PhD in Economics, Statistics and Data Science

The four-year PhD in Economics, Statistics and Data Science (ECOSTATDATA) provides the most effective response to the important challenges which nowadays doctoral programmes in the areas of economics, statistics and data analytics, both in Italy and Europe, have to cope with: i) high qualification of the faculty, in terms of teaching abilities and publication records; ii) capability of attracting high quality students; iii) interdisciplinarity; iv) internationalization; v) relations with the non-academic job market; vi) placement of students who have successfully discussed their dissertations.

ECOSTATDATA builds upon the fruitful collaboration among economists, statisticians and data scientists from the Department of Economics, Management and Statistics (DEMS) and the Department of Statistics and Quantitative Methods of the University of Milano-Bicocca (UniMiB), which has started twenty years ago within the BSc in Statistics and Economics, as well as the MSc in Statistics and Economics and is going on with the more recent MSc in Data Science.

Coordinator: Prof. Matteo Manera

Deputy Coordinator: Prof. Giorgio Vittadini

A.A. 2024-2025 (cycle XL)

Call for Applications

PhD in Economics, Statistics and Data Science

DEMS - University of Milano-Bicocca, Italy

The Department of Economics, Management and Statistics (DEMS) of the University of Milano-Bicocca invites applications to its PhD Programme in Economics, Statistics and Data Science (ECOSTATDATA) for the academic year 2024-25 (XL cycle).

The PhD Programme is articulated in three curricula, Economics (ECO), Statistics (STAT) and Big Data & Analytics for Business (BIDAB). The length of the PhD Programme is four years, starting in late October 2024 (the precise starting date will be announced in due course on the PhD website).

The Call of Applications 2024-2025 offers at least 10 fully-funded scholarships .

The selection procedure is regulated by the official Call for Applications (Bando di Concorso), which will be published in the Doctoral School’s and in the PhD programme websites on April 12, 2024, with deadline on May 14, 2024.

The official Call for Applications contains detailed information on: i) the documents which each candidate has to submit; ii) structure, contents and timing (May 27, 2024 - June 21, 2024) of the entrance examination; iii) description of the projects related to the scholarships and positions offered.

The official Call for Applications will be published here.

Introduction

ECOSTATDATA belongs to the PhD School of UniMiB, it is affiliated to DEMS, it lasts four years and it is articulated in three curricula, the original two curricula Economics (ECO) and Statistics (STAT), and, starting from cycle XXXVII (academic year 2021-2022), the “new” curriculum Big Data & Analytics for Business (BiDAB).

The first-year teaching activities are mainly devoted to structured courses (tool courses), which are compulsory. Some of these courses are fixed and specific to each curriculum, some are in common between the three curricula, some other courses are chosen by students within each curriculum.

The second-year teaching activities take the form of less structured courses (elective courses or reading groups).

In general, the first-year courses are offered by “internal” teachers, while second-year courses are often open to the collaboration of foreign instructors (visiting scholars).

The curriculum Economics (ECO)

This curriculum is indicated to students with a strong background in quantitative economics and provides advanced training in econometrics, microeconometrics, time series analysis, microeconomics and macroeconomics.

The curriculum Statistics (STAT)

This curriculum is designed for students with a strong background in statistics, both methodological and applied, and provides advanced training in probability, stochastic processes, statistical inference, Bayesian statistics, statistical learning, statistical modelling, computational statistics and data analysis.

The “new” curriculum Big Data & Analytics for Business (BiDAB)

This curriculum starts from cycle XXXVII (academic year 2021-2022), and provides students with rigorous training in data management and programming, with focus on: the analysis of large amounts of structured and unstructured data (natural language); the main paradigms of big data and data visualization, based on the use of innovative techniques of machine learning, text and web mining.

“Flexible” and “training” profiles

By means of appropriate sequences of courses, suggested and monitored by the Programme Committee and the supervisors, students are able to build up “flexible” profiles, which are mainly addressed to scientific research, both in universities or in non-academic institutions, at national or international level.

ECOSTATDATA facilitates the interaction between economic, statistical and data management skills by proposing innovative “training” profiles, which are  mainly addressed to the non-academic job market. The “training” profiles aim at:

  • offering to the non-academic job market high-level skills which are not currently available;
  • attracting students who are interested in ECOSTATDATA as a way to gain new and advanced skills to be immediately spent into that segment of the job market which is not academically- or research-oriented;
  • eliciting the collaboration of high-quality national multi-national companies, which are active in human capital investment and are ready to use the instruments of the executive doctorate, the apprenticeship contracts as well as the direct financing of a PhD scholarship on specific research projects.

Length of the programme

The current length of many PhD programmes in economics, statistics and data science in Italy, including the PhD in Economics DEFAP-Bicocca and in Statistics and Mathematical Finance of UniMiB, is three years. This length is insufficient to guarantee that the PhD theses meet the quality standards achieved by the best European PhD programmes. For this reason, ECOSTATDATA lasts four years. This duration is in line with the recent choices of some of the best Italian PhD programmes in economics, statistics and data science, as well as the PhD programmes in this area offered by the most prestigious European academic institutions.

Interdisciplinarity

ECOSTATDATA fosters interdisciplinary research activities, by favouring co-tutorships between economists, statisticians and data scientists, as well as through the “flexible” and “training” profiles.

Relations with the non-academic job market

ECOSTATDATA is particularly active in collaborating with national, multi-national, high-quality and innovation-oriented companies. In particular, ECOSTATDATA is able to: i) offer high-level skills which are not currently available on the non-academic job market; ii) attract students who are interested in ECOSTATDATA as a way to gain new and advanced skills to be immediately spent into that segment of the job market which is not academically- or research-oriented; iii) elicit the collaboration of high-quality national multi-national companies, which are active in human capital investment and are ready to use the modern instruments of the executive doctorate, the apprenticeship contracts as well as the direct financing of PhD scholarships on specific research projects.

Internationalization

The international experience which has flourished within the PhD in Economics DEFAP-Bicocca and the PhD in Statistics and Mathematical Finance of UniMiB, together with the professional networks developed by many faculty members, guarantees that ECOSTATDATA is particularly active in collaborating with prestigious foreign universities, in terms of both students and faculty members exchange programs and joint degrees.

ECOSTATDATA is managed by two bodies:

  • the Programme Committee (PC), that is the executive and decision-making board composed by full professors, associate professors and researcher of UniMiB and from other renowned Italian and foreign universities and research institutions;
  • the Advisory Board (AB), which collaborates with the PC to organize the teaching and research activities of the programme, is headed by the programme Coordinator and is formed by a limited number of professors and researchers who are representative of the three curricula.

The teaching activities proposed by ECOSTATDATA are organized during the first two years and differ for each curriculum, although some courses are common. Some economics courses at the first and the second year within the curriculum Economics can be offered jointly with the PhD programme in Economics and Finance of the Catholic University of Milano.

First- year courses

  • Curriculum Economics (selected courses)

Mathematics; Computational Statistics I; Econometrics; Microeconometrics; Time Series Analysis; Microeconomics; Macroeconomics; Research Methods; Finance.

  • Curriculum Statistics (selected courses)

Mathematical Analysis, Numerical Optimization, Probability, Stochastic Processes, Bayesian Statistics, Statistical Inference, Statistical Learning, Computational statistics II, Statistical Modelling, R for Data Science, Data Management.

  • Curriculum Big Data & Analytics for Business (selected courses)

Databases for Structured/Unstructured Data (SQL); Programming in Python; Data Quality and Cleaning for Big Data; Architecture for Big Data Processing; Machine Learning; Cloud & Distributed Algorithm; Data Mining; Natural Language processing and Understanding; Human-Centered AI; Social Media Analysis; Semantic Web; Deep Learning and Computer Vision for Business; Data Visualization & Visual Analysis.

Second-year courses

Second-year courses are mainly “reading groups”, that are built upon the research interests of both instructors and students, and are  articulated into one/two introductory lecture/s and a series of meetings where students critically discuss the readings assigned by the instructor during the initial lecture.

The second-year courses are generally offered during the first part of the second year, in order forstudents to be full-time dedicated to their dissertations as early as possible.

Within each curriculum, a careful selection of courses, monitored by the PC and the student’s supervisor, allows each student to identify a “flexible” profile, which coherent with his/her research interests.

Exams

Generally, structured courses have written exams, while the exams associated with the reading groups are more flexible (e.g. written projects and/or oral presentations). The organization of the exams (i.e. form, number of questions, etc.) is decided by the PC and communicated to students at the beginning of each course. 

Monitoring the quality of teaching

The PC runs every year a systematic evaluation of the quality of the courses offered by the PhD programme, by submitting to each student of a given course a detailed questionnaire. Data from the questionnaires are elaborated statistically, sent to each instructor, and discussed within the PC, in order to identify potential problems and solutions.

Admissions to the second year and to years after the second

Admission to the second year is based on the performance of each student in the first-year exams, including the number of “fail” and the number of “resits” each student has been given. Admissions to the third and the fourth years are based on the progresses of the research work. Rules on admission to the second and subsequent years, as well as all the other rules regulating the teaching and research activities of ECOSTAT are formalized by the PC and communicated to each student after enrollment.

 

 

Thesis

The Programme Committee (PC) approves the (minimum) number of papers which form a typical PhD dissertation, namely 2. These papers have to be self-contained, independent and potentially publishable on high-quality internationally refereed journals.

Supervision

In order to facilitate students in identifying a sound research project and a suitable supervisor, within the first part of the year the PC organizes a presentation of the research groups which are active among the PC and the Advisory Board (AB) members. Supervisors are asked to systematically monitor the progresses made by their supervisees and periodically report to the PC about the proceedings of their dissertations.

Seminars

PhD students, especially from the second year, are strongly invited to attend the department seminars organized on a weekly basis at UniMiB. Students of both curricula are also invited to present the progress of their research work in specific seminars, which are part of the student’s evaluation process and, if possible, are jointly organized in order to enhance cross-fertilization between economists, statisticians and data scientists. 

Admission to third and fourth year

Admission to the third and fourth year is formalized by the PC, based on the evaluation of the student’s research work. Admission to the third year takes also into account the performance of each student in the second-year exams.

Admission to external evaluation

Fourth-year students should present, by the end of the year, the final version of their dissertation in front of the PC. If possible, each presentation will be assigned a discussant. The admission to the external reviewers is formalized by the PC, based on the overall evaluation of the PhD thesis.

 

Based on the reports of the external reviewers, students are admitted to the discussion in front of the Evaluation Committee either with minor or major revisions. Students who have successfully defended their dissertation are awarded by the Evaluation Committee the title of “PhD in Economics and Statistics” (students enrolled in cycles XXXIV, XXXV and XXXVI) or the title of “PhD in Economics, Statistics and Data Science” (students enrolled from cycle XXXVII). Students can request to (and obtain from) the Administrative Offices of UniMiB an official document reporting the specific curriculum they have been enrolled in.

ECOSTATDATA takes care of the optimal placement of its students. On this respect, the Programme Committee is very active in: i) providing students with systematic and detailed information on the job market, domestic and international, academic and non-academic; ii) advising and assisting students who intend to apply for academic positions abroad.

N. Surname Name University Department Curriculum
1 ALBONICO Alice Milano-Bicocca DEMS ECO
2 ARGIENTO Raffaele Bergamo Economics STAT
3 ATHANASOGLOU Stergios Milano-Bicocca DEMS ECO
4 BEN-PORATH Elchanan Hebrew-Israel Economics ECO
5 BERTOLETTI Paolo Milano-Bicocca DEMS BIDAB
6 BOLLINO Carlo Andrea Perugia Economics ECO
7 BORGONI Riccardo Milano-Bicocca DEMS STAT
8 BORROTTI Matteo Milano-Bicocca DEMS BIDAB
9 CAMBRIA Erik Nanyang Technological University-Singapore Informatics BIDAB
10 CAMELETTI Michela Bergamo Economics STAT
11 CAMERLENGHI Federico Milano-Bicocca DEMS STAT
12 CANDELIERI Antonio Milano-Bicocca DEMS BIDAB
13 CASTELLETTI Federico Milano-Catholic Statistics BIDAB
14 CAVALLI Fausto Milano-Bicocca DEMS ECO
15 CELLA Michela Milano-Bicocca DEMS ECO
16 COLCIAGO Andrea Milano-Bicocca DEMS ECO
17 CONSONNI Guido Milano-Catholic Statistics STAT
18 CRETI' Anna Paris-Dauphine-France Géopolitique de l'Energie et des Matières Premières ECO
19 DALLA PELLEGRINA Lucia Milano-Bicocca DEMS ECO
20 D'AMBROSIO Conchita Luxembourg-Luxembourg Lettres, Sciences Humaines, Arts et Sciences de l'Education ECO
21 DIA Enzo Milano-Bicocca DEMS ECO
22 FARAVELLI Marco Queensland-Australia Economics ECO
23 FERRARIS Leo Milano-Bicocca DEMS ECO
24 GANCIA Gino Milano-Bicocca DEMS ECO
25 GATTAI Valeria Milano-Bicocca DEMS ECO
26 GRESELIN Francesca Milano-Bicocca Statistics and Quantitative Methods STAT
27 GUARISO Andrea Milano-Bicocca DEMS ECO
28 GUERZONI Marco Milano-Bicocca DEMS BIDAB
29 GUINDANI Michele California Irvine-US Statistics BIDAB
30 HECQ Alain Maastricht-The Netherlands Economics BIDAB
31 LEORATO Samantha Milano Economics; Management and Statistics STAT
32 LOVAGLIO Pietro Giorgio Milano-Bicocca Statistics and Quantitative Methods STAT
33 LUNARDON Nicola Venezia Economics STAT
34 MANERA Matteo Milano-Bicocca DEMS BIDAB
35 MANTOVANI Marco Milano-Bicocca DEMS ECO
36 MARCHESI Silvia Milano-Bicocca DEMS ECO
37 MCLACHLAN Geoffrey Queensland-Australia Mathematics STAT
38 MERCORIO Fabio Milano-Bicocca Statistics and Quantitative Methods BIDAB
39 MICHELANGELI Alessandra Milano-Bicocca DEMS ECO
40 MIGLIORATI Sonia Milano-Bicocca DEMS STAT
41 MORANA Claudio Milano-Bicocca DEMS ECO
42 MOSCONE Francesco Brunel London-UK Environment, Health and Societies STAT
43 MURPHY Brendan UCD- Ireland Mathematics and Statistics BIDAB
44 NAIMZADA Ahmad Milano-Bicocca DEMS BIDAB
45 NIPOTI Bernardo Milano-Bicocca DEMS STAT
46 ONGARO Andrea Milano-Bicocca DEMS STAT
47 OSSOLA Elisa Milano-Bicocca DEMS ECO
48 PACI Lucia Milano-Catholic Statistics BIDAB
49 PAGANI Laura Milano-Bicocca DEMS ECO
50 PELAGATTI Matteo Milano-Bicocca DEMS BIDAB
51 PELUSO Stefano Milano-Bicocca Statistics and Quantitative Methods BIDAB
52 PENNONI Fulvia Milano-Bicocca Statistics and Quantitative Methods STAT
53 PIEVATOLO Antonio Milano-National Research Council (CNR)  Institute for Applied Mathematics and Information Technologies BIDAB
54 PINI Alessia Milano-Catholic Statistics BIDAB
55 PORCU Emilio

Khalifa University of Science and Technology - United Arab Emirates

Mathematics, Statistics and Physics STAT
56 QUATTO Piero Milano-Bicocca DEMS STAT
57 RIANI Marco Parma Economics and Business STAT
58 RIGON Tommaso Milano-Bicocca DEMS STAT
59 SOLARI Aldo Venezia Economics STAT
60 STANCA Luca Milano-Bicocca DEMS ECO
61 TAMBURRI Damian Eindhoven-The Netherlands Computer Science BIDAB
62 TOMMASI Chiara Milano Economics; Management and Statistics STAT
63 UGOLINI Andrea Milano-Bicocca DEMS ECO
64 VISETTI Daniela Milano-Bicocca DEMS ECO
65 VITTADINI Giorgio Milano-Bicocca Statistics and Quantitative Methods STAT
66 ZITIKIS Ricardas Western Ontario-Canada Statistics and Actuarial Sciences STAT

The research activities which characterize the PhD programme in Economics, Statistics and Data Science (ECOSTATDATA) are carried out by an active and lively community of junior and senior researchers.

Within DEMS, researchers are organized in clusters, among which the most relevant for ECOSTATDATA are:

- Business, economic and social statistics (coordinator: Prof. Pelagatti)

- Empirical microeconomics and microeconometrics (coordinator: Prof. Manera)

- Experimental and behavioural economics (coordinator: Prof. Stanca)

- Macroeconomics and macroeconometrics (coordinator: Prof. Morana)

- Microeconomics: theory and applications (coordinator: Prof. Gilli)

- Statistics (coordinator: Prof. Ongaro)

- Strategy, organization and innovation (coordinator: Prof. Torrisi)

Detailed information about people involved in each cluster can be found here.

The other two main groups of researchers supporting the programme are affiliated to the Department of Statistics and Quantitative Methods (DiSMeQ) of UniMiB and to the Department of Statistics (DiSTAT), Catholic University of Milano.

Detailed information about the research activities carried on by the DiSMeQ members can be found here.

Detailed information about the research activities carried on by the DiSTAT members can be found here.

PhD in Economics and Statistics

Ex-alumni - Cycle XXXIV

 

Curriculum ECONOMICS

 

Dr. Alessio LOVARELLI

PhD thesis: Essays in Industrial Economics

Tutor:  Prof. Michela Cella, University of Milano-Bicocca

Supervisor(s): Prof. Carlo Andrea Bollino, University of Perugia and Luiss Business School

 

Dr.  Giorgio MASSARI

PhD thesis: Essays on Empirical DSGE Models

Tutor: Prof. Patrizio Tirelli, University of Pavia

Supervisor(s): Prof. Patrizio Tirelli, University of Pavia

 

Dr. Marco MEMBRETTI

PhD thesis: Firm Size and the Macroeconomy

Tutor: Prof. Silvia Marchesi, University of Milano-Bicocca

Supervisor(s): Prof. Andrea Colciago, University of Milano-Bicocca

 

Dr. Mohammad NOORI

PhD thesis: Essays in Empirical Finance

Tutor: Prof. Claudio Morana, University of Milano-Bicocca

Supervisor(s): Prof. Asmerilda Hitaj, University of Insubria

 

Dr. Marco REPETTO

PhD thesis: Black-box Supervised Learning and Empirical Assessment: New Perspectives in Credit Risk Modeling

Tutor: Prof. Matteo Manera, University of Milano-Bicocca

Supervisor(s): Prof. Caterina Liberati, University of Milano-Bicocca; Prof. Lisa Crosato, University of Venezia

 

Dr. Marco RISPOLI

PhD thesis: Essays on Debt Maturity Structure, Investment and Complementarities in Financial Decisions

Tutor: Prof. Luca Stanca, University of Milano-Bicocca

Supervisor(s): Prof. Enzo Dia, University of Milano-Bicocca

 

Curriculum STATISTICS

 

Dr. Luca BRUSA

PhD thesis: Developments in Discrete Latent Variable Models: Dealing with Likelihood Multimodality and Clustering of Simple Hypergraphs

Tutor: Prof. Giorgio Vittadini, University of Milano-Bicocca

Supervisor(s): Prof. Fulvia Pennoni, University of Milano-Bicocca; Prof. Francesco Bartolucci, University of Perugia

 

Dr. Chiara GALIMBERTI

PhD thesis: Advanced Analytics and Machine Learning for Industrial Manufacturing Applications

Tutor: Prof. Aldo Solari, University of Venezia

Supervisor(s): Prof. Stefano Peluso, University of Milano-Bicocca

 

Dr. Filippo GIORGINI

PhD thesis: Global Games of Policy Change: the Role of Sociopolitical Variables in Affecting the Equilibrium and its Uniqueness

Tutor: Prof. Francesca Greselin, University of Milano-Bicocca

Supervisor(s): Prof. Mario Gilli, University of Milano-Bicocca

 

Dr. Camilla SALVATORE

PhD thesis: Essays on Inference for Non-probability Samples and Survey Data Integration

Tutor: Prof. Piergiorgio Lovaglio, University of Milano-Bicocca

Supervisor(s): Prof. Silvia Biffignandi, University of Bergamo

PhD in Economics and Statistics

Ex-alumni - Cycle XXXV

 

Curriculum ECONOMICS

 

Dr. Pietro BOMPREZZI

PhD thesis: Flowing under the Radar: Micro Evidence of Official Lending

Tutor:  Prof. Silvia Marchesi, University of Milano-Bicocca

Supervisor(s): Prof. Silvia Marchesi, University of Milano-Bicocca

 

Dr.  Pietro DE PONTI

PhD thesis: Essays in Applied Economics

Tutor: Prof. Laura Pagani, University of Milano-Bicocca

Supervisor(s): Prof. Maria Luisa Mancusi, Catholic University of Milano; Prof. Valeria Gattai, University of Milano-Bicocca

 

Dr. Francesco FERLAINO

PhD thesis: Essays on Household Heterogeneity and Financial Frictions

Tutor: Prof. Stergios Athanasoglou, University of Milano-Bicocca

Supervisor(s): Prof. Domenico Delli Gatti, Catholic University of Milano

 

Dr. Matteo ROMAGNOLI

PhD thesis: Essays on Energy Economics and Econometrics

Tutor: Prof. Matteo Manera, University of Milano-Bicocca

Supervisor(s): Prof. Matteo Manera, University of Milano-Bicocca; Prof. Anna Cretì, Dauphine University, FR

 

 

 

Curriculum STATISTICS

 

Dr. Federico CORTESE

PhD thesis: Statistical Modeling and Temporal Clustering of Multivariate Time-series with Applications to Financial Data

Tutor: Prof. Matteo Pelagatti, University of Milano-Bicocca

Supervisor(s): Prof. Fulvia Pennoni, University of Milano-Bicocca; Prof. Francesco Bartolucci, University of Perugia; Prof. Petter Kolm, New York University, US; Prof. Erik Lindstrom, Lund University, SE

 

Dr. Alice GIAMPINO

PhD thesis: Innovative Approaches to Bayesian Clustering Methods: Parametric and Nonparametric Perspectives

Tutor: Prof. Sonia Migliorati, University of Milano-.Bicocca

Supervisor(s): Prof. Bernardo Nipoti, University of Milano-Bicocca; Prof. Michele Guindani, University of California at Los Angeles, US

 

Dr. Silvio GERLI

PhD thesis: A Novel Methodology to Make Topic Models Predict Real Topics and to Compare them in Big Data Corpus

Tutor: Prof. Fulvia Pennoni, University of Milano-Bicocca

Supervisor(s): Prof. Matteo Borrotti, University of Milano-Bicocca

 

Dr. Alessandro MASCARO

PhD thesis: Bayesian Approaches to Causal Inference and Discovery from Observational and Interventional Data

Tutor: Prof. Lucia Paci, Catholic University of Milano

Supervisor(s): Prof. Federico Castelletti, Catholic University of Milano

 

Dr. Vincenzo NARDELLI

PhD thesis: Methods for Extracting Valuable Information from Spatial Web and Open Reliable Data

Tutor: Prof. Stefano Peluso, University of Milano-Bicocca

Supervisor(s): Prof. Giuseppe Arbia, Catholic University of Milano

 

Dr. Fabio PIACENZA

PhD thesis: Holistic Approach to Operational Risk: Issues, Solutions, and Decision Making

Tutor: Prof. Francesca Greselin, University of Milano-Bicocca

Supervisor(s): Prof. Francesca Greselin, University of Milano-Bicocca; Prof. Ricardas Zitikis, University of Western Ontario, CA

The ECOSTATDATA PhD students are happy to announce the second edition of the Milano PhD Workshop, that will be held at the premises of the University of Milano-Bicocca, September 23-27, 2024.

The event is jointly organized with the PhD students in economics of the major universities in the Milanese area.

The program of the event is under construction and will be available shortly.

For details you can contact the local organizers:

We are very happy to announce this new initiative: the ECOSTATDATA PhD Seminar Series!

This initiative aims to create a friendly environment where all PhD students at DEMS have the opportunity to present their own research or research proposal to obtain constructive feedback from peers and senior researchers.

Regular reminders before each presentation will be sent, and we really hope you will join this initiative. Your presence and support will be key to make this a success!

The Organizers 

@Angelica Bertucci 

@Ludovica De Carolis 

@Matteo Ferraro 

@Gregorio Ghetti 

@Lorena Popescu 

 

SCHEDULE

March 14, 2024 - Aula Seminari (U7 - 2104) 17:00

Speaker: Alessandro Colombi

Field: Bayesian Nonparametrics

 

March 28, 2024 - Aula Seminari (U7 - 2104) 12:00

Speaker: Andrea Sorrentino

Field: The Economics of Fintech & Game Theory



April 18, 2024 - Aula Seminari (U7 - 2104) 12:00

Speaker: Francesco Ferlaino

Field: Macroeconomics

 

May 09, 2024 - Aula Seminari (U7 - 2104) 17:00


Speaker: Luca Danese

Field: Bayesian Nonparametrics

 

May 16, 2024 - Aula Seminari (U7 - 2104) 12:00


Speaker: Angelica Bertucci


Field: Macroeconomics

 

May 23, 2024 - Aula Seminari (U7 - 2104) 12:00


Speaker: Matteo Ferraro


Field: Development Economics

 

May 30, 2024 Aula Seminari (U7 - 2104) 12:00


Speaker: Lucia Tommasiello


Field: Banking and Finance

 

June 6, 2024 - Aula Seminari (U7 - 2104) 12:00


Speaker: Mattia Longhi


Field: International Financial Markets and Development Macroeconomics

 

June 13, 2024 - Aula Seminari (U7 - 2104) 17:00


Speaker: Claudia Sartirana


Field: Innovation

 

June 20, 2024 - Aula Seminari (U7 - 2104) 17:00


Speaker 1: Ludovica De Carolis


Field: Psychometrics

 

Speaker 2: Jiefeng Bi


Field: Bayesian Statistics

The PhD in Economics, Statistics and Data Science (ECOSTATDATA), the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca, joint with the Italian Society of Econometrics (SIdE), the Free University of Bolzano, the Fondazione Eni Enrico Mattei (FEEM), the International Association of Applied Econometrics (IAAE) and the Rimini Center for Economic Analysis (RCEA), have organized the 4th Italian Workshop on Econometrics and Empirical Economics (IWEEE 2024) - Climate and Energy Econometrics, at the Free University of Bolzano, during the period January 25-26, 2024. 

The PhD in Economics, Statistics and Data Science (ECOSTATDATA), the Center for European Studies (CefES) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized the course Bayesian Structural VAR, held by Prof. Fabio Canova, BI Norwegian Business School, during the period November 9-14, 2023. 

The PhD in Economics, Statistics and Data Science (ECOSTATDATA) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized the course Statistical Learning, held by Prof. Botond Szabo, Bocconi University, during the period October 5-27, 2021.

The PhD in Economics, Statistics and Data Science (ECOSTATDATA) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized the course Statistical Learning, held by Prof. Omiros Papaspiliopoulos, Bocconi University , during the period October 5-27, 2021. Detailed information on this course (instructor, objectives, programme, references, prerequistes) can be found here

The PhD in Economics, Statistics and Data Science (ECOSTATDATA), the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca and the Fondazione Eni Enrico Mattei (FEEM), Milano, have organized the summer school on Frontiers of Energy Econometrics, at the Como Lake School of Advanced Studies, during the period September 13-17, 2021. Detailed information on the programme and the application procedure can be found on the summer school website: https://toee.lakecomoschool.org/

The PhD in Economics and Statistics (ECOSTAT) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized the course Statistical Learning, held by Prof. Rajen Shah, University of Cambridge, during the period October 5-30, 2020. Detailed information on this course (instructor, objectives, programme, references, prerequistes) can be found here.

The PhD in Economics and Statistics (ECOSTAT) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca have organized and hosted the course Statistical Learning and Big Data, held by Prof. Sharon Rosset, Tel Aviv University, during the period October 7-18 2019. Detailed information on this course (instructor, objectives, programme, references, prerequistes) can be found here.

The PhD programme in Economics and Statistics (ECOSTAT) has sponsored the 1st CefES International Conference on European Studies, to be held at the University of Milano-Bicocca, Building U6, on June 10th-11th 2019. Details on this event can be found here.

The PhD programme in Economics and Statistics (ECOSTAT) has sponsored the International Conference on Econometric Models of Climate Change, held at the University of Milano-Bicocca on August 29th-30th 2019. Details on this event can be found here.

Within the Seminar Series DEMS-ECOSTAT, Prof. Peter M Robinson (LSE),  has presented the paper titled “Long-range dependent curve time series” (joint with Degui Li and Han Lin Shang). Prof. Robinson is one of the most famous econometricians worldwide and has been in the editorial boards of the most influential journals in econometrics and statistics, from Econometrica to the Journal of Econometrics, from the Journal of the American Statistical Association to the Annals of Statistics. Peter Robinson’s presentation is available here, while his paper is available here. This event has been held on February 14th 2019, 12.00am, at the Aula del Consiglio, U7, fourth floor, Piazza dell’Ateneo Nuovo 1, 20126 - Milano.

Within the celebrative events of the Twentieth Anniversary of the University of Milano-Bicocca, the Department of Economics, Management and Statistics, in collaboration with the School for Graduate Studies, has organized the International Conference on The Mathematics of Subjective Probability. This event was held on September  3rd-5th  2018, at Room U4/2, Piazza della Scienza 1, 20126 - Milano.

Within the celebrative events of its Twentieth Anniversary, the University of Milano-Bicocca, in collaboration with its School for Graduate Studies, has organized the Lectio Magistralis of Prof. Robert Engle (NYU University), winner of the 2003 Nobel Memorial Prize in Economic Sciences, on “A Financial Approach to Environmental Risk”. This event was held on June 22nd 2018, 10.00am, at the Auditorium Guido Martinotti U12, Via Vizzola 5, 20126 - Milano.

The Center for European Studies (CefES-DEMS-UNIMIB), the PhD program in Economics and Statistics (ECOSTAT-UNIMIB), and the Department of Economics, Management and Statistics (DEMS-UNIMIB) have organized the one-day international conference on Economic and Financial Implications of Climatic ChangeTwo plenary sessions on the economic and financial implications of climatic change have been organized on June 22nd 2018, following Prof. Robert Engle’s talk, from 11.30am to 4.45pm, at the Auditorium Guido Martinotti U12, Via Vizzola 5, 20126 - Milano.

Reading Groups (RG) offered in academic year 2022-23 (XXXVII cycle – II year) for the curriculum in Economics (ECO):

 

I term (October 2022 – December 2022)

Social Network Theory (Instructor: Prof. F. Panebianco, Catholic University of Milano)

Applications of Game Theory (Instructor: Prof. M. Gilli, University of Milano-Bicocca)

Empirical Banking (Instructor: Prof. Elena Beccalli, Catholic University of Milano)

Advanced Asset Pricing and Portfolio Management (Instructor: Prof. A. Tarelli, Catholic University of Milano)

Empirical Corporate Finance (Instructor: Prof. E. Croci, Catholic University of Milano)

Programming in Python (Instructor: Prof. L. Viarengo, Catholic University of Milano)

II term (January 2023 – April 2023)

Spatial Models (Instructor: Prof. S. Colombo, Catholic University of Milano)

Financial Frictions (Instructor: Prof. D. Delli Gatti, Catholic University of Milano)

The Microeconomics of International Trade (Instructor: Prof. V. Gattai, University of Milano-Bicocca)

Innovation and Industrial Evolution (Instructor: Prof. C. Garavaglia, University of Milano-Bicocca)

Structural VAR Models (Instructors: Proff. V. Colombo, G. Rivolta, Catholic University of Milano)

Applied Health Economics and Policy (Instructors: Proff. G. Turati, E. Cottini, L. Salmasi, Catholic University of Milano)

Note: the RG for the curriculum ECO are offered jointly with the PhD in Economics and Finance of the Catholic University of Milano (CUM). CUM is in charge of the timetable of each RG, whose updated version can be found here

The following extra-RG are offered by ECOSTATDATA in the II term:

Expected Utility and Decision Theory (Instructor: Prof. G. Cassese, University of Milano-Bicocca)

Estimated DSGE Models (Instructor: Prof. Alice Albonico, University of Milano-Bicocca)

Authority and Delegation (Instructor: Prof. Irene Valsecchi, University of Milano-Bicocca)

Note: the timetable of the extra-RG is available here

 

Reading Groups (RG) offered in academic year 2022-23 (XXXVII cycle – II year) for the curriculum in Statistics (STAT):

 

I term (October 2022 – December 2022)

The Dependent Dirichlet Process and Related Models (Instructors: Proff. F. Camerlenghi, B. Nipoti, University of Milano-Bicocca)

II term (January 2023 – April 2023)

Some Issues in Statistical Modelling (Instructor: Prof. R. Borgoni, University of Milano-Bicocca)

Empirical Bayes in Bayesian Inference (instructor: Prof. S. Rizzelli, Catholic University of Milano)

Automated Machine Learning & Neural Architectural Search (Instructor: Prof. A. Candelieri, University of Milano-Bicocca)

Deep Learning (Instructor: Prof. M. Borrotti, University of Milano-Bicocca)

Note: the timetable of the RG for the curriculum STAT is available here

 

Reading Groups (RG) offered in academic year 2022-23 (XXXVII cycle – II year) for the curriculum Big Data & Analytics for Business (BIDAB):

 

II term (January 2023 – April 2023)

Databases for Structured and Unstructured Data – SQL (POSTPONED) (Instructor: Prof. F. Mercorio, University of Milano-Bicocca)

Human-centered AI (Instructor: Prof. F.M. Zanzotto, University of Roma-Tor Vergata)

Note: the timetable of the RG for the curriculum BIDAB is available here

I Term

The I term teaching activities start on 24 October 2022 and end on 23 December 2022. The I term exam session starts on 9 January 2023 and ends on 13 January 2023.

Note: the timetable of the I term courses is available here

 

The courses/modules offered during the I term for the curriculum Economics (ECO) are:

Computational Statistics I (Instructor: Prof. G. Bertarelli, University of Pisa)

Mathematics – Linear algebra (Instructor: Prof. N. Pecora, Catholic University of Milano)

Mathematics I (Instructor: Prof. D. Visetti, University of Milano-Bicocca);

Mathematics II (Instructor: Prof. F. Cavalli, University of Milano-Bicocca);

Mathematics III (Instructor: Prof. M. Longo, Catholic University of Milano)

The courses/modules offered during term I for the curriculum Statistics (STAT) are:

Mathematical Analysis (Instructors: Prof. C. Zanco, University of Milano; Proff. C.A. De Bernardi, E. Miglierina, Catholic University of Milano)

Numerical Optimization (Instructor: Prof. L. Mascotto, University of Milano-Bicocca) 

The courses/modules offered during term I for the curriculum Big Data & Analytics for Business (BiDAB) are:

Programming in Python (Instructor: Prof. M. Cesarini, University of Milano-Bicocca)

Architecture for Big Data Processing (Instructor: Prof. V. Moscato, University of Napoli)

Architecture for Big Data Processing Lab (Instructor: Prof. G. Sperlì, University of Napoli)

II Term

The II term teaching activities start on 16 January 2023 and end on 5 April 2023. The II term exam session starts on 17 April 2023 and ends on 21 April 2023. 

The courses/modules offered during the II term for the curriculum Economics (ECO) are:

Econometrics I (Instructor: Prof. M. Manera, University of Milano-Bicocca)

Econometrics I – Tutorials (Instructor: Dr. C. Cattaneo, European Institute on Economics and the Environment)

Econometrics II (Instructor: Prof. M.L. Mancusi, Catholic University of Milano)

Econometrics II – Tutorials (Instructor: Dr. E. Villar, Catholic University of Milano)

Econometrics III (Instructor: Prof. A. Ugolini, University of Milano-Bicocca)

Econometrics III - Tutorials (Instructor: Dr. D. Valenti, Fondazione Eni Enrico Mattei)

Microeconomics I (Instructor: Prof. M. Mantovani, University of Milano-Bicocca)

Microeconomics I – Tutorials (Instructor: Dr. F. Campo, University of Milano-Bicocca)

Microeconomics II (Instructtor: Prof. M. Gilli, University of Milano-Bicocca)

Microeconomics II – Tutorials (Instructor: Prof. M. Gilli, University of Milano-Bicocca)

Microeconomics III (Instructor: Prof. L. Colombo, Catholic University of Milano)

Microeconomics III – Tutorials (Instructor: Dr. D. Bosco, University of Milano-Bicocca)

Microeconomics IV (Instructor: Prof. P. Bertoletti, University of Milano-Bicocca)

Microeconomics IV – Tutorials (Instructor: Dr. G. Crea, University of Pavia)

Note: the timetable of the II term courses for the curriculum ECO is available here.

 

The courses/modules offered during the II term for the curriculum Statistics (STAT) are:

Probability I & II (Instructor: Prof. F. Camerlenghi, University of Milano-Bicocca)

Stochastic Processes (Instructor: Prof. B. Buonaguidi, Catholic University of Milano)

R for Data Science (Instructor: Prof. A. Gilardi, University of Milano-Bicocca)

Statistical Inference I (Instructor: Prof. A. Caponera, University of Milano-Bicocca)

Note: the timetable of the II term courses for the curriculum STAT is available here.

 

The courses/modules offered during the II term for the curriculum Big Data & Analytics for Business (BIDAB) are:

Probability (Instructor: Prof. A. Di Brisco, University of Piemonte Orientale)

Statistical Inference I (Instructor: Prof. R. Ascari, University of Milano-Bicocca)

Note: the timetable of the II term courses for the curriculum BIDAB is available here.

 

III Term

The III term teaching activities start on 26 April 2023 and end on 7 July 2023. The III term exam session starts on 17 July 2023 and ends on 21 July 2023. 

 

The courses/modules offered during the III term for the curriculum Economics (ECO) are:

Mandatory

- Macroeconomics I (Instructor: Prof. G. Femminis, Catholic University of Milano)

- Macroeconomics II (Instructor: Prof. A. Albonico, University of Milano-Bicocca)

- Macroeconomics III (Instructor: Prof. R. Masolo, Catholic University of Milano)

- Macroeconomics IV (Instructor: Dr. B. Barbaro, University of Milano-Bicocca)

Computational Statistics II (Instructor: Prof. A. Pini, Catholic University of Milano)

Research Methods (Instructors: Prof. T. Colussi, Catholic University of Milano; Prof. K. Aktas, University of Milano-Bicocca)

 Optional

- Finance I – Empirical Corporate Finance (Instructor: Prof. A. Signori, Catholic University of Milano)

- Finance II – Asset Pricing Theory (Instructor: Prof. A. Sbuelz, Catholic University of Milano)

- Finance III – Banking (Instructors: Proff. M. Migliavacca, F. Pampurini, Catholic University of Milano)

Note: the timetable of the III term courses for the curriculum ECO is available here.

 

The courses/modules offered during the III term for the curriculum Statistics (STAT) are:

Mandatory

Statistical Inference II (Instructor: Prof. A. Solari, University of Milano-Bicocca)

- Bayesian Statistics (Instructors: Prof. R. Argiento, University of Bergamo; Proff. B. Nipoti, T. Rigon, University of Milano-Bicocca)

- Data Management (CANCELLED)

Optional

Computational Statistics II (Instructor: Prof. A. Pini, Catholic University of Milano)

Note: the timetable of the III term courses for the curriculum STAT is available here.

 

The courses/modules offered during the III term for the curriculum Big Data & Analytics for Business (BIDAB) are:

- Technology and Innovation Management (Instructors: Proff. S. Torrisi, L. D'Agostino, F. Di Pietro, M. Guerzoni, University of Milano-Bicocca)

- Machine Learning (Instructor: Prof. L. Malandri, University of Milano-Bicocca)

- Natural Language Understanding (CANCELLED)

Social Media Analytics (Instructor: Prof. R. Boselli, University of Milano-Bicocca)

Note: the timetable of the III term courses for the curriculum BIDAB is available here.

 

IV Term

The IV term teaching activities start on 4 September 2023 and end on 20 October 2023. The IV term exam session starts on 23 October 2023 and ends on 27 October 2023. 

Note: the timetable of the IV term courses is under construction and is currently shared with all the ECOSTATDATA students, who can monitor online any updates/modifications.

 

The courses/modules offered during the IV term for the curriculum Statistics (STAT) are:

- Statistical Learning (POSTPONED)

- Statistical Modelling I (Instructor: Prof. F. Castelletti, Catholic University of Milano)

- Statistical Modelling II (Instructor: Prof. F. Greselin, University of Milano-Bicocca)

- Statistical Modelling III (Instructor: Dr. S. Verzillo, European Commission - Joint Research Center)

- Statistical Modelling IV (Instructors: Prof. F. Pennoni, University of Milano-Bicocca; Prof. F. Bartolucci, University of Perugia)

The courses/modules offered during the IV term for the curriculum Big Data & Analytics for Business (BIDAB) are:

- Statistical Modelling I (Instructor: Prof. F. Castelletti, Catholic University of Milano)

- Statistical Inference II (Instructor: Prof. R. Ascari, University of Milano-Bicocca)

- Explainable AI for Business Value (Instructor: Prof. F. Mercorio, University of Milano-Bicocca)

- Deep Learning and Computer Vision for Business (Instructor: Prof. E. Frontoni, Polytechnic University of Marche, TBC)

Reading Groups (RGs) offered in academic year 2023-24 (XXXVIII cycle – II year) for the curriculum Economics (ECO):

I term (October 2023 – December 2023) and II term (January 2024 – April 2024)

Note: the RGs for the curriculum ECO are offered jointly with the PhD in Economics and Finance of the Catholic University of Milano. Detailed information on each RG and its timetable can be found here

 

Reading Groups (RGs) offered in academic year 2023-24 (XXXVIII cycle – II year) for the curriculum Statistics (STAT):

I term (November 2023 – December 2023) and II term (January 2024 – April 2024)

Note: the timetable of the RGs for the curriculum STAT is shared online (via Google Calendar) with students officially enrolled in the PhD program. 

- RG Approximate Bayesian Computational Methods (Instructor: Dr. A. Fasano, Catholic University of Milano)

- RG Automated Machine Learning & Neural Architectural Search (Instructor: Prof. A. Candelieri, University of Milano-Bicocca)

- RG Spatio-temporal Data (Instructors: Prof. R. Borgoni and Dr. P. Maranzano, University of Milano-Bicocca)

- RG Some Issues on Statistical Modelling (Instructor: Prof. R. Borgoni, University of Milano-Bicocca)

- RG Deep Learning (Instructor: Prof. M. Borrotti, University of Milano-Bicocca)

Reading Groups (RGs) offered in academic year 2023-24 (XXXVIII cycle – II year) for the curriculum Big Data & Analytics for Business (BIDAB):

I term (November 2023 - December 2023) and II term (January 2024 – April 2024)

Note: the timetable of the RGs for the curriculum BIDAB is shared online (via Google Calendar) with students officially enrolled in the PhD program.

- RG Natural Language Processing (Instructor: Dr. A. Seveso, University of Milano-Bicocca)

- RG Generative AI (Instructor: Dr. Navid Nobani, University of Milano-Bicocca)

 

I Term

The I term teaching activities start on 23 October 2023 and end on 22 December 2023. The I term exam session starts on 8 January 2024 and ends on 12 January 2024.

Note: the timetable of the I term courses is shared online (via Google Calendar) with all students officially enrolled in the PhD program.

 

The courses/modules offered during the I term for the curriculum Economics (ECO) are:

Mathematics – Linear algebra (Instructor: Dr. N. Pecora, Catholic University of Milano)

Mathematics I (Instructor: Dr. D. Visetti, University of Milano-Bicocca);

Mathematics II (Instructor: Prof. F. Cavalli, University of Milano-Bicocca);

Mathematics III (Instructor: Prof. M. Longo, Catholic University of Milano)

- Microeconomics I (Instructor: Prof. M. Mantovani, University of Milano-Bicocca)

 

The courses/modules offered during term I for the curriculum Statistics (STAT) are:

Mathematical Analysis I-II-III (Instructors: Dr. J. Somaglia, Polytechnic of Milano; Proff. C.A. De Bernardi, E. Miglierina, Catholic University of Milano)

Numerical Optimization (Instructor: Dr. L. Mascotto, University of Milano-Bicocca) 

 

The courses/modules offered during term I for the curriculum Big Data & Analytics for Business (BiDAB) are:

Programming in Python (Instructor: Dr. M. Cesarini, University of Milano-Bicocca)

Architecture for Big Data Processing & Lab (Instructors: Prof. V. Moscato and Dr. G. Sperlì, University of Napoli)

 

II Term

The II term teaching activities start on 15 January 2024 and end on 27 March 2024. The II term exam session starts on 8 April 2024 and ends on 12 April 2024.

Note: the timetable of the II term courses is shared online (via Google Calendar) with all students officially enrolled in the PhD program.

 

The courses/modules offered during the II term for the curriculum Economics (ECO) are:

- Microeconomics II (Instructor: Prof. M. Gilli, University of Milano-Bicocca)

- Microeconomics III (Instructors: Prof. L. Colombo and Dr. M. Magnani, Catholic University of Milano)

- Microeconomics IV (Instructors: Prof. P. Bertoletti, University of Milano-Bicocca, and Dr. G. Crea, University of Pavia)

- Econometrics I (Instructors: Prof. M. Manera, University of Milano-Bicocca, and Dr. C. Cattaneo, European Institute on Economics and the Environment)

- Econometrics II (Instructors: Dr. A. Ugolini, University of Milano-Bicocca, and Dr. D. Valenti, Polytechnic of Milano)

- Econometrics III (Instructors: Prof. M.L. Mancusi and Dr. E. Villar, Catholic University of Milano)

- Computational Statistics I (Instructor: Dr. G. Bertarelli, University of Venezia)

 

The courses/modules offered during the II term for the curriculum Statistics (STAT) are:

- Probability I-II (Instructor: Prof. F. Camerlenghi, University of Milano-Bicocca)

- Stochastic Processes (Instructor: Dr. B. Buonaguidi, Catholic University of Milano)

- Statistical Inference I (Instructor: Dr. A. Caponera, Luiss Guido Carli University) 

- R for Data Science (Instructor: Dr. A. Gilardi, Polytechnic of Milano)

 

The courses/modules offered during the II term for the curriculum Big Data & Analytics for Business (BiDAB) are:

- Probability (Instructor: Prof. A. Di Brisco, University of Piemonte Orientale)

Statistical Inference I (Instructor: Dr. R. Ascari, University of Milano-Bicocca)

 

III Term

The III term teaching activities start on 15 April 2024 and end on 5 July 2024. The III term exam session starts on 15 July 2024 and ends on 19 July 2024.

Note: the timetable of the II term courses is shared online (via Google Calendar) with all students officially enrolled in the PhD program.

The courses/modules offered during the III term for the curriculum Economics (ECO) are:

- Computational Statistics II (Instructor: Prof. A. Pini, Catholic University of Milano)

- Macroeconomics I (Instructor: Prof. G. Femminis, Catholic University of Milano)

- Macroeconomics II (Instructors: Prof. A. Albonico, University of Milano-Bicocca)

- Macroeconomics III (Instructors: Dr. B. Barbaro, University of Milano-Bicocca and Prometeia)

- Macroeconomics IV (Instructors: Dr. R. Masolo, Catholic University of Milano)

- Research Methods (Instructors: Dr. S. Ghisolfi and Prof. T. Colussi, Catholic University of Milano)

 

The courses/modules offered during the III term for the curriculum Statistics (STAT) are:

- Statistical Inference II (Instructor: Prof. A. Solari, University of Venezia)

- Principles of Bayesian Statistics (Instructor: Prof. B. Nipoti, University of Milano-Bicocca)

- Bayesian Computations (Instructor: Dr. T. Rigon, University of Milano-Bicocca) 

- Bayesian Modelling (Instructor: Prof. R. Argiento, University of Bergamo)

 

The courses/modules offered during the III term for the curriculum Big Data & Analytics for Business (BiDAB) are:

Statistical Inference II (Instructor: Dr. R. Ascari, University of Milano-Bicocca)

- Social Media Analytics (Instructor: Dr. R. Boselli, University of Milano-Bicocca)

- Machine Learning (Instructor: Dr. L. Malandri, University of Milano-Bicocca)

- Technology and Innovation Management I (Instructor: Prof. S. Torrisi, University of Milano-Bicocca)

- Technology and Innovation Management II (Instructor: Prof. M. Corsino, University of Milano-Bicocca)

- Technology and Innovation Management III (Instructor: Dr. F. Di Pietro, University of Milano-Bicocca)

- Technology and Innovation Management IV (Instructor: Prof. M. Guerzoni, University of Milano-Bicocca)