COURSE UNIT TITLE

: ECONOMETRICS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
ECO 3001 ECONOMETRICS COMPULSORY 3 0 0 6

Offered By

Economics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

Offered to

Economics

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 able to make sound econometric analysis.


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   Be able to make econometric analysis

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

ECON 203 - MONEY AND BANKING

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

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MT Midterm
2 FN Final
3 FCG FINAL COURSE GRADE MT * 0.40 + FN * 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MT * 0.40 + RST * 0.60


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

Further Notes About Assessment Methods

1. Midterm
2. Final

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

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Tutorials 12 1 12
Preparations before/after weekly lectures 12 1 12
Preparation for midterm exam 1 40 40
Preparation for final exam 1 40 40
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 144

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.15455
LO.254455
LO.3555
LO.445
LO.55