Topic outline

    • Readings: Brooks Ch. 2, (2nd ed.) Simple Linear Regression Analysis. See the modified slides from Brooks, Ch. 2, attached

    • Review of the classical multiple linear regression model (with several independent variables).

      Readings: Cjhapter 3 in Brooks, 2nd ed. See also book slides:

      http://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch3_slides.ppt

      Attached there are a few slides (called diagnostic tests) that explain how the assumptions of the simple linear regression  may be checked both graphically and using statistical tests. This may also help you with homework 1.

      Supplementary material is added for those interested


    • Multiple regression. Diagnostics and additional tests for regression analysis, Readings: Brooks Ch. 3--4, see also slides on the publishers page.

    • Regression analysis,:some tests and issues related to time series. Readings: Brooks Ch. 4, see also book's slides

      http://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch4_slides.ppt

      Introduction to Stochastic processes and autocorrelation. Readings: Beginning of Ch. 5, see also book's slides

      http://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch5_slides.ppt

    • Introduction to Stochastic processes and autocorrelation. Readings: Ch. 5, see also book's slides

      http://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch5_slides.ppt


    • AR, MA and ARMA models. Calculation of autocovariance and autocorrelation. Readings: Ch. 5

      See also book's slides http://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch5_slides.ppt


    • Attached materials: meaning  of autocorrelation and partial autocorrelation for AR and MA processes and calculation using Yule-Walker equations.

      Readings: Brooks, Chapter 5. See also slides book's slides http://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch5_slides.ppt


    • Continued with the materials started last week: the meaning  of autocorrelation and partial autocorrelation for AR and MA processes and calculation using Yule-Walker equations.

      In addition: the concept of invertibility (specially for MA-prosesses); How to determine infinite order presentation for AR- (and MA)-prosesses using matching of coefficients (see e.g. Enders).  

      Readings: Brooks, Chapter 5. See also slides book's slides http://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch5_slides.ppt


    • Chapter 5: Box-Jenkins modelling. Autocorrelograms for AR, MA, and ARMA-models; ARIMA-models; Information criteria

      Chapter 7:  Spurious regression Introduction to Random Walk models and unit roots; forms of non-stationarity in practice.

      Readings: Brooks slides in the end of Chapter 5 and beginning of Chapter 7

      http://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch5_slides.ppt

      http://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch7_slides.ppt

    • Review of ARMA models and their representation using lag operator L

      Chapter 7:  Spurious regression, Random Walk models and unit roots; forms of non-stationarity in practice.

      https://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch7_slides.ppt

    • Chapter 7:  Order of integration,Unit root tests; Cointegration, cointegration tests. error correction models.

      see also https://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch7_slides.ppt


    • Unit root tests and Cointegration test, error correction model (not Johansen test)

      Brooks Chapter 7, See also book slides.

    • Introduction to Conditional Heteroscdedasticy models (ARCH, GARCH etc., Brooks, Chapter 8

      Idea of Maximum likelihood estimation (MLE)

      See also the book slides:

      https://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch8_slides.ppt


    • Forecasting with Conditional Heteroscdedasticy models (ARCH, GARCH etc., Brooks, Chapter 8)

      Seasonality and Dummy variables (Brooks, Chapter 9.3)

      Some clarifications and small corrections (shown in red) were added to the Dummy slides (attached) on 28.4.2019, 11:20 pm.

      Some remarks about estimation of ARMA and CH models (e.g. MLE,, Chapter 8)

      See also Brooks' slides

      https://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch8_slides.ppt

      https://www.cambridge.org/features/economics/brooks/downloads/PPT/Ch9_slides.ppt

    • Panel Data, Brooks, Chapter 10

      See also book slides

    • Review of the course topics and the exam.

      Overview of Topics covered in class and exercises (which are required in the exam); Corresponding parts in Brooks, 2nd ed.
      •Review Regression, Ch. 1-3 and 4
      •Advanced topics in regression, Ch.4
      • ARMA models and related concepts, Ch. 5
      •Nonstationarity Ch.7 up to p. 343. (7.1-7.6)
      •Conditional heteroscedasticity models, up to p. 414, Ch. 8.1.- 8.17
      •Seasonality and dummy variables, Ch 9.1-9.4.
      •Panel data: Fixed Effect models, Ch. 10.1.-10.4.

      Chapters 5 and 7 are the most important!