Courses

Management Science

Academic Year 2014 - 2015

Advanced Topics of Complex Networks

Abstract:
This course will be organized as series of reading groups or specialized seminars by members or collaborators of the research unit on Natural Networks (Networks).
Hours:
20
Professors/Lecturers:
Guido Caldarelli (IMT Lucca); Walter Quattrociocchi (IMT Lucca)
Compulsory for:
Complex Networks
Also available for:
Computational Mechanics; Computer Science; Image Analysis; Management Science; Control Systems

Advanced Topics of Econometrics

Abstract:
The main goal of this course is to provide an introduction to/review of the fundamental theoretical concepts and applications of modern econometric techniques used in empirical social sciences. TOPICS covered in the course include: 1) Conventional Methods to Estimate Causal Effects: OLS and IV 2) The Angrist-Imbens-Rubin approach (LATE-IV) 3) Further IV issues and Regression Discontinuity Design (RDD) 4) Matching methods for the estimation of causal effects 5) Differences-in-Differences estimation
Hours:
30
Professors/Lecturers:
Vincenzo Bove (University of Warwick)
Compulsory for:
Economics
Also available for:
Management Science

Advanced Topics of Management Science

Abstract:
This course will be organized as series of reading groups or specialized seminars by members or collaborators of the IMT research units
Hours:
20
Professors/Lecturers:
Massimo Riccaboni (IMT Lucca); Bart Leten (Vlerick Business School)
Compulsory for:
Management Science
Also available for:
Economics

Banking and Finance (long seminar with optional exam)

Abstract:
TBD
Hours:
12
Professors/Lecturers:
Michele Bonollo (IASON ltd.)
Available for:
Complex Networks; Computer Science; Economics; Management Science; Control Systems

Basic Numerical Linear Algebra

Abstract:
The course is aimed to introduce the basic notions about vector spaces, vectors, matrices, and norms, along with the basic numerical methods concerning the solution linear systems. In particular: direct methods for square linear systems and conditioning analysis; direct methods for solving over-determined linear systems in the least square sense, with applications. The course also provides an introduction to Matlab, which is used for implementing the methods.
Hours:
20
Professors/Lecturers:
Luigi Brugnano (Università degli Studi di Firenze)
Compulsory for:
Complex Networks; Economics; Management Science
Also available for:
Computational Mechanics; Computer Science; Image Analysis; Control Systems

Computer Programming and Methodology

Abstract:
This course aims at introducing to students principles and methodologies of computer programming. Emphasis is on good programming style, techniques and tools that allow efficient design, development and maintenance of software systems. The course focuses on the design of computer applications drawing attention to modern software engineering principles and programming techniques, like object-oriented design, decomposition, encapsulation, abstraction, and testing. A significative case study is used to allow students to experiment with the principles and techniques considered in this course. Depending on the background of the class, Java, C++, and/or Python are considered in the course.
Hours:
20
Professors/Lecturers:
Michele Loreti (Università degli Studi di Firenze)
Compulsory for:
Complex Networks; Management Science
Also available for:
Computational Mechanics; Computer Science; Economics; Image Analysis; Control Systems

Data Science with Complex Networks

Abstract:
Complex Systems are everywhere and in the era of massive production of electronic data coming from all sort of devices it is of crucial importance to have the right tools to manage and extract from them all the valuable information. To this aim during this course we will develop both the basic theoretical tools and the practical coding technics to tackle all sort of complex systems, ranging from Trade and Financial Networks, to the World Wide Web and the Social Networks. In particular Complex Networks Theory proved to be successful in the process of handling this enormous quantity of data and in order to apply these concepts to the various cases it is crucial to define a clear strategy and guidelines to represent the system data in the shape of a network. Using the Python scripting language we will introduce state of the art methods and algorithms to cope with some reference dataset.
Hours:
20
Professors/Lecturers:
Guido Caldarelli (IMT Lucca); Alessandro Chessa (IMT Lucca)
Compulsory for:
Complex Networks
Also available for:
Computational Mechanics; Computer Science; Economics; Image Analysis; Management Science; Control Systems

Econometrics I

Abstract:
This course presents a comprehensive treatment of econometric methods for linear models and assumes working knowledge of undergraduate econometrics basic linear algebra, basic probability theory, and statistics that are covered in the pre-courses.
Hours:
40
Professors/Lecturers:
Alessandro Bucciol (Università degli Studi di Verona); Emanuele Bacchiocchi (Università degli Studi di Milano)
Compulsory for:
Economics; Management Science

Econometrics II

Abstract:
TBD
Hours:
40
Professors/Lecturers:
Carla Rampichini (Università degli Studi di Firenze); Luigi Benfratello (Politecnico di Torino); Tiziano Razzolini (Università di Siena)
Compulsory for:
Economics
Also available for:
Management Science

Economic Growth and Development

Abstract:
The main goal of the course is to introduce students to the Neoclassical growth model, the overlapping-generations model and endogenous technological change. The course will provide the basic tools required to study long run growth and provide some answers to the fundamental question of why economies grow and why some countries are much richer than others. The main topics will be the following. Stylized facts of economic growth and development. Introduction to the Solow growth model. Neoclassical growth. Overlapping generations and dynamic efficiency. Neoclassical endogenous growth: capital accumulation, externalities and human capital. The Shumpeterian approach to economic growth. The effect of institutions on long run growth.
Hours:
40
Professors/Lecturers:
Massimiliano Gaetano Onorato
Compulsory for:
Economics
Also available for:
Management Science

Empirical Studies in Economics and Management

Abstract:
The course aims at providing students with hands-on empirical tools to test the behaviour of economic agents that are heterogeneous in nature. How productive is a firm, an industry or a country?
Why? Where is it more profitable to locate an economic activity? How long can we expect a company to outlive its competitors? After introductions to up-to-date illustrative contributions to economic literature, students will be asked to perform their own analyses and comment results after applications to micro data provided during the course. The objective is to develop a critical understanding of the iterative research process leading from real economic data to the choice of the best tools available from the analyst kit.
Hours:
20
Professors/Lecturers:
Fabio Pammolli (Politecnico di Milano); Armando Rungi (IMT Lucca)
Compulsory for:
Management Science
Also available for:
Economics

Ethics and Research: Objectivity, Neutrality and Values in Science

Abstract:
The course has been cancelled
Hours:
10
Professors/Lecturers:
Tbd
Available for:
Analysis and Management of Cultural Heritage; Computational Mechanics; Complex Networks; Computer Science; Economics; Image Analysis; Management Science; Control Systems

Finance

Abstract:
The course covers important topics in modern quantitative finance and risk management: efficient market hypothesis and violations, financial markets micro-structure and types of arbitrage, general principles of modelling the price dynamics of financial assets, market risk and other types of financial risks, Value-at-Risk (VaR) approach and applications, modelling of extreme events and crisis, VaR analysis for financial derivatives, copula methods,modelling of trends in time series in connection with technical analysis, and the foundations of high-frequency arbitrage trading. This course will enable the students to develop both theoretical knowledge and practical skills to analyze modern financial markets.
Hours:
20
Professors/Lecturers:
Roberto Renò (Università degli Studi di Siena)
Compulsory for:
Management Science
Also available for:
Complex Networks; Economics; Control Systems

Foundations of Probability Theory and Statistical Inference

Abstract:
This course aims at introducing the fundamental concepts of probability theory and statistical
inference.
Some proofs are sketched or omitted in order to have more time for examples, applications and
exercises.
In particular, the course deals with the following topics:

• probability space, random variable, expectation, variance, cumulative distribution function, discrete and absolutely continuous distributions, random vector, joint and marginal distributions, joint cumulative distribution function, covariance,
• conditional probability, independent events, independent random variables, conditional probability density function, order statistics,
• multivariate Gaussian distribution,
• probability-generating function, Fourier transform/characteristic function,
• types of convergence and some related important results,
• point estimation, interval estimation, hypothesis testing, linear regression, introduction to Bayesian statistics.
Hours:
30
Professors/Lecturers:
Irene Crimaldi (IMT Lucca)
Compulsory for:
Complex Networks; Economics; Management Science
Also available for:
Computational Mechanics; Computer Science; Image Analysis; Control Systems

Funding and Management of Research and Intellectual Property (long seminar without exam)

Abstract:
This long seminar aims at providing an overview on the management of intellectual property rights (copyright transfer agreements; open access; patents, etc.). Funding opportunities for PhD students, post-docs, and researchers are also presented (scholarships by the Alexander von Humboldt Foundation; initiatives by the Deutscher Akademischer Austausch Dienst; scholarships offered by the Royal Society in UK; bilateral Italy-France exchange programmes; Fulbright scholarships; Marie Curie actions; grants for researchers provided by the European Research Council). For each funding scheme, specific hints on how to write the proposal are given.
Hours:
10
Professors/Lecturers:
Marco Paggi (IMT Lucca)
Available for:
Analysis and Management of Cultural Heritage; Computational Mechanics; Complex Networks; Computer Science; Economics; Image Analysis; Management Science

Game Theory

Abstract:
Mechanism Design. Revelation principle, Dominance and Nash Implementation. Strategic and Axiomatic Bargaining. Asymmetric Information and Optimal Contracts. Moral Hazard and Adverse Selection models. Signaling and Screening Models. Applications. Static games of complete information: definition of a game; normal form representation; strongly and weakly dominated strategies; Nash Equilibrium (NE); mixed strategy equilibrium. Applications of NE and introduction to market competition; Cournot competition; Bertrand competition; externalities; public goods. Dynamic games of complete information: definition of a dynamic game; extensive form representation; perfect and imperfect information; Backward Induction equilibrium; Subgame Perfect equilibrium. Repeated games: Definition; one-shot deviation property; folk theorem; application to Rubinstein bargaining. Static games of incomplete information: Bayesian games; Bayesian Nash equilibrium. Dynamic games of incomplete information: perfect Bayesian equilibrium; signalling games, cheap talk.
Hours:
40
Professors/Lecturers:
Nicola Dimitri (Università degli Studi di Siena)
Compulsory for:
Complex Networks; Economics; Management Science
Also available for:
Computer Science; Control Systems

Innovation and Industrial Dynamics

Abstract:
Size and Growth of Economic systems. The growth of Business Firms: theoretical framework. Gibrat legacy.
Hours:
20
Professors/Lecturers:
Massimo Riccaboni (IMT Lucca)
Compulsory for:
Management Science
Also available for:
Economics

International Economics and Business

Abstract:
This course, as its name suggests, is comprised of two main sections, the first being international economics and the second being international business. In the first section, we focus our attention on the real (as opposed to monetary) side of international economics, i.e., international trade of goods and services. We start from the two neoclassical trade models (Ricardo and Heckscher-Ohlin) that were developed in the early parts of the 19th and 20th centuries. We then move to the more recent “new” trade models which emphasize economies of scale, monopolistic competition, and firm heterogeneity. Finally, we introduce the empirical workhorses for analyzing trade, the gravity equation and the network framework. In the second section, we focus on foreign direct investment (FDI) and multinational enterprises (MNEs). We first cover some theoretical models of FDI, which are closely related to the trade models taught in the first section. Then we cover more specific topics such as global value chains (GVCs) and corporate networks. Finally, we discuss some future applications of Orbis data (rich information of MNEs).
Hours:
20
Professors/Lecturers:
Massimo Riccaboni (IMT Lucca); Zhen Zhu (IMT Lucca)
Compulsory for:
Management Science
Also available for:
Economics

Introduction to Network Theory

Abstract:
TBD
Hours:
10
Professors/Lecturers:
Guido Caldarelli (IMT Lucca)
Compulsory for:
Analysis and Management of Cultural Heritage; Complex Networks; Management Science
Also available for:
Computational Mechanics; Computer Science; Economics; Image Analysis; Control Systems

Machine Learning and Pattern Recognition

Abstract:
Basics of pattern recognition and machine learning and real world applications in imaging, internet, finance. Similarities and differences. Decision theory, ROC curves, Likelihood tests. Linear and quadratic discriminants. Template based recognition and feature detection/extraction. Supervised learning (Support vector machines, Logistic regression, Bayesian). Unsupervised learning (clustering methods, EM, PCA, ICA). Current trends in Machine Learning. Prerequisites: Probability and basic random processes, linear algebra, basic computer programming, numerical methods.
Hours:
20
Professors/Lecturers:
Sotirios Tsaftaris (The University of Edinburgh)
Compulsory for:
Image Analysis
Also available for:
Computational Mechanics; Computer Science; Management Science; Control Systems

Macroeconomics

Abstract:
Search models. Equilibrium search and matching. Two-sided search model. Efficiency wages. Implicit contacts. Insider-outsider models. Traditional Keynesian Theories of Fluctuations. The Lucas Imperfect-Information Model and The Lucas Critique. The New Keynesian Economics. Consumption. Investment.
Hours:
40
Professors/Lecturers:
Cristina Tealdi (Heriot-Watt University); Davide Ticchi (Università Politecnica delle Marche)
Compulsory for:
Economics
Also available for:
Management Science

Macroeconomics II

Abstract:
Dynamic stochastic general equilibrium models. The Real Business Cycle Theory. International real business Cycles. The New Keynesian Economics. Monetary policy.
Hours:
40
Professors/Lecturers:
Davide Ticchi (Università Politecnica delle Marche); Gilles Saint-Paul (Paris School of Economics)
Compulsory for:
Economics
Also available for:
Management Science

Management and Corporate Finance

Abstract:
Applications of quantitative techniques to managerial decisions (data-driven decision making). Topics include applications of data mining, machine learning, statistical models, predictive analytics, econometrics, optimization, risk analysis, decision theory, data visualization and business communication in finance, marketing, operations, R&D, business intelligence and other business areas generating and consuming large amounts of data.
Hours:
20
Professors/Lecturers:
Fabio Pammolli (Politecnico di Milano)
Compulsory for:
Analysis and Management of Cultural Heritage; Management Science
Also available for:
Complex Networks; Computer Science; Economics; Control Systems

Management of Complex Systems: Approaches to Problem Solving

Abstract:
Methods and approach to problem solving. Problem analysis; analysis of complex systems (related to cultural heritage, such as a city of art organization, promotion, etc.). The course will include practical simulations. The course will be linked to a seminar on specific Case studies.
Hours:
40
Professors/Lecturers:
Andrea Zocchi; Dario Cacciatore (Whirlpool Corporation)
Compulsory for:
Analysis and Management of Cultural Heritage
Also available for:
Complex Networks; Computer Science; Management Science; Control Systems

Microeconomics I

Abstract:
The course covers classical decision theory and partial equilibrium analysis. It aims to provide a smooth transition from undergraduate- to graduate-level Microeconomics, and to build a solid foundation for future study and research.
Hours:
40
Professors/Lecturers:
Nicola Dimitri (Università degli Studi di Siena)
Compulsory for:
Economics
Also available for:
Management Science

Microeconomics II

Abstract:
TBD
Hours:
40
Professors/Lecturers:
Nicola Dimitri (Università degli Studi di Siena); Marco Pagnozzi (Università degli Studi di Napoli Federico II)
Compulsory for:
Economics
Also available for:
Management Science

Network Theory

Abstract:
Course description: Basic of Graph Theory: degree, clustering, connectivity, assortativity, communities. Analysis of Complex Networks, datasets and software. Community Detection, Modularity, Spectral Properties. Fractals, Self-Organised Criticality, Scale Invariance. Random Graph, Barabasi Albert Model, Fitness model, Small world. HITS Algorithm and PageRank. Real instances of Complex Networks in Biology and Social Sciences. Board of Directors, Ownership Networks, measures of Centrality and Control. World Trade Web, Minimal Spanning Trees, Competition and Products spaces. Prerequisites: Linear algebra and matrix computation, calculus and mathematical analysis.
Hours:
10
Professors/Lecturers:
Guido Caldarelli (IMT Lucca); Antonio Scala (CNR - Istituto di Sistemi Complessi)
Compulsory for:
Complex Networks
Also available for:
Computational Mechanics; Computer Science; Image Analysis; Management Science; Control Systems

Optimal Control

Abstract:
Discrete-time optimal control: dynamic programming for finite/infinite horizon and deterministic/stochastic optimization problems. LQ and LQG problems, Riccati equations, Kalman filter. Deterministic continuous-time optimal control: the Hamilton-Jacobi-Bellman equation and the Pontryagin’s principle. Examples of optimal control problems in economics.
Hours:
20
Professors/Lecturers:
Giorgio Stefano Gnecco (IMT Lucca)
Compulsory for:
Complex Networks; Economics; Management Science
Also available for:
Computational Mechanics; Computer Science; Image Analysis; Control Systems

Project Management

Abstract:
Project management; event management; communication and marketing; practical tools of organization; budgeting. Dealing with multiple stakeholders/ Risk management / Time management / PM tips to run an international research/Management plan concept on heritage sites / When applying for funds how do we measure project success / How we manage the output of the management plan / Flat organisations.
Hours:
30
Professors/Lecturers:
Beatrice Manzoni (SDA Bocconi School of Management)
Compulsory for:
Analysis and Management of Cultural Heritage
Also available for:
Management Science

Scientific Writing, Dissemination and Evaluation (long seminar without exam)

Abstract:
TBD
Hours:
8
Professors/Lecturers:
Luca Aceto (Reykjavik University)
Available for:
Analysis and Management of Cultural Heritage; Computational Mechanics; Complex Networks; Computer Science; Economics; Image Analysis; Management Science; Control Systems

Socio-Economic Networks

Abstract:
TBD
Hours:
10
Professors/Lecturers:
Massimo Riccaboni (IMT Lucca); Giorgio Fagiolo (Scuola Superiore Sant’Anna, Pisa)
Compulsory for:
Complex Networks; Management Science
Also available for:
Computer Science; Economics; Control Systems

Statistics Lab.

Abstract:
- Brief introduction to R (http://www.r-project.org/)
- Creating random variables.
- Applications to the central limit theorem and the law of large numbers
- Descriptive statistics: (i) Representing probability and cumulative distribution functions in discrete and continuous cases; (ii) calculating mean, variance, concentration indexes, covariance and correlation coeff.
- Statistical inference: (i) Point estimation and properties; (ii) interval estimation and properties; (iii) hypothesis testing and properties.
- Theory and applications of simple regression model (model, assumptions, estimation methods, residual diagnostics).
- If time permits:
Theory and applications of Bootstrap and Jacknife elements for simple parameters and for the regression model parameters.

Prerequisites: The topics of “Foundations of Probability Theory and Statistical inference” are
supposed known.
Hours:
10
Professors/Lecturers:
Irene Crimaldi (IMT Lucca); Rodolfo Metulini (IMT Lucca)
Available for:
Computational Mechanics; Complex Networks; Computer Science; Economics; Image Analysis; Management Science; Control Systems

Stochastic Processes and Stochastic Calculus

Abstract:
This course aims at introducing some important stochastic processes (Markov chains, martingales,
Poisson process, Wiener process) and Ito calculus.
Some proofs are sketched or omitted in order to have more time for examples, applications and
exercises.
In particular, the course deals with the following topics:
- Markov chains (definitions and basic properties, classification of states, invariant measure, stationary distribution, some convergence results and applications, passage problems, random walks, urn models, introduction to the Markov chain Monte Carlo method),
- conditional expectation,
- martingales (definitions and basic properties, Burkholder transform, stopping theorem and some
applications, predictable compensator and Doob decomposition, some convergence results, game theory, random walks, urn models),
- Poisson process,
- Markov processes,
- Wiener process and Ito calculus,
- Ornstein-Uhlenbeck process.

Prerequisites: The topics of “Foundations of Probability Theory and Statistical Inference” are supposed to be known.
Hours:
30
Professors/Lecturers:
Irene Crimaldi (IMT Lucca); Andrea Gabrielli ( Istituto dei Sistemi Complessi (ISC) - CNR, UOS "Sapienza")
Compulsory for:
Complex Networks
Also available for:
Computational Mechanics; Computer Science; Economics; Image Analysis; Management Science; Control Systems

Theory and Numerics of Ordinary and Partial Differential Equations

Abstract:
The first lesson of the course will provide a primer on complex variables. Using this mathematical formalism, the focus of the remaining first part of the course will be to introduce linear ordinary and linear partial differential equations, and the "cheap" methods to solve them using Fourier and Laplace transforms. The ordinary and partial differential equations will be placed into a context of applied mathematics (e.g. classic deterministic and stochastic systems) saving the theoretical approach for advanced lectures. The lecture notes will be provided in Mathematica computable document format, with an emphasis on graphical in-class demonstration.
The second part of the course will introduce PhD students to numerical techniques for the approximate treatment of linear partial differential equations (PDEs) governing physical, engineering and financial problems. The theoretical fundamentals of the finite element method are introduced step-by-step in reference to exemplary model problems related to heat conduction, linear elasticity and pricing of stock options in finance. Special attention is given to the finite element technology and to the implementation of the weak forms into a research code for fast intensive computations.
Hours:
40
Professors/Lecturers:
Alexander Petersen (IMT Lucca); Marco Paggi (IMT Lucca)
Compulsory for:
Computational Mechanics; Complex Networks; Economics
Also available for:
Computer Science; Image Analysis; Management Science; Control Systems

Time Series

Abstract:
TBD
Hours:
40
Professors/Lecturers:
Luca Gambetti (Universitat Autònoma de Barcelona)
Compulsory for:
Economics
Also available for:
Management Science

Topics in Applied Economics (long seminar without exam)

Abstract:
TBD
Hours:
10
Professors/Lecturers:
Fabio Pammolli (Politecnico di Milano); Laurence J. Kotlikoff (Boston University)
Compulsory for:
Economics; Management Science