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İzmir Ekonomi Üniversitesi

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    GRADUATE SCHOOL

    Financial Economics (Without Thesis)

    ECON 576 | Course Introduction and Application Information

    Course Name
    Econometrics
    Code
    Semester
    Theory
    (hour/week)
    Application/Lab
    (hour/week)
    Local Credits
    ECTS
    ECON 576
    Fall/Spring
    0
    0
    3
    7.5

    Prerequisites
    None
    Course Language
    English
    Course Type
    Elective
    Course Level
    Second Cycle
    Mode of Delivery -
    Teaching Methods and Techniques of the Course -
    National Occupation Classification -
    Course Coordinator
    Course Lecturer(s)
    Assistant(s) -
    Course Objectives
    Learning Outcomes

    The students who succeeded in this course;

    • will be able to conduct econometric analysis on stationary time-series.
    • will be able to conduct econometric analysis on non-stationary time-series data.
    • will be able to conduct econometric analysis using instruments in dynamic and non-dynamic models.
    • will be able to conduct econometric analysis on panel data.
    • will be able to conduct econometric analysis for binary dependant variable models.
    Course Description This course begins with the traditional econometric methods of matrix regression and general regression theory as well as the traditional understanding of econometric modeling. Additional topics include linear regression analysis, the least squares method, the ML estimator, univariate time series model, autoregressive moving average (ARIMA) modeling, BoxJenkins hashing, deterministic and stochastic trends, differential equations, nonstationary, seasonality, volatility, trends and transformations, multiequation timeseries models, cointegration and errorcorrection models, Logit, Probit and Tobit models, system models, and SUR, VAR, and panel data models.
    Related Sustainable Development Goals

     



    Course Category

    		Core Courses
    Major Area Courses
    Supportive Courses
    Media and Management Skills Courses
    Transferable Skill Courses

     

    WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

    Week Subjects Related Preparation
    1 Introduction Grene Ch. 1
    2 Probability and Distributions OSE Ch.5 , Greene Appendix B
    3 Multivariate Distributions OSE Ch.6, Greene Appendix B10
    4 Estimation and Inference OSE Ch. 7, Greene Appendix C
    5 Estimation and Inference OSE Ch. 8, Greene Appendix C
    6 The Linear Regression Model Greene Ch.2
    7 Least Squares Greene Ch.3
    8 Classical Multiple Linear Regression Greene Ch.4
    9 Midterm Exam
    10 Hypothesis Testing Greene Ch.5
    11 Functional Form and Structural Change Greene Ch.6
    12 Heteroscedasticity Greene Ch.9
    13 Serial Correlation Greene Ch.20
    14 Nonstationary Data Greene Ch.21
    15 Review of the Semester
    16 Review of the Semester

     

    Course Notes/Textbooks
    Econometric Analysis, William H. Greene, 8th. edition, Pearson.
    Online Statistics Education: A Multimedia Course of Study (http://onlinestatbook.com/). Project Leader: David M. Lane, Rice University.
    Suggested Readings/Materials

     

    EVALUATION SYSTEM

    Semester Activities Number Weigthing
    Participation
    Laboratory / Application
    Field Work
    Quizzes / Studio Critiques
    Portfolio
    Homework / Assignments
    1
    40
    Presentation / Jury
    Project
    1
    30
    Seminar / Workshop
    Oral Exams
    Midterm
    1
    30
    Final Exam
    Total

    Weighting of Semester Activities on the Final Grade
    3
    100
    Weighting of End-of-Semester Activities on the Final Grade
    Total

    ECTS / WORKLOAD TABLE

    Semester Activities Number Duration (Hours) Workload
    Theoretical Course Hours
    (Including exam week: 16 x total hours)
    16
    3
    48
    Laboratory / Application Hours
    (Including exam week: '.16.' x total hours)
    16
    0
    Study Hours Out of Class
    16
    6
    96
    Field Work
    0
    Quizzes / Studio Critiques
    0
    Portfolio
    0
    Homework / Assignments
    1
    30
    30
    Presentation / Jury
    0
    Project
    1
    20
    20
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    1
    20
    20
    Final Exam
    0
        Total
    214

     

    COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

    #
    		 Program Competencies/Outcomes
    * Contribution Level
    1
    2
    3
    4
    5
    1

    To improve and deepen expertise in economics and finance.
    -
    -
    -
    X
    -
    2

    To be able to comprehend the interaction between economics, finance and related fields.
    -
    -
    X
    -
    -
    3

    To be able to apply the advanced level knowledge acquired in economics and finance.
    -
    -
    -
    -
    X
    4

    To be able to create new knowledge by combining the knowledge of finance and economics with the knowledge coming from other disciplines and be able to solve problems which requires expert knowledge by applying scientific methods.
    -
    -
    -
    -
    X
    5

    To be able to use computer programs needed in the fields of economics and finance as well as information and communication technologies in advanced levels.
    -
    -
    -
    -
    X
    6

    To be able to think analytically to identify problems in finance and economics and to be able to make policy recommendations in economics and finance based on scientific analysis of issues and problems.
    -
    -
    -
    -
    X
    7

    To be able to develop new strategic approaches for unexpected, complicated situations in finance and economics and take responsibility in solving it.
    -
    -
    X
    -
    -
    8

    To protect the social, scientific and ethical values at the data collection, interpretation and dissemination stages and to be able to institute and observe these values.
    -
    -
    X
    -
    -
    9

    To be able to critically evaluate the knowledge in finance and economics, to lead learning and carry out advanced level research independently.
    -
    -
    X
    -
    -
    10

    To be able to use a foreign language for both following scientific progress and for written and oral communication.
    -
    -
    X
    -
    -

    *1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

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