At the end of this course, the students; 1) Use advanced econometric analysis techniques in the analysis of economic problems. 2) Examine the econometric models used specific to different data types. 3) Apply different econometric analysis methods through the Stata package program.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
In this course, instrumental variables, simultaneous equation models, binary outcome models, Tobit model, count data modeling and panel data models are discussed.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Introduction to Stata
2nd Week
Creating variables, drawing summary statistics and plotting of data in Stata
3rd Week
Multiple Regression Analysis Stata Applications
4th Week
Instrumental Variables
5th Week
Applications with Instrumental Variables
6th Week
Simultaneous Equation Models
7th Week
Applications with Simultaneous Equation Models
8th Week
Midterm
9th Week
Applications with Binary Outcome Models
10th Week
The Tobit Model and Sample Selection Corrections
11th Week
Applications with The Tobit Model and Sample Selection Corrections
12th Week
Count Data Modeling
13th Week
Panel Data Regression Models
14th Week
Applications with Panel Data Regression Models
RECOMENDED OR REQUIRED READING
Damodar N. Gujarati and Dawn C. Porter, Basic Econometrics, 5th Edition. McGraw-Hill/Irwin. Jeffrey M. Wooldridge, Introductory Econometrics: Modern Approach, 5th Edition. South-Western, Cengage Learning. Lee C. Adkins and R. Carter Hill, Using Stata for Principles of Econometrics, 4th Edition. John Wiley & Sons, Inc. R. Carter Hill, William E. Griffiths and Guay C. Lim, Principles of Econometrics, 4th Edition. John Wiley & Sons, Inc.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Lecture,Discussion,Problem Solving
ASSESSMENT METHODS AND CRITERIA
Quantity
Percentage(%)
Mid-term
1
40
Assignment
1
10
Total(%)
50
Contribution of In-term Studies to Overall Grade(%)
50
Contribution of Final Examination to Overall Grade(%)
50
Total(%)
100
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
1,5
1,5
Preparation for Quiz
0
0
0
Individual or group work
14
3
42
Preparation for Final exam
1
30
30
Course hours
14
2
28
Preparation for Midterm exam
1
25
25
Laboratory (including preparation)
14
1
14
Final exam
1
1,5
1,5
Homework
1
5
5
Total Workload
147
Total Workload / 30
4,9
ECTS Credits of the Course
5
LANGUAGE OF INSTRUCTION
English
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
