A.A. 2022-2023 (cycle XXXVIII)

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 2022-23 (XXXVIII 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 2022 (the precise starting date will be announced in due course).

We offer at least ten fellowships (for a period of four years) to the highest ranked applicants. Each  fellowship pays a grant of a minimum of € 16.200 (gross income) per year. The monthly allowance can be increased up to 50% for our PhD students visiting academic or scientific institutions abroad. There will also be allowances (research funds) for short-period mobility (from the first year).

Additional scholarships and positions are also available on specific research projects in collaboration with national and international companies of primary importance.

The selection procedure is regulated by the official Call for Applications (Bando di Concorso), which is expected to be published in the Doctoral School’s and in the PhD programme websites on April 21st 2022. The official Call for Applications contains detailed information on: i) the documents which each candidate has to submit; ii) structure, contents and timing (approximately during June 2022) of the entrance examination; iii) description of the projects related to the additional scholarships and positions.

The link to the official Call for Applications can be found here.

Introduction

ECOSTAT 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.

ECOSTAT 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 ECOSTAT 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, ECOSTAT 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

ECOSTAT 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

ECOSTAT is particularly active in collaborating with national, multi-national, high-quality and innovation-oriented companies. In particular, ECOSTAT 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 ECOSTAT 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 ECOSTAT is particularly active in collaborating with prestigious foreign universities, in terms of both students and faculty members exchange programs and joint degrees.

ECOSTAT 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 ECOSTAT 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.

The Programme Committee (PC) approves the (minimum) number of papers which form a typical PhD dissertation. These papers have to be 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 in 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.

ECOSTAT 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.

The research activities which characterize the PhD programme in Economics, Statistics and Data Science (ECOSTAT) 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 ECOSTAT 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.

The PhD in Economics and Statistics (ECOSTAT) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca organize the course Statistical Learning, held by Professor 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

On 5th November 2020 the Faculty/research groups presentation has taken place, according to the following schedule:

9:30 – 9:45
International and Development Economics
Presenter: Prof. Silvia Marchesi (DEMS, University of Milano-Bicocca) 

9:45 – 10:00
Bayesian Statistics 
Presenter: Prof. Bernardo Nipoti (DEMS, University of Milano-Bicocca)

10:00-10:15
Microeconomic Theory, Public and Political Economics
Presenter: Prof. Mario Gilli (DEMS, University of Milano-Bicocca)

10:15 – 10:30
Statistical Modelling I: Methods, Applications and Computations
Presenter: Prof. Fulvia Pennoni (DiSMeQ, University of Milano-Bicocca)

10:30– 10:45
Behavioral and Experimental Economics
Presenter: Prof. Marco Mantovani (DEMS, University of Milano-Bicocca)

10:45-11:00
Statistical Modelling II: Methods, Applications and Computations
Presenter: Prof. Raffaele Argiento (DiSTAT, Catholic University of Milano)

11:00-11:15
Banking and Finance
Presenter: Prof. Vittoria Cerasi (DEMS, University di Milano-Bicocca) 

11:15-11:30
Macroeconomics and Macroeconometrics
Presenters: Proff. Andrea Colciago and Claudio Morana (DEMS, University di Milano-Bicocca)

11:30-11:45
Economic Statistics 
Presenter: Prof. Matteo Pelagatti (DEMS, University of Milano-Bicocca)

11.45-12:00
Applied Statistics: Education and Health 
Presenter: Prof. Paolo Berta (DiSMeQ, University di Milano-Bicocca)

12:00-12:15
Applied Microeconomics and Microeconometrics
Presenter: Prof. Laura Pagani (DEMS, University di Milano-Bicocca)

12:15-12:30
Computational Statistics, Data Mining and Statistical Learning
Presenter: Prof. Aldo Solari (DEMS, University di Milano-Bicocca)

Selected presentations are available upon request. Requests should be submitted here.

On November 26 and 27, 2020, XXXIV cycle students have presented their research projects in front of the Programme Committee, the DEMS faculty and their supervisors.  

The PhD in Economics and Statistics (ECOSTAT) and the Department of Economics, Management and Statistics (DEMS) at the University of Milano-Bicocca organize the course Statistical Learning, held by Professor 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 organize and host 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) sponsors the 1^st CefES International Conference on European Studies, to be held at the University of Milano-Bicocca, Building U6, on June 10th-11^th 2019. Details on this event can be found here.

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

Within the Seminar Series DEMS-ECOSTAT, Prof. Peter M Robinson (LSE),  will present 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 will be 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, is pleased to announce the International Conference on The Mathematics of Subjective Probability. This event will be 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, is pleased to announce 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 will be held on June 22nd 2018, 10.00am, at the Auditorium Guido Martinotti U12, Via Vizzola 5, 20126 - Milano.

The newly established 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) are delighted of organizing the one-day international conference on Economic and Financial Implications of Climatic Change. Two plenary sessions on the economic and financial implications of climatic change have been organized on June 22^nd 2018, following Prof. Robert Engle’s talk, from 11.30am to 4.45pm, at the Auditorium Guido Martinotti U12, Via Vizzola 5, 20126 - Milano.

I Term

The I term teaching activities start on 4 November 2019 and end on 20 December 2019. The I term exam session starts on 7 January 2020 and ends on 10 January 2020.

The timetable of the I term courses is available here.

The courses/modules offered during the I term for the curriculm ECO are:

- Computational Statistics I (Instructor: Prof. Bertarelli)

- Mathematics I (Instructor: Prof. Pireddu)

- Mathematics II (Instructor: Prof. Cavalli)

- Mathematics – Linear algebra (Instructor: Prof. Pecora)

- Mathematics III (Instructor: Prof. Longo)

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

- Mathematical Analysis (modules I, II and III; Instructors: Proff. Zanco, De Bernardi, Miglierina)

- Numerical Optimization (Instructor: Prof. Dassi)

II Term

The II term teaching activities start on 13 January 2020 and end on 27 March 2020.  The II term exam session starts on 30 March 2020 and ends on 9 April 2020.

The courses/modules offered during the II term for the curriculm ECO are:

- Econometrics I – The Linear Regression Model (Instructor: Prof. Manera)

- Econometrics II – Microeconometrics (Instructor: Prof. Mancusi)

- Econometrics III – Time Series Part I & II (in common with curriculum STAT; Instructor: Dr. Bastianin)

- Microeconomics I – Consumption, Production, Market Forms  (Instructor: Prof. Athanasoglou)

- Microeconomics II – Game Theory (Instructor: Prof. Gilli)

- Microeconomics III – Contract Theory (Instructor: Prof. Colombo)

- Microeconomics IV – (Instructor: Prof. Bertoletti)

The courses/modules offered during the II term for the curriculm STAT are:

- Probability I (Instructor: Prof. Camerlenghi)

- Probability II (Instructor: Prof. Camerlenghi)

- Stochastic Processes (Instructor: Prof. Davydov)

- Computational Statistics II (in common with curriculum ECO – Instructor: Dr.ssa Pini)

- Statistical Inference I (Instructor: Prof. Lunardon)

- Econometrics III – Time Series Part I & II (in common with curriculum ECO; Instructor: Dr. Bastianin)

III Term

The timetable of the III term courses is available here.

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

-  Macroeconomics I –  (Instructor: Prof. Femminis)

-  Macroeconomics III –  (Instructor: Prof. Tirelli)

-  Macroeconomics III – (Instructor: Dr.ssa Albonico)

-  Macroeconomics II –  (Instructor: Prof. Ropele)

-  Macroeconomics IV – (Instructor: Dr.ssa Barbaro)

- Research Methods – (Instructor: Prof. Colussi)

- Finance I – Empirical Corporate Finance (Instructor: Prof. Signori)

- Finance II – Asset Pricing Theory (Instructor: Prof. Sbuelz)

- Finance III – Banking (Instructor: Prof. Cerasi)

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

- Statistical Inference II (Instructor: Prof. Solari)

- Statistical Inference III (Instructor: Prof. Dolera)

- Bayesian Statistics I (Instructor: Prof. Ntzoufras)

- Bayesian Statistics II (Instructor: Prof. Argiento)

- R for Data Science – (Instructor: Prof. Melloncelli)

- Data Management (Instructor: Prof. Maurino)

Some of the courses are offered jointly with the PhD program in Economics and Finance of the Catholic University of Milan (UCSC). For this reason, some lectures will be held at the premises of UCSC, as clearly indicated in the timetable.

IV Term

The IV term teaching activities start beginning of September 2020.  The IV term exam session will be fixed in due course. 

The timetable of the IV term courses for the curriculum STAT is available here.

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

- Statistical Modelling (Instructors: Prof.ssa F. Greselin, Prof. Verzillo, Prof.ssa F. Pennoni, F. Bartolucci) 

- Statistical Learning I & II (Instructor: Prof. Rajen Shah)

- Statistical Learning III (Instructor: Prof. Aldo Solari)

Courses (reading groups) offered in year 2020-21 for the curriculum ECO:                             

Reading groups in Advanced Macroeconomics                                                         

Instructor                                                 Title                                                                              Term

Andrea Colciago - Rajssa Mechelli            Heterogeneous Agents Models in Macroeconomics         I

Domenico Delli Gatti                                 Financial Frictions                                                          II

Silvia Marchesi                                          The Economics of Sovereign Debt                                   I

Domenico Massaro                                    Behavioral and Experimental Macroeconomics               II

Patrizio Tirelli                                            Unconventional Monetary Policies                                  II

Reading groups in Advanced Microeconomics                  

Istructor                                                     Title                                                                             Term

Gianluca Cassese                                        Fixed Point Techniques in Equilibrium Analysis             II

Stefano Colombo                                        Spatial Models in Microeconomics                                 II

Valeria Gattai                                              International Economics                                                 I

Fabrizio Panebianco                                    Social Network Theory                                                   I

Reading groups in Advanced Econometrics                        

Instructor                                                     Title                                                                            Term

Andrea Bastianin                                        Economic Forecasting                                                     II

Andrea Monticini                                        Bootstrap Methods for Time Series                                 II

Gazi Salah Uddin                                        Advanced Time Series Modelling                                     I

Reading groups in Advanced Finance                    

Instructor                                                     Title                                                                           Term

Elena Beccalli                                              Empirical Banking                                                          I

Ettore Croci                                                Advanced Corporate Finance                                          I

Andrea Tarelli                                             Advanced Asset Pricing and Portfolio Management        II

Reading groups in Advanced Computational Statistics and Coding                         

Instructor                                                     Title                                                                             Term

Alice Albonico                                            Estimated DSGE models                                                   II

Domenico Massaro                                    Computational Frameworks in Macroeconomics               II

The timetable of the reading groups for the curriculum ECO offered during term I can be found here.

The timetable of the reading groups for the curriculum ECO offered during term II can be found here

Courses (reading groups) offered in year 2020-21 for the curriculum STAT:

Instructor                                                  Title                                                             Term 

Paci Lucia                        Statistics for Spatio-Temporal Data                                          I

Camerlenghi – Nipoti       Bayesian Non parametric Mixture Models                                 II

Borgoni Riccardo             Some issues in Statistical Modelling                                         II

Borrotti Matteo                Introduction to Deep Learning                                             II-III

Candelieri Antonio           Automated Machine Learning&Neural Architecture Search       III

The timetable of the reading groups for the curriculum STAT is available here

I Term

The I term teaching activities start on 26 October 2020 and end on 23 December 2020. The I term exam session starts on 7 January 2021 and ends on 13 January 2021. 

The timetable of the I term courses is available here.

For term I lessons will be online in live mode. Students will be contacted by the professors for more details.

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

- Computational Statistics I (Instructor: Prof. Bertarelli)

- Mathematics – Linear algebra (Instructor: Prof. Pecora)

- Mathematics I (Instructor: Prof. Pireddu);

- Mathematics II (Instructor: Prof. Cavalli);

- Mathematics III (Instructor: Prof. Longo)

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

- Mathematical Analysis (modules I, II and III; Instructors: Proff. Zanco, De Bernardi, Miglierina)

- Numerical Optimization (Instructor: Prof. Dassi) 

II Term

The II term teaching activities start on 11 January 2021 and end on 31 March 2021.  The II term exam session starts on 6 April 2021 and ends on 9 April 2021. 

For term II the lessons will be online in live mode.  Students will be contacted by the professors for more details.

The return to live lessons will be communicated promptly, as soon as the pandemic conditions allow it.

The timetable of the II term courses is available here.

The courses/modules offered during term II for the curriculm ECO are:

- Econometrics I – The Linear Regression Model (Instructor: Prof. Manera)

- Econometrics II – Microeconometrics (Instructor: Prof. Mancusi);

- Econometrics III – Time Series Part I & Part II (Instructor: Prof. Bastianin; Part II  in common with curriculum STAT)

- Microeconomics I – Consumption, Production, Market Forms  (Instructor: Prof. Athanasoglou)

- Microeconomics II – Game Theory (Instructor: Prof. Gilli)

- Microeconomics III – Contract Theory (Instructor: Prof. Colombo)

- Microeconomics IV – (Instructor: Prof. Bertoletti)

The courses/modules offered during term II for the curriculm STAT are:

- Probability I & II (Instructor: Prof. Camerlenghi)

- Stochastic Processes (Instructor: Prof. Buonaguidi)

- R for Data Science (Instructor: Prof. Melloncelli)

- Statistical Inference I (Instructor: Prof. Lunardon)

- Econometrics III – Time Series – Part II (Instructor: Prof. Bastianin) 

Courses (Reading Groups) offered in year 2021/22 for the curriculum ECO:

I term:

II term:

Courses (Reading Groups) offered in year 2021/22 for the curriculum STAT:

I Term

The I term teaching activities start on 25 October 2021 and end on 23 December 2021. The I term exam session starts on 7 January 2022 and ends on 14 January 2022. 

The timetable of the I term courses is available here

Lessons will be in presence

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

- Computational Statistics I (Instructor: Prof. Bertarelli)

- Mathematics – Linear algebra (Instructor: Prof. Pecora)

- Mathematics I (Instructor: Prof. Pireddu);

- Mathematics II (Instructor: Prof. Cavalli);

- Mathematics III (Instructor: Prof. Longo)

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

- Mathematical Analysis (modules I, II and III; Instructors: Proff. Zanco, De Bernardi, Miglierina)

- Numerical Optimization (Instructor: Prof. Dassi) 

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

- Programming in Python (Instructor: prof. Mirko Cesarini)

- Architecture for Big Data Processing (Instructor: prof. Vincenzo Moscato)

- Architecture for Big Data Processing Lab (Instructor: prof. GianCarlo Sperli)

II Term

The II term teaching activities start on 17 January 2022 and end on 8 April 2022.  The II term exam session starts on 18 April 2022 and ends on 22 April 2022.

The timetable of the II term courses is available here.

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

- Econometrics I – The Linear Regression Model (Instructor: Prof. Manera)

- Econometrics II – Microeconometrics (Instructor: Prof. Mancusi);

- Econometrics III – Time Series Part I & Part II (Instructor: Prof. Bastianin; Part II  in common with curriculum STAT)

- Microeconomics I – Consumption, Production, Market Forms  (Instructor: Prof. Athanasoglou)

- Microeconomics II – Game Theory (Instructor: Prof. Gilli)

- Microeconomics III – Contract Theory (Instructor: Prof. Colombo)

- Microeconomics IV – (Instructor: Prof. Bertoletti)

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

- Probability I & II (Instructor: Prof. Camerlenghi)

- Stochastic Processes (Instructor: Prof. Buonaguidi)

- R for Data Science (Instructor: Prof. Melloncelli)

- Statistical Inference I (Instructor: Prof. Cattelan)

- Econometrics III – Time Series – Part II (Instructor: Prof. Bastianin)

The courses/modules offered during term II for the curriculum BiDAB are:

- Probability (Instructor: Prof. DiBrisco)

- Big Data Processing Lab (Hadoop/Spark) (Instructor: Prof. Tamburri)

- Statistical Inference I (Instructor: Prof. Ascari)

- Statistical Inference II (Instructor: Prof. Corradin)

III Term

The III term teaching activities start on 26 April 2022 and end on 8 July 2022.  The III term exam session starts on 18 July 2022 and ends on 28 July 2022. 

For term III the lessons will be in presence.

The timetable of term III courses is available here.

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

-  Macroeconomics part I –  (Instructor: Prof. Femminis)

-  Macroeconomics part II –  (Instructor: Prof. Gobbi);

-  Macroeconomics part III –  (Instructor: Prof. Ropele);

-  Macroeconomics - Esercitazioni – (Instructor: Dr.ssa Barbaro)

-  Research Methods – (Instructor: Prof. Colussi – Dr.ssa Villar)

-  Computational Statistics II – Part I (Instructor: Prof. Pini)

-  Finance I – Empirical Corporate Finance (Instructor: Prof. Signori)

-  Finance II – Asset Pricing Theory (Instructor: Prof. Sbuelz)

-  Finance III – Banking (Instructor: Dr.ssa Migliavacca)

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

- Statistical Inference II (Instructor: Prof. Solari)

- Statistical Inference III (Instructor: Prof. Dolera)

- Bayesian Statistics I (Instructor: Prof. Nipoti)

- Bayesian Statistics II (Instructor: Prof. Argiento)

- Computational Statistics II – Part I (Instructor: Prof. Pini)

- Computational Statistics II – Part II (Instructor: Prof. Rigon)

- Data Management (Instructor: Prof. Maurino)

The courses/modules offered during term III for the curriculum BiDAB are:

- Technology and Innovation Management

   * The sources of innovation and the strategic management of intellectual property (Instructor: Prof. Torrisi)

   * Collaborative innovation and internationalization of R&D (Instructor: Prof.ssa D'Agostino)

   * The financing of innovation (Instructor: Prof.ssa Di Pietro)

   * Technology diffusion, firms’ survival and knowledge Sharing (Instructor: Prof. Guerzoni)

- Natural Language Understandings (Instructor: Prof. Cambria)

- Social Media Analytics (Instructor: Prof. Boselli)

- Machine Learning (Instructor: Prof. Malandri)