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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
EKO 637TIME SERIES ANALYSIS II3 + 02nd Semester10

COURSE DESCRIPTION
Course Level Doctorate Degree
Course Type Elective
Course Objective The aim of this lecture is to analyze theoretical modelling techniques of time series, to show the application of the theoretical models using software program (STATA and Eviews) and to assessment empirical works that have been reference in the literature regarding the models discussed in the class.
Course Content The lectures include the following subjects: Non-stationarity and ARIMA (p,d,q) Processes; Seasonal ARMA (p, q) Processes; Unit Root Tests; Structural Breaks; Vector Autoregressions (VAR); Structural Vector Autoregressions (SVAR); Cointegration; Vector Error Correction Models(VECMs); ARCH, GARCH and Time-Varying Variance; Nonlinear Models and Breaks.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES

COURSE'S CONTRIBUTION TO PROGRAM
Data not found.

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)14684
Assignments51365
Mid-terms13030
Final examination13939
Total Work Load

ECTS Credit of the Course






260

10
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2022-2023 Spring1MEHMET İVRENDİ
Details 2020-2021 Spring1MEHMET İVRENDİ


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
EKO 637 TIME SERIES ANALYSIS II 3 + 0 1 Turkish 2022-2023 Spring
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Prof. Dr. MEHMET İVRENDİ mivrendi@pau.edu.tr İİBF A0202 %80
Goals The aim of this lecture is to analyze theoretical modelling techniques of time series, to show the application of the theoretical models using software program (STATA and Eviews) and to assessment empirical works that have been reference in the literature regarding the models discussed in the class.
Content The lectures include the following subjects: Non-stationarity and ARIMA (p,d,q) Processes; Seasonal ARMA (p, q) Processes; Unit Root Tests; Structural Breaks; Vector Autoregressions (VAR); Structural Vector Autoregressions (SVAR); Cointegration; Vector Error Correction Models(VECMs); ARCH, GARCH and Time-Varying Variance; Nonlinear Models and Breaks.
Topics
WeeksTopics
1 Introduction and Basics, The Lag Operator , Ergodicity and Stationarity and The Wold Decomposition
2 Univariate Stationary Processes: AR(p), MA(q) and ARMA(p,q) processes and Forecasting
3 Granger Causality, Causality Tests, Applying Causality Tests in a Multivariate Setting
4 Vector Autoregressive Processes(VAR): Representation of the System, Granger Causality, Impulse Response Analysis and Variance Decomposition
5 Vector Autoregressive Processes(VAR): Representation of the System, Granger Causality, Impulse Response Analysis and Variance Decomposition
6 Nonstationary Processes: Forms of Nonstationarity, Trend Elimination, Unit Root Tests
7 Decomposition of Time Series, Fractional Integration, Seasonal Integration , Deterministic versus Stochastic Trends in Economic Time Series
8
9 Cointegration: Cointegration in Single Equation Models, Representation, Estimation and Testing
10 Cointegration in Vector Autoregressive Models: The Vector Error Correction Representation ,The Johansen Approach , Analysis of Vector Error Correction Models
11 Nonstationary Panel Data: Issues with Panel Data, Panel Unit Root Tests,
12 Panel Cointegration: Single Equation Approaches and System Approaches
13 Autoregressive Conditional Heteroscedasticity: ARCH Models and GARCH Models
14 Autoregressive Conditional Heteroscedasticity: Estimation and Testing and Multivariate Models , ARCH/GARCH Models as Instruments of Financial Market Analysis
Materials
Materials are not specified.
Resources
ResourcesResources Language
G. Kirchgässner, J. Wolters and U. Hassler(2013) Introduction to Modern Time Series Analysis, Second edition, Springer English
W. Enders ( 2015) -Applied Econometric Time Series- Fourth Edition, WileyEnglish
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam50Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes