Information
Code | IEM721 |
Name | Limited Dependent Variable Models I |
Term | 2024-2025 Academic Year |
Term | Fall and Spring |
Duration (T+A) | 3-0 (T-A) (17 Week) |
ECTS | 6 ECTS |
National Credit | 3 National Credit |
Teaching Language | Türkçe |
Level | Yüksek Lisans Dersi |
Type | Normal |
Mode of study | Yüz Yüze Öğretim |
Catalog Information Coordinator | Prof. Dr. SEDA ŞENGÜL |
Course Instructor |
Prof. Dr. SEDA ŞENGÜL
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
The aim of this course is to teach the regression models that are appropriate when the dependent variable is binary, ordinal, nominal , count, censored and truncated, to apply the regression models that are appropriate when the dependent variable is censored, truncated, binary, ordinal, nominal or count and to interpret the result obtaine
Course Content
the contents of this course are the structure of data set for using limited dependent variable models, the advantage of limited dependent variable models and the models like linear probability models, binary probit and binary logit models, ordered probit and ordered logit models, orderd probit and orderd logit models, multinomial probit and multinominal logit models, etc.
Course Precondition
No prerequisites are required.
Resources
D. Gujarati "Introduction to econometrics"
Notes
Lectures
Course Learning Outcomes
Order | Course Learning Outcomes |
---|---|
LO01 | Student understands the structure of the data used in limited dependent variables models. |
LO02 | Students acquire the regression models that are appropriate when the dependent variable is censored, truncated, binary, ordinal, nominal or count. |
LO03 | Students apply the regression models that are appropriate when the dependent variable is censored, truncated, binary, ordinal, nominal or count. |
LO04 | Students make applications related to limited dependent models. |
LO05 | Students interpret the results of the analysis on limited dependent models. |
Relation with Program Learning Outcome
Order | Type | Program Learning Outcomes | Level |
---|---|---|---|
PLO01 | Bilgi - Kuramsal, Olgusal | Explains contemporary concepts about Econometrics, Statistics, and Operation Research | 4 |
PLO02 | Bilgi - Kuramsal, Olgusal | Explains relationships between acquired knowledge about Econometrics, Statistics, and Operation Research | 3 |
PLO03 | Bilgi - Kuramsal, Olgusal | Explains how to apply acquired knowledge in the field to Economics, Business, and other social sciences | 2 |
PLO04 | Beceriler - Bilişsel, Uygulamalı | Performs conceptual analysis to develop solutions to problems | 2 |
PLO05 | Beceriler - Bilişsel, Uygulamalı | Models problems with Mathematics, Statistics, and Econometrics | 4 |
PLO06 | Beceriler - Bilişsel, Uygulamalı | Interprets the results obtained from the most appropriate method to predict the model | 5 |
PLO07 | Beceriler - Bilişsel, Uygulamalı | Synthesizes the information obtained by using different sources within the framework of academic rules in a field that does not research | 4 |
PLO08 | Beceriler - Bilişsel, Uygulamalı | Uses acquired knowledge in the field to determine the vision, aim, and goals for an organization/institution | 2 |
PLO09 | Beceriler - Bilişsel, Uygulamalı | Searches for new approaches and methods to solve problems being faced | 3 |
PLO10 | Beceriler - Bilişsel, Uygulamalı | Presents analysis results conveniently | 1 |
PLO11 | Beceriler - Bilişsel, Uygulamalı | Collects/analyzes data in a purposeful way | 1 |
PLO12 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Converts its findings into a master's thesis or a professional report in Turkish or a foreign language | 2 |
PLO13 | Beceriler - Bilişsel, Uygulamalı | Develops solutions for organizations using Econometrics, Statistics, and Operation Research | 3 |
PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Performs an individual work to solve a problem with Econometrics, Statistics, and Operation Research | 4 |
PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Leads by taking responsibility individually and/or within the team | 4 |
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 | 3 |
PLO17 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses a package program of Econometrics, Statistics, and Operation Research or writes a new code | |
PLO18 | 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 | |
PLO19 | Yetkinlikler - Alana Özgü Yetkinlik | Interprets data on economic and social events by following current issues | |
PLO20 | Yetkinlikler - Alana Özgü Yetkinlik | Applies social, scientific and professional ethical values |
Week Plan
Week | Topic | Preparation | Methods |
---|---|---|---|
1 | Data structure in Limited Dependent Variable Models | Reading related sources | Öğretim Yöntemleri: Anlatım |
2 | Limited Dependent Variable Models and OLS | Reading related sources | Öğretim Yöntemleri: Anlatım |
3 | Linear probability model, Binary Probit and Binary Logit | Reading related sources | Öğretim Yöntemleri: Anlatım |
4 | Linear probability model, Binary Probit and Binary Logi | Reading related sources and preparing the data set | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
5 | Linear probability model, Binary Probit and Binary Logit (II) | Reading related sources, problem set and application | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
6 | Ordered Probit and ordered Logit Models | Reading related sources | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
7 | Ordered Probit and ordered Logit Models (II) | Reading related sources, problem set and application | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
8 | Mid-Term Exam | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
|
9 | Multinominal Probit model and Multinominal Logit Model | Reading related sources | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
10 | Multinominal Probit model and Multinominal Logit Model (II) | Reading related sources, problem set and application | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
11 | Sequantial Probit and Sequential Logit Models | Reading related sources | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
12 | Sequantial Probit and Sequential Logit Models (II) | Reading related sources, problem set and application | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
13 | Bivariate Probit and Bivariate Logit Models | Reading related sources | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
14 | Bivariate Probit and Bivariate Logit Models (II) | Reading related sources, problem set and application | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
15 | Conditional Probit and Conditional Logit Models | Reading related sources, problem set and application | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
16 | Term Exams | Ölçme Yöntemleri: Yazılı Sınav |
|
17 | Term Exams | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
Works | Number | Time (Hour) | Workload (Hour) |
---|---|---|---|
Course Related Works | |||
Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
Assesment Related Works | |||
Homeworks, Projects, Others | 0 | 0 | 0 |
Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
Final Exam | 1 | 30 | 30 |
Total Workload (Hour) | 157 | ||
Total Workload / 25 (h) | 6,28 | ||
ECTS | 6 ECTS |