COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Time Series Models II * ECMZ   406 8 3 3 4

Prerequisites and co-requisites
Recommended Optional Programme Components None

Language of Instruction English
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Asst.Prof.Dr. Fela ÖZBEY
Instructors
Dr. Öğr. ÜyesiFELA ÖZBEY1. Öğretim Grup:A
 
Assistants
Goals
The aim of this course is to give the students a good theoretical and empirical understanding of statistical methods used in multivariate time series analysis.
Content
This course involves the study of stochastic and deterministic trends,Unit root tests, VAR models, determination of the maximal lag of the system, Granger Causality, error correction represantation, cointegration, Engle-Granger cointegration test, Johansen cointegration test, ARDL models, bounds test.

Learning Outcomes
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Explains Econometric concepts
2
Acquires basic Mathematics, Statistics and Operation Research concepts
3
Equipped with the foundations of Economics, and develops Economic models
4
Describes the necessary concepts of Business
5
Models problems with Mathematics, Statistics, and Econometrics
6
Estimates the model consistently and analyzes & interprets its results
7
Acquires the ability to analyze, benchmark, evaluate and interpret at conceptual levels to develop solutions to problems
8
Collects, edits, and analyzes data
9
Uses a package program of Econometrics, Statistics, and Operation Research
10
Effectively works, take responsibility, and the leadership individually or as a member of a team
11
Awareness towards life-long learning and follow-up of the new information and knowledge in the field of study
12
Develops the ability of using different resources in the form of academic rules, synthesis the information gathered, and effective presentation in an area which has not been studied
13
Uses Turkish and at least one other foreign language, academically and in the business context
14
Good understanding, interpretation, efficient written and oral expression of the people involved
15
Improves his/herself constantly by defining educational requirements considering interests and talents in scientific, cultural, art and social fields besides career development
16
Questions traditional approaches and their implementation while developing alternative study programs when required
17
Recognizes and implements social, scientific, and professional ethic values
18
Follows actuality, and interprets the data about economic and social events

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Nonstationary Processes - Forms of Nonstationarity, Trend Elimination Students will be prepared by studying relevant subjects from source books according to the weekly program
2 Nonstationary Processes - Dickey-Fuller Tests Students will be prepared by studying relevant subjects from source books according to the weekly program
3 Nonstationary Processes - The Phillips-Perron Test, Unit Root Tests and Structural Breaks, KPSS test Students will be prepared by studying relevant subjects from source books according to the weekly program
4 Vector Autoregressive Processes: Stationarity conditions and MA Represantation of the System Students will be prepared by studying relevant subjects from source books according to the weekly program
5 Vector Autoregressive Processes - Error Correction Represantation, , FPE, AIC, BIC, HQ criteria Students will be prepared by studying relevant subjects from source books according to the weekly program
6 Vector Autoregressive Processes - Granger Causality, Impulse Response Analysis Students will be prepared by studying relevant subjects from source books according to the weekly program
7 Vector Autoregressive Processes - Variance Decomposition Students will be prepared by studying relevant subjects from source books according to the weekly program
8 Midterm Exam Students will be prepared by studying relevant subjects from source books according to the weekly program
9 Cointegration - Definition and Properties of Cointegrated Processes Students will be prepared by studying relevant subjects from source books according to the weekly program
10 Cointegration - Cointegration in Single Equation Models: Represantation, Estimation and Testing Students will be prepared by studying relevant subjects from source books according to the weekly program
11 Cointegration - Cointegration in Vector Autoregressive Models: The Vector Error Correction Representation, The Johansen Approach Students will be prepared by studying relevant subjects from source books according to the weekly program
12 Cointegration - Cointegration in Vector Autoregressive Models: Analysis of Vector Error Correction Models, Cointegration and Economic Theory Students will be prepared by studying relevant subjects from source books according to the weekly program
13 ARDL models, static and dynamic equilibrium Students will be prepared by studying relevant subjects from source books according to the weekly program
14 Bounds test Students will be prepared by studying relevant subjects from source books according to the weekly program
15 An overview Students will be prepared by studying relevant subjects from source books according to the weekly program
16-17 Final exam Students will be prepared by studying relevant subjects from source books according to the weekly program

Recommended or Required Reading
Textbook
Additional Resources