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Course 2019-2020 a.y.

30464 - EMPIRICAL RESEARCH METHODS AND DATA ANALYSIS

BESS-CLES
Department of Economics

Course taught in English

Go to class group/s: 13

BESS-CLES (7 credits - I sem. - OB  |  SECS-P/01)
Course Director:
JEROME FRANS ADDA

Classes: 13 (I sem.)
Instructors:
Class 13: JEROME FRANS ADDA


Suggested background knowledge

The course is built on prior knowledge of econometric methods, statistics and economic modelling.


Mission & Content Summary
MISSION

The course aims at introducing students to empirical research methods and data analysis. The course brings two sets of skills, practical skills to analyze data but also an introduction to how research is being done and evaluated. The first part of the course reviews common econometric methods and introduce students to a widely used statistical software (Stata) through examples and case studies. The second part of the course lets the students elaborate their own research idea and guide them through its implementation and final presentation in class.

CONTENT SUMMARY
  • Overview of common econometric methods such as ordinary least squares, difference-in-difference and regression discontinuity.
  • Implementation of those methods using Stata, a statistical software.
  • Work on group specific projects to develop a research question, derive a related empirical model and statistical analysis of data. 

Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • Capacity to define a relevant research question.
  • Capacity to derive a relevant econometric model and tools.
  • Capacity to apply those tools to economic data.
  • Capacity to interpret the results and express a critical view on them.
APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • Formulate a relevant research question.
  • Devise a strategy to investigate this question with data.
  • Understand the difference between different econometric methods.
  • Apply the relevant method to answer a particular question.
  • Master common econometric and data handling commands.
  • Present the research output in a clear way that can be discussed by peers.
  • Offer critical views on research produced by others.

Teaching methods
  • Face-to-face lectures
  • Online lectures
  • Exercises (exercises, database, software etc.)
  • Group assignments
  • Interactive class activities (role playing, business game, simulation, online forum, instant polls)
DETAILS
  • Online lectures to gain deeper knowledge of the statistical software.
  • Exercises to gain deeper knowledge of the statistical software.
  • Group assignments to work on a research project (definition, statistical analysis and report).
  • Interactive class activities to discuss and offer critical views on other groups work.

Assessment methods
  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
  • x   x
  • Group assignment (report, exercise, presentation, project work etc.)
  • x   x
  • Peer evaluation
  • x    
    ATTENDING STUDENTS
    • Online assessment with closed answers on specific parts of the course.
    • Group assignment to formulate a research question and to do statistical analysis.
    • Peer evaluation on the results produced by each group.
    NOT ATTENDING STUDENTS
    • Written online exam on all parts covered in the course.

    Teaching materials
    ATTENDING AND NOT ATTENDING STUDENTS
    • ANGRIST, PISCHKE,  Mostly Harmless Econometrics: An Empiricist's Companion, 2009. 1st Edition.

    • Online video tutorials on Stata (many are available on YouTube).

    • Empirical research articles to be communicated this summer.

    Last change 01/06/2019 09:35