Information
Code | IEM1820 |
Name | Macroeconometrics II |
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. MEHMET ÖZMEN |
Course Instructor |
1 |
Course Goal / Objective
It has been aimed to develop the skills needed to do empirical research in the field of macroeconomics, provide an introduction to the methods of modern applied macroeconometrics and analyze dynamic stochastic general equilibrium models.
Course Content
Techniques in Solving the Deterministic Steady-State, Spectral Analysis, Factor Models, GMM, Single Equation Methods, Simulated Method of Moments, Maximum Likelihood, Bayesian Methods and Hybrid Models.
Course Precondition
None
Resources
Hayashi, F. (2011). Econometrics. Princeton University Press.
Notes
Favero, C. A. (2001). Applied macroeconometrics. Oxford University Press.
Course Learning Outcomes
Order | Course Learning Outcomes |
---|---|
LO01 | Identifying empirical features and characteristics of various types of macroeconomic and financial data |
LO02 | Understanding the key econometric techniques regarding the macroeconomic and financial data |
LO03 | Applying the test and forecasting techniques correctly according to the data and selected model |
LO04 | Understanding the changing properties of macroeconomic variables over business cycle expansions and contractions |
LO05 | Evaluating empirical studies in macroeconomics and finance critically |
LO06 | Using STATA econometric software for macroeconomic and financial data |
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 | 5 |
PLO02 | Bilgi - Kuramsal, Olgusal | Develops new knowledge using current concepts in Econometrics, Statistics and Operations Research | 3 |
PLO03 | Bilgi - Kuramsal, Olgusal | Explain for what purpose and how econometric methods are applied to other fields and disciplines | 4 |
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 | 5 |
PLO06 | Beceriler - Bilişsel, Uygulamalı | Interprets the results obtained from the most appropriate method to predict the model | 5 |
PLO07 | Beceriler - Bilişsel, Uygulamalı | Performs conceptual analysis to develop solutions to problems | 4 |
PLO08 | Beceriler - Bilişsel, Uygulamalı | Collects data on purpose | 4 |
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 | 3 |
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 | 4 |
PLO12 | Beceriler - Bilişsel, Uygulamalı | It researches current approaches and methods to solve the problems it encounters and proposes new solutions | 5 |
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 | 3 |
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 | 4 |
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 | 3 |
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 | 5 |
Week Plan
Week | Topic | Preparation | Methods |
---|---|---|---|
1 | Filters and Business Cycle Estimation | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
2 | Heterocedasticity and Autocorrelation Consistent (HAC) Variance Estimation | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
3 | Beveridge-Nelson Decomposition, Shortcuts to Time Series Asymptotics and Convergence to Stochastic Integrals | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
4 | Kalman and Particle Filtering | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
5 | Nonlinear Time Series Analysis | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
6 | Threshold Models and STAR | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
7 | Markov Switching and Applications | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
8 | Mid-Term Exam | Studying the Course Content | Öğretim Yöntemleri: Bireysel Çalışma |
9 | Dynamic Stochastic General Equilibrium Models | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
10 | Calibrating and Matching Moments | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
11 | Generalized Method of Moments (GMM) Estimation | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
12 | Bayesian Analysis of Linear Time Series Models | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
13 | Wavelets | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
14 | Principal Component Analysis and Factor Augmented VAR | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
15 | Linear (and Nonlinear) Rational Expectations (LRE) Models | Reading the Textbook | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
16 | Term Exams | Studying the Whole Course Content | Öğretim Yöntemleri: Bireysel Çalışma |
17 | Term Exams | Studying the Whole Course Content | Öğretim Yöntemleri: Bireysel Çalışma |
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 |