Online, Italy

Estimating Linear Regression Models With Exogenous And Endogenous Variables In Stata

This applied course offer a rigorous overview of the more advanced technical capabilities currently available in Stata for linear regression analysis. Thus providing participants with a unique hands-on opportunity to acquire the necessary theoretical and applied skills to independently apply advanced linear regression techniques in Stata. In the opening session, the application of Ordinary Least Squares (OLS) techniques for both estimation and inference in linear models in the presence of exogenous regressors is discussed. In the second session, participants address the problems which arise when trying to estimate linear models containing endogenous regressors. Instrumental Variable and Generalized Methods of Moments (GMM) techniques for both estimation and inference, together with a discussion of the available tests for both weak identification and inference procedures under weak identification, therefore form the core of this closing session.



COURSE STRUCTURE
Individual sessions are composed of both a theoretical component (in which the techniques and underlying principles behind them are explained), and an applied (hands-on) segment using Stata, during which participants implement the techniques using real data under the watchful eye of the course tutor. Throughout the course, theoretical sessions are reinforced by applied examples, in which the course tutor discusses and highlights potential pitfalls and the advantages of individual techniques. The intuition behind the choice and implementation of a specific technique is of the utmost importance. In this manner, the course leader is able to bridge the “often difficult” gap between abstract theoretical methodologies, and the practical issues one encounters when dealing with real data.



COURSE OUTCOME
At the end of the course, participants are expected to be able to autonomously implement the theories and methodologies discussed during the course.

Target group

This course is particular interest to researchers in public and private research centres, Master and Ph.D. Students working in the following fields: Agricultural Economics, Economics, Finance, Management, Public Health, and the Political and Social Sciences seeking to acquire the applied and theoretical toolset to enable them to independently apply linear regression techniques in their empirical research.

Course aim

This applied course offer a rigorous overview of the more advanced technical capabilities currently available in Stata for linear regression analysis. Thus providing participants with a unique hands-on opportunity to acquire the necessary theoretical and applied skills to independently apply advanced linear regression techniques in Stata. In the opening session, the application of Ordinary Least Squares (OLS) techniques for both estimation and inference in linear models in the presence of exogenous regressors is discussed. In the second session, participants address the problems which arise when trying to estimate linear models containing endogenous regressors. Instrumental Variable and Generalized Methods of Moments (GMM) techniques for both estimation and inference, together with a discussion of the available tests for both weak identification and inference procedures under weak identification, therefore form the core of this closing session.

Fee info

EUR 710: Full-Time Students*: € 710.00
Ph.D. Students: € 910.00
Academic: € 1060.00
Commercial: € 1420.00



*To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters students, access to student participation rates. Part-time master and doctoral students who are also currently employed will however, be allocated academic status.