Econometrics

Universidad Carlos III de Madrid

Course Description

  • Course Name

    Econometrics

  • Host University

    Universidad Carlos III de Madrid

  • Location

    Madrid, Spain

  • Area of Study

    Business, Business Administration, Business Management, Economics, Mathematics, Statistics

  • Language Level

    Taught In English

  • Prerequisites

    STUDENTS ARE EXPECTED TO HAVE COMPLETED
    Mathematics for Economics I
    Mathematics for Economics II
    Statistics I
    Statistics II
    Principles of Economics
    Microeconomics

  • Course Level Recommendations

    Lower

    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • ECTS Credits

    6
  • Recommended U.S. Semester Credits
    3
  • Recommended U.S. Quarter Units
    4
  • Overview

    Econometrics
    Bachelor in Business Administration
    Departamento de Economía
    Compulsory
    ECTS Credits : 6.0
    Semester : 2
    Course : 2

    COMPETENCES AND SKILLS THAT WILL BE ACQUIRED AND LEARNING RESULTS.
    This course offers an introduction to data analysis in Social Science with the assistance of the multiple regression model. The emphasis is on the interpretation of the model and the application of statistical inference techniques to solve relevant practical problems. The course discusses in detail how to make inferences under non-standard situations, relevant in Social Sciences, due to the nature of the variables in the model (qualitative, transformed to allow nonlinear relations or non-observable,) or to the nature of data. The rigorous formal justification of the applied statistical inference techniques is out of the scope of this course. The background in Probability, Statistics, Algebra and Calculus offered in Mathematics I & II and Statistics I & II is more than enough for this course. At the end of the course, the student will acquire a good working knowledge on the interpretation of the linear
    regression model, discriminating between alternative specifications by means of statistical inference, and using GRETL for estimation and hypothesis testing.

    DESCRIPTION OF CONTENTS: PROGRAMME
    This course offers an introduction to data analysis in Social Science with the assistance of the multiple regression model. The emphasis is on the interpretation of the model and the application of statistical inference techniques with the objective of solving relevant practical problems. The course discusses in detail how to make inferences under non-standard situations, relevant in Social Sciences, due to the nature of the variables in the model (qualitative, transformed to allow nonlinear relations or non-observable) or to the nature of data.

    The course follow Chapters 1 to 8 and 15 of Wooldridge (2009).

    Syllabus:
    1. The nature of econometrics and economic data (Wooldridge Ch. 1)
    2. The simple regression model (Wooldridge Ch. 2).
    3. Multiple regression analysis: estimation (Wooldridge Ch. 3)
    4. Multiple regression analysis: inference (Wooldridge Ch. 5)
    5. Multiple regression analysis: OLS asymptotics (Wooldridge Ch. 5)
    6. Multiple regression analysis: further issues (Wooldridge Ch. 6)
    7. Multiple regression analysis with qualitative information: binary (or dummy) variables (Wooldridge Ch. 7).
    8. Heteroskedasticity (Wooldridge Ch. 8).
    9. Instrumental variables estimation and two stages least squares (Wooldridge Ch. 15).

    LEARNING ACTIVITIES AND METHODOLOGY
    The free software GRETL is the main learning tool of this course. The different concepts are discussed in the context of analyzing relevant cases of study in Social Sciences using real data.
    Homeworks, to be handed in class periodically, require to use GRETL.
    The text of the course is Wooldridge (2003). Chapters 1-8 and the 15 are covered. Data sets and cases of study discussed are those of this textbook.

    ASSESSMENT SYSTEM
    The continuous evaluation consists of 2 exams during the curse, whose grade will depend also on the homeworks handed in according to the instructor criteria.
    Continuous Evaluation Grade = Exam 1 × 0,3 + Exam 2 × 0,7
    "Convocatoria Ordinaria" Final Grade = Continuous Evaluation × 0,4 + Final × 0,6
    "Convocatoria Extraordinaria" Final Grade= max{Continuous Evaluation × 0,4+ Final × 0,6; Final}
    % end-of-term-examination: 60
    % of continuous assessment (assigments, laboratory, practicals?): 40

    BASIC BIBLIOGRAPHY
    - Wooldridge, J.M. Introductory Econometrics. A Modern Approach, South-Western College Publishing, 2009
    - Goldberger, A.S. Introductory Econometrics, Harvard University Press, 1998
    - Gujarati, D.N. Basic Econometrics, McGraw-Hill, 2009
    - Stock, J.H. & M.W. Watson Introduction to Econometrics, Addison Wesley, 2007
    - Greene, W.H. Econometric analysis , Prentice Hall, 2008
    - Jonhston, J. Econometric Methods, The McGraw-Hill Companies, 1997

    ADITIONAL BIBLIOGRAPHY
    - Wooldridge, J.M. Econometric analysis of cross section and panel data , The MIT Press, 2009
    - Hayashi, F. Econometrics, Princeton University Press, 2000

Course Disclaimer

Please note that there are no beginning level Spanish courses offered in this program.

Courses and course hours of instruction are subject to change.

Eligibility for courses may be subject to a placement exam and/or pre-requisites.

Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.

ECTS (European Credit Transfer and Accumulation System) credits are converted to semester credits/quarter units differently among U.S. universities. Students should confirm the conversion scale used at their home university when determining credit transfer.

Please reference fall and spring course lists as not all courses are taught during both semesters.

Availability of courses is based on enrollment numbers. All students should seek pre-approval for alternate courses in the event of last minute class cancellations

Please note that some courses with locals have recommended prerequisite courses. It is the student's responsibility to consult any recommended prerequisites prior to enrolling in their course.