Prerequisite (s)
Mathematics, Mathematics for Economists, Introduction to Economics I, and Introduction to Economics II.
Course Aim
This course introduces the fundamental concepts and tools of macroeconomic analysis.
Course Goals
This course aims at teaching how to construct macroeconomic models used to explain changes in macroeconomic magnitudes such as Gross Domestic Product, Unemployment, General Price Level, Interest Rate, Economic Growth Rate, and Exchange Rate.
Course Learning Outs and Proficiencies
The main learning output of this course is to have students learn basic macroeconomic concepts and magnitudes and how the relationships between macroeconomic variables are defined through macroeconomic models.
Required Readings:
—Erdal Ünsal (2007), Makro Ekonomi, İmaj Yayıncılık, Ankara.
Suggested Readings:
—Kemal Yıldırım, Doğan Karaman ve Murat Taşdemir (2007), Makroekonomi, Seçkin Yayıncılık, Ankara.
—Tümay Ertek (2005, Makroekonomiye Giriş, Beta, İstanbul.
Assessment Criteria
Midterm 30% and Final 70%
Semester Course Plan
Week/Subjects
1
National Income Accounting I
2
National Income Accounting II
3
Total Supply
4
Total Demand I
5
Total Demand II
6
Income and Expenditure
7
Wages and Unemployment
8
Inflation
9
Monetary Policy
10
Fiscal Policy
11
Income Policy
12
Open Economy Macroeconomics I
13
Open Economy Macroeconomics II
14
Introduction to Macro Models
Harun Ozturkler- ozturkler@alumni.american.edu
Saturday, September 6, 2008
Undergraduate Applied Econometrics
Prerequisite (s)
Econometrics I, and Econometrics II
Course Aim
By employing econometric package programs, this course aims at teaching students how econometric methods are used in practice.
Course Goals
Ability to construct simple econometric models
Learning How to Use Econometric Package Programs
Learning How to Collect Data and Prepare for the Analysis
Learning how to Compute Econometric Models
Learning how to Evaluate Results Obtained from the Computation of Econometric Models
Course Learning Outs and Proficiencies
The main learning output of this course is to teach how econometric methods can be used by employing econometric package programs.
Required Readings:
- Eviews, RATS, and Stata Software Manuals.
Suggested Readings:
-James H. Stock and Mark W. Watson (2007), Introduction to Econometrics: International Edition, Addison-Wesley, Boston.
-James D. Hamilton (1994), Times Series Analysis, Princeton University Pres, New Jersey.
-Myoung-Jae Lee (2002), Panel Data Econometrics: Methods-of-moments and Limited Dependent Variables, Academic Press, San Diego.
Assessment Criteria
Midterm 30% and Final 70%
Semester Course Plan
Week/Subjects
1
Review of Econometric Models I
2
Review of Econometric Models II
3
Data Collection and Preparation for the Analysis I
4
Data Collection and Preparation for the Analysis II
5
Econometric Software II: E-views I
6
Econometric Software II: E-views II
7
Econometric Software II: E-views III
8
Econometric Software III: RATS I
9
Econometric Software III: RATS II
10
Econometric Software IV: RATS III
11
Econometric Software V: Stata I
12
Econometric Software VI: Stata II
13
Econometric Software VI: Stata III
14
Assessment of Model Results
Econometrics I, and Econometrics II
Course Aim
By employing econometric package programs, this course aims at teaching students how econometric methods are used in practice.
Course Goals
Ability to construct simple econometric models
Learning How to Use Econometric Package Programs
Learning How to Collect Data and Prepare for the Analysis
Learning how to Compute Econometric Models
Learning how to Evaluate Results Obtained from the Computation of Econometric Models
Course Learning Outs and Proficiencies
The main learning output of this course is to teach how econometric methods can be used by employing econometric package programs.
Required Readings:
- Eviews, RATS, and Stata Software Manuals.
Suggested Readings:
-James H. Stock and Mark W. Watson (2007), Introduction to Econometrics: International Edition, Addison-Wesley, Boston.
-James D. Hamilton (1994), Times Series Analysis, Princeton University Pres, New Jersey.
-Myoung-Jae Lee (2002), Panel Data Econometrics: Methods-of-moments and Limited Dependent Variables, Academic Press, San Diego.
Assessment Criteria
Midterm 30% and Final 70%
Semester Course Plan
Week/Subjects
1
Review of Econometric Models I
2
Review of Econometric Models II
3
Data Collection and Preparation for the Analysis I
4
Data Collection and Preparation for the Analysis II
5
Econometric Software II: E-views I
6
Econometric Software II: E-views II
7
Econometric Software II: E-views III
8
Econometric Software III: RATS I
9
Econometric Software III: RATS II
10
Econometric Software IV: RATS III
11
Econometric Software V: Stata I
12
Econometric Software VI: Stata II
13
Econometric Software VI: Stata III
14
Assessment of Model Results
Undergraduate Econometrics II
Prerequisite (s)
Mathematics, Mathematics for Economists, Statistics I, Statistics II, and Econometrics I
Course Aim
This aim of this course is to teach specific econometric subjects together with time series and panel data analysis. Furthermore, it also intends to cover latest developments in econometric methods.
Course Goals
Learning specific econometric subjects.
Learning how to construct, estimate and assess times series models.
Learning how to construct, estimate and assess panel data models models.
Ability to follow latest developments in econometric modeling techniques.
Learning how to use econometric models in evaluating economic policies.
Learning how to use the results of econometric models in economic policy suggestions.
Course Learning Outs and Proficiencies
The main learning output of this course is to teach specific econometric methods and how to follow latest developments in econometric analysis. Evaluation of economic policies in the framework of the results obtained from econometric models and economic policy suggestions are two other important learning outputs of this course.
Required Readings:
—Damodar N. Gujurati (2001), Temel Ekonometri, Çevirenler: Gülay Güllük Şenesen ve Ümit Şenesen, Literatür Yayınları, İstanbul.
Suggested Readings:
— Peter Kennedy (2006), Ekonometri Kılavuzu, Çevirenler: Muzaffer Sarımeşeli ve Şenay Açıkgöz, Gazi Kitabevi, Ankara.
— Tümay Ertek (1996), Ekonometriye Giriş, Beta, İstanbul.
— James H. Stock and Mark W. Watson (2007), Introduction to Econometrics: International Eddition, Addison-Wesley, Boston.
Assessment Criteria
Midterm 30 % and Final 70%
Semester Course Plan
Week/Subjects
1
Traditional Econometric Methods
2
Modern Econometric Approaches
3
Regression Analysis with Dummy Independent Variables
4
Regression Analysis with a Dichotomous Dependent Variable: Linear Probability Model
5
Regression Analysis with a Dichotomous Dependent Variable: Logit Model
6
Regression Analysis with a Dichotomous Dependent Variable: Probit Model
7
Regression Analysis with a Dichotomous Dependent Variable: Tobit Model
8
Data Types and Econometric Analysis
9
Time Series Analysis I
10
Time Series Analysis II
11
Panel Data Analysis I
12
Panel Data Analysis II
13
Econometric Models and Economic Policy Evaluation
14
Econometric Models and Economic Policy Suggestions
Mathematics, Mathematics for Economists, Statistics I, Statistics II, and Econometrics I
Course Aim
This aim of this course is to teach specific econometric subjects together with time series and panel data analysis. Furthermore, it also intends to cover latest developments in econometric methods.
Course Goals
Learning specific econometric subjects.
Learning how to construct, estimate and assess times series models.
Learning how to construct, estimate and assess panel data models models.
Ability to follow latest developments in econometric modeling techniques.
Learning how to use econometric models in evaluating economic policies.
Learning how to use the results of econometric models in economic policy suggestions.
Course Learning Outs and Proficiencies
The main learning output of this course is to teach specific econometric methods and how to follow latest developments in econometric analysis. Evaluation of economic policies in the framework of the results obtained from econometric models and economic policy suggestions are two other important learning outputs of this course.
Required Readings:
—Damodar N. Gujurati (2001), Temel Ekonometri, Çevirenler: Gülay Güllük Şenesen ve Ümit Şenesen, Literatür Yayınları, İstanbul.
Suggested Readings:
— Peter Kennedy (2006), Ekonometri Kılavuzu, Çevirenler: Muzaffer Sarımeşeli ve Şenay Açıkgöz, Gazi Kitabevi, Ankara.
— Tümay Ertek (1996), Ekonometriye Giriş, Beta, İstanbul.
— James H. Stock and Mark W. Watson (2007), Introduction to Econometrics: International Eddition, Addison-Wesley, Boston.
Assessment Criteria
Midterm 30 % and Final 70%
Semester Course Plan
Week/Subjects
1
Traditional Econometric Methods
2
Modern Econometric Approaches
3
Regression Analysis with Dummy Independent Variables
4
Regression Analysis with a Dichotomous Dependent Variable: Linear Probability Model
5
Regression Analysis with a Dichotomous Dependent Variable: Logit Model
6
Regression Analysis with a Dichotomous Dependent Variable: Probit Model
7
Regression Analysis with a Dichotomous Dependent Variable: Tobit Model
8
Data Types and Econometric Analysis
9
Time Series Analysis I
10
Time Series Analysis II
11
Panel Data Analysis I
12
Panel Data Analysis II
13
Econometric Models and Economic Policy Evaluation
14
Econometric Models and Economic Policy Suggestions
Undergraduate Econometrics I
Prerequisite (s)
Mathematics, Mathematics for Economists, Statistics I, and Statistics II.
Course Aim
This course introduces the econometric models employed in testing and evaluating economic models.
Course Goals
Learning about economic variables and the behavioral relationships among them.
Ability to analyze the characteristics of economic models.
Learning how to transform economic models into econometric models
Learning how to estimate econometric models
Learning how to assess the results obtained from econometric models
Learning how to analyze the deviations from the assumptions of the econometric models
Course Learning Outputs and Proficiencies
The main learning output of this course is to learn how economic theory models the behavioral relationships among economic variables. In addition, the course aims at teaching how economic models are transformed into econometric models and how econometric models are estimated.
Required Readings:
—Damodar N. Gujurati (2001), Temel Ekonometri, Çevirenler: Gülay Güllük Şenesen ve Ümit Şenesen, Literatür Yayınları, İstanbul.
Suggested Readings:
— Peter Kennedy (2006), Ekonometri Kılavuzu, Çevirenler: Muzaffer Sarımeşeli ve Şenay Açıkgöz, Gazi Kitabevi, Ankara.
— Tümay Ertek (1996), Ekonometriye Giriş, Beta, İstanbul.
Assessment Criteria
Midterm 30% and Final 70%
Semester Course Plan
Week/Subjects
1
The behavioral relationships among economic variables
2
Economic Models
3
Data types, Data Sources, and Data Collecting
4
Classical Linear Regression Analysis: Two-Variable Case
5
Hypothesis Testing in Two-Variable Regression Analysis
6
Classical Linear Regression Analysis: Multiple Variable Case
7
Hypothesis Testing in Multiple Variable Regression Analysis
8
The Matrix Approach to Linear Regression Model I
9
The Matrix Approach to Linear Regression Model II
10
Deviations from the Assumptions the Classical Model: Multicollinearity
11
Deviations from the Assumptions the Classical Model: Heteroscedasticity
12
Deviations from the Assumptions the Classical Model: Autocorrelation
13
Deviations from the Assumptions the Classical Model: Model Specification Errors
14
Nonlinear Regression Models
Mathematics, Mathematics for Economists, Statistics I, and Statistics II.
Course Aim
This course introduces the econometric models employed in testing and evaluating economic models.
Course Goals
Learning about economic variables and the behavioral relationships among them.
Ability to analyze the characteristics of economic models.
Learning how to transform economic models into econometric models
Learning how to estimate econometric models
Learning how to assess the results obtained from econometric models
Learning how to analyze the deviations from the assumptions of the econometric models
Course Learning Outputs and Proficiencies
The main learning output of this course is to learn how economic theory models the behavioral relationships among economic variables. In addition, the course aims at teaching how economic models are transformed into econometric models and how econometric models are estimated.
Required Readings:
—Damodar N. Gujurati (2001), Temel Ekonometri, Çevirenler: Gülay Güllük Şenesen ve Ümit Şenesen, Literatür Yayınları, İstanbul.
Suggested Readings:
— Peter Kennedy (2006), Ekonometri Kılavuzu, Çevirenler: Muzaffer Sarımeşeli ve Şenay Açıkgöz, Gazi Kitabevi, Ankara.
— Tümay Ertek (1996), Ekonometriye Giriş, Beta, İstanbul.
Assessment Criteria
Midterm 30% and Final 70%
Semester Course Plan
Week/Subjects
1
The behavioral relationships among economic variables
2
Economic Models
3
Data types, Data Sources, and Data Collecting
4
Classical Linear Regression Analysis: Two-Variable Case
5
Hypothesis Testing in Two-Variable Regression Analysis
6
Classical Linear Regression Analysis: Multiple Variable Case
7
Hypothesis Testing in Multiple Variable Regression Analysis
8
The Matrix Approach to Linear Regression Model I
9
The Matrix Approach to Linear Regression Model II
10
Deviations from the Assumptions the Classical Model: Multicollinearity
11
Deviations from the Assumptions the Classical Model: Heteroscedasticity
12
Deviations from the Assumptions the Classical Model: Autocorrelation
13
Deviations from the Assumptions the Classical Model: Model Specification Errors
14
Nonlinear Regression Models
Subscribe to:
Posts (Atom)