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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EKO 5065 ECONOMETRIC TIME SERIES ANALYSIS I ELECTIVE 3 0 0 5

Offered By

Econometrics

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR ŞENAY ÜÇDOĞRUK BIRECIKLI

Offered to

Econometrics

Course Objective

It provides knowledge of time series techniques and the applications time series analysis and estimation.

Learning Outcomes of the Course Unit

1   To be able to define time series analyis. 2   To be able to detect and resolve seasonal fluctuations. 3   To be able to apply appropriate methods for time series. 4   To be able to estimate future and interpret the results by using economic time series data. 5   To be able to modelling time series encountering in public and private sector and to do statistical implications of these models.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Basic Concepts, Introduction 2 Time Series Forms 3 Time Series Processes 4 Analysis of Time Series with Difference Equations 5 Linear Time Series Models 6 Linear Time Series Models More 7 The Applications of Linear Time Series Models 8 Mid-term 9 Stationary Probability Processes 10 Testing for Stationarity with Unit Root, Unit Root Tests 11 Unit Root Tests in case of breakage, Seasonal Unit Roots 12 Stationary of Tendency and Difference Stationary Processes, Spurious Regression, Cointegration 13 Stationary Analysis: Structural Break Test 14 Stationary Analysis: Structural Break Test More

Recomended or Required Reading

1- Hamilton, J., Time Series Analysis, 1994. 2- Enders, W., Applied Econometric Time Series, John Wiley, 2004. 3- Franses, P.H., Time Series Models for Business and Economic Forecasting, Camb. Uni. Press, 1998. 4- Patterson, K., Introduction to Econometrics, A Time series Approach, 2001 5- Chatfield, C., The Analysis of Time Series, An Introduction, 5th ed., 1995. 6- Reinsel, G.C., Elements of Multivariate Time Series Analysis, 2003. 7- Lutkepohl, H., Introduction to Multiple Time Series Analysis, 1993.

Planned Learning Activities and Teaching Methods

Discussing, Problem solving, Lecture Method, Question-Answer Method

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 STT TERM WORK (SEMESTER) 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.30 + FIN* 0.40 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Preparation for midterm exam 1 30 30 Preparation for final exam 1 30 30 Preparations before/after weekly lectures 13 2 26 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 131

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 LO.1 1 1 1 LO.2 1 1 1 LO.3 1 1 1 LO.4 1 1 1 LO.5 1 1 1