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Information
| Code | IEM1805 |
| Name | Panel Data Analysis I |
| Term | 2023-2024 Academic Year |
| Term | Fall and Spring |
| Duration (T+A) | 4-0 (T-A) (17 Week) |
| ECTS | 8 ECTS |
| National Credit | 4 National Credit |
| Teaching Language | Türkçe |
| Level | Doktora Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. KENAN LOPCU |
| Course Instructor |
1 |
Course Goal / Objective
It is aimed that students learn the basic econometric methods of Panel Data Analysis and can use these methods with economic applications.
Course Content
This course is the first of two semesters designed to provide students with applications of panel data analysis and methods.
Course Precondition
No prerequisites
Resources
Hsiao, C. (2022). Analysis of panel data. Cambridge university press. Raj, B., & Baltagi, B. H. (Eds.). (2012). Panel data analysis. Springer Science & Business Media. Tatoğlu, F. Y. (2012). Panel veri ekonometrisi. Beta Yayınevi.
Notes
Related Articles
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | The student understands the basic concepts of Panel Data Analysis. |
| LO02 | Students understand the features of basic panel econometric models |
| LO03 | Students gain the ability to estimate basic panel econometric models. |
| LO04 | Students gain the ability to interpret the basic panel econometric models they predict economically. |
| LO05 | Students gain the ability to check for violations of panel estimators' assumptions. |
| LO06 | Students gain the ability to use methods and techniques to correct violations of panel estimators' assumptions. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Identify an econometric problem and propose a new solution to it | 3 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Develops new knowledge using current concepts in Econometrics, Statistics and Operations Research | 3 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Explain for what purpose and how econometric methods are applied to other fields and disciplines | 3 |
| PLO04 | Beceriler - Bilişsel, Uygulamalı | Using her knowledge, brings original solutions to problems in Economics, Business Administration and other social sciences | 3 |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Creates a new model using mathematics, statistics and econometrics knowledge to solve the problem encountered | 4 |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Interprets the results obtained from the most appropriate method to predict the model | 4 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Performs conceptual analysis to develop solutions to problems | 3 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Collects data on purpose | 4 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Synthesizes the information obtained by using different sources within the framework of academic rules in a field that does not research | 3 |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Presents analysis results conveniently | 4 |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Converts its findings into a master's thesis or a professional report in Turkish or a foreign language | 3 |
| PLO12 | Beceriler - Bilişsel, Uygulamalı | It researches current approaches and methods to solve the problems it encounters and proposes new solutions | 2 |
| PLO13 | Beceriler - Bilişsel, Uygulamalı | Develops long-term plans and strategies using econometric and statistical methods | 4 |
| PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Performs self-study using knowledge of Econometrics, Statistics and Operations to solve a problem | 4 |
| PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Leads the team by taking responsibility | 3 |
| PLO16 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the necessity of lifelong learning, it constantly renews itself by following the current developments in the field of study | 2 |
| PLO17 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses acquired knowledge in the field to determine the vision, aim, and goals for an organization/institution | 3 |
| PLO18 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses a package program of Econometrics, Statistics, and Operation Research or writes a new code | 4 |
| PLO19 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Interprets the feelings, thoughts and behaviors of the related persons correctly/expresses himself/herself correctly in written and verbal form | 3 |
| PLO20 | Yetkinlikler - Alana Özgü Yetkinlik | Applies social, scientific and professional ethical values | |
| PLO21 | Yetkinlikler - Alana Özgü Yetkinlik | Interprets data on economic and social events by following current issues | 3 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | The basic concept of panel data econometrics | Readings | Öğretim Yöntemleri: Anlatım, Tartışma |
| 2 | Panel data models 1 | Readings | Öğretim Yöntemleri: Anlatım, Tartışma |
| 3 | Panel data models 2 | Readings | Öğretim Yöntemleri: Anlatım, Tartışma |
| 4 | Estimation of panel data models | Reading and problem set | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 5 | Pooled Least Squares Method | Reading and problem set | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 6 | First Difference Estimator | Reading and problem set | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 7 | Within Estimator | Reading and problem set | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 8 | mid-term exam | Ölçme Yöntemleri: Ödev, Yazılı Sınav |
|
| 9 | Between Estimator | Readings and problem set | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 10 | The maximum likelihood estimator of the fixed effects model | Reading and problem set | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 11 | Random effects model | Readings and problem set | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 12 | Generalized least squares method | Readings and problem set | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 13 | Testing assumptions about panel data models | Reading and problem set | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 14 | Heterogeneity tests for panel data models | reading and problem set | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 15 | Cross-section dependency tests for panel data models | Reading and problem set | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 16 | Relaxing the assumptions about panel data models | Reading and problem set | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 17 | Final exam | Ölçme Yöntemleri: Yazılı Sınav, Ödev |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 4 | 56 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 8 | 112 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 2 | 4 | 8 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 12 | 12 |
| Final Exam | 1 | 24 | 24 |
| Total Workload (Hour) | 212 | ||
| Total Workload / 25 (h) | 8,48 | ||
| ECTS | 8 ECTS | ||