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Course 2023-2024 a.y.

20358 - ECONOMETRICS - PREPARATORY COURSE

Department of Economics

Course taught in English

DES-ESS (I/II sem. - P) - EMIT (I/II sem. - P) - GIO (I/II sem. - P) - DSBA (I/II sem. - P) - PPA (I/II sem. - P)
Course Director:
GIOVANNI BRUNO

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


Synchronous Blended: Lessons in synchronous mode in the classroom (for a maximum of one hour per credit in remote mode)

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 06/07/2023 08:22