COURSE UNIT TITLE

Offered By

Master`s Degree in Financial Economics (Non-Thesis-Evening)

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR SAADET KASMAN

Offered to

Master`s Degree in Financial Economics (Non-Thesis-Evening)

Course Objective

The aim of this course is to provide the basic tools of statistics, optimization and econometrics useful for analyzing data, with specific application to problems of economics and finance. It is meant to equip the students with the quantitative skills they need in economics and finance. Introduction to quantitative techniques widely used by economists; various methods of applied statistics that facilitate the understanding of economic and finance literature; elements of probability, correlation, multiple regression and hypothesis testing; manipulating and interpreting economic data are a list of topics analyzed.

Learning Outcomes of the Course Unit

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

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. Assignments

Assessment Methods

Further Notes About Assessment Methods

None

Assessment Criteria

1. The learner will clearly define basic quantitative methods used in economic modeling.
2. The learner will use necessary optimization methods to solve economic problems.
3. The learner will clearly recognize the problems with existing econometric models.
4. The learner will build econometric models for estimation purposes.
5. The learner will interpret empirical results and draw policy implications.

Language of Instruction

English

Course Policies and Rules

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

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes