Week

Topic

1-2

Introduction to time series

*LK, Chapter 1
*P, Chapter 2
Lecture Notes & Slides 1: Examples of Time Series, Basic Concepts, Trend, Moving Averages, Classical Decomposition

EViews Tutorial on calculating growth rates and estimating deterministic trends: PDF tutorial file, Data file (GDP, Turkey, 88:Q1-05:Q2)

3-4

ARMA models

 ‡P, Section 3.4
*LK, Section 2.1-2.6, 2.8-2.10
‡C, Chapter 3-6
‡H, Chapters 1-3, 5

Lecture Notes & Slides 1: ARIMA Models: Properties, ARIMA Models: Identification

ARMA model identification, estimation, and diagnostic check using EVievs: PDF Tutorial file, Data file (change in quarterly business inventories, 1955.Q1-1969.Q4)

5-6

ARMA Models (continued): Diagnostic check, forecasting

*LK, Section 2.1-2.6, 2.8-2.10

*Lecture notes:
Foreacasting in ARIMA Models
Forecast Accuracy
Diebold-Mariano Statistics for Forecast Accuracy

Classical decomposition, X11/X12 seasonal filters

*Lecture notes:
Lecture notes on classical decomposition
Lecture notes on seasonal dummy model and X12 deseasonalization


EViews Tutorial on modeling and forecasting: PDF tutorial file, Data file (GDP, Turkey, 88:Q1-05:Q2) 

7-8

Long-memory (fractionally integrated) models

         *Lecture notes

 Tests for structural breaks

         *LK, Chapter 1

9

MIDTERM EXAM

10

Random walks and unit root testing 

          *P, Chapter 6, Section 7.6-7.8
          ‡LK, Section 2.7
          ‡C, Chapter 10
          ‡H, Chapters 15, 17

ARIMA Models: Properties,  (read pp. 5-14)
AR(p) Companion form and dynamic multipliers
ADF Test Procedure

11

Random walks and unit root testing (continued)

Trend/cycle decomposition 

* Lecture notes.

12

**ARCH/GARCH

           *P, Chapter 16
           ‡LK, Chapter 5
           ‡H, Chapter 21
           Slides (by Chris Brooks)

13

VAR, impulse-response functions, variance decomposition 

‡P, Chapter 14.2
*LK, Chapter 3
‡C, Chapter 7
‡H, Chapter 11
Slides (by Chris Brooks)
Lecture Notes 1
Lecture Notes 2
Lecture Notes 3

14

Granger causality

        *LK, Chapter 3.7
        ‡C, Chapter 7.5
        ‡H, Chapter 11.2

Spurious regressions

 *P, Chapter 8.2
‡H, Chapters 18.3

15

Cointegration

        *P, Chapter 8,14
        ‡LK, Chapter 3
        ‡C, Chapter 11
        ‡H, Chapter 19
        Slides by Chris Brooks
        Lecture Notes 1
        Lecture Notes 2

16

Final Exam