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Accreditata MUR con D.M. 02/12/2005
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Economia, management e mercati internazionali, classe L-33

Applied Economics: Industries, Markets, Regions


Anno accademico: 2021/2022



Crediti: 9 ECT CFU

Scarica il programma

  • January 2020- ongoing: Fixed-term researcher type A at the University of Naples Parthenope.
  • May 2021- January 2022: Research fellow at the Interdepartmental Research Centre Laboratory of Urban and Regional Planning “Raffaele d’Ambrosio” (L.U.P.T.) of the University of Naples Federico II.
  • March 2021- ongoing: Lecturer for the course of Other Knowledge Useful for the World of Work-Problem Solving (3 CFU) for the IUL Online University (L-33 – Class of degrees in Economics).
  • March 2021- November 2021: University Tutor for the course of Institutions of Economics (SECS-P/01 -9 CFU) for the IUL Online University (L-33 – Class of degrees in Economics). Massimiliano Cerciello.
  • November 2020-November 2021: University Tutor for the teaching of Introduction to Mathematics and Principles of Financial Mathematics (SECS-S/06 -9 CFU) for the IUL Online University (L-33 – Class of degrees in Economics). Sonia Lombardi.
  • November 2017-July 2021: PhD in Economics, Statistics and Sustainability- Cycle XXXIII- at the University of Naples Parthenope.
  • November 2019-December 2019: Visiting Researcher at Athens University of Economics and Business (AUEB), Athens (GR).
  • January 2019-October 2019: University Tutor for the course of Microeconomics (SECS-P/01-9 CFU) for the University of Naples Parthenope (L-33 – Class of degrees in Economics).
  • September 2016-July 2017: Second level Master in Economics and Finance at the University of Naples Federico II.
  • February 2014-April 2016: Master’s degree in Economics and Finance at the University of Naples Parthenope with grade 110L/110. Supervisor: Prof. Giuseppe De Marco. Dissertation title: “Multifractals Models in Finance”.
  • October 2010-February 2014: Bachelor’s degree in Economics at the University of Naples Parthenope with a mark of 104/110. Supervisor: Prof. Enrico Marchetti. Dissertation title: “La recente crisi italiana tra vincoli monetari e sostenibilità del debito pubblico”.



The course consists of 3 modules:

  • Module 1 – Recalls of Statistics and Introduction to GRETL
  • Introduction to Statistics.
  • Recalls of Descriptive Statistics.
  • Introduction to Inferential Statistics.
  • Recalls of Inferential Statistics.
  • Recalls of Econometrics.
  • GRETL: Introduction.


  • Module 2: Applications of Statistics in GRETL
  • Simple Linear Regression.
  • Multiple Linear Regression.
  • Forecasting and Goodness of Estimate.
  • Linear Regression with Time Series I.
  • Linear Regression with Time Series II.
  • Linear Regression with Panel Data.


  • Module 3: Applications in Macroeconomics and Finance
  • Macroeconomic time series.
  • Applications for Macroeconomics I.
  • Applications for Macroeconomics II.
  • Financial Time Series.
  • Applications for Finance I.
  • Applications for Finance II.

IUL’s “Applied Economics: Industry, Markets, and Regions” teaches students statistical thinking concepts essential for learning from data and communicating insights. By the end of the course, you will be able to perform simple and multiple regression analysis, understand key principles of time series analysis and select appropriate tests of significance for multiple contexts.


This course introduces “GRETL”, the official econometrics application for Introduction to Econometrics. This course seeks to present the structure and philosophy for data analysis implemented in GRETL, showing its potentiality by presenting applications in the economic, business, and financial fields.


This course is divided into 3 main modules:

  • Module 1: Review of Statistics and Introduction to GRETL.
  • Module 2: Applications of Statistics in GRETL.
  • Module 3: Applications for Macroeconomics and Finance

The coures aims to provide the following tools

  • Module 1: Understanding and applying theoretical models for statistical-econometric evaluations applicable to economic, financial and business situations.
  • Module 2: Learning application skills using GRETL software.
  • Module 3: Developing a logic to handle the countless cases in which GRETL software is used, enabling the student to move as a professional in the world of data science.

A. Knowledge and understanding
Understanding the functioning of theoretical models for statistical-econometric evaluations of economic, financial and business issues; knowledge of application techniques using GRETL software; ability to understand and analyse economic, business and financial issues using computational techniques.

B. Applied knowledge and understanding
Measuring, estimating and assessing relationships between macroeconomic, financial aggregates and business choices; carrying out quantitative and qualitative data analysis with a focus on economic and/or financial decision-making processes, also exploiting the opportunities arising from the availability of large data aggregates; estimating the parameters of a statistical – econometric model, quantifying the effect of one variable on another, verifying assumptions of interest on parameters, correct model specification, forecasting; estimating and verifying economic – business relationships on the basis of available empirical evidence.

C. Autonomy of judgement
Ability to take reasoned and sustainable positions with reference to economic issues; autonomously search and find data, information, sources, doctrine for economic, business and financial evaluations; autonomously use and rework data collected; autonomously apply theoretical models for evaluation purposes.

D. Communication skills
Use of technically correct and effective vocabulary in a professional context; argumentation on economic, business and financial issues, with language mastery and adequate scientific references; proper use of the IT tools learnt.

E. Learning ability
Developing a study method appropriate to the different fields, functional to the autonomous development of knowledge/competences (the acquisition of a study method that is not mechanical or mnemonic, but reasoned and focused on concepts); ability to carry out autonomous statistical analyses in the GRETL environment.


A. Use of advanced textbooks, knowledge of some cutting-edge topics within the subject studied.

B. Professional approach to work and possession of appropriate skills to devise arguments, support them and to solve problems within the subject studied. Ability to collect and interpret data useful for making independent judgements.

C. Ability to communicate information, ideas, problems and solutions to specialists and non-specialists.

D. Ability to undertake further studies with a high degree of autonomy.


  • 9 hours of recorded video lessons available on the platform.
  • 3 synchronous meetings on the
  • Podcasts of all the above-mentioned video lessons.



  • 1 course orientation forum.
  • 3 in-depth thematic forums (1 per module).
  • Possibility to carry out work in groups.
  • 3 structured e-activities (as described in the section in itinere assessment methods”).



Teaching materials are provided for each module: in-depth thematic studies, articles and slides by the lecturer, open access readings, online resources, reference bibliography, etc.

  • Borra, S., & Di Ciaccio, A. (2014). Statistica: metodologie per le scienze economiche e sociali. (p. 190). McGraw-Hill.
  • Hill, R. C., Griffiths, W. E., & Lim, G. C. (2020). Principi di econometria. Zanichelli.

Access to the final examination is subject to the following 3 e-activities:

  • Etivity 1 1 paper of approx. 1,000 words – module 1
  • Etivity 2 – n. 1 paper of approx. 1,000 words – module 2
  • Etivity 2 – n. 1 paper of approx. 1,000 words – module 3

The assessment of learning will take the form of an oral interview on the course contents and on the final report submitted, if any. The grade (min 18, max 30 with possible honours) is determined by the level of performance for each of the following dimensions of the oral presentation: mastery of contents, appropriateness of definitions and theoretical references, clarity of argument, command of specialist language