 ultra metal-poor stars with planar orbits that show a slight preference for prograde motion (around ∼ 7% above the expected value of 0.5). The fraction of ultra metal-poor prograde orbits that we find is smaller than in other simulations of previous studies and than the observed fraction in the Milky Way. Moreover, we traced those stars back to our earliest available snapshot (t = 1.87 Gy after the Big Bang) and proved that all of them (except two) belonged to the primordial blocks from which the proto-galaxy was formed. Finally, we conclude that low metallicity stars are excellent indicators about the history of formation and assembly of its galax

Product expenditure patterns in the ECPF survey: an analysis using multiple group latent-variables models

Using data form the Spanish household budget survey, we investigate some aspects of household heterogeneity on several product expenditures. We adopt a latent-variable model approach to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household typologies. The analysis discloses significant variations across groups on the mean levels of expenditures and on the way income and family size affect expenditures. Asymptotic robust methods are used to account for possible non-normality of the data

Estudio y simulación del DBA OBS-aware para EPONs

El desarrollo de tecnologías de red de acceso basadas en el uso de la fibra óptica como medio de transmisión ha permitido, en comparación con las redes de acceso de cable, incrementar en varios órdenes de magnitud la capacidad de transmisión de datos en el segmento más cercano al usuario. Las redes de acceso ópticas pasivas (Passive Optical Networks, PONs) se caracterizan por no tener componentes activos intermedios entre el usuario y la central. Entre ellas se definen las redes Ethernet PON (EPON), cuya arquitectura se basa en el transporte de tráfico Ethernet, manteniendo las características de la especificación 802.3 sobre fibra óptica. En la red troncal la fibra óptica es el medio de transmisión predominante, siendo la conmutación de circuitos la técnica más utilizada debido, principalmente, a la falta de un equivalente real a las memorias de acceso aleatorio (Random Access Memory, RAM) que permita soportar conmutación de paquetes en el dominio óptico. Para poder beneficiarse de las ventajas del multiplexado estadístico de usuarios que proporciona la conmutación de paquetes sin los requisitos tecnológicos que supone su implementación en redes ópticas, se definió la conmutación óptica de ráfagas (Optical Burst Switching, OBS). En OBS, los datos de los usuarios se agregan en los nodos frontera formando unidades de datos de longitud superior (ráfagas). Antes de la transmisión de cada ráfaga, se envía un paquete de control con el objetivo de configurar los dispositivos intermedios, permitiendo así que el envío de los datos se pueda realizar íntegramente en el dominio óptico. El presente estudio desarrolla el escenario de simulación que interconecta una red de acceso EPON con una red troncal basada en la tecnología de conmutación OBS

Estimadores compuestos en estadística regional: aplicación para la tasa de variación de la ocupación en la industria

This work is part of a project studying the performance of model based estimators in a small area context. We have chosen a simple statistical application in which we estimate the growth rate of accupation for several regions of Spain. We compare three estimators: the direct one based on straightforward results from the survey (which is unbiassed), and a third one which is based in a statistical model and that minimizes the mean square error.Borrowing strength, empirical best linear unbiased prediction, mean square error, synthetic estimation