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 3001	ECONOMETRICS	COMPULSORY	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 provide an overall introduction to applications of econometric tools to economic measures. Emphasis is on the economic modeling, estimation techniques, and interpretation of empirical findings. The use of computer is an integrated part of the course. No prior knowledge of programming is required. 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, financial and social topics, and make them ready for statistical and econometric analysis.
2	Demonstrate understanding of building econometric models that describe the data generating process behind data.
3	Identify problems with existing econometric 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 4121 - THE POLITICAL ECONOMY OF INDUSTRIAL SOCIETY

Recomended Optional Programme Components

None

Course Contents

Week	Subject	Description
1	Math and Statistics Review
2	Intro to empirical models: Economic models vs. empirical models
3	Two variable regression models
4	Assumptions of Classical Linear Regression Model
5	Gauss Markov Theorem
6	Confidence Intervals and Hypothesis Testing
7	Multiple Linear Regression Models
8	Multicollinearity
9	Regression with Dummy variables
10	Heteroscedasticity
11	Autocorrelation
12	Omitted variable bias problem

Recomended or Required Reading

1. Gujarati, D. N. Basic Econometrics, 2 nd Ed. McGraw-Hill, 1988
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 econometric tools to engage independent research.
2. The learner will clearly recognize the problems with existing econometric models
3. The learner will build 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