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Information
| Code | IEM1817 |
| Name | Microeconometrics I |
| 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. SEDA ŞENGÜL |
| Course Instructor |
1 |
Course Goal / Objective
The aim of this course is to teach the analysis of the economic behavior of individulas or firms by using individual level data such as cross-section and panel data.
Course Content
Discrete, censored, count models and linear panel data models used to determine the economic behavior of economic units such as individual-firm will be the content of this course.
Course Precondition
No prerequisites are required.
Resources
Tansel, A. (2015). Ekonometriye Giris, Modern Yaklasim. METU Studies in Development, 42(2), 333. Gujarati, D. N., & Ekonometri, T. (2001). Literatür Yayınları No: 33. Dougherty, C. (2011). Introduction to econometrics. Oxford university press, USA.
Notes
Lectures
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | The data structure used micro econometrics are well known |
| LO02 | To learn maximum likelihood estimator and nonlinear regression models |
| LO03 | to gain the ability to make a micro-econometric study with the cross-sectional data on its own. |
| LO04 | to be able to make an econometric study on its own with the panel data and to be able to solve any economic problems |
| LO05 | Solves econometric problem using package program. |
| LO06 | Identify post-estimation problems of an econometric model. |
| LO07 | analyzes and interprets the econometric model. |
| LO08 | Describes the knowledge of statistics, operations research and mathematics |
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 | 1 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Develops new knowledge using current concepts in Econometrics, Statistics and Operations Research | 1 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Explain for what purpose and how econometric methods are applied to other fields and disciplines | 2 |
| PLO04 | Beceriler - Bilişsel, Uygulamalı | Using her knowledge, brings original solutions to problems in Economics, Business Administration and other social sciences | 5 |
| 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 | 3 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Performs conceptual analysis to develop solutions to problems | 2 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Collects data on purpose | 2 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Synthesizes the information obtained by using different sources within the framework of academic rules in a field of research | 5 |
| 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 | Beceriler - Bilişsel, Uygulamalı | Uses a package program/writes a new code for Econometrics, Statistics, and Operation Research | |
| 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 | |
| PLO18 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses acquired knowledge in the field to determine the vision, aim, and goals for an organization/institution | |
| 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 | |
| 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 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Data used on micro econometrics studies and data stuctures | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Anlatım, Tartışma, Beyin Fırtınası |
| 2 | Linear models and ordinary least squares | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Anlatım |
| 3 | Maximum likelihood and Nonlinear -least-squares estimation (II) | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama |
| 4 | Maximum likelihood and hypothesis tests | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Soru-Cevap |
| 5 | Models for cross-section data | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Proje Temelli Öğrenme |
| 6 | Binary outcome models | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Anlatım, Proje Temelli Öğrenme |
| 7 | Multinominal models | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Tartışma |
| 8 | Mid-Term Exam | Students are prepared for the midterm exam. | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Multinominal models (II) | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Proje Temelli Öğrenme |
| 10 | Tobit and selection models selection models | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Anlatım, Proje Temelli Öğrenme |
| 11 | Tobit and selection models (II) | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Anlatım, Tartışma, Proje Temelli Öğrenme |
| 12 | Models of count data | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Anlatım, Tartışma, Proje Temelli Öğrenme |
| 13 | Panel data models | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Anlatım, Proje Temelli Öğrenme |
| 14 | Linear panel data models | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Anlatım, Bireysel Çalışma, Proje Temelli Öğrenme |
| 15 | Linear panel data models (II) | Students will be prepared by studying relevant subjects from source books according to the weekly program. | Öğretim Yöntemleri: Anlatım, Bireysel Çalışma, Proje Temelli Öğrenme |
| 16 | Term Exams | Students are prepared for the final exam. | Öğretim Yöntemleri: Anlatım |
| 17 | Term Exams | Students are prepared for the final exam. | Ölçme Yöntemleri: Yazılı Sınav, Proje / Tasarım |
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 | ||