Matrix algebra. Probability and destribution theory. Statistical inference. Computation and optimization. The classical multiple linear regression model: specification and estimation. Inference and prediction. Functional form, nonlinearity, and specification. Large-sample results and alternative estimators for the classical regression model. Nonlinear regression models. Nonspherical disturbances, generalizad regression and GMM estimation. Heteroscedasticy. Autocorrelated disturbances. Models for panel data. Systems of regression equations. Simultaneous-equations models. Regressions with lagged variables. Time-series models. Models with discrete dependent variables. Limited dependt variable and duration models.
