| Semester | Course Unit Code | Course Unit Title | T+P+L | Credit | Number of ECTS Credits |
| 5 | ECON301 | ECONOMETRICS I | 3+0+0 | 3 | 5 |
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Language of Instruction
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English
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Level of Course Unit
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Bachelor's Degree
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Department / Program
|
ECONOMICS
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Type of Program
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Formal Education
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Type of Course Unit
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Compulsory
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Course Delivery Method
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Face To Face
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Objectives of the Course
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Introducing hypothesis testing, estimation and inference.
Showing how to analyze and test economic theory with empirical data.
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Course Content
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Statistics and econometrics knowledge that is necessary to understand and conduct econometric analysis is developed throughout the course at advanced undergraduate level. Simple and multiple linear regression models are examined in detail with related subjects such as dummy variables, omitted variable bias, interpretation of partial regression coefficients, model evaluation and goodness of fit criteria. In addition, classical assumptions of linear regression models are tested and examined.
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Course Methods and Techniques
|
-
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Prerequisites and co-requisities
|
( ECON205 )
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Course Coordinator
|
None
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Name of Lecturers
|
Asist Prof.Dr. Eda Ustaoğlu eda.ustaoglu@agu.edu.tr
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Assistants
|
Research Assist. Gülcan Doğanay gulcan.doganay@agu.edu.tr
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Work Placement(s)
|
No
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Recommended or Required Reading
Course Category
|
Mathematics and Basic Sciences
|
%30
|
|
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Social Sciences
|
%70
|
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Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"
Assessment Methods and Criteria
|
In-Term Studies
|
|
Yarıyıl İçi Çalışmalarının Başarı Notunun Katkısı
|
4
|
%
40
|
|
Yarıl yılSonu Sınavı/Dönem Projesinin Başarı Notuna Katkısı
|
1
|
%
30
|
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Final examination
|
1
|
%
30
|
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Total
|
6
|
%
100
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ECTS Allocated Based on Student Workload
|
Activities
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Total Work Load
|
|
Ev Ödevi
|
7
|
3
|
21
|
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Sınıf İçi Aktivitesi
|
14
|
3
|
42
|
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Okuma
|
14
|
3
|
42
|
|
Araştırma
|
14
|
3
|
42
|
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Final Sınavı
|
1
|
2
|
2
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Total Work Load
| |
|
Number of ECTS Credits 5
149
|
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
| No | Learning Outcomes |
|
1
| Test economic hypotheses and check significance properties. |
|
2
| Construct a novel econometric model and test overall performance of the model. |
|
3
| Calculate simple and partial correlations between variables within a model. |
|
4
| Choose appropriate functional form in regression models. |
Weekly Detailed Course Contents
| Week | Topics | Study Materials | Materials |
| 1 |
Introduction to Econometrics and the Nature of Economic Data
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| 2 |
Review of Probability and Statistics Essentials
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| 3 |
The Simple Linear Regression Model (SLRM)
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| 4 |
Properties of OLS Estimators
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| 5 |
Hypothesis Testing in SLRM
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| 6 |
Goodness of Fit and Model Evaluation
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| 7 |
Multiple Linear Regression Model (MLRM)
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| 8 |
Midterm Exam
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|
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| 9 |
Multicollinearity and Omitted Variable Bias
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| 10 |
Dummy Variables and Interaction Terms
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| 11 |
Functional Form and Model Specification
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| 12 |
Heteroskedasticity
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| 13 |
Autocorrelation (Brief Introduction)
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| 14 |
Review
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Recommended Optional Programme Components
Contribution of Learning Outcomes to Programme Outcomes
Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant
https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=70492&lang=en