First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
STATISTICAL SCIENCES
Course unit
STATISTICAL MODELS FOR ECONOMIC DATA
SCP4063394, A.A. 2019/20

Information concerning the students who enrolled in A.Y. 2018/19

Information on the course unit
Degree course Second cycle degree in
STATISTICAL SCIENCES
SS1736, Degree course structure A.Y. 2014/15, A.Y. 2019/20
N0
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Number of ECTS credits allocated 9.0
Type of assessment Mark
Course unit English denomination STATISTICAL MODELS FOR ECONOMIC DATA
Website of the academic structure http://www.stat.unipd.it/studiare/ammissione-laurea-magistrale
Department of reference Department of Statistical Sciences
E-Learning website https://elearning.unipd.it/stat/course/view.php?idnumber=2019-SS1736-000ZZ-2018-SCP4063394-N0
Mandatory attendance No
Language of instruction Italian
Branch PADOVA
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge MASSIMILIANO CAPORIN SECS-S/03

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses SECS-S/03 Statistics for Economics 9.0

Course unit organization
Period First semester
Year 2nd Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Lecture 9.0 64 161.0 No turn

Calendar
Start of activities 30/09/2019
End of activities 18/01/2020
Show course schedule 2019/20 Reg.2014 course timetable

Examination board
Board From To Members of the board
5 Commissione a.a.2019/20 01/10/2019 30/09/2020 CAPORIN MASSIMILIANO (Presidente)
BERNARDI MAURO (Membro Effettivo)
BISAGLIA LUISA (Membro Effettivo)

Syllabus
Prerequisites: Those required by the rules of the degree course.
Target skills and knowledge: The course objective is to provide students the tools needed to build and use statical models, mostly of dynamic nature, in the presence of economic darta. The introduction and the study of the main feature of the various model classes will be accompanied by the economic interpretation of the models outcome with examples based on real data.
Examination methods: Written exam with theoretical questions and practical exercises.
Assessment criteria: The evaluation points at verifying the ability of the student to build models adequate to the analysis of economic data, and to interpret the model outcome from an economic point of view.
Course unit contents: Introduction: classification and features of economic data; main classes of models relevant for the analysis of economic relationships.
Multivariate time series models: VAR, SVAR and VECM models, identification, estimation and use.
Panel data models: estimation and specification with one-way error component; dynamic panel data models.
Simultaneous equations models: structural form, reduced form, identification and estimation (main principles).
State-space models: examples, specifications, estimation and use (main principles).
Planned learning activities and teaching methods: Theoretical lectures. Examples with real data for the economic interpretation of model results. Analytical exercises sessions.
Additional notes about suggested reading: Main book references: Lutkepohl and Baltagi.
Slides.
Textbooks (and optional supplementary readings)
  • Greene W. H., Econometric Analysis (7th edition). --: Prentice Hall, 2012. Cerca nel catalogo
  • Baltagi, B. H., Econometric Analysis of Panel Data (4th edition). --: Wiley, 2008. Cerca nel catalogo
  • Tsay R. S., Multivariate Time Series Analysis With R and Financial Applications. --: Wiley, 2014. Cerca nel catalogo
  • Durbin J. and Koopman S.J., Time Series Analysis by State Space Methods (2nd edition). --: Oxford University Press, 2012. Cerca nel catalogo
  • Petris G., Petrone S., Campagnoli P., Dynamic Linear Models with R. --: Springer, 2009. Cerca nel catalogo
  • Lutkepohl, H., New Introduction to Multiple Time Series Analysis. --: Springer, 2007. Cerca nel catalogo