COURSE UNIT TITLE

: ECONOMETRICS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
ECN 5061 ECONOMETRICS COMPULSORY 3 0 0 7

Offered By

Economics (English)

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR SAADET KASMAN

Offered to

Economics (English)

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

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Math and Statistics Review
2 Intro to empirical models
3 Two-variable regression models
4 Assumptions of Classical Linear Regression Model
5 Confidence intervals and hypothesis testing
6 Multiple Linear Regression Models
7 Midterm
8 Multicollinearity
9 Regression with dummy variables
10 Heteroscedasticity and Autocorrelation
11 Simultaneous Equations
12 Limited Dependent Variables
13 Introduction to the Time series models
14 General Overview

Recomended or Required Reading

1. Gujarati, D. N. Basic Econometrics, 2nd 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 MTE MIDTERM EXAM
2 FCG FINAL COURSE GRADE
3 FCGR FINAL COURSE GRADE MTE * 0.40 + FCG* 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + RST* 0.60


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

Further Notes About Assessment Methods

None

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

It is obligatory to attend at least 70% of the classes.

Contact Details for the Lecturer(s)

adnan.kasman@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Tutorials 13 2 26
Preparations before/after weekly lectures 13 1 13
Preparation for midterm exam 1 30 30
Preparation for final exam 1 35 35
Preparing assignments 1 25 25
Midterm 1 2 2
Final 1 2 2
TOTAL WORKLOAD (hours) 172

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.154
LO.245
LO.344
LO.4554
LO.5445

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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