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...

Abstract Taking account of the time-delayed phenomenon in diffusion of new products, we propose the timedelayed Verhulst model and then establish grey time-delayed Verhulst model using the method of greying differential equations. The related parameter packets of the novel model is obtained under the rule of OLS. The results show that traditional grey Verhulst model is a special example of grey...

In this paper we examine the influence of foreign direct investment inflows on energy intensities of developing countries empirically. We first show that a simple OLS estimation, as it is found in the literature, suggests energy intensity reductions from FDI inflows, which is consistent with the hypothesis of energy saving technology transfer via FDI. However, such a regression turns out to be ...

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 ...

This paper demonstrates that the randomization-based “Neyman” and constanteffects estimators for the variance of estimated average treatment effects are equivalent to a variant of White’s “heteroskedasticity-robust” estimator and the homoskedastic ordinary least squares (OLS) estimator, respectively.