Introduction to computer programming, comparison of softwares, reproduction of published results. The Lab builds on previous econometric knowledge and makes the student aware of the practical difficulties in collecting the data and in processing them.
Greene Econometric Analysis 6th Ed 2008; articles on topics chosen each semester
Learning Objectives
The aim of the course is to expose the student to practicalities ancountered when doing applied research. Some programming skills will be developed and reproduction of published results attempted.
Prerequisites
Econometrics (both Macro and Micro modules)
Teaching Methods
Hands on approach. Lectures followed by practical examples (reproduction of published papers results)
Further information
Additional material available on the Moodle platform
Type of Assessment
A paper on a topic chosen by the student and the instructor
Course program
Introduction to a matrix based programming language (MATLAB). Basics: importing data, the command line, review of matrix algebra, storing the results. The Classical Linear Econometric Model in matrix form. OLS estimators and covariance matrix. Robust forms under heteroskedasticity and serial correlation. Testing linear and nonlinear restrictions. Residual diagnostics, auxiliary regressions. Simulation based analysis of estimators properties and departures from ideal conditions. The second half of the course will be devoted to the replication of the results from some published papers, both in macro and in micro applications.