## Topic outline

• ### Materials

• 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:

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

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

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

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

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

• 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).

• 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

• 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.

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

• 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)

• 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)

• Panel Data, Brooks, Chapter 10