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

Calculation of the variance in surveys of the economic climate

Public opinion surveys have become progressively incorporated into systems of official statistics. Surveys of the economic climate are usually qualitative because they collect opinions of businesspeople and/or experts about the long-term indicators described by a number of variables. In such cases the responses are expressed in ordinal numbers, that is, the respondents verbally report, for example, whether during a given trimester the sales or the new orders have increased, decreased or remained the same as in the previous trimester. These data allow to calculate the percent of respondents in the total population (results are extrapolated), who select every one of the three options. Data are often presented in the form of an index calculated as the difference between the percent of those who claim that a given variable has improved in value and of those who claim that it has deteriorated. As in any survey conducted on a sample the question of the measurement of the sample error of the results has to be addressed, since the error influences both the reliability of the results and the calculation of the sample size adequate for a desired confidence interval. The results presented here are based on data from the Survey of the Business Climate (Encuesta de Clima Empresarial) developed through the collaboration of the Statistical Institute of Catalonia (Institut d’Estadística de Catalunya) with the Chambers of Commerce (Cámaras de Comercio) of Sabadell and Terrassa.Economic climate, variances, sampling methods.

Calculation of the variance in surveys of the economic climate.

Public opinion surveys have become progressively incorporated into systems of official statistics. Surveys of the economic climate are usually qualitative because they collect opinions of businesspeople and/or experts about the long-term indicators described by a number of variables. In such cases the responses are expressed in ordinal numbers, that is, the respondents verbally report, for example, whether during a given trimester the sales or the new orders have increased, decreased or remained the same as in the previous trimester. These data allow to calculate the percent of respondents in the total population (results are extrapolated), who select every one of the three options. Data are often presented in the form of an index calculated as the difference between the percent of those who claim that a given variable has improved in value and of those who claim that it has deteriorated. As in any survey conducted on a sample the question of the measurement of the sample error of the results has to be addressed, since the error influences both the reliability of the results and the calculation of the sample size adequate for a desired confidence interval. The results presented here are based on data from the Survey of the Business Climate (Encuesta de Clima Empresarial) developed through the collaboration of the Statistical Institute of Catalonia (Institut d’Estadística de Catalunya) with the Chambers of Commerce (Cámaras de Comercio) of Sabadell and Terrassa.Economic climate, variances, sampling methods.

Improving both domain and total area estimation by composition

In this article we propose small area estimators for both the small and large area parameters. When the objective is to estimate parameters at both levels, optimality is achieved by a sample design that combines fixed and proportional allocation. In such a design, one fraction of the sample is distributed proportionally among the small areas and the rest is evenly distributed. Simulation is used to assess the performance of the direct estimator and two composite small area estimators, for a range of sample sizes and different sample distributions. Performance is measured in terms of mean squared errors for both small and large area parameters. Small area composite estimators open the possibility of reducing the sample size when the desired precision is given, or improving precision for a given sample size.Peer Reviewe

Estimadores compuestos en estadística regional: una aplicación a la estimación de la tasa de variación de la ocupación en la industria

Este trabajo es parte de un proyecto que estudia la aplicación de estimadores compuestos (combinación de estimadores directos e indirectos) para áreas pequeñas en estadística regional. Comparamos tres estimadores: uno directo basado en datos muestrales de cada Comunidad Autónoma (CA), otro sintético (indirecto) que combina los datos estatales con información específica de las CCAA, y un tercer estimador, el compuesto, basado en un modelo estadístico que se concreta en una combinación lineal de los dos anteriores. Ilustramos el método de análisis adoptado mediante la estimación de la tasa de variación de la ocupación industrial en las diferentes CCAA de España

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

Smoothing the Catalan tourism micro-data time series

In this paper we propose a method for smoothing the Catalan tourism time series between 1997 and 2000. These time series, built upon a micro database drawn from a survey conducted by the Statistical Institute of Catalonia, are somewhat volatile due, it would seem, to the incomplete nature of the information. The application of a smoothing procedure based on the combination of classical techniques and weighted moving averages allows us to overcome the problems caused by this lack of information and to obtain time series that evolve smoothly over time

Metodología experimental para la estimación anual de la aportación del turismo al PIB municipal. Aplicación a 50 municipios de Catalunya

En aquest treball es presenta una metodologia experimental per a l'estimació anual del PIB que genera l'activitat turística a escala municipal. La metodologia proposada utilitza fonts d'informació públiques disponibles amb actualització anual, com els ocupats localitzats per activitat econòmica, la productivitat sectorial i els salaris. L'aspecte més innovador de la metodologia correspon a l'estimació sectorial generada pel turisme. Es tracta d'una aproximació que es pot qualificar de contrastiva, perquè consisteix a comparar l'ocupació interior sectorial dels municipis turístics amb un conjunt de municipis no turístics, que tenen tota la seva ocupació dedicada a fer front a la demanda generada pels residents. Els resultats que se n'obtenen permeten no només conèixer el pes de l'activitat turística municipal, tant en PIB com en ocupats, sinó també la composició sectorial. Els resultats obtinguts per a 50 municipis catalans són consistents amb estimacions prèvies (Barcelona) i amb l'evolució temporal que s'observa al Compte satèl·lit del turisme de l'INE (2018-2021).En este trabajo se presenta una metodología experimental para la estimación anual del PIB que genera la actividad turística a escala municipal. La metodología propuesta emplea fuentes de información públicas disponibles con actualización anual, como los ocupados localizados por actividad económica, la productividad sectorial y los salarios. El aspecto más innovador de la metodología corresponde a la estimación sectorial generada por el turismo. Se trata de una aproximación que se puede calificar de contrastiva, porque consiste en comparar la ocupación interior sectorial de los municipios turísticos con un conjunto de municipios no turísticos, que tienen toda su ocupación dedicada a hacer frente a la demanda generada por sus propios residentes. Los resultados que se obtienen permiten no sólo conocer el peso de la actividad turística municipal, tanto en PIB como en ocupados, sino también su composición sectorial. Los resultados obtenidos para 50 municipios catalanes son consistentes con estimaciones previas (Barcelona) y con la evolución temporal que se observa en la Cuenta satélite del turismo del INE (2018-2021)

Smoothing the Catalan tourism micro-data time series

In this paper we propose a method for smoothing the Catalan tourism time series between 1997 and 2000. These time series, built upon a micro database drawn from a survey conducted by the Statistical Institute of Catalonia, are somewhat volatile due, it would seem, to the incomplete nature of the information. The application of a smoothing procedure based on the combination of classical techniques and weighted moving averages allows us to overcome the problems caused by this lack of information and to obtain time series that evolve smoothly over time