IEM1806 Panel Data Analysis II

8 ECTS - 4-0 Duration (T+A)- . Semester- 4 National Credit

Information

Unit INSTITUTE OF SOCIAL SCIENCES
ECONOMETRICS (PhD)
Code IEM1806
Name Panel Data Analysis II
Term 2024-2025 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
The current term course schedule has not been prepared yet.


Course Goal / Objective

It is aimed that the students have learned the basics of the Panel Data Analysis method and that they can use these methods for economic problems.

Course Content

This course comprehensively addresses the theoretical and practical aspects of panel data models. It primarily covers the structure of panel data, estimation methods for fixed and random effects models. Additionally, models with discrete, limited, and censored dependent variables (probit, logit, Tobit) are detailed. It includes testing assumptions and applications of robust estimators in cases of deviations from these assumptions.

Course Precondition

No prerequisites

Resources

Raj, B., & Baltagi, B. H. (Eds.). (2012). Panel data analysis. Springer Science & Business Media. Baltagi, B. H., & Baltagi, B. H. (2008). Econometric analysis of panel data (Vol. 4). Chichester: John Wiley & Sons. Tatoğlu, F. Y. (2012). İleri panel veri analizi: Stata uygulamalı. İstanbul: Beta Yayınları..

Notes

Related Articles and data sets


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Explain the fundamental aspects of the Panel Data Analaysis
LO02 Estimates basic panel data models
LO03 Students explain basic panel econometric methods related to discrete and limited dependent variables.
LO04 Estimates basic panel models of discrete dependent variables
LO05 Interpret estimated panel data models economically.
LO06 Estimates basic panel models of limited dependent variables
LO07 Censored panel data estimates models of dependent variables
LO08 Estimates panel multinomial models


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 2
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 of 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
PLO12 Beceriler - Bilişsel, Uygulamalı It researches current approaches and methods to solve the problems it encounters and proposes new solutions
PLO13 Beceriler - Bilişsel, Uygulamalı Develops long-term plans and strategies using econometric and statistical methods 2
PLO14 Beceriler - Bilişsel, Uygulamalı Uses a package program/writes a new code for Econometrics, Statistics, and Operation Research 4
PLO15 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Performs self-study using knowledge of Econometrics, Statistics and Operations to solve a problem
PLO16 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Leads the team by taking responsibility
PLO17 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 3
PLO18 Yetkinlikler - İletişim ve Sosyal Yetkinlik Uses acquired knowledge in the field to determine the vision, aim, and goals for an organization/institution 3
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 Basic concepts of discrete and bounded dependent variable models 1 Reading the relevant sections from the source books on basic concepts related to Discrete and Limited Dependent Variable models Öğretim Yöntemleri:
Anlatım
2 Basic concepts of discrete and bounded dependent variable models 2 Reading the relevant section from the source books on basic concepts related to Discrete and Limited Dependent Variable models Öğretim Yöntemleri:
Anlatım, Soru-Cevap
3 Basic concepts of censored models Reading the relevant section from the source books on basic concepts related to censored models Öğretim Yöntemleri:
Anlatım, Tartışma
4 Panel Logit Model Reading the relevant section from the source books on Panel Logit Model Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
5 Estimation of Panel Logit Model Reading the relevant section from the source books on Estimation of Panel Logit Model and Problem Set Öğretim Yöntemleri:
Anlatım, Gösterip Yaptırma
6 Panel Probit Model Reading the relevant section from the source books on Panel Probit Model Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama, Soru-Cevap
7 Estimation of the Panel Probit Model Reading the relevant section from the source books on Estimation of Panel Probit Model and Problem set Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama, Problem Çözme
8 Mid-term exam reviewing the topics Ölçme Yöntemleri:
Yazılı Sınav, Ödev
9 Panel Data Discrete Regression Model Reading the relevant section from the source books on Panel Data Discrete Regression Model Öğretim Yöntemleri:
Anlatım, Gösterip Yaptırma
10 Panel Tobit Model Reading the relevant section from the source books on the Panel Tobit Model Öğretim Yöntemleri:
Anlatım, Tartışma
11 Estimation of the Panel Tobit Model Panel Tobit Modelinin Tahmini ile ilgili kaynak kitaplardan ilgili bölümü okuma and problem set Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama, Problem Çözme
12 Panel Count Models Reading the relevant section from the source books on Panel Count Models Öğretim Yöntemleri:
Anlatım, Tartışma
13 Estimation of Panel Count Models Reading the relevant section from the source books on Estimation of Panel Counting Models and dataset research Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama
14 Panel Multinomial Models Reading the relevant section from the source books on Panel Multi-State Models Öğretim Yöntemleri:
Anlatım, Tartışma
15 Estimation of Panel Multinomial Models Reading the relevant section from the source books on Estimation of Panel Multi-State Models Öğretim Yöntemleri:
Anlatım, Alıştırma ve Uygulama, Proje Temelli Öğrenme
16 Final homework general repetition and data set finding(Düzenlendi)Orijinali geri yükle Ölçme Yöntemleri:
Ödev
17 Final exam reviewing the topics Ölçme Yöntemleri:
Ödev, Yazılı Sınav


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

Update Time: 27.02.2025 06:53