First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
STATISTICS FOR ECONOMICS AND BUSINESS
Course unit
STRUCTURAL MODELS FOR ECONOMIC AND SOCIAL SCIENCES
SCP4063771, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2016/17

Information on the course unit
Degree course First cycle degree in
STATISTICS FOR ECONOMICS AND BUSINESS
SC2095, Degree course structure A.Y. 2014/15, A.Y. 2018/19
N0
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Number of ECTS credits allocated 9.0
Type of assessment Mark
Course unit English denomination STRUCTURAL MODELS FOR ECONOMIC AND SOCIAL SCIENCES
Website of the academic structure http://www.stat.unipd.it/studiare/ammissione-lauree-triennali
Department of reference Department of Statistical Sciences
E-Learning website https://elearning.unipd.it/stat/course/view.php?idnumber=2018-SC2095-000ZZ-2016-SCP4063771-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 ADRIANO PAGGIARO SECS-S/03

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines SECS-S/03 Statistics for Economics 9.0

Course unit organization
Period Second semester
Year 3rd Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Laboratory 2.0 16 34.0 No turn
Lecture 7.0 48 127.0 No turn

Calendar
Start of activities 25/02/2019
End of activities 14/06/2019
Show course schedule 2019/20 Reg.2014 course timetable

Examination board
Board From To Members of the board
3 Commissione a.a.2018/19 01/10/2018 30/09/2019 PAGGIARO ADRIANO (Presidente)
BERNARDI MAURO (Membro Effettivo)
BISAGLIA LUISA (Membro Effettivo)

Syllabus
Prerequisites: Statistica 2, Modelli Statistici 1
Target skills and knowledge: The course presents different approaches and statistical methods used for applications in the economic field, both from the methodological point of view and with numerous case studies on real data.
Through the laboratory activities, the course also provides the tools for using the Stata software, one of the main tools used for statistical analysis in the economic and econometric fields.

The goal is to allow the student to be able to:
1. Define in detail a research question of interest in the economic field which can be answered with an empirical approach.
2. Identify the most suitable method to solve a specific problem and understand the assumptions needed to answer the question of interest.
3. Use the method appropriately with the Stata software.
4. Interpret the results correctly in light of the initial question, the assumptions made and the available data.
Examination methods: Knowledge and skills are verified by means of a practical test using the computer and a subsequent oral discussion of the results. The test consists in analyzing a dataset containing economic data and answering some written questions related to the chosen method, the plausibility of its assumptions in the specific context and the interpretation of the resulting empirical results. The oral discussion deals with the presented analyses and links them to the methods presented in the course.
Assessment criteria: The evaluation of the student's preparation is based on:
- Understanding of a research question and ability to provide a coherent answer based on the available data.
- Autonomy and critical attitude in choosing and applying the methodologies acquired in the course for the solution of specific real cases.
Course unit contents: 1) Introduction to modeling in the economic field
- Specification and economic interpretation of parameters
- Structural parameters and reduced form

2) Specification and estimation of linear models
- Model specification and interpretation of the assumptions in economic applications
- OLS estimation
- Heteroschedasticity, GLS estimates and robust standard errors
- Characteristics of variables (categorical variables, non-linear transformations, interactions)
- Exogenous and endogenous variables

3) Introduction to advanced methods for the analysis of economic data
- Analysis of longitudinal data
- Instrumental variables
- Simultaneous equation models
- Non-linear models
- Policy impact evaluation
Planned learning activities and teaching methods: The course is organized in lectures (48 hours) with joint use of tablet and traditional whiteboard, in which are presented the main methodological aspects and numerous empirical applications in the economic field, and case studies in the computer room (16 hours) where students can apply the acquired knowledge by analyzing real data with the Stata software. In both cases there is a continuous interaction with the students in order to discuss alternative solutions to the proposed research questions.
Among the soft skills, the course and the modalities of examination are linked to the active use of a software, the development of research skills and problem solving skills and a certain dose of creativity to identify and compare possible alternative solutions to the same question.
Additional notes about suggested reading: The lessons follow the textbook both for the theoretical part and the numerous empirical examples, which are then partly used in the computer room. Additional material is available on the Moodle platform.
Textbooks (and optional supplementary readings)
  • Wooldridge, Jeffrey M., Introduction to econometrics. Andover: Cengage Learning, 2014. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Laboratory
  • Problem based learning
  • Case study
  • Interactive lecturing
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)
  • One Note (digital ink)
  • Stata

Sustainable Development Goals (SDGs)
Quality Education Gender Equality Decent Work and Economic Growth