Econometrics Michael P. Murray Pdf Crack
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OVERVIEW
Part I - The Linear Regression Model
1. What is Econometrics?
2. Choosing Estimators: Intuition and Monte Carlo Methods
3. Linear Estimators and the Gauss-Markov Theorem
4. Blue Estimators for the Slope and Intercept of a Straight Line
5. Residuals
6. Multiple Regression
Part II - Specification and Hypothesis Testing
7. Testing Single Hypotheses in Regression Models
8. Superfluous and Omitted Variables, Multicollinearity and Binary Variables
9. Testing Multiple Hypotheses
Part III - Further Topics in Regression
10. Heteroskedastic Disturbances
11. Autoregressive Disturbances
12. Large Sample Properties Of Estimators: Consistency and Asymptotic Efficiency
13. Instrumental Variables Estimation
14. Systems of Equations
15. Randomized Experiments and Natural Experiments
16. Analyzing Panel Data
17. Forecasting
18. Stochastically Trending Variables
19. Logit and Probit Models: Truncated and Censored Samples
Statistical Appendix
WEB EXTENSION 1 USING CALCULUS AND ALGEBRA FOR THE SIMPLEST CASE: n = 3
WEB EXTENSION 2 LOCAL AVERAGE TREATMENT EFFECTS
WEB EXTENSION 3 GENERALIZED METHOD OF MOMENTS ESTIMATORS AND IDENTIFICATION
WEB EXTENSION 4 MAXIMUM LIKELIHOOD ESTIMATION
WEB EXTENSION 5 ESTIMATORS FOR SYSTEMS OF EQUATIONS
WEB EXTENSION 6 MULTIPLE COINTEGRATING RELATIONSHIPS
WEB EXTENSION 7 LOG-ODDS AND LOGIT MODELS: USING GROUPED DATA
WEB EXTENSION 8 MULTINOMIAL MODELS
show more
Part I - The Linear Regression Model
1. What is Econometrics?
2. Choosing Estimators: Intuition and Monte Carlo Methods
3. Linear Estimators and the Gauss-Markov Theorem
4. Blue Estimators for the Slope and Intercept of a Straight Line
5. Residuals
6. Multiple Regression
Part II - Specification and Hypothesis Testing
7. Testing Single Hypotheses in Regression Models
8. Superfluous and Omitted Variables, Multicollinearity and Binary Variables
9. Testing Multiple Hypotheses
Part III - Further Topics in Regression
10. Heteroskedastic Disturbances
11. Autoregressive Disturbances
12. Large Sample Properties Of Estimators: Consistency and Asymptotic Efficiency
13. Instrumental Variables Estimation
14. Systems of Equations
15. Randomized Experiments and Natural Experiments
16. Analyzing Panel Data
17. Forecasting
18. Stochastically Trending Variables
19. Logit and Probit Models: Truncated and Censored Samples
Statistical Appendix
WEB EXTENSION 1 USING CALCULUS AND ALGEBRA FOR THE SIMPLEST CASE: n = 3
WEB EXTENSION 2 LOCAL AVERAGE TREATMENT EFFECTS
WEB EXTENSION 3 GENERALIZED METHOD OF MOMENTS ESTIMATORS AND IDENTIFICATION
WEB EXTENSION 4 MAXIMUM LIKELIHOOD ESTIMATION
WEB EXTENSION 5 ESTIMATORS FOR SYSTEMS OF EQUATIONS
WEB EXTENSION 6 MULTIPLE COINTEGRATING RELATIONSHIPS
WEB EXTENSION 7 LOG-ODDS AND LOGIT MODELS: USING GROUPED DATA
WEB EXTENSION 8 MULTINOMIAL MODELS
show more
Murray is Charles Franklin Phillips Professor of Eco- nomics, Bates College, Lewiston, ME 04240. This work was partially supported by the U.S. Department of Housing and Urban Development. The author is grateful to David Aschauer, Rosanne Ducey, Robert En- gle, Carl Schwinn, and an anonymous referee for useful comments on.
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