Information
Code | IEM1817 |
Name | Microeconometrics 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. 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
D. Gujarati "Introduction to Econometrics"
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 |
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 that does not 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 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Performs self-study using knowledge of Econometrics, Statistics and Operations to solve a problem | 1 |
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 | |
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, Soru-Cevap, Alıştırma ve Uygulama |
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: Anlatım, Soru-Cevap, Problem Çözme |
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, Proje Temelli Öğrenme |
8 | Mid-Term Exam | Students are prepared for the midterm exam. | Öğretim Yöntemleri: Soru-Cevap |
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, Bireysel Çalışma, Proje Temelli Öğrenme |
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 |