## Topic outline

• • ### Topic 1: Introduction to Econometric Methods

##### 1. Review of your knowledge from the Statistics course.2. Introduction to the subject.
• ### Topic 2: Linear Regression with One Regressor

1.  The simple linear model;
2.  Least Squares regression with one explanatory variable;
3.  Derivation of the regression coefficients;
4.  Interpretation of a regression equation;
5. Goodness of fit: R2.

• • ### Topic 3: Properties of the regression Coefficients and Hypothesis test and confidence intervals

1. Assumptions for regression models with not-stochastic regressors.
2. The random components and unbiasedness of the OLS regression coefficients .
3. Precision of the regression coefficients.
4. Testing hypotheses relating to the regression coefficients.
5. The F test of goodness of fit.

• ### Lab class in STATA for Chapter #2 or Topic #3

1. Open the study guide for Chapter #2 and additional exercises for chapter #2.

2. Solve the following exercises A2.3; A2.4;A2.5; A2.6.

3. Solve the exercises 2.2; 2.14; 2.19: 2.26; 2.29 from additional exercises.

• ### Topic 4: Multiple regression analysis

1.  Derivation and interpretation of the multiple regression coefficients;
2. Properties of the multiple regression coefficients;
3. Multicollinearity;
4. Godness of fit: R2;
5. Prediction.

• • ### Topic 5: Nonlinear Models and Transformations

1. Linearity and non-linearity;
2. Logarithmic transformations;
3.  Models with quadratic and interactive variables;
4. Non-linear regression.
• • ### Topic 6: Dummy Variables

1. Illustration of the use of a dummy variable;
2. Extension to more than two categories and to multiple sets of dummy variables;
3. Slope dummy variables;
4. The Chow test

• ### Lab Class in STATA for Topic 6 or chapter #5

1. Open additional exercises for chapter #5;
2. Solve the following exercises: 5.1;5.3; 5.6;5.11;5.15.5.19.

• ### Topic 7: Heteroscedasticity

1. Heteroscedasticity and its implications;
2. Detection of heteroscedasticity;
3. Remedies for heteroscedasticity;

• • ### Midterm exam #2, November 23

• ### Topic 8: Autocorrelation and testing Normality assumptions

1. The problem of autocorrelation;
2. Testing autocorrelation: Durbin-Watson and Breush-Godfrey tests;
3. Remedies for autocorrelation.
4. Testing the Normality assumption.

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