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Information
| Code | IEM1802 |
| Name | Econometric Theory II |
| Term | 2023-2024 Academic Year |
| Semester | . Semester |
| 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. HASAN ALTAN ÇABUK |
Course Goal / Objective
The aim of this course is to teach econometrics methods at an advanced level to the graduates of Econometrics, Mathematics or Statistics.
Course Content
Multiple linear regression model, least squares estimation, finite sample properties of eccalc estimators, asymptotic properties. Functional form and structural change; binary variables, structural breakage modeling and testing, model stability testing. Nonlinear regression models, generalized regression model, variable variance problem, multiple correlation, panel data models, regression equations system, simultaneous equations model, maximum likelihood estimation, models with delayed variable, time series models.
Course Precondition
There are no prerequisites for the course
Resources
Domar N. Gujarati (Çevirenler Ümit Şenesen ve Gülay Günlük Şenesen), Temel Ekonometri, Literatür Yayıncılık, 1. Baskı, İstanbul, 1999
Notes
lecture notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | The student carries the basic econometrics knowledge to the advanced level |
| LO02 | Uses information technologies and at least one computer programming language related to econometrics, statistics and operations research fields. |
| LO03 | Makes research on topics related to econometrics, uses its knowledge to the maximum extent in this research and makes this research report and presents it in the best way. |
| LO04 | Being aware of the necessity of lifelong learning, it follows current developments and renews itself continuously |
| LO05 | Will be able to follow current issues, interpret data on economic and social events. |
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 | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Develops new knowledge using current concepts in Econometrics, Statistics and Operations Research | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Explain for what purpose and how econometric methods are applied to other fields and disciplines | |
| PLO04 | Beceriler - Bilişsel, Uygulamalı | Using her knowledge, brings original solutions to problems in Economics, Business Administration and other social sciences | |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Creates a new model using mathematics, statistics and econometrics knowledge to solve the problem encountered | |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Interprets the results obtained from the most appropriate method to predict the model | 4 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Performs conceptual analysis to develop solutions to problems | |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Collects data on purpose | 5 |
| 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 | |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Presents analysis results conveniently | 2 |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Converts its findings into a master's thesis or a professional report in Turkish or a foreign language | |
| PLO12 | Beceriler - Bilişsel, Uygulamalı | It researches current approaches and methods to solve the problems it encounters and proposes new solutions | 3 |
| PLO13 | Beceriler - Bilişsel, Uygulamalı | Develops long-term plans and strategies using econometric and statistical methods | 5 |
| PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Performs self-study using knowledge of Econometrics, Statistics and Operations to solve a problem | |
| PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Leads the team by taking responsibility | |
| 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 acquired knowledge in the field to determine the vision, aim, and goals for an organization/institution | |
| 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 | Review of Multiple Linear Regression Model and Linear Hypothesis Tests | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 2 | Deviations from Classical Linear Regression Model: Multiple Linear Connection | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 3 | Deviations from the Classical Linear Regression Model: Autocorrelation | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 4 | Deviations from the Classical Linear Regression Model: Variable Variance | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım |
| 5 | Deviations from the Classical Linear Regression Model: General Review | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 6 | Structural Change and Chow Test | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 7 | Article work | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 8 | Mid-Term Exam | Öğretim Yöntemleri: Anlatım, Problem Çözme |
|
| 9 | Structural Change and Dummy Variables | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 10 | Multi Equation Econometric Models: Structural Model and Reduced Mold | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 11 | Multiple Equation Econometric Models: Investigation of Determinability on Structural Model | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 12 | Multi-Equation Econometric Models: Reduced Pattern | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 13 | Multiple Equation Econometric Models: Investigation of Determinability on Structural Model-1 | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 14 | Preparing Article work | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 15 | Making Article work | Students will be able to read the related sections of the textbooks | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 16 | Term Exams | Öğretim Yöntemleri: Anlatım |
|
| 17 | Term Exams | Ölçme Yöntemleri: Sözlü Sınav |
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 | ||