Insegnamento a.a. 2022-2023

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


Mission & Content Summary

MISSION

The course intends to provide students with an introduction to methods of linear regression in econometrics.

CONTENT SUMMARY

Matrix algebra useful for linear regression:

-matrix operations;

-determinants;

-linear independence;

-rank;

-inverse matrix;

-vector spaces and projection matrices;

-quadratic forms;

-calculus.  

Linear regression:  

-parameter identification

-parameter estimation;

-hypothesis testing;

-specifications tests;

-linear regression using Stata

 


Intended Learning Outcomes (ILO)

KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...

      

 

APPLYING KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...

apply the main procedures of linear regression in econometrics


Teaching methods

  • Face-to-face lectures

DETAILS

      

 


Assessment methods

  Continuous assessment Partial exams General exam
  • Active class participation (virtual, attendance)
 x    

ATTENDING AND NOT ATTENDING STUDENTS

     

 


Teaching materials


ATTENDING AND NOT ATTENDING STUDENTS

Lecture notes, slides and Stata material will be uploaded in BBoard at the beginning of the course. 

Last change 09/06/2022 23:01
Go to modules: E-learning class-group
DSBA (I/II sem. - P)
Course Director:
GIOVANNI BRUNO

Classes: 1 (I/II sem.)
Instructors:
Class 1: GIOVANNI BRUNO


Mission & Content Summary

MISSION

The course intends to provide students with an introduction to methods of linear regression in econometrics.

CONTENT SUMMARY

Matrix algebra useful for linear regression:

-matrix operations;

-determinants;

-linear independence;

-rank;

-inverse matrix;

-vector spaces and projection matrices;

-quadratic forms;

-calculus.  

Linear regression:  

-parameter identification

-parameter estimation;

-hypothesis testing;

-specifications tests;

-linear regression using Stata


Intended Learning Outcomes (ILO)

KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...

    

 

APPLYING KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...

apply the main procedures of linear regression in econometrics


Teaching methods

  • Face-to-face lectures

DETAILS

    

 


Assessment methods

  Continuous assessment Partial exams General exam
  • Active class participation (virtual, attendance)
 x    

ATTENDING AND NOT ATTENDING STUDENTS

   

 


Teaching materials


ATTENDING AND NOT ATTENDING STUDENTS

Lecture notes, slides and Stata material will be uploaded in BBoard at the beginning of the course. 

Last change 10/06/2022 15:14