Course 2020-2021 a.y.

20358 - ECONOMETRICS - PREPARATORY COURSE

Department of Economics
Course taught in English
Insegnamento offerto in modalita' e-learning
DES-ESS (I/II sem. - P) - EMIT (I/II sem. - P) - GIO (I/II sem. - P) - PPA (I/II sem. - P)
Course Director:
GIOVANNI BRUNO

Module: E-learning class-group
Instructors:
Class 1: GIOVANNI BRUNO


Class-group lessons delivered online

Mission & Content Summary

MISSION

The course provides an introduction to the use of econometric methods in economics. A good knowledge of undergraduate Mathematics and Statistics is required. Matrix algebra is reviewed in depth. The main topics studied in the course are the linear regression model, parameter estimation and hypothesis testing, model specification and model selection. The topics are addressed both from a theoretical point of view and by means of computer based empirical applications.

CONTENT SUMMARY

The linear regression model:

  • Specification, underlying hypotheses.
  • Parameter estimation, one regressor case.
  • Parameter estimation, many regressors case.
  • Interpreting the estimated parameters.
  • Properties of the estimators.
  • Analysis of variance, R2.
  • Interval estimation Hypothesis testing, the t- and F-tests.
  • Collinearity, omitted variables, redundant variables Examples.
  • Matrix algebra.

Teaching methods

  • Face-to-face lectures

DETAILS


Assessment methods

  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
     x

Teaching materials


ATTENDING AND NOT ATTENDING STUDENTS

  • W.H.GREENE, Econometric Analysis, Prentice Hall, 2007, 6th edition. 
  • J.M. WOOLDRIDGE, Introductory econometrics, SOUTH WESTERN-CENGAGE, 2009, 4th edition. 
Last change 28/07/2020 13:19