Introduction to a matrix based programming language (R). 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.