Econometric Analysis

Part 1: matrix algebra; probability and distribution theory; statistical inference. Part 2: the classical linear regression model; multiple regression; hypothesis tests with the classical multiple regression model; functional form non-linearity and specification; data problems; large-sample results for the classical regression model; nonlinear regression models; an introduction to nonlinear optimization. Part 3: nonspherical disturbances; heteroscedasticity; autocorrelated disturbances; models that use both cross-section and time-series data. Part 4: systems of regression equations; distributed lag models; time series models; simultaneous equations models; models with discrete dependent variables; limited dependent variable and duration models.