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Description:	The purpose of this course is to introduce students to the theory and application of econometric methods. It covers the basic tools of estimation and inference in the context of the single-equation linear regression model, and deals primarily with least squares methods of estimation.
Topics:	Probability and Distribution Theory. Statistical Inference. Classical Regression Model: The Simple Regression Model. Classical Regression Model: Multiple Regression Model. Inference and Prediction in Multiple Regression Model. Extensions of Classical Regression Model: Heteroskedasticity, Autocorrelation, Multicollinearity, Dummy Variables Generalized Least Square. Instrumental variables. Large Sample Results for The Classical Regression Model.
Teaching:	56 hours during first semester