Economics and Statistics - ECOSTAT
The new PhD in Economics and Statistics (ECOSTAT) has been created to provide the most effective response to the important challenges which doctoral programs in the areas of economics and statistics, both in Italy and Europe, have to cope with nowadays, namely: 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.
ECOSTAT builds upon the successful experiences of the PhD in Economics DEFAP-Bicocca and the PhD in Statistics and Mathematical Finance, both active at the University of Milan-Bicocca (UniMiB) until the current academic year.
ECOSTAT carries over the fruitful collaboration among economists and statisticians from the Department of Economics, Management and Statistics (DEMS) and the Department of Statistics and Quantitative Methods of 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
Vice-Coordinator: Prof. Giorgio Vittadini
This section aims at describing the innovative characteristics of ECOSTAT with respect to the PhD programs in economics and in statistics currently offered by other prestigious Italian and European universities, while details on each novelty are presented in the next sections.
ECOSTAT belongs to the PhD School of UniMiB, it is affiliated to DEMS, it lasts four years and it is articulated in two curricula, Economics (ECO) and Statistics (STAT).
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 two 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).
2.2. “Flexible” profiles vs “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 and statistical skills by proposing two innovative “training” profiles, which are mainly addressed to the non-academic job market. The “training” profiles aim at: i) offering to the non-academic job market high-level skills which are not currently available; ii) 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; iii) 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.
The two “training” profiles proposed by ECOSTAT are briefly described below.
2.2.1. Dynamic Macroeconomics/Forecasting
This profile enables to gain advanced skills in the empirical use (specification and calibration/simulation) of the DSGE models, with specific reference to the role of central banks, fiscal policies (taxation, public expenditure and public debt) and the effects of monetary policy shocks. This profiles focuses also on the most advanced techniques to forecast macroeconomic variables. The technical differences between forecasting and nowcasting are considered, especially from the viewpoint of data characteristics and availability (historical data vs “contemporaneous” data). Different approaches to nowcasting are illustrated (“in-filling”, mixed-data sampling models, factor models, factor with ragged edges, bridge equations). Particular attention is paid to the strategies for producing accurate nowcasts.
Students who are interested in this profile belong to the curriculum ECO, which is appropriately integrated in order to include courses on the following topics: advanced macroeconomics, advanced time series econometrics; Bayesian statistics; forecasting/nowcasting techniques.
2.2.2. Big Data Analytics/Data Science
Following this profile, students learn the key elements of programming and data management with focus on the analysis of large amounts of structured and unstructured data (e.g., 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. This profile enables to gain advanced skills in project management, with particular reference to data driven innovation of decision processes.
Students who are interested in this profile come from the curriculum STAT, integrated with a selection of courses on the following topics: programming and languages for data management (Python and SQL); data management (data integration and data quality); data analysis for economics and social sciences (SAS and R); architectures and paradigms for big data (relational DB vs No SQL); machine learning; text mining and web analytics; data visualization; project management.
2.3. Length of the program
The current length of many PhD programs in economics and statistics in Italy, including the PhD in Economics DEFAP-Bicocca and in Statistics and Mathematical Finance of UniMiB, is three yers. This length is insufficient to guarantee that the PhD theses meet the quality standards achieved by the best European PhD programs. For this reason, ECOSTAT lasts four years. This duration is in line with the recent choices of some of the best Italian PhD programs in economics and statistics, as well as the PhD programs in this area offered by the most prestigious European academic institutions.
ECOSTAT fosters interdisciplinary research activities, by favouring co-tutorships between economists and statisticians, as well as through the “flexible” and “training” profiles.
2.5. 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.
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: i) the Program Committee (PC), that is the executive and decision-making board composed by full professors, associate professors and researcher of UniMiB and from other Italian and foreign universities and research institutions; ii) the Advisory Board (AB), which collaborates with the PC to organize the teaching and research activities of the program, is headed by the program Coordinator and is formed by a limited number of professors and researchers who are representative of the two 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 ECO can be offered jointly with the PhD program in Economics and in Economics and Finance of the Catholic University of Milan.
5.1. First- year courses
5.1.1. Specific to the curriculum ECO and in common with the curriculum STAT
Mathematics(§), Econometrics (§), Microeconomics, Macroeconomics, Computational statistics(§), Research methods(§), Public economics(*), Finance(*).
5.1.2. Specific to the curriculum STAT e in common with the curriculum ECO
Mathematics(§), Probability, Stochastic processes, Bayesian statistics, Statistical inference, Statistical learning, Computational statistics(§), Statistical modelling, Econometrics(§), Research methods(§).
5.2. Second-year courses
Second-year courses belong to two different categories: “structured” and “reading groups”. The structured courses offered by each curriculum are generally tool courses, which are formed by one or more self-contained parts of frontal lectures and classes. Conversely, the reading groups are built upon the research interests of the instructor, and they are typically articulated into an introductory lecture and a series of meetings where students critically discuss the readings assigned by the instructor during the initial lecture. The number of reading groups is generally wider than the number of structured courses.
The second-year courses are generally offered during the first part of the second year, in order to allow students to dedicate 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.
5.4. Monitoring the quality of teaching
The PC runs every year a systematic evaluation of the quality of the courses offered by the PhD program, 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.
5.5. Admission to the second year
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. 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.
 (§) in common (partially or totally) with the other curriculum; (*) in alternative.
The Program 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.
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 and statisticians.
6.3. 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.
6.4. 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 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 by dedicating a unit of administrative personnel to the following specific activities: i) provide students with detailed information on the job market, domestic and international, academic and non-academic; ii) advise and assist students wishing to apply for academic positions abroad.
The Department of Economics, Management and Statistics (DEMS) of the University of Milan-Bicocca invites applications to its PhD Program in Economics and Statistics (ECOSTAT) for the academic year 2018-19. The PhD Program is articulated in two curricula, Economics (ECO) and Statistics (STAT). The length of the PhD Program is four years, starting in November 2018. The precise starting date of the Program will be announced in due course.
We offer at least eight 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. The number of scholarships may increase if sponsorships on specific research projects become available. There will also be allowances (research funds) for short-period mobility (from the second year).
Additional scholarships and positions are also available. In particular, one additional scholarship is offered to excellent candidates willing enter the PhD program in order to develop a dissertation project focused on European studies. Moreover, two additional “advanced apprenticeship” positions (dottorato in alto apprendistato) are open to brilliant candidates willing to enter the PhD program and, at the same time, be part-time employed at a primary multinational company in order to develop a dissertation on focused on advanced analytics, machine learning, customer intelligence and forecasting.
The selection procedure is regulated by the official Call for Applications (Bando di Concorso), which is expected to be published in the Italian Official Journal (Gazzetta Ufficiale) after the acknowledgment issued by Italian Governmental agencies, at the beginning of May 2018, and also posted on the PhD School’s and on the PhD program’s websites. The official Call for Applications contains detailed information on: i) the documents which each candidate has to submit; ii) structure, contents and timing (within the period early July 2018 - late September 2018) of the entrance examination; iii) description of the projects related to the additional scholarships and positions.
The link to the official Call for Applications is here.
|1||ARBIA||Giuseppe||Cattolica del Sacro Cuore||Scienze Statistiche||Statistics|
|2||ATHANASOGLOU||Stergios||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|3||BAILLIE||Richard||King's College London - Regno Unito||Economics||Economics|
|4||BEN-PORATH||Elchanan||The Hebrew University of Jerusalem - Israele||Economics||Economics|
|5||BINELLI||Chiara||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|8||BRENDAN||Murphy||University College Dublin - Irlanda||Mathematics and Statistics||Statistics|
|9||CELLA||Michela||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|10||COLCIAGO||Andrea||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|11||CONSONNI||Guido||Cattolica del Sacro Cuore||Scienze Statistiche||Statistics|
|12||CRETI'||Anna||Paris-Dauphine University - Francia||Géopolitique de l'Energie et des Matières Premières||Economics|
|13||D'AMBROSIO||Conchita||University of Luxembourg - Lussemburgo||Lettres, Sciences Humaines, Arts et Sciences de l'Education||Economics|
|14||FARAVELLI||Marco||University of Queensland - Australia||Economics||Economics|
|15||GRESELIN||Francesca||Milano-Bicocca||Statistica e Metodi Quantitativi||Statistics|
|16||GUINDANI||Michele||University of California Irvine - Stati Uniti||Statistics||Statistics|
|17||HECQ||Alain||Maastricht University - Paesi Bassi||Economics||Economics|
|18||LOVAGLIO||Pietro Giorgio||Milano-Bicocca||Statistica e Metodi Quantitativi||Statistics|
|19||LUNARDON||Nicola||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Statistics|
|20||MANERA||Matteo||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|21||MARCHESI||Silvia||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|22||MCLACHLAN||Geoffrey||University of Queensland - Australia||Mathematics||Statistics|
|23||MENDOLA||Mariapia||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|24||MICHELANGELI||Alessandra||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|25||MIGLIORATI||Sonia||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Statistics|
|26||MORANA||Claudio||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|27||MOSCONE||Francesco||Brunel University London - Regno Unito||Environment, Health and Societies||Statistics|
|28||NAIMZADA||Ahmad||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|29||ONGARO||Andrea||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Statistics|
|30||OTTONE||Stefania||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|31||PACI||Lucia||Cattolica del Sacro Cuore||Scienze Statistiche||Statistics|
|32||PAGANI||Laura||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|33||PELAGATTI||Matteo||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Statistics|
|34||PELUSO||Stefano||Cattolica del Sacro Cuore||Scienze Statistiche||Statistics|
|35||PENNONI||Fulvia||Milano-Bicocca||Statistica e Metodi Quantitativi||Statistics|
|36||PIEVATOLO||Antonio||Consiglio Nazionale delle Ricerche (CNR) - Milano||Istituto di Matematica Applicata e Tecnologie Informatiche||Statistics|
|37||PORCU||Emilio||Newcastle University - Regno Unito||Mathematics, Statistics and Physics||Statistics|
|38||QUATTO||Piero||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Statistics|
|39||RIANI||Marco||Parma||Scienze Economiche e Aziendali||Statistics|
|40||SANTORO||Emiliano||University of Copenhagen - Danimarca||Economics||Economics|
|41||SCHARFSTEIN||Daniel||Johns Hopkins University - Stati Uniti||Bloomberg School of Public Health||Statistics|
|42||SOLARI||Aldo||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Statistics|
|43||STANCA||Luca||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|44||TIRELLI||Patrizio||Milano-Bicocca||Economia, Metodi Quantitativi e Strategie di Impresa||Economics|
|45||VITTADINI||Giorgio||Milano-Bicocca||Statistica e Metodi Quantitativi||Statistics|
|46||ZITIKIS||Ricardas||University of Western Ontario - Canada||Statistics and Actuarial Sciences||Statistics|
Academic year 2018-19 (cycle XXXIV)
Scholarships on specific projects
1) In collaboration with the new PhD program in Economics and Statistics (ECOSTAT) at the University of Milano-Bicocca, Siemens SPA Italy opens two “advanced apprenticeship” positions (dottorato in “alto apprendistato”) to brilliant candidates willing to enter the PhD program ECOSTAT and, at the same time, be part-time employed at Siemens Italy in order to develop dissertations focused on advanced analytics, machine learning, customer intelligence and forecasting.
The two projects are described below.
Project 1: “Advanced analytics and machines learning for industrial manufacturing applications”
This project deals with intelligent maintenance to predict possible failures in a production machine, based on Internet of Things (IoT) data coming from the machine’s sensors. Time-based and break-fix maintenance no longer provide the required results in terms of optimizing asset management costs. With the continuous collection and intelligent analysis of operating data, mainly through IoT Platforms (PassS), digitalization has opened up entirely new possibilities. We look to develop intelligent algorithms which, based on the machine model (Digital Twin), are able to produce insights that make it possible to predict the best possible time for maintaining machine and plant components.
Project 2: “Advanced analytics, customer intelligence and forecasting”
This project aims at identifying predictive models with respect to reference markets and sales potentials, in terms of both up-selling and cross selling. Based on the construction of a data lake and the use of intelligent algorithms, the project investigates the relationships between historical sales dynamics and customers potentials, which are typically “internal” data, with data from external sources, such as balance sheets of individual companies and firms, sectoral data, and key macroeconomic variables.
2) In collaboration with the new PhD program in Economics and Statistics (ECOSTAT) at the University of Milano-Bicocca, Symphonia SGR opens one “executive” position, dedicated to its employees (dottorato “executive”), on a project mainly focused on advanced techniques of quantitative asset and risk management of financial portfolios, such as: i) dynamic factor models aimed at forecasting the economic cycle and the behavior of real and financial markets; ii) machine learning techniques aimed at dynamically updating portfolio positions; iii) risk management strategies based on the estimation of ex-ante risk measures aimed at identifying the optimal timing for reducing the portfolio exposition to specific risk factors. Additional theoretical and empirical issues related to the quantitative management of financial portfolios will be discussed within the PhD program.