INTERMEDIATE ECONOMETRICS
CEU, Economics Department



Lecturers: László Mátyás (lectures 1-6) and Gábor Kőrösi (lectures 7-24)
Course: 4 credits
 

Textbooks :

Greene, W. H. [2000]: Econometric Analysis; Prentice Hall, (4th edition), referred to as Greene, or
Greene, W. H. [2003]: Econometric Analysis; Prentice Hall, (5th edition), referred to as Greene03

Banerjee, A., J. Dolado, J.W. Galbraith, and D. F. Hendry [1993]: Co-integration, Error-Correction, and the Econometric
Analysis of Non-Stationary Data; Oxford University Press

Hamilton, J. D. [1994]: Time Series Analysis; Princeton University Press
 
Lecture 1: Introduction to Asymptotic Theory in Econometrics
Greene, Sections 4.4, and 6.1-4

Lecture 2: Estimation of the Linear Model: LS and ML
Greene, Sections 4.5, and 6.4-8

Lecture 3: Estimation of the Linear Model: Large-Sample results
Greene, Sections 9.1-5, and 9.6.1

Lecture 4: Estimation of the Linear Model: Nonspherical distributions
Greene, Sections 11.1-4

Lecture 5: Introduction to the Generalised Method of Moments Estimation
Greene, Sections 4.7, 11.5, 11.6, and 15.5

Lecture 6: Exercises

Lecture 7: Inference and Prediction
Greene, Sections 3.10, 4.8-9, and 7.1-5, or
Greene03, Sections B.11 C.6, C.7, 4.7, 4.8, and 6.1-3

Lecture 8: Hypothesis Tests : Structural Break and Nonnested Models
Greene, Sections 7.11, 7.6-8, and 7.10, or
Greene03 Sections 6.6 7.4, 7.5, 8.3, and 8.4

Lecture 9: Hypothesis Tests : Special issues
Greene, Sections 7.9, 8.1-4, 9.3.5, 9.6.3-4, 9.5.4, 11.5.4, and 11.6, or
Greene03 Sections 6.5, 7.1-3, 8.1, 8.2, 17.5, 5.5, and 18.4

Lecture 10: Systems of Regression Equations
Greene, Sections 15.1-5, or
Greene03 Sections  14.1-3

Lecture 11: Simultaneous Equations Models
Greene, Sections 16.1-7, or
Greene03 Sections 15.1-7

Lecture 12: Sample Selection, Limited Dependent Variable Models, Bayesian and pretest estimator
Greene, Sections 20.2, 20.4, 19.7, 19.8, 9.8 and 8.5
Greene03 Sections  22.2, 22.4, 21.7, 21.8, and 8.2

Lecture 13: Estimation Frameworks
Greene03 (5th ed only!!) Chapter 16

Lecture 14: Exercises

Lecture 15: Stationarity; Distributed Lags and Stochastic Difference Equations
Greene, Sections 13.1-3, 17.1-3, Banerjee et al., Chapter 1, and Hamilton, Chapters 1-2

Lecture 16: Stationary Time Series : ARMA and VAR models
Hamilton, Chapter 3, and Sections 11.2, 11.4-6; Greene, Sections 18.1-2 and 17.5, and Banerjee et al., Chapter 1

Lecture 17: Non-stationarity : Integrated Processes and Unit Roots
Banerjee et. al. Chapter 3 and Section 4.1; Greene, Section 18.3; Hamilton, Chapters 15 and 16

Lecture 18: Non-stationarity : Unit Root Tests
Banerjee et. al. Sections 4.2-6; Hamilton, Chapter 17 and Section 18.3; and
Kwiatkowski, D., Phillips, P. C. B., Schmidt, P. and Shin Y. [1992]: Testing the Null Hypothesis of Stationarity Against
the Alternative of Unit Root; Journal of Econometrics, Vol. 54, pp. 159-178.

Lecture 19: Linear Transformations and Error Correction; Co-Integration (1): Representations
Banerjee et al. Chapter 2 and Sections 5.1-6; Greene, Section 17.4; Hamilton, Section 19.1

Lecture 20: Regression with Integrated Variables
Banerjee et al Section 5.4-6, Chapter 6; and Hamilton, Section 18.3

Lecture 21: Co-Integration (2) : Testing
Banerjee et al Chapter 6; Hamilton, Section 19.2; and
Shin Y. [1994] : A Residual-based Test of the Null Cointegration against the Alternative of no Cointegration; Econometric
Theory, Vol. 10, pp. 91-115.

Lecture 22: Co-Integration (3): Working with cointegrations
Greene, Section 18.4 and Banerjee et al. Chapter 7; Hamilton, Section 19.3

Lecture 23: Co-Integration (3) : ML
Banerjee et al. Chapters 8 and 9; Hamilton, Chapter 20

Lecture 24: Exercises
 

Assessment:

For audit:Students should get at least 50% for the assignments; exam is not required.

For grade: The final mark will be composed of two components: two assignments (10+20 %),
and final examination (70 %).