A robust version of the Ordinary Least Squares accommodating the idea of weighting the order statistics of the squared residuals (rather than directly the squares of residuals) is recalled and its properties are studied. The existence of solution of the corresponding extremal problem and the consistency under heteroscedasticity is proved. 1. BASIC FRAMEWORK AND WEIGHTING THE ORDER STATISTICS Le...

We show that previous results on the asymptotic e ciency of OLS versus GLS in the context of trending data carry over to regressors of the fractionally integrated type

The creative capital possessed by the members of the creative class in region is either acquired through education or present innately in these members. Therefore, the creative infrastructure in the region is the sum of a part representing creative capital obtained through education and a second part denoting creative capital present innately in the creative class members. A researcher wishes t...

This note formalizes bias and inconsistency results for ordinary least squares (OLS) on the linear probability model and provides sufficient conditions for unbiasedness and consistency to hold. The conditions suggest that a btrimming estimatorQ may reduce OLS bias. D 2005 Elsevier B.V. All rights reserved.

The simultaneous prediction of average and actual values of study variable in a linear regression model is considered in this paper. Generally, either of the ordinary least squares estimator or Stein-rule estimators are employed for the construction of predictors for the simultaneous prediction. A linear combination of ordinary least squares and Stein-rule predictors are utilized in this paper ...

AbstractIn this paper we formulate Stein–minimax type estimators and compare the performance properties with other estimators in case of mean value predictions. When the model is estimated by ordinary least squares it has been observed that least squares predicted is unbiased while minimax and Stein-minimax predictors are biased. The superiority conditions of the estimators have been derived by...

The Maximum Capture problem (MAXCAP) is a decision model that addresses the issue of location in a competitive environment. This paper presents a new approach to determine which store’s attributes (other than distance) should be included in the new Market Capture Models and how they ought to be reflected using the Multiplicative Competitive Interaction model. The methodology involves the design...

This study aims to examine the link between inequality and diffusion of Information and Communications Technology (ICT). It focuses on a set of 32 African countries. ICT diffusion rate for all the countries was calculated. Two estimation techniques were used: Fractional Regression Model method and Ordinary Least Squares. The results indicate that inequality contributed to the development of ICT...

A censored variable has a large fraction of observations at the minimum or maximum. Because the censored variable is not observed over its entire range ordinary estimates of the mean and variance of a censored variable will be biased. Ordinary least squares (OLS) estimates of its regression on a set of explanatory variables will also be biased. These estimates are not consistent, i.e., the bias...

This paper explores the correlates of career satisfaction among Canadian managers, professionals and executives, specifically the career satisfaction experience of both visible minority and non-visible minority immigrants. Survey data collected from over 13,000 managers, professionals and executives in 43 Canadian organizations were analysed using the ordinary least squares multiple regression ...