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Information
| Code | IEM768 |
| Name | Applied Econometric Models |
| Term | 2024-2025 Academic Year |
| Semester | . Semester |
| 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 | Doç. Dr. ÇİLER SİGEZE GÜNEY |
Course Goal / Objective
The aim of this course is to introduce students to different econometric models, to make them analyse these models using statistical software programs such as STATA, R and to interpret the results obtained.
Course Content
Linear regression models, linear probability models, Probit and Logit models, multinomial models, ordered regression models, quantile regression, linear instrumental variable regression models
Course Precondition
None
Resources
Uygulamalarla Miikroekonometri, Editörler: Prof. Dr. Şenay ÜÇDOĞRUK BİRECİKLİ, Prof. Dr. Seda ŞENGÜL
Notes
Applied Econometrics using STATA, Ricardo Perez-Truglia, Harvard University.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Recognise different econometric models. |
| LO02 | Recognise limited dependent variable models. |
| LO03 | Applies limited dependent variable models in STATA and R programmes. |
| LO04 | Recognise linear instrumental variable models. |
| LO05 | Applies linear instrumental variable models in STATA and R programmes. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Explains contemporary concepts about Econometrics, Statistics, and Operation Research | 3 |
| 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 | |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Models problems with Mathematics, Statistics, and Econometrics | 3 |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Interprets the results obtained from the most appropriate method to predict the model | 3 |
| 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 | 3 |
| 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 | |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Presents analysis results conveniently | 4 |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Collects/analyzes data in a purposeful way | 4 |
| PLO12 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Converts its findings into a master's thesis or a professional report in Turkish or a foreign language | 3 |
| PLO13 | Beceriler - Bilişsel, Uygulamalı | Develops solutions for organizations using Econometrics, Statistics, and Operation Research | 4 |
| PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Performs an individual work to solve a problem with Econometrics, Statistics, and Operation Research | 3 |
| PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Leads by taking responsibility individually and/or within the team | |
| 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 | |
| PLO17 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses a package program of Econometrics, Statistics, and Operation Research or writes a new code | 4 |
| 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 | 4 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | An introduction to STATA and R sofwares | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Soru-Cevap, Anlatım, Alıştırma ve Uygulama, Gösterip Yaptırma |
| 2 | Linear regression model and Least Squares estimator, STATA and R software applications | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Soru-Cevap, Alıştırma ve Uygulama, Anlatım, Gösterip Yaptırma |
| 3 | Linear Probability Model and STATA and R software applications | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Gösterip Yaptırma |
| 4 | Probit Model and Logit Model | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
| 5 | STATA and R applications of Probit and Logit models | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Gösterip Yaptırma |
| 6 | Ordered Probit Model, Ordered Logit Model | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
| 7 | STATA ve R applications of Ordered Probit Model and Ordered Logit Model | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Soru-Cevap, Anlatım, Alıştırma ve Uygulama, Gösterip Yaptırma |
| 8 | Mid-Term Exam | Ölçme Yöntemleri: Yazılı Sınav, Ödev |
|
| 9 | Multinomial Probit Model and Multinomial Logit Model | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
| 10 | STATA ve R applications of Multinomial Probit Model and Multinomial Logit Model | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Gösterip Yaptırma, Alıştırma ve Uygulama |
| 11 | Quantile Regression | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
| 12 | STATA and R applications of Quantil Regression | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Gösterip Yaptırma |
| 13 | Linear instrumental variable models -IV, STATA and R applications | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Gösterip Yaptırma |
| 14 | Linear instrumental variable models -2SLS, STATA and R applications | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Gösterip Yaptırma |
| 15 | Linear instrumental variable models -GMM, STATA and R applications | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Soru-Cevap, Anlatım, Alıştırma ve Uygulama, Gösterip Yaptırma |
| 16 | Term Exams | Ölçme Yöntemleri: Yazılı Sınav, Ödev |
|
| 17 | Term Exams | Ölçme Yöntemleri: Yazılı Sınav, Ödev |
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 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 2 | 20 | 40 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 15 | 15 |
| Total Workload (Hour) | 154 | ||
| Total Workload / 25 (h) | 6,16 | ||
| ECTS | 6 ECTS | ||