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Information
| Unit | INSTITUTE OF SOCIAL SCIENCES |
| ECONOMETRICS (PhD) | |
| Code | IEM1820 |
| Name | Macroeconometrics II |
| Term | 2018-2019 Academic Year |
| Term | 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 |
The current term course schedule has not been prepared yet.
|
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
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Identifying empirical features and characteristics of various types of macroeconomic and financial data |
| LO02 | Developing a firm understanding of the key econometric techniques used to analyse macroeconomic and financial data by scholars and market analysts |
| LO03 | Applying of testing and forecasting techniques correctly as dictated by the data and selected model |
| LO04 | Understanding how time-varying models may capture the changing properties of macroeconomic variables over business cycle expansions and contractions |
| LO05 | Evaluating empirical studies in macroeconomics and finance and some of the problems associated with estimating time series data critically |
| LO06 | Using STATA econometric software extensively to analyse 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 | |
| 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 of 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 | Beceriler - Bilişsel, Uygulamalı | Uses a package program/writes a new code for Econometrics, Statistics, and Operation Research | 3 |
| PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Performs self-study using knowledge of Econometrics, Statistics and Operations to solve a problem | 3 |
| PLO16 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Leads the team by taking responsibility | |
| PLO17 | 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 |
| PLO18 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses acquired knowledge in the field to determine the vision, aim, and goals for an organization/institution | |
| 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 | |
| 2 | Heterocedasticity and Autocorrelation Consistent (HAC) Variance Estimation | Reading the Textbook | |
| 3 | Beveridge-Nelson Decomposition, Shortcuts to Time Series Asymptotics and Convergence to Stochastic Integrals | Reading the Textbook | |
| 4 | Kalman and Particle Filtering | Reading the Textbook | |
| 5 | Nonlinear Time Series Analysis | Reading the Textbook | |
| 6 | Threshold Models and STAR | Reading the Textbook | |
| 7 | Markov Switching and Applications | Reading the Textbook | |
| 8 | Mid-Term Exam | Studying the Course Content | |
| 9 | Dynamic Stochastic General Equilibrium Models | Reading the Textbook | |
| 10 | Calibrating and Matching Moments | Reading the Textbook | |
| 11 | Generalized Method of Moments (GMM) Estimation | Reading the Textbook | |
| 12 | Bayesian Analysis of Linear Time Series Models | Reading the Textbook | |
| 13 | Wavelets | Reading the Textbook | |
| 14 | Principal Component Analysis and Factor Augmented VAR | Reading the Textbook | |
| 15 | Linear (and Nonlinear) Rational Expectations (LRE) Models | Reading the Textbook | |
| 16 | Term Exams | Studying the Whole Course Content | |
| 17 | Term Exams | Studying the Whole Course Content |
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 | ||