Dokuz Eylül University Information Package / Courses Catalog

Description of Individual Course Units

Course Unit Code	Course Unit Title	Type Of Course	D	U	L	ECTS
UEC 4511	TIME SERIES ECONOMETRICS	ELECTIVE	3	0	0	6

Offered By

ECONOMICS (UOLP-SUNY ALBANY)

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ERDOST TORUN

Offered to

ECONOMICS (UOLP-SUNY ALBANY)

Course Objective

The objective of the course is to skills for dealing with univariate and multivariate time series modeling of economic and financial data. Stationary and nonstationary time series with unit roots, AR, MA, ARMA and ARIMA models, cointegration, error correction models, VAR and causality are the main topics to be covered.. The use of computer is an integrated part of the course. Students are expected to prepare a term project to demonstrate their skills developed in the course.

Learning Outcomes of the Course Unit

1	Be able to collect raw data related to economic and financial, and make them ready for statistical and econometric analysis.
2	Demonstrate understanding of building time series models that describe the data generating process behind data.
3	Identify problems with existing time series models so that the learner could employ appropriate econometric tools to solve the problem.
4	Be able to interpret the estimation results so that the learner can draw implications from the results.
5	.Demonstrate engaging an independent empirical research in order to prepare a tem project.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

UEC 3001 - ECONOMETRICS

Recomended Optional Programme Components

None

Course Contents

Week	Subject	Description
1	Math and Statistics Review
2	Time Series and their characteristics
3	Linear time series analysis and its application
4	Linear time series analysis and its application
5	Conditional heteroscedastic models
6	Conditional heteroscedastic models
7	Conditional heteroscedastic models
8	Multivariate time series analysis and its applications
9	Multivariate time series analysis and its applications
10	Multivariate time series analysis and its applications
11	Multivariate volatility models and their applications
12	Multivariate volatility models and their applications

Recomended or Required Reading

1.Ruey S. Tsay, Analysis of Financial Time Series, 2 nd Ed. Willey, 2005
2.Lecture Notes

Planned Learning Activities and Teaching Methods

1.Lectures
2.Class Discussions
3.Term Project

Assessment Methods

SORTING NUMBER	SHORT CODE	LONG CODE	FORMULA
1	MT	Midterm
2	TP	TermProject
3	FN	Final
4	FCG	FINAL COURSE GRADE	MT * 0.30 +TP * 0.30 + FN * 0.40
5	RST	RESIT
6	FCGR	FINAL COURSE GRADE (RESIT)	MT * 0.30 +TP * 0.30 + RST * 0.40

*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

1.Midterm
2.Final
3.Term Project

Assessment Criteria

1.The learner will use necessary statistical and time series econometric tools to engage independent research.
2.The learner will clearly recognize the problems with existing econometric models
3.The learner will build time series econometric models for estimation purposes
4.The learner will interpret empirical results
5.The learner will draw some policy implications from estimation results

Language of Instruction

English

Course Policies and Rules

1. Attending at least 70 percent of lectures is mandatory.
2. Plagiarism of any type will result in disciplinary action.

Contact Details for the Lecturer(s)

To be announced.

Office Hours