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Information
| Code | IEM1819 |
| Name | Macroeconometrics I |
| Term | 2024-2025 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 execute and assess analysis of time series data in univariate and multivariate applied contexts making use of theoretical and applied tools used by professional economists to analyze time series data.
Course Content
In this course, the topics of autoregressive moving average processes, non-stationary time series models, unit root tests, vector autoregression models and cointegration analysis will be covered.
Course Precondition
None
Resources
Durlauf, S. N. & Blume, L. E. (2010). Macroconometrics and time series analysis. New York: Palgrave Macmillan.
Notes
Favero, C. A. (2001). Applied macroeconometrics. Oxford University Press on Demand.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Analyzing macro/aggregate data |
| LO02 | Interpreting time-series models |
| LO03 | Forecasting major macro variables and simulations of macro-models |
| LO04 | Adopting skills and knowledge of econometric modelling for strategic thinking and understanding |
| LO05 | Using the econometric concepts and tools in the analysis of economic behaviors of countries |
| LO06 | Explaining the inter-linkages among sectors and markets of various economies |
| LO07 | Writing basic concepts in macroeconometrics |
| LO08 | Listing differences between Vector Autoregression (VAR) ve Structural VAR models |
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 | 3 |
| 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 | Business cycles and Basic concepts of Time Series Models | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 317-342) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 2 | Difference Equations | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 193-201) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Soru-Cevap |
| 3 | Fractals | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 94-98) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 4 | Functional Central Limit Theorems | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 99-104) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Tartışma |
| 5 | Spectra and Univariate Filtering of Time-Series Data | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 250-259) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 6 | Autocorrelated Disturbances and ARMA Models | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 317-342) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Problem Çözme |
| 7 | Rational Expectations | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 193-201) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Grup Çalışması |
| 8 | Mid-Term Exam | Studying the Course Content | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Granger Causality, Impulse Response Functions, Variance Decomposition | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 119-150) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Soru-Cevap |
| 10 | Multivariate Time Series | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 317-342) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Grup Çalışması |
| 11 | Structural Vector Autoregressions | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 303-307) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 12 | Unit Roots from the Frequentist and the Bayesian Perspective | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 347-368) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Tartışma |
| 13 | Spurious Regressions | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 265-268) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 14 | Cointegration and Error Correction Models | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 53-59) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Soru-Cevap |
| 15 | Maximum Likelihood Estimation | Durlauf & Blume (2010) - Macroconometrics and time series analysis (pp. 317-342) | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Problem Çözme |
| 16 | Term Exams | Studying the Whole Course Content | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Studying the Whole Course Content | Ölçme Yöntemleri: Yazılı 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 | ||