IEM1817 Microeconometrics I

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

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

Update Time: 11.05.2023 04:58