Scheda programma d'esame
QUANTITATIVE ECONOMICS FOR BUSINESS
MARCO MARTINEZ
Academic year2022/23
CourseMANAGEMENT FOR BUSINESS AND ECONOMICS
Code548PP
Credits6
PeriodSemester 2
LanguageEnglish

ModulesAreaTypeHoursTeacher(s)
QUANTITATIVE ECONOMICS FOR BUSINESSSECS-P/05LEZIONI42
MARCO MARTINEZ unimap
SIMONE TONINI unimap
Programma non disponibile nella lingua selezionata
Learning outcomes
Knowledge

The course objective is to introduce you to the study of econometrics with a predominantly applied approach. The courses discuss theoretical aspects of the discipline but it emphasizes their empirical application to economic and policy-relevant questions.

Assessment criteria of knowledge

There will be two take-home assignments to be completed during the Easter Break (due 15th of April) and by the end of May (due 31st of May), respectively. No delays are allowed in the delivery of the take-home assignments. Each homework is worth 15% of the final grade.

 

Passing both homeworks allows you to then complete the course with a written assessment worth 70% of the grade. You are strongly encouraged to complete the homeworks and then complete the final 70% assessment.

You can also complete the homeworks if you cannot attend the course in person, provided that you deliver your assignments on time. If you are interested in the homework and cannot attend the course, please send an email to the lecturers.

 

The alternative route is a longer and more comprehensive written final exam, worth 100% of the final grade.

Skills

Students who successfully complete Quantitative Economics for Business should be comfortable with basic statistics and probability.

They should be able to use a statistical/econometric computer package to estimate an econometric model and be able to report the results of their work in a non-technical and literate manner.

In particular, a student who successfully completes Quantitative Economics for Business will be able to estimate and interpret linear regression models and be able to distinguish between economic and statistical importance. They should be able to critique reported regression results in applied academic papers and interpret the results for someone who is not trained as an economist.

Assessment criteria of skills

Small projects will be carried out in order to understand how to use the R statistical software.

Prerequisites

It is requested a basic knowledge of statistics.

Teaching methods

There will be a mixture of theoretical and practical lessons.

Syllabus
  1. Introduction to R and basic concepts of statistics
  2. Hypothesis testing and introduction to linear regressions with a single regressor
  3. Linear regression with a single regressor: hypotheses testing and confidence intervals
  4. Linear regression with multiple regressors
  5. Linear regression with multiple regressors: hypotheses testing and confidence intervals.
  6. Linear regression with binary dependent variables
  7. Non-linear regression
  8. Impact evaluation based on multiple regression
  9. Regression with panel data
  10. Instrumental variables regression
Bibliography

Stock, J. H. e Watson, M.W: Introduction to Econometrics, Third Update, Global Edition.

Additional useful, but non-compulsory, material will be provided during the course.

Assessment methods

Your grade will consist of:

  • Homework assignments (15%+15%)
  • Final exam (70%) 

The alternative route is a longer and more comprehensive written final exam, worth 100% of the final grade.

Notes

The course can only be attended in person (not online).

Updated: 10/03/2023 18:44