Bayesian prediction for small areas using sur models

Sample surveys are usually designed and analyzed to produce estimates for larger areas and/or populations. Nevertheless, sample sizes are often not large enough to give adequate precision for small area estimates of interest. To circumvent such difficulties, borrowing strength from related small areas via modeling becomes essential. In line with this, we propose a hierarchical multivariate Bayes prediction method for small area estimation based on the seemingly unrelated regressions (SUR) model. The performance of the proposed method was evaluated through simulation studies.     

Humps and Bumps in Lifetime Consumption

In this article we argue that the life-cycle model that allows demographics to affect household preferences and relaxes the assumption of certainty equivalence can generate hump-shaped consumption profiles over age that are very similar to those observed in household-level data sources and, in particular, match the differences in shape across different education groups. Liquidity constraints or myopia are not required to explain the empirical features of observed life-cycle patterns.     

R2 Bounds for Predictive Models: What Univariate Properties Tell us About Multivariate Predictability

ABSTRACT

A long-standing puzzle in macroeconomic forecasting has been that a wide variety of multivariate models have struggled to out-predict univariate models consistently. We seek an explanation for this puzzle in terms of population properties. We derive bounds for the predictive R² of the true, but unknown, multivariate model from univariate ARMA parameters alone. These bounds can be quite tight, implying little forecasting gain even if we knew the true multivariate model. We illustrate using CPI inflation data. Supplementary materials for this article are available online.     

Library Relocation & Collection Shifts

Abstract

For authors, publishers, and researchers, the information roadmap charts and utilizes evolving technology. “Infomediary” is a new name for an old role, describing participation in both traditional and emerging ways to deliver information and publications. This article briefly defines the role of the infomediary and the types of services provided by companies such as Ingenta, ISI (Institute for Scientific Information), and Gale. The best infomediaries will provide rational order to the growing and changing base aggregation of published material as it moves from researcher to author to publisher to library and back to researcher, particularly as that material evolves from print to electronic form.     

The Thomson ISI Journal Selection Process

Abstract

For more than four decades, Thomson ISI (Institute for Scientific Information) has been committed to a fundamental mission: to provide essential products and services that enable access to and management of the highest quality, most relevant materials for all participants in the research process. In 1958, Dr. Eugene Garfield started ISI by borrowing five hundred dollars from Household Finance. Current Contents^® of Chemical, Phamaco-Medical & Life Sciences was the sole product, covering 286 journals. Today the Thomson ISI database covers more than 16,000 international journals, books, and proceedings in the sciences, social sciences, and arts and humanities. This article describes the processes and standards that result in ISI's abstracting and indexing services. Serials Review 2003; 29:210–212.