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Information
| Unit | FACULTY OF ECONOMICS AND ADMINISTRATIVE SCIENCES |
| ECONOMICS PR. | |
| Code | EKMS412 |
| Name | Econometrics II |
| Term | 2024-2025 Academic Year |
| Semester | 8. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Label | FE Field Education Courses E Elective |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. HASAN ALTAN ÇABUK |
| Course Instructor |
Doç. Dr. ÇİLER SİGEZE GÜNEY
(Bahar)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
This course Econometrics, Economics and Finance Sections are registered with the knowledge of basic mathematics and statistics İ.İ.B. School aims to teach students the methods of basic econometrics. This course titles contained in the above-mentioned branches of econometric applications for students who want to do the research aims to support their work areas
Course Content
Econometrics, econometrics methods, econometrics models
Course Precondition
There are no course prerequisites.
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
Lecture notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Analyzes time series data and performs trend, seasonal effects, autocorrelation and stationarity tests. |
| LO02 | Evaluates the suitability of the econometric model, tests the validity of the model, and uses appropriate criteria when selecting the model. |
| LO03 | Obtains accurate results by testing model errors such as outliers, multicollinearity, and heteroskedasticity. |
| LO04 | Simulates the behavior of complex economic models using simulation techniques and the Monte Carlo method. |
| LO05 | Apply the theoretical knowledge taught in the econometrics course to applied data analysis through econometric software such as Stata, EViews or R. |
| LO06 | Use advanced package programs related to econometrics, statistics and operations |
| LO07 | Describes the knowledge of statistics, operations research and mathematics |
| LO08 | Have the ability to analyze, compare, evaluate and interpret at a conceptual level to develop solutions to problems. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Explain the importance of demand and supply in economy science and the well-running conditions of the market economy | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Define the role of pricing within the event advantage of the market economy. | 3 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Define the role of the state in economy, money and financial policies, the central bank and the structure of the market. | 4 |
| PLO04 | Bilgi - Kuramsal, Olgusal | Perceive the costs and benefits arising from the global economy | 3 |
| PLO05 | Bilgi - Kuramsal, Olgusal | Produce numerical and policy options when confronted with problems. | |
| PLO06 | Bilgi - Kuramsal, Olgusal | Use quantitative and qualitative techniques of model building, decoding and interpretation. | 5 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Use the theory of economics in the analysis of economic events. | 5 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Use computer programs, do synthesis and present prepared data efficiently. | |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Apply the methods of economic analysis. | 5 |
| PLO10 | Bilgi - Kuramsal, Olgusal | Analyze at conceptual level and acquires ability in comparing, interpreting, evaluating and synthesizing in order to develop solutions to problems | |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Use of different sources about an unfamiliar field within academic principles, synthesize gained data and presents effectively. | |
| PLO12 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Take responsibility individually and / or in a team, take leadership and work effectively. | |
| PLO13 | Yetkinlikler - Öğrenme Yetkinliği | Follow innovative developments in the field being aware of the necessity of lifelong learning and improving him-/herself.. | |
| PLO14 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Use Turkish and at least one foreign language in accordance with the requirements of academic and work life. | |
| PLO15 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Understand and interpret related people´s feelings, thoughts, and behaviours correctly; expresse him-/herself accurately in written and oral language. | |
| PLO16 | Yetkinlikler - Alana Özgü Yetkinlik | Question traditional approaches, practices and methods. | |
| PLO17 | Yetkinlikler - Alana Özgü Yetkinlik | Recognize and apply social, scientific and professional ethical values. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Repeating Multiple Linear Regression Model and Linear Hypothesis Testing | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Anlatım |
| 2 | Deviations from the classical linear regression model: Multicollinearity | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Problem Çözme |
| 3 | Deviations from the classical linear regression model: Autocorrelation | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 4 | Deviations from the classical linear regression model: Heterocedasticity | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Anlatım |
| 5 | Deviations from the classical linear regression model: General repetition | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Problem Çözme |
| 6 | Structural Change and Chow Test | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Anlatım |
| 7 | Making sample question solutions | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Problem Çözme |
| 8 | Mid-Term Exam | exam | Ölçme Yöntemleri: Yazılı Sınav, Ödev |
| 9 | Structural Change and Dummy Variables | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 10 | Multiple Equation Econometric Models: Structural Model and Reduced-Form | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 11 | Multiple Equation Econometric Models: Determination of Structural Model | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Problem Çözme |
| 12 | Multiple Equation Econometric Models: Dtermination of Reduced-Form | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 13 | Multiple Equation Econometric Models: Indirect OLS and Two stage OLS | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Problem Çözme |
| 14 | Multiple Equation Econometric Models: Two stage OLS | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Problem Çözme |
| 15 | Problem solving | Students will be prepared by studying relevant subjects from source books according to weekly program | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 16 | Term Exams | exam | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | exam | Ölçme Yöntemleri: Yazılı Sınav |
Assessment (Exam) Methods and Criteria
Current term shares have not yet been determined. Shares of the previous term are shown.
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 100 | 40 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
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 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||