At the end of this course, the students; 1) Explain the limitations of the regression model and possible remedies. 2) Use appropriate econometric tools to detect basic econometric problems in the regression model. 3) Test the validity of different models by using appropriate econometric tools. 4) Examine extensions to the basic regression model which address special features of different data structures. 5) Performs and interprets econometric analysis using a software package.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
This course is a continuation of the Econometrics I course. Multicollinearity, heteroscedasticity, autocorrelation, econometric modeling, dynamic econometric models, time series econometrics and qualitative responsive regression models are discussed.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Multicollinearity
2nd Week
Multicollinearity Continued
3rd Week
Heteroscedasticity
4th Week
Heteroscedasticity Continued
5th Week
Autocorrelation
6th Week
Autocorrelation Continued
7th Week
Econometric Modeling
8th Week
Midterm
9th Week
Econometric Modeling Continued
10th Week
Dynamic Econometric Models
11th Week
Time Series Econometrics
12th Week
Time Series Econometrics Continued
13th Week
Qualitative Responsive Regression Models
14th Week
Qualitative Responsive Regression Models Continued
RECOMENDED OR REQUIRED READING
Damodar N. Gujarati ve Dawn C. Porter, Temel Ekonometri, 5. Basımdan çeviri. Çev: Ümit Şenesen ve Gülay Günlük Şenesen. Literatür Yayınları, İstanbul. Lee C. Adkins and R. Carter Hill, Using Stata for Principles of Econometrics, 4th Edition. John Wiley & Sons, Inc. Jeffrey M. Wooldridge, Ekonometriye Giriş 1-Modern Yaklaşım, 4. Basımdan çeviri. Çeviri Editörü: Prof. Dr. Ebru Çağlayan Akay. Nobel Akademik Yayıncılık. Jeffrey M. Wooldridge, Ekonometriye Giriş 2-Modern Yaklaşım, 4. Basımdan çeviri. Çeviri Editörü: Prof. Dr. Ebru Çağlayan Akay. Nobel Akademik Yayıncılık.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Lecture,Discussion,Problem Solving,Practice
ASSESSMENT METHODS AND CRITERIA
Quantity
Percentage(%)
Mid-term
1
40
Quiz
2
15
Total(%)
55
Contribution of In-term Studies to Overall Grade(%)
55
Contribution of Final Examination to Overall Grade(%)
45
Total(%)
100
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
1,5
1,5
Preparation for Quiz
2
10
20
Individual or group work
14
3
42
Preparation for Final exam
1
25
25
Course hours
14
3
42
Preparation for Midterm exam
1
20
20
Laboratory (including preparation)
0
0
0
Final exam
1
1,5
1,5
Homework
0
0
0
Total Workload
152
Total Workload / 30
5,06
ECTS Credits of the Course
5
LANGUAGE OF INSTRUCTION
Turkish
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)