Disturbances in the classical linear regression model that do not have constant variances are said to be heteroscedastic. A vector of standardized residuals is defined whose distribution depends only ...

For testing general linear hypotheses in multiple regression models, it is shown that non-stochastically shrunken ridge estimators yield the same central F-ratios and t-statistics as does the least ...

Description: An introduction to the modern techniques of econometrics and their applications. Topics include: the classical linear regression model (specification, estimation, inference, and ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

This module will develop your core econometrics skills. The first half of the module provides a grounding in key econometric techniques covering elements such as the classical linear regression model, ...