The course provides a common disciplinary basis that is divided into the following teachings:
- Databases for Bibliographic Research (8 hours; first year)
- Statistical Methods for the Analysis of Economic and Business Data (36 hours; first year)
- Qualitative Research Methodology (20 hours; first year)
- Quantitative Research Methodology (28 hours; first year)
- Game Theory (13 hours; first year)
- Big databases and economic analysis. An application on patent data (12 hours; first year)
Other Learning Activities
The course provides the following interdisciplinary and cross-skills activities:
- Language Enhancement
- Computer Enhancement
- Research and Knowledge Management of European and International Research Systems
- Valuing and Dissemination of Results, Intellectual Property, and Open Access to Research Data and Products
- Seminars
- Laboratory Activities
Course Schedule:
- Databases for Bibliographical Research (Cristina ZERBINI; Laura L'EPISCOPO - University of Parma)
The course aims to provide knowledge about the processes and methods of publishing research products and the useful tools to perform an adequate analysis of the scientific literature through databases.
The first part of the course focuses on the relevance of scientific publications for the advancement of international knowledge and personal career in academia. The different types of publication, the structure of a scientific paper, the choice of journal, and the process of review and publication are also covered through the sharing of any personal experiences lived by doctoral students.
During the second part of the course, the focus shifts to literature review: from the choice of keywords, to the use of the various databases that the University of Parma provides (e.g., Ebsco Host, Emerald, Essper) as well as other sources available online (e.g., Researchgate, Academia.edu, Scienceopen, Iris, sole24ore), to reference management software (Zotero and Mendeley cite). The course will include hands-on classroom exercises by participants.
Lecture schedule and timetable
Wednesday, December 14, 2022 HOURS 10 am-1 pm - UNIPR
Wednesday, December 14, 2022 HOURS 2 pm-17 - UNIPR
Thursday, December 15, 2022 HOURS 10 a.m.-1 p.m. - UNIPR
- Statistical Methods for the Analysis of Economic and Business Data (Andrea CERIOLI; Fabrizio LAURINI - University of Parma)
The course aims to homogenize doctoral students' knowledge on some advanced statistical methodologies, of particular relevance in economic-business sciences and typically applicable to big data. The course consists of two modules.
The first module focuses on statistical models and algorithms oriented to prediction and segmentation. The methodologies analyzed are: measures of association and association rules, as well as their applications to Market Basket Analysis; the linear regression model, of which both classical inferential aspects and diagnostic techniques to reveal violations of basic assumptions are covered; the logistic regression model, developed mainly for predictive purposes of individual behavior; classification trees, for which the issues of overfitting and estimation of misclassification rates are also addressed; Cluster Analysis and the non-hierarchical K-means segmentation algorithm. All methodologies are applied to examples of economic or business interest using SPSS software.
The second module focuses on the development of theory and algorithms aimed at describing phenomena characterized by dynamics that evolve over time. Two complementary strands are addressed: the first extends multiple regression models to the case of data marked by seasonal data through seasonal ARIMA-type models. For these models, basic assumptions are introduced, all inferential results and post-fitting diagnostics are developed. The goal is the construction of models that can be used to provide reliable predictions in the short to medium term. The regression model is subsequently extended to the case of data present in panel form. The methodological part will be accompanied by practical exercises where students can test what they have learned in the methodological sessions. Two assigments are scheduled at the end of the course.
Lecture schedule and timetable
Thursday, December 15, 2022 14 - 18
Tuesday, January 10, 2023 9 - 13
Thursday, January 19, 2023 9 - 13
Tuesday, January 24, 2023 HOURS 9 - 13
Wednesday, January 25, 2023 HOURS 10-13 and 14 - 16
Thursday, January 26, 2023 HOURS 9 - 13
Tuesday, January 31, 2023 HOURS 10 - 13 - 14 - 16
Tuesday, February 7, 2023 HOURS 9 - 13 (UNIPR)
- Methodology of Qualitative Research (Caterina CAVICCHI; Emidia VAGNONI; Giovanni MASINO; Chiara OPPI - University of Ferrara)
The module intends to introduce doctoral students to research design and then delve into qualitative research methodologies. Therefore, the following contents will be addressed:
- Definition of research topic;
- Identification of relevant research questions;
- Literature analysis and systematic literature review;
- Relationship between theory and research - hints of epistemology and ontology;
- Qualitative research methods - rationale, strengths and weaknesses;
- Approaches to qualitative research - ethnography, grounded research, action research, narrative research, case studies;
- Qualitative case studies - research design and how to collect data;
- Action research - research design and how to conduct it;
- Data collection methods - focus groups and qualitative interviews;
- Data analysis methods - text analysis and content analysis.
Lecture Schedule and Timetable
Oppi March 8, 2023 HOURS 11am-1pm - UNIFE
Oppi March 15, 2023 HOURS 2:30pm-4pm:30 - UNIFE
Masino March 28, 2023 HOURS 10am-1pm - UNIFE
Cavicchi March 15, 2023 HOURS 11am-1pm UNIFE
Cavicchi March 29, 2023 HOURS 11am-1pm UNIFE
Vagnoni March 28 - postponed to April 13, 2-4 p.m. - UNIFE
Vagnoni May 8, 2023 HOURS 10 a.m. - 1 p.m. UNIFE
All lectures will be held in Lecture Hall EC4 in Ferrara, Pa, 11 Voltapaletto Street.
Final Verification
Presentation of a Qualitative Research Proposal - UNIFE
- Quantitative Research Methodology (Beatrice LUCERI; Donata Tania VERGURA; Simone AIOLFI - University of Parma)
The course aims to expand knowledge on the collection and analysis of primary and secondary data using different quantitative research techniques.
The first part focuses on the use of quantitative research techniques for primary data collection. The lectures delve into two research techniques. The focus is initially on the structured questionnaire and the main methods of data analysis, with emphasis on determining the validity and reliability of the measurement model. Subsequently, the lectures focus on the technique of experiments and quasi-experiments in order to understand the process of constructing the experimental protocol, the types of data collected, and the basic methods of analysis.
The second part of the course aims to provide the theoretical knowledge and application tools for conducting systematic reviews of the scientific literature based on a quantitative approach. First, the course focuses on the use of the open source software SciMAT for conducting longitudinal bibliometric analyses in order to map the cognitive structure and thematic evolution over time of a given strand of research. Secondly, the course offers an overview of the theoretical and practical tools useful for conducting a systematic literature review using meta-analysis and critically reading meta-analyses published in the scientific literature.
During the lectures, papers published in the scientific literature will be discussed and illustrated, and reference will be made to the use of some data analysis software (mainly SPSS).
At the end of the course, students are given sufficient time (about two months) to develop the research design of the research topic of interest and write the paper containing the research questions and hypotheses, the methodology employed and the expected results. The papers are evaluated individually and discussed collegially to pool strengths and weaknesses of the research designs.
Lecture Schedule and Timetable
Thursday, February 9, 2023 HOURS 9:30-13:30
Thursday, February 16, 2023 HOURS 9.30-13.30
Tuesday, February 21, 2023 HOURS 9.30-13.30
Thursday, February 23, 2023 HOURS 9.30-13.30
Tuesday, March 7, 2023 4 HOURS 9.30-13.30
Discussion group work: to be determined at the end of the course
- Game Theory (Chiara LODI - University of Urbino)
Game theory represents the strategic interaction between different agents and has become a relevant tool in economics studies. This course will provide the basic concepts related to game theory and different real-world applications. Specifically, the most famous games (Prisoner Dilemma, Battle of Sexes, Chicken Game) are presented in their original form and through examples from environmental economics. Some mathematical tools are provided, as well as a basic introduction of sequential games and concepts of bounded rationality. Lectures are devoted to the following topics:
- Basic concepts-rationality, payoffs, classification and representation of games, strategies and Nash equilibrium, prisoner's dilemma (original game, monopoly to duopoly; e.g., common access to natural resources);
- Main games: battle of the sexes (original game; e.g., battle of the sexes: mutually exclusive environmental project), chicken game (original game, transboundary species conservation policy), basic principal-agent model;
- Sequential games- Entrant-Incumbent game and Stackelberg competition;
- Bounded rationality and dynamic adaptive model.
Lecture Schedule and Timetable
Thursday, March 2, 2023 10 a.m.-12.30 p.m. - UNIFE
Friday, March 3, 2023 10 a.m.-12.30 p.m. - UNIFE
Thursday, March 30, 2023 10 a.m.-12.30 p.m. - UNIFE
Thursday, March 30, 2023 10 a.m.-12.30 p.m.00-12:30 - UNIFE
Friday, March 31, 2023 HOURS 10:00-12:30 - UNIFE
Thursday, April 13, 2023 HOURS 10:00-12:30 - UNIFE
- Big databases and economic analysis. An application on patent data (Ugo RIZZO; Nicolò BARBIERI; Marianna GILLI - University of Ferrara)
Given the importance of big data for decision making and policy making, the ability to analyze large databases has become increasingly important for researchers. This module aims to develop students' ability to manage and analyze large databases using the OECD patent database.
The data management employed is STATA and the fundamentals for its use are provided; precisely the content delivered is as follows:
- Open dataset; import datasets from other sources;
- Variables-types, command to create and replace them;
- Rename and label variables; how to code them;
- Learn the operation of if and looping commands (foreach, forvalues)
- Learn the operation of keep and drop commands; design subsets of data
The knowledge needed to describe data with STATA is provided and, precisely:
- Descriptive statistics;
- Building the main summary tables (estout) and graphs (two-way command).
The course continues with an introduction to patent databases, delving into the following aspects:
- OECD patent databases;
- Overview of the OECD Regpat database;
- Identification of key patent information (technology classes, citations, patent families, etc.);
- Construction of some key variables with patent data;
- Warning for the use of patent data for the study of innovations.
Finally, the course addresses the issue of using patent information for economic purposes. To this end, the following topics are covered in depth:
- Analysis of the economics of innovation with patent data;
- Main indicators that can be inferred from patent data;
- Application of the patent-based indicator;
- Answering research questions based on the analysis of patent data (examples).
- Language Enhancement - Academic writing (William Alexandre Iones)
The University of Parma's School of Economics and Law's Doctoral Program in Economic and Legal Sciences organizes through the University Language Center the 36-hour course Study skills: English for Academic Purposes. The course is taught in English with a native speaker and is aimed at providing skills needed to write scientific papers, attend conferences and present research papers in English. Students are offered practical experience in English through the performance of tasks associated with a variety of academic assignments. Specifically, the assignments consist, though not exclusively, of: listening to lectures/presentations and taking notes; writing a short paper from notes; reading and writing an abstract/abstract/research paper/report/peer review; designing a poster; preparing and delivering a presentation; describing processes; verbalizing data; commenting on graphs; drafting curriculum vitae; drafting formal international correspondence; and suggested exercises based on grammar "workshops." Ongoing assessment of the various projects will be used to formulate the final grade based on students' active participation, task completion and level of learning. Finally, courses in Italian for foreigners are organized by the University of Ferrara's Centro Linguistico di Ateneo through the local doctoral school IUSS-Ferrara 1391. Attendance at the courses involves the acquisition of credits.
Lecture schedule and timetable
from 10/01/2023 to 23/03/2023;
Tuesdays and Thursdays, 2:30 to 4 pm.30
All lectures will be held in Classroom "C" (Economics building) except for the one on 23/2 which will be held in Classroom K10 (New Didactic Pole on Kennedy Street/corner V.lo Santa Maria).
Final recognition of CFUs is provided only for those who attend at least 75% of the lectures.
Registration opens on 01/12/2022 at 10:00 a.m. and closes on 31/01/2023 at 12:00 p.m.
Registration can be done with the University credentials of each doctoral student at the link https://elly2022.cla.unipr.it/course/view.php?id=69:
To be able to profitably follow the course, one must already possess a general knowledge of English at the B2 level.
Before enrolling, to avoid taking an inappropriate course, you must take the self-assessment test.
The Doctoral Schools of the Universities of Parma and Ferrara (the School of Economics and Law and IUSS-Ferrara 1391, respectively) organize seminars and lectures for the acquisition of appropriate computer skills:
- Scientific-technological: advanced computer technologies and computational/simulation environments;
- Life sciences: in-depth study of the most popular computer systems and dedicated databases;
- Humanities: computerized cataloging and archiving, science dissemination, EU databases and use of econometric software.
Attendance results in the acquisition of credits.
- Activity Introduction to Python (Pietro BATTISTON - University of Parma)
Through this course, students will learn the basics of
programming in Python and approach some
standard tools for data analysis. Specific applications will vary
based on participants' needs and research interests.
The meetings will all be interactive in nature and will cover the following topics:
- Introduction to syntax and fundamental data structures;
- Rudiments of object-oriented programming;
- Control flow, forms, input/output;
- Introduction to numpy and pandas for data manipulation;
- Examples of using statsmodels or scikit-learn for analysis in individual or group project presentations.
Lecture schedule and timetable
Friday, December 16, 1:00 p.m.-4:30 p.m.
Friday, January 20, 1:00 p.m.-4:00 p.m.30
Tuesday, February 14, HOURS 10:30 -13.30
- Management of Research and Knowledge of European and International Research Systems
The Doctoral Schools of the Universities of Parma and Ferrara (respectively the Doctoral School in Economic and Legal Sciences and the IUSS-Ferrara 1391) organize for doctoral courses cycles of seminars and lectures dedicated to Technology Transfer and Knowledge of Research and Financing Systems addressed to doctoral students of scientific disciplines, law and economics who, by choice or necessity, will have to deal with the world of innovation and the renewal of the country, even outside the academic context.
Attendance at seminars and lectures results in the acquisition of credits.
- Valorization and Dissemination of Results, Intellectual Property and Open Access to Data and Research Products
The Doctoral Schools of the Universities of Parma and Ferrara (respectively the Doctoral School in Economic and Legal Sciences and IUSS-Ferrara 1391) organize cycles of seminars and lectures dedicated to the Protection of Intellectual Property. Special attention is paid to the rules of conduct to be followed when writing the final doctoral dissertation paper.
In-depth seminars on the areas of research in which the doctoral program is organized are provided in all three years both by faculty members participating in the College and by external lecturers, from Italian and foreign universities, who collaborate on an ongoing basis with the training project. The goal is to transfer specialized knowledge and innovative research insights on thesis work to students.
- Statistics for the Social Sciences
The Statistics course of the PhD in Neuroscience at the University of Parma is also open to students of the PhD in Economics and Management of Innovation and Sustainability who wish to deepen their knowledge of data analysis techniques in the social sciences.
The course aims to deepen the theoretical and applicative tools to understand and develop independently the most important statistical techniques that constitute the applications of the General Linear Model (GLM) and its extension (Generalized Linear Model) most frequently used in psychobiological and cognitive neuroscience research. Lectures will be eminently practical in nature: ad hoc dataframes will be provided for each topic, and analyses will be conducted in the classroom using the R processing environment (R Core Team, 2020). Emphasis will be placed, from time to time, on research areas of primary interest to PhD students in the Cycle. Topics: general linear model; relationship models between quantitative variables: zero- and higher-order correlation, multiple linear regression, path analysis; relationship models between continuous and nominal/categorical variables: Analysis of Variance (factorial, repeated-measures designs, mixed models); relationship models between categorical variables (Generalized Linear Model): Poisson and logistic (binary and multinomial) regression; Robust Analysis and non-parametric tests.
Students may avail themselves for research activities of the numerous laboratories and research centers of the Departments on which the doctoral course is hinged. By way of example only, those related to the Parma campus are given below:
- Business Administration - LAM-Laboratory in Accounting and Management, SILAB-Social Impact Lab, University Center for Bioethics;
- Finance, Banking and Insurance - Research Laboratory in Governance and Internal Controls in Banks in collaboration with Tor Vergata;
- Marketing - Research Laboratory in Neuromarketing, Loyalty Observatory, RetaiLab;
- Economic Sciences - Research Laboratory in Experimental Economics, Unintended Consequences Lab, LEIGIA-Laboratory on the Economics of Enterprises of Italy, Germany and Austria.
- Course in Statistics - prof.ssa Annalisa Pelosi
Lecture schedule and timetable
Thursday, May 18, 2023, 3-5 pm
Tuesday, May 23, 2023, 15-17
Tuesday, May 30, 2023, 15-17
Lecture Room 2 via Volturno 39, University of Parma, Parma
Seminar Day in Honor of Prof. Pasinetti - April 14, 2023 15:00 - 17:30
Department of Economics and Management, Aula Magna, University of Ferrara
Seminar Dr.ssa Giulia Mattioli - April 19, 14:30-16:30
"Circular public procurement: the obligation of environmental sustainability in public procurement procedures."
Lecture room EC1 Department of Economics and Management, Via Voltapaletto 11, Ferrara.
