Objectives

This course has the main following objectives:

  • Provide trainees with knowledge of econometrics – the statistical methods applied in economics to test socio-economic hypotheses and forecast social-economic variables.
  • Provide trainees data analysis and software skills to conduct regressions and tests.
  • The course will focus mainly on the practical applications of econometrics.

Trainees

The course is open to all; individuals who have basic statistics knowledge and are interested in the courses are encouraged to enroll . The course is relevant for graduate students and researchers from universities, research institutes, and ministries.

Textbook

Wooldridge, Jeffrey M. (2008). Introductory Econometrics: A Modern Approach. South-Western College Publishers, Fourth Edition (ISBN: 9780324581621).

Software

Stata

Course prerequisites

  • Basic statistics
  • Basic mathematics

  • Content of the course

    The course will last for 5 days with the contents as follows:

    Day 1

    Chapter 1. The Nature of Econometrics and Economic Data

    Chapter 2. The Simple Regression Model

    Chapter 3. Multiple Regression Analysis: Estimation

    Chapter 4. Multiple Regression Analysis: Inference

    Day 2

    Chapter 5. Multiple Regression Analysis: OLS Asymptotics

    Chapter 6. Multiple Regression Analysis: Further Issues

    Chapter 7. Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables

    Chapter 8. Heteroskedasticity

    Day 3

    Chapter 9. More on Specification and Data Problems

    Chapter 10. Basic Regression Analysis with Time Series Data

    Chapter 11. Further Issues in Using OLS with Time Series Data

    Chapter 12. Serial Correlation and Heteroskedasticity in Time Series Regressions

    Day 4

    Chapter 13. Pooling Cross Sections Across Time. Simple Panel Data Methods

    Chapter 14. Advanced Panel Data Methods

    Chapter 15. Instrumental Variables Estimation and Two Stage Least Squares

    Day 5

    Chapter 16. Simultaneous Equations Models

    Chapter 17. Limited Dependent Variable Models and Sample Selection Corrections

    Chapter 18. Advanced Time Series Topics