Offerta Dottorati
Economics, Management and Statistics - Ciclo 38
Ciclo:
38
Coordinatore:
Prof. Fabrizio Cesaroni
Lingua:
Inglese
Posti e Borse:
4 posti con borsa e 1 senza borsa
Bando:
Url Dottorato:
Descrizione del progetto:
Il presente progetto di dottorato si sviluppa attorno ad un percorso formativo il cui contenuto e la cui articolazione permetterà agli studenti partecipanti di acquisire le competenze necessarie per lo svolgimento di attività di ricerca in ambito internazionale. Il percorso è strutturato in tre curriculum (Economics, Management e Statistics) con una base formativa comune. Gli studenti che seguono i vari curriculum avranno così la possibilità di approfondire le conoscenze specifiche dell’area scientifica di interesse e di acquisire delle competenze specializzate per la realizzazione di attività di ricerca nel proprio ambito scientifico, secondo i più alti standard internazionali. Allo stesso tempo, la base formativa comune garantisce che tutti gli studenti, indipendentemente dal curriculum seguito, abbiano sviluppato un approccio mentale all’attività di ricerca e acquisito un bagaglio minimo di conoscenze e competenze metodologiche proprie della ricerca scientifica, da utilizzarsi trasversalmente su più ambiti disciplinari.
Inoltre il percorso formativo promuoverà la partecipazione attiva degli studenti ai network internazionali della ricerca, sia mediante l’organizzazione di iniziative (seminari, workshop, progetti di ricerca) svolte in ambito locale ma con il coinvolgimento di ricercatori internazionali, sia stimolando gli studenti a interfacciarsi con le altre realtà della ricerca a livello internazionale, mediante lo svolgimento di periodi di visiting all’estero, la partecipazione a convegni e conferenze internazionali, la partecipazioni a workshop e summer/winter school. Dato il carattere intrinsecamente aperto e internazionale della ricerca scientifica, le cui conoscenze difficilmente possono inquadrarsi nei limitati vincoli istituzionali o territoriali, sviluppare un senso di appartenenza ad una comunità estesa a livello internazionale e allacciare rapporti di collaborazione con i membri della stessa rappresenta una condizione essenziale per lo svolgimento dell’attività di ricerca anche (e soprattutto) dopo la conclusione del percorso di dottorato, una volta intrapresa la carriera professionale.
Obiettivi del corso:
Il presente progetto di dottorato si prefigge l’obiettivo di creare un ambiente stimolante per studenti altamente motivati ed in possesso di un potenziale adeguato ad intraprendere successive attività di ricerca sia in ambito accademico che in istituzioni di ricerca nazionali ed internazionali. Nello specifico, il presente dottorato si prefigge i seguenti obiettivi:
a) Attirare studenti italiani e stranieri motivati ed interessati a svolgere attività di ricerca avanzata – tale obiettivo attiene non solo alle modalità di selezione iniziale dei candidati, ma anche alle attività da svolgersi successivamente durante il percorso formativo, che devono essere volte anche alla promozione di una cultura della ricerca, che stimoli l’interesse per la scoperta e l’adozione di una mentalità analitica e razionale;
b) Fornire adeguate competenze teoriche ed empiriche per svolgere attività di ricerca ritenute di elevato profilo qualitativo da un punto di vista internazionale – tale obiettivo si estrinseca sia mediante la partecipazione attiva da parte degli studenti alle attività espressamente previste dal percorso formativo, sia mediante il coinvolgimento degli stessi in progetti di ricerca a carattere nazionale e internazionale;
c) Sviluppare la capacità di condurre attività di ricerca singolarmente e/o quali membri di gruppi di ricerca a carattere internazionale – il perseguimento di tale obiettivo risulta particolarmente importante in quanto i dottori di ricerca in Economics, Management and Statistics, al termine del percorso di dottorato, una volta intrapresa la carriera professionale presso l’accademia o altre istituzioni di ricerca, dovranno essere in grado di determinare in autonomia e indipendenza gli obiettivi dei propri progetti di ricerca, di individuare ed attuare le migliori modalità di realizzazione pratica degli stessi, nonché di convertire i risultati della ricerca in output che possano avere adeguata diffusione nella comunità scientifica di riferimento e in generale nella società (secondo gli obiettivi di terza missione perseguiti dall’università). Acquisire un elevato grado di maturità e indipendenza diventa quindi un requisito fondamentale per ogni ricercatore che si proietti nel mondo internazionale della ricerca.
Sbocchi occupazionali e professionali previsti
Al termine del percorso formativo e di ricerca, i dottori di ricerca in Economics, Management and Statistics avranno un bagaglio di conoscenze e competenze necessarie per trovare impiego sia presso il settore pubblico sia presso il settore privato.
Il primo e più immediato sbocco professionale è in ambito accademico istituzionale, nonché presso istituzioni di ricerca pubbliche e private. Il taglio internazionale del Dottorato (interamente in lingua inglese) consentirà ai futuri dottori di ricerca di indirizzare la loro carriera sia in Italia che all’estero. Inoltre, il costante incoraggiamento offerto agli studenti a partecipare a summer/winter school, nonché i notevoli incentivi a far trascorrere periodi di ricerca (visiting research) presso università e centri di ricerca di elevata qualificazione e localizzate al di fuori dei confini nazionali permetterà ai dottorandi di instaurare importanti forme di collaborazione e interazioni scientifiche con altri membri della comunità scientifica di appartenenza, che si riveleranno utili ai fini del loro inserimento professionale in Italia e all'estero al termine del percorso formativo.
Un secondo sbocco occupazione è quello privato presso imprese. Infatti, esiste oggi da parte delle imprese una crescente necessità di dotarsi di figure professionali in grado di comprendere e sviluppare i processi finanziari, manageriali e decisionali che possano permettere alle stesse di competere in modo efficace sul mercato globalizzato, anche alla luce della recente sfida della sostenibilità e dell’innovazione. Il perseguimento da parte delle imprese di tali obiettivi richiede non solo l’adozione di un approccio razionale e rigoroso alla gestione aziendale (al pari del rigore metodologico proprio della ricerca scientifica), ma anche un certo grado di apertura verso soluzioni e best practice provenienti dall’esterno dell’impresa. In questo senso il carattere internazionale del dottorato fornirà ai dottori in Economics, Management and Statistics una certa dimestichezza ad operare in un ambiente aperto e globalizzato che si rivelerà utile anche in ambito lavorativo presso imprese private.
Infine, un terzo sbocco occupazione è quello che riguarda organismi internazionali quali l’Unione Europea, l’ONU, l’FMI e la Banca Mondiale, solo per citarne alcune. Tali istituzioni, al fine di perseguire il proprio fine istituzionale, sono dotate internamente di centri studi il cui obiettivo è produrre analisi e fornire statistiche che siano di supporto alla successiva azione di policy. Il dottore di ricerca in Economics, Management and Statistics possiede le competenze necessarie per analizzare i complessi fenomeni economici e statistici che sono al centro dell’azione di tali organismi.
Il primo e più immediato sbocco professionale è in ambito accademico istituzionale, nonché presso istituzioni di ricerca pubbliche e private. Il taglio internazionale del Dottorato (interamente in lingua inglese) consentirà ai futuri dottori di ricerca di indirizzare la loro carriera sia in Italia che all’estero. Inoltre, il costante incoraggiamento offerto agli studenti a partecipare a summer/winter school, nonché i notevoli incentivi a far trascorrere periodi di ricerca (visiting research) presso università e centri di ricerca di elevata qualificazione e localizzate al di fuori dei confini nazionali permetterà ai dottorandi di instaurare importanti forme di collaborazione e interazioni scientifiche con altri membri della comunità scientifica di appartenenza, che si riveleranno utili ai fini del loro inserimento professionale in Italia e all'estero al termine del percorso formativo.
Un secondo sbocco occupazione è quello privato presso imprese. Infatti, esiste oggi da parte delle imprese una crescente necessità di dotarsi di figure professionali in grado di comprendere e sviluppare i processi finanziari, manageriali e decisionali che possano permettere alle stesse di competere in modo efficace sul mercato globalizzato, anche alla luce della recente sfida della sostenibilità e dell’innovazione. Il perseguimento da parte delle imprese di tali obiettivi richiede non solo l’adozione di un approccio razionale e rigoroso alla gestione aziendale (al pari del rigore metodologico proprio della ricerca scientifica), ma anche un certo grado di apertura verso soluzioni e best practice provenienti dall’esterno dell’impresa. In questo senso il carattere internazionale del dottorato fornirà ai dottori in Economics, Management and Statistics una certa dimestichezza ad operare in un ambiente aperto e globalizzato che si rivelerà utile anche in ambito lavorativo presso imprese private.
Infine, un terzo sbocco occupazione è quello che riguarda organismi internazionali quali l’Unione Europea, l’ONU, l’FMI e la Banca Mondiale, solo per citarne alcune. Tali istituzioni, al fine di perseguire il proprio fine istituzionale, sono dotate internamente di centri studi il cui obiettivo è produrre analisi e fornire statistiche che siano di supporto alla successiva azione di policy. Il dottore di ricerca in Economics, Management and Statistics possiede le competenze necessarie per analizzare i complessi fenomeni economici e statistici che sono al centro dell’azione di tali organismi.
Tipo di organizzazione
Dottorato in forma non associata (Singola Università)
Curriculum dottorali afferenti al Corso di dottorato
| n. | Denominazione Curriculum | Breve Descrizione |
|---|---|---|
| 1. | ECONOMICS | Il curriculum di Economics si focalizza sugli ambiti disciplinari e di ricerca propri dell’economia, quali il funzionamento dei mercati e delle istituzioni economiche, i processi di crescita, le scelte di consumo e di investimento degli agenti economici ed i problemi dell’equilibrio dei mercati, nonché temi più specifici quali l’economia della criminalità, i modelli di tassazione e di ridistribuzione della ricchezza, l’economia delle istituzioni sanitarie. L’obiettivo del curriculum è di fornire conoscenze e favorire la formazione di competenze specializzate in tali ambiti, con un forte taglio metodologico e applicativo incentrato sullo sviluppo di rigorosi modelli economici e di analisi quantitativa dei dati. |
| 2. | MANAGEMENT | Il curriculum di Management si focalizza sulla ricerca scientifica relativa ai processi di gestione e di formulazione strategica da parte delle imprese e delle organizzazioni, soffermandosi in particolare su ambiti disciplinari quali la gestione strategica, la gestione dei processi innovativi e di sviluppo tecnologico, la gestione della sostenibilità, l’analisi del comportamento dei consumatori e lo sviluppo di strategie di marketing, la gestione dei processi finanziari, i processi imprenditoriali ed il ricorso agli strumenti dei mercati finanziari. L’obiettivo del curriculum è di favorire l’acquisizione di conoscenze e competenze di ricerca in tali ambiti, basate su un mix di approcci metodologici sia di tipo qualitativo che quantitativo e su un appropriato bagaglio di conoscenze teoriche. |
| 3. | STATISTICS | Il curriculum di Statistics si focalizza sui metodi matematici, statistici ed econometrici utilizzati negli studi quantitativi di natura economico-manageriale, soffermandosi, in particolare, sui modelli statistici per l’analisi delle serie temporali e dei dati panel, dei dati finanziari, delle teorie economiche delle preferenze dei consumatori e dell’utilità, dei fenomeni economici spaziali, nonché sui metodi statistici di analisi dei dati primari ottenuti attraverso survey. L’obiettivo del curriculum è di formare ricercatori in grado di applicare le migliori tecniche di indagine statistica esistenti, nonché di sviluppare nuovi modelli e soluzioni che superino le limitazioni intrinseche nelle tecniche attuali. |
Prova orale 08/09/2022 ore 09:00
Aula Teams (link)
LE ISCRIZIONI ONLINE SULLA PIATTAFORMA ESSE3 AI CORSI DI DOTTORATO DI RICERCA A.A. 2022/2023 SONO APERTE DAL 27/09/2022 ALLE 23:59 DEL 07/10/2022
ONLINE ENROLLMENT ON THE ESSE3 PLATFORM FOR THE PhD COURSES A.Y. 2022/2023 IS AVAILABLE FROM 27/09/2022 TO 11:59 pm OF 07/10/2022
Oral exam 08/09/2022 at 09:00 am
Teams Classroom (link)
Avvisi Decreto Rettorale nomina Commissione ammissioneVerbale criteriD.R. approvazione atti-graduatoria-ammissione_38° cicloD.R. inizio attività dottorali DM 351 e 352_38° cicloD.R. Assegnazione borsa FSE_38° ciclo
Attività didattica programmata/prevista
| n. | Denominazione dell’insegnamento | Numero di ore totali sull’intero ciclo | Distribuzione durante il ciclo di dottorato | Descrizione del corso | Eventuale curriculum di riferimento |
|---|---|---|---|---|---|
| 1. | Mathematics-Linear algebra | 12 | primo anno | - The Euclidean space: sum and scalar multiplication, properties of addition and multiplication, inner product, norms, and distances, - Matrices: definition, matrix operations, matrix multiplication, determinant of a matrix, properties of determinant, inverses matrices, minors and cofactors, calculations of inverse matrix, the rank of a matrix. - Vector space: definition, vector subspaces, linear combinations, linear dependence and independence, basis, and dimension. - Linear system: definition, properties, and theorems. - Eigenvalues and eigenvectors: definitions, properties, and theorems. |
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| 2. | Statistics | 27 | primo anno | Broad course objectives: understand basic principles of descriptive and inferential statistics. Learn the language and core concepts of probability theory. - A brief introduction to statistics: descriptive statistics: frequency distribution and graphs; measure of central tendency; measure of variation; measure of position. - Probability and distribution theory: basic concepts of probability and counting; conditional probability and the multiplication rule; the addition rule; introduction to random variable - Discrete probability distributions: probability distribution; binomial distribution. - Normal probability distribution: normal distribution and standard normal distribution; sampling distribution and the central limit theorem; normal approximations to binomial distribution. - Estimation and inference. - Confidence intervals: for the mean (large and small sample); for population proportions; for variance. - Hypothesis testing with one sample; hypothesis testing with two samples. Chi-square test of goodness of fit and independence; analysis of variance; introduction to nonparametric testing. - Methods of finding estimators: methods of moments; maximum likelihood; other methods. - Simple regression: correlation; linear regression; tests of significance of parameter estimates; test of goodness of fit and correlation; properties of ordinary least-squares estimators. Introduction to multiple regression analysis. - Matrix algebra: terminology; algebraic manipulation of matrices; geometry matrices; solution of a system of linear equations; partitioned matrices; characteristics roots and vectors; quadratic forms and definite matrices; calculus and matrix algebra. |
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| 3. | Econometrics | 27 | primo anno | Classical Linear Regression Model: - Assumptions of the linear regression models - Least squares - Evaluating the fit of the regression - Statistical properties - Prediction Multiple Regression - Testing restrictions - Hypothesis about the coefficients - Goodness of fit - Prediction - Other hypothesis tests - Large sample results - Nonspherical disturbances |
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| 4. | Introduction to STATA | 12 | primo anno | This course introduces students to the practical use of the statistical package Stata, which represents one of the mostly used and worldly recognized software tools for performing complex statistical analyses. Outputs of the Stata software package are commonly accepted by most scientific journals and reviews. - Stata features and interface, general structure of the commands. Clauses, options, do file etc. - Generate string, numerical and categorical conversions. Time series features, importing and exporting data, combining datasets, reconfiguring datasets. - Descriptive analysis, popular tests, tables, and graphics - OLS, model selection and Diagnostic analysis |
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| 5. | Engaging in Research | 6 | primo anno | The course aims at offering to students an overview of various research methods that are usually applied to economics and management research, by highlighting for each of them their main goals, proper context of utilization, main software packages and analytical procedures. The ultimate goal of the course is to develop students’ skills to design a research plan in economics and management, execute it, and eventually being able to convert research outcomes in academic publications (articles). The course is organized as a set of seminars, held by lecturers actively involved in academic research. |
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| 6. | Microeconomics-Theory of consumption | 9 | primo anno | Contents This course is intended to give students an overview over the first elements of advanced microeconomic theory, particularly regarding consumption behavior, single-product markets with or without market power, and multi-market (general) equilibrium. Each student can choose any (and not necessarily only one) group of the above-mentioned credits to enroll. Structure. The instructor will agree with registered students upon a series of online meetings through Teams. All students, regardless of the course/s chosen, is expected to attend these meetings. Meetings will last two hours and will serve to: a) establish a personalized list of papers and chapters to study, b) identify and resolve questions and doubts regarding the reading materials, c) prepare a list of exercises and numerical problems the student should solve on her own, d) correct and discuss the solutions provided. Assessment. At the end of the course, the student will receive an evaluation from the instructor, on a Pass or Fail basis, for each of the group of credits undertaken by the student. |
ECONOMICS |
| 7. | Microeconomics-Theory of production | 9 | primo anno | The course will focus of aspects related to the firms’ production process, with its implications on costs and cost structures. Specifically, the topics addressed by the course are the following: (i) Production sets; (2) Profit maximization and costs minimizations; (3) The geometry of cost and supply in the single-output case; (4) Aggregation; (5) Efficient production (6) Production and the objectives of the firm. The main reference for the course is Mas-Colell, A., Whinston, M. D., & Green, J. R. (1995). Microeconomic theory (Vol. 1). New York: Oxford university press. Assessment: At the end of the course, the student will receive an evaluation from the instructor, on a Pass or Fail basis, for each of the group of credits undertaken by the student. |
ECONOMICS |
| 8. | Microeconomics-Markets | 6 | primo anno | The course will focus on the functioning of markets by considering the peculiar role of market power. Specifically, the following topics will be addressed: (1) Pareto optimality and competitive equilibrium; (3) Partial equilibrium competitive analysis; (3) The fundamental welfare theorems in a partial equilibrium context; (4) Welfare analysis in the partial equilibrium context; (5) Free-entry and long-run competitive equilibria; (6) Market power: monopoly pricing; (7) Static models of oligopoly; (8) Repeated interactions; (9) Entry; (10) The competitive limit; (11) Strategic precommitments. At the end of the course, the student will receive an evaluation from the instructor, on a Pass or Fail basis, for each of the group of credits undertaken by the student. | ECONOMICS |
| 9. | Microeconomics- Games | 6 | primo anno | The course will focus on the following topics: (1) Definition of games; (2) The extensive form representation of a game; (3) Strategies and the normal form representation of a game; (4) Randomized choices; (5) Dominant and dominated strategies; (6) Rationalizable strategies; (7) Games of incomplete information: Bayesan Nash equilibrium; (8) The possibility of mistakes: Trembling-hand perfection. The main reference for the course is Mas-Colell, A., Whinston, M. D., & Green, J. R. (1995). Microeconomic theory (Vol. 1). New York: Oxford university press. | ECONOMICS |
| 10. | Macroeconomics-Labor Economics | 9 | primo anno | Objectives This course discusses a selection of relevant topics in the macro-labour economics literature. The aim of the module is proving the student with: (i) an overview of a selection of models that study the emergence of involuntary unemployment; (ii) tools that are necessary for those interested in developing empirical and theoretical research in the field of labour economics in macroeconomics, including solution of closed form macroeconomic models, dynamic programming and Bellman’s optimality principle. Syllabus Efficiency wages theory: the Shapiro-Stiglitz model of unemployment as a discipline device; an application to the dual economy literature (Moene 1988). Search theory: the basic model of job search (McCall 1970); the Diamond (1982) coconut model; the Diamond-Mortensen-Pissarides search and matching model. |
ECONOMICS |
| 11. | Macroeconomics-Growth | 9 | primo anno | The course “Applied Economics – Growth” will deal with the following topics: 1. Stylised facts 2. Income heterogeneity in the long run 3. Basic growth analytics: the Solow model and the role of human capital 4. Basic tools: growth regressions and panel issues 5. The rise and fall of growth econometrics 6. A simple framework of proximate and deep determinants 7. Basic tools: growth and development accounting 8. Productivity and technology 9. Geography and Institutions 10. Institutions, History and Identification |
ECONOMICS |
| 12. | Macroeconomics-Investments and Consumption | 9 | primo anno | Objectives This course covers two important macroeconomic topics. It presents the consumption choices of households as well as the investment decisions of firms. Indeed, consumption and investment are important to both growth and volatility, as much of the most insightful empirical work in macroeconomics in recent decades has focused on consumption and investment. Syllabus a. Consumption theory and empirics (Romer 2018, chapter 8) b. Investment (Romer 2018, Chapter 9) c. Other articles and lecture notes will be shared during the classes. |
ECONOMICS |
| 13. | Health Economics | 12 | primo anno | The topics that will be discussed are: 1. Characteristics of health; key concepts and links (and differences) with economics. Implicit and explicit rationing. Average and marginal cost. Opportunity costs. 2. Insurance in healthcare. Moral hazard and adverse selection. The trade-off between equity and efficiency. 3. Economic evaluation of healthcare: cost minimization analysis; cost-benefit analysis; cost-effectiveness analysis; cost-utility analysis. 4. The issue of quality of life. 5. Artificial intelligence and the analysis of corruption in healthcare. 6. Innovation in healthcare. Health technology assessment. |
ECONOMICS |
| 14. | Taxation and Redistribution | 12 | primo anno | Description of the course The aim of this short theoretical course is to introduce that part of the public economics which study the theory of taxation and redistribution, providing students with the necessary theoretical tools and skills to assess the impact of taxes in the economy. Course content Both positive and normative aspects of taxation will be addressed. What is the social cost of taxation? How does taxation affect the behaviour of economic agents? Who really pays taxes? How to choose an optimal tax system? • Introduction to taxes: a taxonomy of taxation • Efficiency cost of taxation • Effects of taxes on - Consumers - Labor supply - Savings • Tax incidence theory • Tax design: Optimal direct and indirect taxation |
ECONOMICS |
| 15. | Economics of crime | 12 | primo anno | The course will provide a thorough introduction to theoretical models and empirical investigations of economics of crime with a special focus on organized crime and corruption. Recently, the economic approach to crime has generated a large and growing literature and provided excellent insights on the causes of criminal behavior, the social costs of crime, and the design of enforcement policies. In particular, the course will present: (1) the analysis of corruption, its measurement, its causes and effects, and the prevention policies against corruption; (2) the analysis of organized crime, its causes and macroeconomic effects, the design of internal rules, the markets of interest. Further topics will include the crimes without victims, drugs market and drugs legalization, prostitution market and prostitution liberalization, capital punishment, minorities and crime, gender and crime, and environmental crime. Finally, the course devotes a specific section to crime data and statistics existing at international and Italian levels. | ECONOMICS |
| 16. | General equilibrium | 12 | primo anno | Objectives This course presents traditional and recent developments topics in macroeconomics. The aim of the module is proving the student with tools that are necessary for those interested in developing empirical and theoretical research in macroeconomics, including solution of closed form macroeconomic models, log-linearization of equilibrium solution, calibration of macroeconomic models, estimation and interpretation of early warning systems for predicting systemic banking crisis. Syllabus 1. Neoclassical growth, and the data 2. Systemic crisis 3. Real Business Cycle and Keynesian models 4. Unemployment 5. Consumption theory and empirics 6. Inflation and monetary policy |
ECONOMICS |
| 17. | Law and Economics | 12 | primo anno | Objectives Effective property and contract rights are fundamental to economic growth and development. It has moved econimists to study legal concepts, such as litigation costs, property rules, liability rules, default rules, strict liability. The course provides purely theoretical tools to improve students’ understanding of the dynamics of Law and Economics focusing on the following fields: property law, contract law and crime & punishment. Syllabus - Introduction: What is law & economics? - An economic analysis of Contract Law - Topics on the Economics of Contract Law - Persuasion games and the logic of Trials - Topics on Trials |
ECONOMICS |
| 18. | Circular economy and urban symbiosis | 12 | primo anno | Reading and discussion on the papers: • Smart and sustainable logistics of Port cities: A framework for comprehending enabling factors, domains and goals • Digital Technologies for Urban Metabolism Efficiency: Lessons from Urban Agenda Partnership on Circular Economy • Understanding Sensor Cities: Insights from Technology Giant Company Driven Smart Urbanism Practice • Integrating strategic environmental assessment and material flow accounting: a novel approach for moving towards sustainable urban futures We’ll analyze methods and barriers for an environmental sustainable transition in urban complex systems. | MANAGEMENT |
| 19. | Consumer Behavior | 12 | primo anno | This course provides an overview of theory and research in Consumer Behavior. The topics covered in this course are about System I and II, Consumer Attention and Perception, Consumer Learning, Self-control, and Pro-social Behavior. Students will learn about various perspectives, examine different methodologies, explore some original empirical research, make connections between theory and empirical research, and practice critiquing and identifying insight in research. These skills are important preconditions to developing one's original ideas. The course will be divided into two parts: the first part will consist of a critical review of key articles on each topic, so the students will be challenged to review all the following articles (using the summary sheet provided); the second part will consist in a brief Research Paper Proposal that will demonstrate the knowledge and application of behavioral theories introduced and discussed in this module. The paper should include a brief literature review, leading research questions, conceptual framework with potential hypotheses, research design and related methodological procedures, and contributions and implications of the research. |
MANAGEMENT |
| 20. | Empirical corporate finance | 12 | primo anno | Course description: the course will cover the most recent developments in research in corporate finance. The course aims to give students an understanding of the frontier of current research (e.g., entrepreneurial finance, work conditions and corporate finance implications, corporate governance, endogeneity concerns in corporate finance). The emphasis is on theoretical foundations of corporate finance, but so much emphasis will be on the discussion of selected empirical evidence. Upon completion of the course, students should be able to explain a research paper, identify its key findings analysing its contribution with a view to being able to develop one’s own research. | MANAGEMENT |
| 21. | Life cycle sustainability assessment | 12 | primo anno | The course focuses first on giving an overview on sustainability and circular economy (importance, concepts, strategies and impacts) and then presents sustainability assessment methods based upon the Life Cycle Thinking (LCT). In particular, the Life Cycle Assessment (LCA) is widely applied and used as a technique to assess environmental impacts associated with all the stages of a product’s life from raw material extraction through materials processing, manufacture, distribution, use, repair and maintenance, and disposal or recycling. But LCA only assesses environmental impacts, while sustainability is a holistic concept spanning the environment, economy, and society. Thus, LCA has broadened also to include Life Cycle Costing (LCC) and Social LCA (S-LCA), drawing on the three-pillar or ‘triple bottom line’ model of sustainability, within the Life Cycle Sustainability Assessment (LCSA) framework. Finally, the theme of circularity assessment is also introduced. | MANAGEMENT |
| 22. | Risk management for banking | 12 | primo anno | The course will focus on the methods and models that can be adopted by banks to manage risk associated to investments. In fact, any investment embeds a certain level of risk, which is associated to the duration of the investment over time, and the structure of paybacks. Specific topics that will be discussed during the course are the following: Parametric VaR models; Historical simulation VaR methodologies; Monte Carlo VaR methodologies; Evaluation of VaR models’ forecasting performance; Scoring models; Merton’s model; Credit portfolio models; Operational risk. | MANAGEMENT |
| 23. | Strategic management | 12 | primo anno | Course overview This doctoral-level strategy seminar is an introductory course for Ph.D. students who expect to conduct research in strategic management or related areas (e.g., international business, organization theory, sociology of organizations, industrial organization, entrepreneurship, marketing strategy, supply chain management, corporate finance, etc.). The seminar involves a critical review of various theoretical approaches to strategy research. It also examines some of the central questions in management with economic approaches as a starting point, but with an eye to behavioral perspectives on these same questions. |
MANAGEMENT |
| 24. | Strategy & Organization | 12 | primo anno | Course objective This subject examines some of the main theoretical foundations around which strategic management has developed globally in the last decades. Some managerial theories originate from an Industrial Organization perspective, other from a more managerial point of view. Irrespective of their origin, the diverse theoretical approaches pursue the common goal of identifying the sources of firms’ sustainable competitive advantage and, on a broader extent, the sources of heterogeneities among competing firms. Accordingly, the aim of the course is to help students comprehend the differences and complementarities among alternative theoretical approaches that can be adopted in performing strategic management research, and to understand their evolution over time |
MANAGEMENT |
| 25. | Technology and Innovation management | 12 | primo anno | COURSE OBJECTIVE The objectives of the course are the following: − to provide participants with fundamental concepts of Technology and Innovation, their relationship with economics and the organizational environment, and their overall impact on management and organizations; − to present participants with the conceptual frameworks and analytical tools needed to do research on themes and topics of the Technology and Innovation Management field; − to expose participants to a hybrid set of methods to understand the wide array of approaches to develop research in the field of Technology and Innovation. |
MANAGEMENT |
| 26. | Mathematics-Mathematical functions | 12 | primo anno | Course content The course will focus on the following topics: Functions of many variables. Partial derivatives and directional derivatives; Differentiability. Concavity and generalized concavity; Implicit Function Theorems and their applications. Study material will include both slides and readings provided by the lecturer, and the following basic References: - Mathematics for Economics, C. Simon, L. Blume, - Handbook of generalized convexity and generalized monotonicity, N. Hadjisavvas, S. Komlosi, S. Shaible, Springer, 2005 |
STATISTICS |
| 27. | Applied Statistics- Analysis of discrete variables | 12 | primo anno | Part 1 – Binary Choice Models - Probability Models for Binary Choices - The Linear Probability Model - The Probit and Logit Models - Estimation and Inference - Maximum Likelihood Estimation - Maximizing the Log Likelihood Function - The EM Algorithm - Hypothesis Testing and Goodness of Fit Part 2 – Multiple Choice Models - Ordered Responses Choice Models - Unordered Responses Choice Models |
STATISTICS |
| 28. | Applied Statistics-Demography | 12 | primo anno | Objectives This course presents the basic statistical tools to analyze data related to society and population. The aim of the course is to give students the abilities to begin with an independent research project in the field of demography. The prerequisites of this course include Intermediate Statistics and Intermediate Mathematics. Familiarity with statistical software is useful but not compulsory. The course is structured in two parts: (1) survival analysis, that is analyzing data when the variable of interest is a duration until the occurrence of some event (2) R software for the Social Sciences. |
STATISTICS |
| 29. | Applied Statistics-Social Statistics | 12 | primo anno | The course provides theoretical and empirical tools to build new composite indicators and interpreting existing ones in the Social Sciences field. Composite indicators are spreading in social sciences as it is witnessed by the last decades proliferation of contributions in several fields (well-being, quality of life, multiple deprivation, sustainability, competitiveness, development, …), both at institutional and academic level. This course focuses on measurement issues, with particular reference to the choice of transformation and pooling functions as well as weighting schemes. A focus will be also on the passage from qualitative to quantitative measurement. Lectures will combine theoretical and empirical aspects of measurement through composite indicators. |
STATISTICS |
| 30. | Statistical and Econometric models-Models for panel data | 12 | primo anno | The course is intended to provide an introduction to the theoretical and empirical issues related to the estimation of panel data, both static and dynamic. The course is divided in two parts (each of them lasting 6 hours). First part: • An introduction to panel data: structure and types; • Panel estimators (pooled OLS, random effects, fixed effects, first differences); • Estimator properties (consistency and efficiency); • Tests for choosing between models (Breusch-Pagan LM test, Hausman test); • Instrumental variables and endogeneity. Second part: • An introduction to dynamic model; • The first difference estimator; Statistical and Econometric Models for Panel Data • Arellano–Bond GMM estimator; • Blundell–Bond GMM estimator During the module, we will make use of real examples in Stata to show how the software produces estimates. |
STATISTICS |
| 31. | Statistical and Econometric models-Models for time series | 12 | primo anno | Aims of the course • Understand the use of stochastic linear models for time series analysis • Acquire competence in temporal data processing through the use of Gretl software Contents • Theoretical and sampling moments • White Noise stochastic process • Autoregressive (AR) process • Moving Average (MA) process • ARMA stochastic process • Box and Jenkins models • Stationary and ARMA processes • Time series transformations to induce stationarity • Estimate ARMA processes • Forecasts • Applications |
STATISTICS |
| 32. | Statistical and Econometric models—Models for financial data | 12 | primo anno | Objectives The course is designed to cover the econometric and statistical tools to gain understanding of the main features of financial data both in theoretical and practical frameworks. After the illustration of the main statistical and econometric features of financial time series, in particular for the analysis of prices and returns, the course will be focused on classical univariate and multivariate models for volatility, correlation models and the recent Multiplicative Error Models and Heterogeneous AutoRegressive models. The analysis of real cases will be conducted by means of econometric softwares. |
STATISTICS |
| 33. | Mathematics for Economics and Finance-Optimization | 12 | primo anno | Objective: The main goal of the course is to provide students with the relevant mathematical tools and techniques for solving decision problems of quantitative nature, arising in economics, finance, business and management. The prerequisites of the course include the basic Linear Algebra and Differentiable Calculus of real functions with one variable. Syllabus: Multivariable calculus: gradient and directional derivatives. Concavity and Convexity. Extreme points. Unconstrained problems. Equality constraints: Lagrange problem. Inequality constraints: Kuhn-Tucker conditions; Mixed constraints. Applications. |
STATISTICS |
| 34. | Mathematics for Economics and Finance-Preferences and Utility theories | 12 | primo anno | The course “Mathematics for Economics and Finance – Preferences and utility theories” will deal with the following topics: Social Welfare functions, Social choice functions, Arrow's impossibility theorem, strategy-proofness, social grading functions, social-ranking functions, majority-grade, majority-ranking, majority-value. Applications. References: - Game Theory; M. Maschler, E. Solan, and S. Zamir (Chapter 21, Social Choice) - Majority Judgment, Measuring, Ranking, and Electing; M. Balinki and R. Laraki (Applications) |
STATISTICS |
| 35. | Mathematics for Economics and Finance-Financial mathematics | 12 | primo anno | Objectives This is a course in the applied aspects of mathematical finance. The theory of stochastic calculus is the main mathematical tool used in this course: some basic theoretical aspects are introduced in order to have the instruments to understand and deal with financial markets applications; with this aim, various exercises will be discussed. Moreover, we cover the basic Black-Scholes theory and we extend it to the case of several underlying assets. Topics: Option markets and contracts: basic definitions and illustrations of option contracts, types of options (financial options, options on futures, commodity options, other types of options) Stochastic Processes, Winer Process, Information, Martingales, Stochastic Calculus, Itò Formula Stochastic Differential Equations, Geometric Brownian Motion Portfolio Dynamics, Continuous time option pricing |
STATISTICS |
| 36. | Advances in Statistics-Clustering | 12 | primo anno | Objectives - Knowledge and understanding: On completion, the student will be able: i) to implement the main methods used in cluster analysis; ii) to summarize the main features of a dataset and extract knowledge from data properly. - Making judgements: On completion, the student will be able to choose a suitable statistical model, apply it, and perform the analysis using a statistical software. - Communication and learning skills: On completion, the student will be able to present the results from the statistical analysis, and which conclusions can be drawn. |
STATISTICS |
| 37. | Advances in Statistics- Introduction to R | 12 | primo anno | The course aims to provide basic understanding of the software R and its programming language. It covers several topics including the introduction to basing commands, the graphical environment and, estimation of linear and non-linear models. The adoption of the RStudio interface is strictly recommended. Course Content • Lecture 1: Introduction to R. − Working with matrices; − The graphical environment. • Lecture 2: Linear Regression Model. • Lecture 3: Introduction to Time Series. − Main features of time series; − Stationarity; − ARIMA models. • Lecture 4: Vector autoregressive (VAR) models. • Lecture 5: Volatility models - ARCH and GARCH. • Lecture 6: Volatility models - Multiplicative Error Model (MEM) |
STATISTICS |
| 38. | Advances in Statistics-Spatial Statistics | 12 | primo anno | Sampling -Simple Random Sampling -Stratified Random Sampling -Systematic Random Sampling -Cluster Random Sampling -Spatial Sampling Spatial statistics -Global measure of spatial autocorrelation - The spatial weight matrix W -Local measure of spatial autocorrelation -Identification of spatial clusters and spatial outliers -Modelling spatial relations: Geographically Spatial Regression and Spatial Panel Regression -Principal component analysis for spatial data -Socio-Economic Applications |
STATISTICS |
| 39. | Digital Transformation and SMEs: threats and opportunities | 12 | primo anno | Digital transformation is a phenomenon that deeply impacts the business environment by reshaping the nature of how firms do business. The rapid evolution of the environment (synthesized by the VUCA acronym) and the rapid evolution of digital technologies represent a challenge for firms but also a chance to scout new business opportunities. Succeeding in this volatile environment requires a deep understanding of how digital technologies impact the business environment and how to deal with the changes generated. This is particularly true for SMEs whose structurally deal with a lack of resources. This course aims to introduce students to the digital transformation strategies for SMEs and the opportunities digital transformation presents. The course provides a broad perspective of digital transformation and explains how SMEs can leverage it to open new business opportunities. The course deals with the following main topics: (1) Dealing with Digital Transformation Recognize and define digital technologies opportunities and threats in various forms and explore SMEs’ strategies; (2) Business Models Identify the most suitable business models to create value; (3) Ecosystem Evolution Examine the importance of ecosystems from different viewpoints and explore the evolution and the internal dynamics of new ecosystems. |
MANAGEMENT |
| 40. | Macroeconomics: fiscal and monetary policy coordination | 12 | primo anno | Understanding the fundamental role of fiscal and monetary policy coordination represents the core of modern theoretical debate in political economy. The course aims at unveiling the evolution fiscal and monetary policy coordination since its origins to the most recent developments. Specifically, the course focuses on the role of the coordination between fiscal and monetary policy as a tool for the macroeconomic stabilization. We will try to analyze as institutions and governments use fiscal and monetary policy to guarantee the 'normal' function of economic system, according to the three main economic theories (Neoclassical, Keynesian, and Monetarist theory). In particular, we will try to understand in what Neoclassical, Keynesian and Monetarist models differ, and why they disagree about the role of fiscal and monetary policy coordination as a tool for ensuring the stability of the economic system. |
ECONOMICS |
Altre attività didattiche (seminari, attività di laboratorio e di ricerca, formazione interdisciplinare, multidisciplinare e transdisciplinare)
| n. | Tipo di attività | Descrizione dell’attività (e delle modalità di accesso alle infrastrutture per i dottorati nazionali) |
|---|---|---|
| 1. | Seminari | Per tutti gli studenti del dottorato è prevista la partecipazione a seminari e convegni, che contribuiscono all'ottenimento di CFU. In particolare: - per gli studenti del primo anno, 7 CFU dovranno essere conseguiti con la frequenza di lezioni e seminari di approfondimento nelle aree disciplinari (SSD) dei singoli indirizzi; - per gli studenti del secondo anno, 20 CFU vengono conseguiti con la frequenza di seminari di approfondimento nelle aree disciplinari (SSD) dei singoli indirizzi, organizzati dall'Università di Messina; - per gli studenti del terzo anno, 10 CFU vengono conseguiti con la frequenza di seminari di approfondimento nelle aree disciplinari (SSD) dei singoli indirizzi, organizzati dall'Università di Messina |
| 2. | Attività di laboratorio | L'attività di ricerca è prevista soprattutto per gli studenti del secondo e del terzo anno. In particolare: - per gli studenti del secondo anno, 40 CFU vengono attribuiti dal collegio docenti alle attività connesse con la ricerca specifica dei singoli dottorandi, incluse le attività di partecipazione a congressi, seminari, scuole, soggiorni all’estero. I crediti formativi sono così distribuiti: attività individuale di ricerca, da discutere nella relazione per il passaggio al terzo anno (n.20 CFU); stesura tesi (n 12 CFU); partecipazione ad attività connesse con la ricerca a scelta del dottorando: convegni, congressi, soggiorni all’estero di tipo “Erasmus” o di altro tipo (n 8 CFU). - per gli studenti del terzo anno, 50 CFU vengono attribuiti dal collegio docenti alle attività connesse con la ricerca specifica dei singoli dottorandi, incluse le attività di partecipazione a congressi, seminari, scuole, soggiorni all’estero. I crediti formativi sono così distribuiti: attività individuale di ricerca, da discutere in un seminario prima dell’ammissione all’esame finale (n.12 CFU); stesura tesi (n 30 CFU); partecipazione ad attività connesse con la ricerca a scelta del dottorando: convegni, congressi, soggiorni all’estero di tipo “Erasmus” o di altro tipo (n 8 CFU). |
Componenti del collegio (Personale Docente e Ricercatori delle Università Italiane)
| n. | Cognome | Nome | Ateneo | Qualifica | SSD |
|---|---|---|---|---|---|
| 1. | ABBATE | Tindara | MESSINA | Professore Associato (L. 240/10) | SECS-P/08 |
| 2. | BUSETTA | Giovanni | MESSINA | Ricercatore confermato | SECS-S/03 |
| 3. | CALTABIANO | Marcantonio | MESSINA | Professore Associato (L. 240/10) | SECS-S/04 |
| 4. | CAMPOLO | Maria Gabriella | MESSINA | Professore Associato (L. 240/10) | SECS-S/05 |
| 5. | CESARONI | Fabrizio | MESSINA | Professore Ordinario (L. 240/10) | SECS-P/08 |
| 6. | CINICI | Maria Cristina | MESSINA | Ricercatore a t.d. - t.pieno (art. 24 c.3-b L. 240/10) | SECS-P/08 |
| 7. | CRUPI | Antonio | MESSINA | Ricercatore a t.d. - t.pieno (art. 24 c.3-b L. 240/10) | SECS-P/08 |
| 8. | D'AGOSTINO | Elena | MESSINA | Ricercatore confermato | SECS-P/03 |
| 9. | DI PINO INCOGNITO | Antonino | MESSINA | Professore Ordinario (L. 240/10) | SECS-S/05 |
| 10. | DONATO | Maria Bernadette | MESSINA | Professore Associato (L. 240/10) | SECS-S/06 |
| 11. | FORGIONE | Antonio | MESSINA | Professore Associato (L. 240/10) | SECS-P/11 |
| 12. | GIACCONE | Sonia Caterina | CATANIA | Professore Associato (L. 240/10) | SECS-P/08 |
| 13. | IOPPOLO | Giuseppe | MESSINA | Professore Ordinario (L. 240/10) | SECS-P/13 |
| 14. | LA ROCCA | Elvira Tiziana | MESSINA | Professore Associato (L. 240/10) | SECS-P/08 |
| 15. | LEONIDA | Leone | MESSINA | Professore Ordinario (L. 240/10) | SECS-P/03 |
| 16. | LEOTTA | Antonio | CATANIA | Professore Associato (L. 240/10) | SECS-P/07 |
| 17. | LIOTTI | Giorgio | MESSINA | Ricercatore a t.d. - t.pieno (art. 24 c.3-b L. 240/10) | SECS-P/01 |
| 18. | MAIMONE ANSALDO PATTI | Dario | MESSINA | Professore Associato (L. 240/10) | SECS-P/03 |
| 19. | MAZZA | Angelo | CATANIA | Professore Ordinario (L. 240/10) | SECS-S/04 |
| 20. | MENDOLA | Daria | PALERMO | Professore Associato (L. 240/10) | SECS-S/05 |
| 21. | MIGLIARDO | Carlo | MESSINA | Ricercatore confermato | SECS-P/01 |
| 22. | MILASI | Monica | MESSINA | Professore Associato (L. 240/10) | SECS-S/06 |
| 23. | MILLEMACI | Emanuele | MESSINA | Professore Associato (L. 240/10) | SECS-P/02 |
| 24. | MIRALLES ASENSIO | Antonio | MESSINA | Professore Associato confermato | SECS-P/01 |
| 25. | NOTO | Guido | MESSINA | Ricercatore a t.d. - t.pieno (art. 24 c.3-b L. 240/10) | SECS-P/07 |
| 26. | OTRANTO | Edoardo | MESSINA | Professore Ordinario | SECS-S/01 |
| 27. | PUNZO | Antonio | CATANIA | Professore Ordinario (L. 240/10) | SECS-S/01 |
| 28. | REITO | Francesco | CATANIA | Professore Associato (L. 240/10) | SECS-P/02 |
| 29. | SALOMONE | Roberta | MESSINA | Professore Ordinario (L. 240/10) | SECS-P/13 |
| 30. | SPAGNOLO | Fabio | MESSINA | Professore Associato (L. 240/10) | SECS-S/01 |
| 31. | STAGLIANO' | Raffaele | MESSINA | Professore Ordinario (L. 240/10) | SECS-P/09 |
| 32. | TOMASELLI | Venera | CATANIA | Professore Associato confermato | SECS-S/05 |
| 33. | VERMIGLIO | Carlo | MESSINA | Professore Associato (L. 240/10) | SECS-P/07 |
Componenti del collegio (Personale non accademico dipendente di Enti italiani o stranieri e Personale docente di Università Straniere)
| n. | Cognome | Nome | Ateneo/Ente di appartenenza | Qualifica | SSD |
|---|---|---|---|---|---|
| 1. | ANDRIEU | Guillaume | MONTPELLIER BUSINEE SCHOOL | Professore di Univ.Straniera | SECS-P/09 |
| 2. | APPIO | Francesco | SKEMA BUSINESS SCHOOL DI PARIGI | Professore di Univ.Straniera | SECS-P/08 |
| 3. | BARONE-ADESI | Giovanni | UNIVERSITÀ DELLA SVIZZERA ITALIANA | Professore di Univ.Straniera | SECS-P/11 |
| 4. | BAUWENS | Luc | UNIVERSITÉ CATHOLIQUE DE LOUVAIN | Professore di Univ.Straniera | SECS-P/05 |
| 5. | PIOLATTO | Amedeo | AUTONOMOUS UNIVERSITY OF BARCELONA | Professore di Univ.Straniera | SECS-P/01 |
| 6. | SZOPIK-DEPCZYŃSKA | Katarzyna | UNIVERSITY OF SZCZECIN | Ricercatore di Univ.Straniera | SECS-P/13 |
| 7. | ZAWADZKA | Danuta | TECHNICAL UNIVERSITY OF KOSZALIN | Professore di Univ.Straniera | SECS-P/11 |
| 8. | ZIEGELMANN | Flavio A. | UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL | Professore di Univ.Straniera | SECS-S/01 |
Coordinatore
Prof. Fabrizio Cesaroni
tel. +39 090 6766148 e-mail: fabrizio.cesaroni@unime.it
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