Econometric Techniques

Universidad Carlos III de Madrid

Course Description

  • Course Name

    Econometric Techniques

  • Host University

    Universidad Carlos III de Madrid

  • Location

    Madrid, Spain

  • Area of Study

    Business Administration, Economics, International Economics, Peace and Conflict Studies

  • Language Level

    Taught In English

  • Course Level Recommendations


    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

  • Recommended U.S. Semester Credits
  • Recommended U.S. Quarter Units
  • Overview

    The goal of this course is understand the time evolution of the most relevant economic time series (GNP, Unemployment, inflation, interest rates, exchange rates, financial asset prices, etc.) and the analysis of the dynamic causal relationships existing among those variables in order to perform forecasts and economic policy analysis.
    To achieve this goal, the student must acquire knowledge, abilities (specific and general) and attitudes.
    Knowledge: At the end of the course the student will be able to:
    - Construct adequate models to obtain forecasts
    - Construct adequate models to analyze causal relationships between economic variables
    - To analyze the growth of economic variables and their long-term relationship.
    In term of concrete questions, the student will learn to answer in a quantitative and synthetic way, via an empirical project, to questions of this type:
    - How interest rates affect economic growth, employment level, prices, etc.?
    - How economic growth affects C02 levels, and those affect temperature?
    - Is it possible to forecast the returns of financial assets?
    Specific abilities:
    - Isolate and analyze the main characteristics of the evolution of economic data.
    - Distinguish different types of data and the components of a time series.
    - Build appropriate models for testing economic hypotheses and forecasting.
    - Evaluate and criticize different approaches for dealing with an applied problem.
    General skills
    - Solve complex problems.
    - Discrimination of relevant information contained in economic data on a problem.
    - Relate different description measures of data and diagnostics on the validity of a model.
    - Flexibility on the use of a model for different goals.
    - Use of computer packages of econometric modeling.
    - Analysis and synthesis.
    - Group work.
    - Oral, written and graphical communication skills.
    - Critic attitude on solutions and models provided by alternative analysts.
    - Constructive attitude based on partial information and approaches.
    The basic contents of the course are:
    - Characteristics of time series data.
    - Univariate statitionary models.
    - Forecasting and model selection.
    - The linear regression model with autocorrelated error: robust inference.
    - Dynamic single-equation econometric models: endogeneity problems. Instrumental variables solutions (Two Step Least Squares). Endogeneity tests.
    - Dynamic multi-equation models (VAR) and causality analysis.
    - Non stationary processes: trend-cycle decomposition.
    - Regression with nonstationary variables: testing different economic theories.
    The teaching methodology minimizes the formal aspects, focusing on the intuitive discussion of concepts and intensive work with real data sets, aiming that the student reaches a practical mastering of econometrics with time series economic data.
    The course comprises lectures, and problem and practical classes:
    Lectures and problem classes:
    - They will use both blackboard and computer with projector.
    - Each section contains a typical empirical application.
    - The applied data analysis is performed with the packagae E-Views (or alternatively with the free software GRETL) and the database HIS Global Insight (reachable online through library).
    Computer practical classes:
    - Every week there will be a session in the computer room to solve applied empirical problems related with the empirical course project.
    Final Exam (60%) + Practical classes (20%) + Empirical Project (20%).
    Final exam: it assesses the knowledge acquired by the students in the course.
    The practical classes include problem sets related with the theoretical concepts developed in the course and student progress will be assessed through three-week quizzes in class.
    The empirical project is chosen by the student among the choices offered by the lecturer at the beginning of the course. It contains a maximum of five pages where the student has to show her/his capacity for synthesis and analysis, critic reasoning and a good command of quantitative tools.

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.


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