Unit ECONOMETRICS
- Course
- Finance and quantitative methods for economics
- Study-unit Code
- A003080
- Location
- PERUGIA
- Curriculum
- Statistical data science for finance and economics
- Teacher
- Carlo Andrea Bollino
- Teachers
-
- Carlo Andrea Bollino
- Hours
- 42 ore - Carlo Andrea Bollino
- CFU
- 6
- Course Regulation
- Coorte 2023
- Offered
- 2023/24
- Learning activities
- Caratterizzante
- Area
- Economico
- Academic discipline
- SECS-P/05
- Type of study-unit
- Obbligatorio (Required)
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
English- Contents
The Econometrics course provides the analytical tools and fundamental methods for the study of economic relations and for the quantification of structural parameters. The student acquires autonomous skills of estimation and modeling of the quantities and relationships of economic theory.- Reference texts
J.H. Stock M.W. Watson, Introduction to econometrics, Pearson, 2012- Educational objectives
Obiettivi formativi OBIETT_FORM Sì Offrire agli studenti gli strumenti pratici con il quale elaborare analisi empiriche dei vari modelli econometrici To provide to students the practical tools through which carry out empirical analysis for the various econometric models- Prerequisites
Statistics- Teaching methods
Theoretical lessons present the estimation methods and the practical lessons show the student the use of the R software, the main functions and codes used in the empirical analyses.- Other information
For information on support to students with disabilities, see: http://www.unipg.it/disabilita-e-dsa".- Learning verification modality
Students can develop an essay in which they will present the econometric analysis carry out on empirical datasets proposed by the tutor
Students with disabilities and/or with DSA are invited to visit the page dedicated to the tools and measures envisaged and to agree in advance what is necessary with the teacher (https://www.unipg.it/disabilita -e-dsa)- Extended program
1) Installing R and Rstudio
2) Basic Programming Concept and Terminology
3) R Packages
4) First Practical Session
5) Data Visualization
6) Data Wrangling
7) Basic Regression Models
8) Test of Hypothesis- Obiettivi Agenda 2030 per lo sviluppo sostenibile
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