This paper considers the effect of aggregation on the variance of parameter estimates for a linear regression model with random coefficients and an additive error term. Aggregate and microvariances are compared and measures of relative efficiency are introduced. Necessary conditions for...

This paper attempts to provide the user of linear multiple regression with a battery of diagnostic tools to determine which, if any, data points have high leverage or influence on the estimation process and how these possibly discrepant data points differ from the patterns set by the majority of...

This chapter focuses on resistant estimation procedures and methods for evaluating the impact of particular data elements on regression estimates. Model builders using macroeconomic time series are often plagued by occasional unusual events, leading them to decrease the weights to be attached to...