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Department of Economics, Management and Statistics  DEMS

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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

NEW!!! Call for applications 2024-2025 (XL cycle)

A.A. 2024-2025 (cycle XL)

Call for Applications

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 .

The PhD programme (in a nutshell...)

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.

Teaching activities

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.

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.

Research activities

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.

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.

Thesis discussion

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.

Programme committee

Research groups.

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 .

Ex-alumni - XXXIV cycle

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

Ex-alumni - XXXV cycle

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

Milano PhD Workshop 2024

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:

PhD students' seminar series 2023-2024

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  

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

Speaker: Andrea Sorrentino

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

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

Speaker:  Matteo Ferraro

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

Speaker:  Lucia Tommasiello

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

Speaker:  Mattia Longhi

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

Speaker:  Claudia Sartirana

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

Speaker 1:  Ludovica De Carolis

Speaker 2:  Jiefeng Bi

Field: Bayesian Statistics

Past events (selected) 2018-2024

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 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) has sponsored the International Conference on Econometric Models of Climate Change, 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),  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 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.

XXXVII cycle - Teaching activities - Year II (terms I - II) - reading groups

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)

-  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 . 

XXXVIII cycle - Teaching activities - Year I (terms I - II - III - IV) - courses

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)

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 .

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:

- 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)

- 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:

-  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)

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 .

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 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)

XXXVIII cycle - Teaching activities - Year II (terms I - II) - reading groups

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)

XXXIX cycle - Teaching activities - Year I (terms I - II - III) - courses

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.

-  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)

-  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) 

-  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)

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.

- 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)

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)

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.

- 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)

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Economics and Finance, PhD

Bocconi University, Italy

• Study options for Economics and Finance
• About Economics and Finance

Courses you may be interested in at other institutions

Other courses at bocconi university, study options for this course, about economics and finance, phd - at bocconi university.

The PhD in Economics and Finance at Bocconi University is a 4-year full-time program designed for highly qualified and motivated students who wish to acquire first-rate research skills. It started in 2010 with a merger of the PhD programs in Economics and in Finance.

The program has been organized within the two curricula of Economics and Finance (students select one curriculum when they apply). By its nature, the program is multidisciplinary and students have the option to choose from a wide range of electives. Dedicated mentorship and support are offered to students throughout their time at Bocconi.

Our first-year students acquire a broad set of theoretical and methodological skills required in both economics and finance (mathematics, statistics, econometrics, microeconomics), as well as to their curriculum (macroeconomics for Economics, asset pricing and corporate finance for Finance).

In the second year , students choose their field of specialization within their curriculum (e.g. asset pricing, accounting, banking, corporate finance, development economics, econometrics, economic history, microeconomic theory, industrial dynamics and organization, international economics, macroeconomics, political economics and public economics). The third and fourth years are entirely dedicated to research , including attendance at regular seminars held by internationally renowned internal and external faculty.

Our PhD classes are enriched by interaction among students from all over the world, with backgrounds not only in economics and finance, but also other disciplines such as engineering and statistics. International exchanges are promoted within the framework of the European Doctoral Group in Economics (http://www.edge-page.net/).

Faculty members are highly performing in terms of international publications and are active members of the international community . They publish in or serve on the editorial boards of leading research journals, such as American Economic Review, Econometrica, Journal of Econometrics, Journal of Economic Theory, Journal of Finance, Journal of Monetary Economics, Journal of Political Economy, Mathematical Finance, Quarterly Journal of Economics, Review of Economic Studies and many others. Faculty members have been and currently are the recipients of prestigious competitive grants (e.g., by the European Research Council and the National Science Foundation in the United States).

The PhD program is designed to prepare and foster an academic career on the international job market. Other career opportunities include central banks, governments and international organizations. In the last few years, our students have been hired by prestigious schools and organizations such as: ESSEC International Business School, The Bank of England, Bank of Italy, Harvard University, London Business School, National Bank of New Zealand, Queen Mary College, Xiamen University, Toulouse School of Economics and others.

Entry requirements for this course

Contact Bocconi University to find course entry requirements.

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Related Information

Find out more about studying in Italy

Coursework provides students with specialized knowledge in Economics and the necessary tools and background for economic analysis and frontier research.

During the first year, students receive a rigorous training in Mathematics, Microeconomics, Macroeconomics and Econometrics. Three or four courses of 20 hours each are usually offered in each area. In the second year, students attend a selection of field courses and start working on their dissertation under the supervision of a Faculty member. The third year is entirely dedicated to research and completion of the thesis.

First-year coursework consists of Lectures (approximately six hours per week) and Tutorials (approximately two hours per week). Second-year coursework is concentrated in the Fall term and consists of Lectures (approximately six hours per week), essay-writing and students presentations.

To complement internal coursework, distinguished lecturers from other Italian or foreign Universities are invited to give series of seminars on specific topics.

Exchange-student agreements allow students to attend PhD courses at Bocconi University, the University of Varese and DEFAP (a joint program of the Catholic University of Milan and the University of Milano-Bicocca), and thus deepen their knowledge in their research fields.

Students have to enroll in courses by the 25th of the month prior to the start date, here: https://www.unimi.it/en/study/postgraduate-study/doctoral-research-phd-programmes/following-your-plan-study/phd-courses-catalogue

2nd and 3rd year

First term - october 2023 - january 2024 - timetable.

Mathematics

• Static and Dynamic Optimization , Prof. Elena Molho and Prof. Daria Ghilli

Microeconomics

• Theory of Production and Consumption Decisions , Prof. Marzio Galeotti
• General Equilibrium Theory , Prof. Enrico Minelli
• Experimental Economics , Prof Antonio Filippin
• Risk and Game Theory , Prof. Paolo Garella
• Contract Theory , Prof. Claudia Meroni

Second Term - January 2024 - March 2024-  Timetable

Econometrics

• Econometrics , Prof.Andrea Bastianin
• Microeconometrics , Prof. Lorenzo Trapani
• Time Series Econometrics , Prof. Fabrizio Iacone

Third Term - April 2024 - June 2024 -  Timetable

Macroeconomics

• Growth Theory ,
• Theory of Economic Fluctuations , Prof. Guido Ascari
• Dynamic Stochastic General Equilibrium Models ,
• Economic Policy Evaluation ,  Prof. Giovanna d'Adda

During their 2nd and 3rd year students are asked to attend seminars in the University of Milan and Pavia.

The third year is entirely dedicated to research and completion of the thesis. Students carry out their research under the supervision of a Faculty member.

The thesis generally consists of a brief introduction and two chapters that provide original contributions to the development of knowledge, i.e. new theoretical and/or empirical results. The thesis chapters should be in the form of original papers publishable on international scientific journals with peer review.

For Information on thesis requirements and admission to the public defense see here .

To complement internal coursework, distinguished economists from other Italian or foreign Universities and International Organization are invited to give series of seminars on specific topics.

Year 2023-24

MILAN  - October 2023: Visiting Professor Daniel Kresiman   "7 Big Questions for Labor Economists"

MILAN DEMM : please consult this page  to see the seminars' calendar

PAVIA 

Copyright © 2016 PhD in Economics MILANO-PAVIA. All Rights Reserved - WEB: ModusOperandi | Privacy Policy | Cookie Policy

Mariano Massimiliano Croce

My research focuses on asset pricing in general equilibrium models in which there is uncertainty about the long horizon perspectives of the economy (growth news shocks). Projects include the study of international asset prices and exchange rates; the interaction between asset prices, investment decisions, wealth and welfare on a global scale; links between investors’ information and asset prices; growth implications of fiscal policy risks.

I have published in leading academic journals such as, for example, The American Economic Review, The Journal of Political Economy, The Journal of Finance, The Journal of Financial Economics, The Review of Financial Studies, and The Journal of Monetary Economics . Since September 2017, I am a CEPR Reseach Fellow . In April 2018, I was appointed as an NBER Research Associate .

I teach courses in finance and global macroeconomics at several leading academic institutions such as Bocconi , Wharton, STERN, ISB , Kenan-Flagler B.S. (UNC) . In the PhD program, I teach empirical asset pricing and advanced methods for macro-finance. I received an award for my teaching in the PhD program and in 2019 I have been nominated Director of the PhD in Economics and Finance in Bocconi.

I received my PhD in Economics from New York University and master’s and bachelor’s degrees in economics from L. Bocconi University, Milan. He served as a research intern at Federal Reserve Board of Governors in Washington, D.C. and the European Central Bank in Frankfurt.

In 2021, I was appointed as a Co-Editor of Economics Letters.

My research focuses on asset pricing in general equilibrium models in which there is uncertainty about the long horizon perspectives of the economy (growth news shocks). 

When the markets Get CO.V.I.D: COntagion, Viruses, and Information Diffusion

Concealed carry, the leading premium, volatility risk pass-through, persistent government debt and aggregate risk distribution, growth risks, asset prices, and welfare, government debt and the returns to innovation, recursive allocations and wealth distribution with multiple goods: existence, survivorship, and dynamics, currency risk factors in a recursive multicountry economy, bkk the ez way: international long-run growth news and capital flows, news shocks and the production-based term structure of equity returns, investor information, long-run risk, and the term structure of equity, long-run productivity risk: a new hope for production-based asset pricing, international asset pricing with recursive preferences, toward a quantitative general equilibrium asset pricing model with intangible capital, international robust disagreement, the market price of fiscal uncertainty, fiscal policies and asset prices, risks for the long run and the real exchange rate, the short and long run benefits of financial integration.

I have a long teaching history in MBA, Executive MBA, PhD, and undergraduate programs. I teach courses such as Global Economics, Investments, Corporate Finance, International Capital Markets, Financial Econometrics, Empirical Asset Pricing; and Advanced Methods for Macro Finance.

People of the Department of Economics

Core Faculty

Jerome Frans Adda

Jan David Bakker

Tito Michele Boeri

Elisa Borghi

Valentina Bosetti

Maristella Botticini

Michela Braga

Giovanni Bruno

Angelo Marcello Cardani

Christoph Carnehl

Gabriele Natale Deana

Francesco Decarolis

Alexia Delfino

Erika Deserranno

Alfredo Di Tillio

Sarah Beate Eichmeyer

Carlo Ambrogio Favero

Giuseppe Ferraguto

Stefano Fiorin

Chiara Fumagalli

Francesco Giavazzi

Anna Gibert Rivas

Pamela Giustinelli

Joseph-Simon Goerlach

Basile Grassi

Luigi Iovino

Rafael Jimenez Duran

Eliana La Ferrara

Thomas Emile Robert Le Barbanchon

Marco Maffezzoli

Massimiliano Marcellino

Donato Masciandaro

Tommaso Monacelli

Massimo Morelli

Sara Negrelli

Salvatore Nunnari

Marco M. Ottaviani

Gianmarco Ottaviano

Fausto Panunzi

Nicola Pavoni

Roberto Perotti

Michele Polo

Marta Prato

Carlo Rasmus Schwarz

Dmytro Sergeyev

Ksenia Shakhgildyan

Andrew Michael Spence

Mara Pasquamaria Squicciarini

Guido Enrico Tabellini

Antonella Trigari

Department fellows.

Umberto Platini

Visiting professors.

Stefano Della Vigna

Francis Kramarz

Sda-bocconi faculty with teaching appointments in the department.

Matteo Giacomo Di Castelnuovo

Faculty and academic services staff.

Rebecca Foriwa Hughes

Patrizia Pellizzari

Sara Picciallo

Marika Podelli

Erika Somma

Giovanna Tramontano

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PhD Students at the Best US Schools Come from Bocconi

Adam Eric Greenberg Makes Top List

A paper on the psychological factors at play in the decision to claim retirement benefits in the US was in the final selection for the AMA's Paul E. Green Award  

Graziella Romeo Joins Top Academic Journal

The International Journal of Constitutional Law has a new Associate Editor.  

THE FAILURE TO PREVENT FRAUD IN THE UK CORPORATE ENVIRONMENT Seminar of Crime Law

NICHOLAS RYDER - Cardiff University April 29, 2024 at 10:30 - 12:00 Room 1-C3-01, Via Roentgen 1

Clare Balboni - Firm Adaptation in Production Networks: Evidence from Extreme Weather Events in Pakistan

CLARE BALBONI - LSE April 29, 2024 at 12:30 - 13:45 Alberto Alesina Seminar Room 5.e4.sr04, floor 5, Via Roentgen 1

Bocconi University     •     Via Röntgen 1     •     20136 Milano MI Italy

Welcome to my website! I am a 5th-year PhD candidate in Economics from Bocconi University. I am on the 2023-2024 job market. 

I am interested in the political economy of development, particularly how politics, institutions, and culture influence development outcomes. 

Contact : [email protected]         Link to: CV (Updated Nov. 11, 2023)       Currently in Milan

Working Papers

Curbing Bureaucratic Information Manipulation ( Job Market Paper )     [ Paper ] ( Updated Dec . 4 , 2023 )

Bureaucrats are often incentivized to manipulate information, which may have real consequences. Leveraging China's 2009 reform punishing economic data manipulation and counties' quasi-random reform exposure, I provide rich causal evidence showing that the reform led to: (1) a decrease in GDP growth manipulation amounting to 5% of reported GDP growth, driven by a reputational discipline effect; (2) an increase in local officials' development effort manifested in both policy changes and downstream impacts, consistent with an effort reallocation effect. These results thus highlight the far-reaching costs of such manipulation and the welfare implications of curbing it.

Virtuous Leaders and Government Corruption     [draft soon ]

with Cindy Shen (Stanford) and Zhengyang Zhou (UBC)

This paper analyzes modern political corruption through a cultural lens. Drawing on Confucianism that flourished in Imperial China emphasizing virtuous leadership, we show lower corruption in governments led by mayors with greater ancestral exposure to such culture. For causal identification, we leverage: (1) the irrelevance of Confucianism in leader selection and allocation; and (2) the exogeneity in Confucian academy location choices. We provide support for the virtuous leadership mechanism and rule out alternative explanations, such as changes in formal institutions, education inputs, or government revenue. We further show that the persistence of this effect stems from the intergenerational transmission of cultural norms. 

Reciprocity and State Capacity     [draft soon ]

with Yu Luo (CUFE) and Ming-ang Zhang (CUFE)

This paper tests the social contract view of the state within the realm of pollution control. Using a unique dataset on firm-level emission records from China, we find that firms with prior government subsidies achieved greater emission reductions after a national pollution control campaign, likely through output cuts and clean technology adoption. Such reductions, which we interpret as driven by reciprocity between firms and governments, were more pronounced for firms with a greater desire to reciprocate the government and paid off as higher future government subsidies. We find little support for other mechanisms, such as reduced financial constraints, political connections, forced reductions, and data manipulation. In aggregate, regions that previously granted more subsidies to firms witnessed greater reductions in pollution concentrations.

Publications

Incentives, Penalties, and Rural Air Pollution     [ Paper ] 

Journal of Development Economics March 2023

I test the role of economic incentives and command and control in reducing agricultural fires, a major source of air pollution in most rural regions across the world caused by burning crop residues after harvest. To tackle data shortage, I use high-resolution satellite data to construct a fine measure of agricultural fires as well as other geographic characteristics at 1 km × 1 km resolution for China. Using the staggered arrival of biomass power plants, which purchase crop residues as production inputs from nearby areas, as a shock to economic incentives, I find a more than 30% drop in agricultural fires in the vicinity of a plant after its opening relative to areas farther away. Such drop cannot be explained by structural transformation, migration, or enhanced regulation near the plant, and is consistent with an incentive-based explanation. I then examine the effectiveness of a command and control policy that bans agricultural fires within 15 km of airports. Using a spatial regression discontinuity design, I find no evidence that such a policy works.  

Go with the Politician     [ Paper ] 

American Economic Journal: Economic Policy May 2023

with Chunyang Wang (PKU)  

Chinese local leaders are frequently moved across prefectures. By combining local leader rotation data and comprehensive firm land parcel purchase data across prefectures from 2006 to 2016, this paper examines how firm-politician connections affect resource allocation and finds that a firm headquartered in a leader's previous work prefecture purchases three times more land parcels in that leader's new governing prefecture than the prefecture-year mean, at half the unit prices. Identification is from within-firm-year variation in various prefectures through exogenous politician rotation. Land usage efficiency is lower for these follower firms' land parcels. Land allocation distortion is also economically sizable.  

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MICHELE POLO

MARCO PERCOCO

OLIVIERO BACCELLI

VALENTINA BOSETTI

ALBERTO BRAMANTI

ANDREA COLLI

EDOARDO CROCI

LUIGI DE PAOLI

Claudio Zara

MIRIAM ALLENA

ANNAMARIA BAGAINI

CLAUDIO BRENNA

CHIARA CANDELISE

FRANCESCO COLELLI

ALESSANDRO DE CARLI

ALBERTO DELL'ACQUA

DAVIDE DELLA VALENTINA

MATTEO DONELLI

SUSANNA DORIGONI

CAMILLA FACHERIS

FABRIZIO FRACCHIA

MARZIO GALEOTTI

Maximilian Göbel

GABRIELE GREA

Massimo Guidolin

FABIO IRALDO

BENEDETTA LUCCHITTA

Monia Magnani

MAURIZIO MALPEDE

PAOLA CALOGERO

CARLOTTA MILANI