Courses

Economics, Networks and Business Analytics

Academic Year 2017 - 2018

Advanced Numerical Analysis

Abstract:
1. General considerations on matrices

Matrices:definitions and properties; norm of matrices
The condition number of a matrix
Sparse matrices and sparse formats (sparsity, structure, functionals)
The role of the PDE discretization (e.g., parameter dependence)


2.a Direct methods for general linear systems

Factorizations: definitions and properties
Factorization algorithms
Cost and numerical stability


2.b Direct methods for sparse linear systems

Factorizations of banded matrices
Ordering strategies to minimize the fill-in of a matrix
Solution of sparse triangular systems
Sparse matrices in Matlab: memorization and handling
Predefined functions for the direct solution of systems


3. Numerical solution of large-scale linear systems

Krylov subspace methods (CG, MINRES, GMRES, IDR family)
Structured problems
Preconditioning
Algebraic multigrid methods (hints)
Numerical experiments with Matlab and the IFISS package


4. Numerical solution of eigenvalue problems

Standard and generalized eigenproblems
Typical numerical methods
Equation of motion in structural dynamics: quadratic eigenproblems
Hours:
20
Professors/Lecturers:
Claudio Canuto (Politecnico di Torino); Valeria Simoncini (Università di Bologna)
Available for:
Computer Science and System Engineering; Economics, Networks and Business Analytics

Analytics in Economics and Management

Abstract:
The aim of this course is to teach students how to produce a research paper in economics and management using hands-on empirical tools for different data structures. We will bridge the gap between applications of methods in published papers and practical lessons for producing your own research.
After introductions to up-to-date illustrative contributions to literature, students will be asked to perform their own analyses and comment results after applications to microdata provided during the course.

How productive is a firm, an industry or a country? Why? Where is it more profitable to locate an economic activity? Who buys what products? How long can we expect a company to outlive its competitors? What is the relationship between economic welfare and size of a city? How do economic agents interact socially in a geographic space or in a workplace?

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. Students are expected to be familiar with macroeconomics, microeconomics and econometrics from the first-year sequence.

Final scores will be based 50% on individual presentations of a selected supplemental reading and 50% on an individual homework.
Hours:
20
Professors/Lecturers:
Massimo Riccaboni (IMT Lucca)
Compulsory for:
Economics, Networks and Business Analytics

Banking and Finance (long seminar without exam)

Abstract:
One of the most challenging task in finance is the gap between theoretical models and the actual software implementation. Cross some different areas (derivatives evaluation, risk management, accounting issues) several problems arise: discretization, analytical approximation, montecarlo simulation vs. numerical probability, optmization and so on. After a short overview of the main financial areas, the course aims to give some insights on these topics, with a special focus on the risk management current hard problems and the related software algorithms.

Prerequisites: Stochastic Processes and Stochastic Calculus + Finance
Hours:
10
Professors/Lecturers:
Michele Bonollo (IASON ltd.)
Available for:
Computer Science and System Engineering; Economics, Networks and Business Analytics

Complex Systems Analytics

Abstract:
Complex System Analytics will provide the mathematical basis for the analysing and modelling of Complex Systems. In particular we shall see concepts as

Fractal Dimension
Scale-free distributions
Self-Organised Criticality
Deterministic chaos and logistic maps

During the course we shall consider and comment several pieces of research on these topics in order to understand the possible applications to the personal line of research of the students participating.
Hours:
10
Professors/Lecturers:
Guido Caldarelli (IMT Lucca)
Available for:
Analysis and Management of Cultural Heritage; Economics, Networks and Business Analytics; Cognitive, Computational and Social Neurosciences

Complex Systems Theory

Hours:
20
Professors/Lecturers:
Guido Caldarelli (IMT Lucca)
Compulsory for:
Economics, Networks and Business Analytics
Also available for:
Computer Science and System Engineering; Cognitive, Computational and Social Neurosciences

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:
Tbd
Available for:
Computer Science and System Engineering; Economics, Networks and Business Analytics; Cognitive, Computational and Social Neurosciences

Convex Optimization

Abstract:
The course covers the basics of convex optimization methods, with an emphasis on numerical algorithms that can solve a large variety of optimization problems arising in control engineering, machine learning, mechanical engineering, statistics, economics, and finance.
Hours:
20
Professors/Lecturers:
Tbd
Available for:
Computer Science and System Engineering; Economics, Networks and Business Analytics

Critical Thinking (long seminar without exam)

Abstract:
Critical Thinking is an introductory course in the principles of good reasoning. Its main focus lies in arguments, their nature, their use and their import. Unlike a course in pure Logic, which would spell out universal formal rules of correct reasoning, Critical Thinking is more concerned with the unruly nature of real argumentation that does not allow unambiguous and definite formalization. The course is designed to serve as a methodical preparation for more effective reasoning and improved cognitive skills. Its ambition is to develop those intellectual dispositions that are essential for effective evaluation of truth claims as well as for making reasonable decisions based on what we know or believe to know. It is more about the quality of our beliefs and the reasons that support them than about their content. It will make ample use of examples taken from real world case studies, books, scientific or newspaper articles. Students will be encouraged to participate in the discussion over each example, and to find out more of their own.
Hours:
10
Professors/Lecturers:
Gustavo Cevolani (IMT Lucca)
Compulsory for:
Analysis and Management of Cultural Heritage
Also available for:
Economics, Networks and Business Analytics; Cognitive, Computational and Social Neurosciences

Data Science Lab

Abstract:
The aim of this class is to provide students with R language fundamentals and basic sintax. In particular, lessons will cover the following topics:

- Overview of R features
- The basics (vectors, matrices, objects, manipulation, basic statements)
- Reading data from files
- Probability distributions
- Basic statistical models
- Graphical procedures
- R packages overview
Hours:
15
Professors/Lecturers:
Valentina Tortolini (IMT Lucca)
Available for:
Computer Science and System Engineering; Economics, Networks and Business Analytics; Cognitive, Computational and Social Neurosciences

Decision-Making in Economics and Management

Abstract:
The main goals of the course are:

(1) to take economic theories and methodologies out into the world, applying them to interesting questions of individual behavior and societal outcomes;

(2) to develop a basic understanding of human psychology and social dynamics as they apply to marketing contexts;

(3) to become familiar with the major theory and research methods for analyzing consumer behavior; (4) to develop market analytics insight into consumer actions.

Most of time will be devoted to close reading of research papers, including discussion of the relative merits of particular methodologies. Students will participate actively in class discussion, engage with cutting-edge research, evaluate empirical data, and write an analytical paper. The course aims at enabling students to develop and enhance their own skills and interests as applied microeconomists.
Hours:
20
Professors/Lecturers:
Massimo Riccaboni (IMT Lucca)
Compulsory for:
Analysis and Management of Cultural Heritage; Economics, Networks and Business Analytics
Also available for:
Cognitive, Computational and Social Neurosciences

Econometrics I

Abstract:
This modular sequence provides a graduate-level introduction to econometric analysis. A variety of methods are introduced theoretically and illustrated via applications drawn from recent papers in the applied literature. The aim of the sequence is to bridge the step between a technical econometrics course and actual research practice. The goal is to provide students with the necessary knowledge to understand in what contexts are certain techniques useful and how to implement each method in empirical research.

Module 1 (P. Zacchia and A. Rungi) – Multiple Linear Regression
o Theory and Algebra of OLS
o Non-spherical Errors and Inference
o Functional Form
o Analysis of Variance

Module 2 (P. Zacchia) - Core Econometric Theory
o Review of Asymptotic Theory
o Structural Models, Identification and Causality
o Simultaneous Equation Models, 2SLS and 3SLS
o Introduction to M-Estimation
o Generalized Method of Moments
o Maximum Likelihood Estimation

Module 3 (A. Rungi) - Panel Data, Dynamic Models and Nonlinear Models
o Linear and Static Panel Data Models
o Linear and Dynamic Panel Data Models
o Non-Linear Models
o Multinomial Models

Prerequisites: Introduction to Economics + Matrix Algebra + Foundations of Probabilistic and Statistical Inference
Hours:
40
Professors/Lecturers:
Armando Rungi (IMT Lucca); Paolo Zacchia (IMT Lucca)
Compulsory for:
Economics, Networks and Business Analytics
Also available for:
Computer Science and System Engineering

Econometrics II

Abstract:
This course deals with the following topics:

1) Regression and Causality: a) Properties of the Conditional Expectation Function; b) Bad controls; c) Omitted variable bias; d) Measurement errors; e) Simultaneous equations; f) How to write an empirical project.

2) The Evaluation Problem and Randomised Experiments: a) Introduction to the evaluation problem; b) Randomised Experiments; c) Practical problems when running experiments; d) Duflo et al (2007) on randomization in development; e) Application I: Krueger (1999) on class size and educational test scores; f) Application II: Blundell et al (2004) on education and earnings in the UK.

3) Quasi-Experiments: a) Matching; b) Propensity Score Matching; c) Evaluating the validity of matching estimators; d) Application I: Caliendo et al., (2005) on job creation in Germany; e) Application II: Jones and Olken (2009) on assassination and institutions.

4) Differences-in-Differences: a) Basics; b) Regression Differences-in-Differences; c) The Synthetic Control Method; d) Application I: Card & Krueger (1994) on minimum wage and unemployment; e) Application II: Abadie & Gardeazabal (2003) on the effect of terrorism in the Basque region; f) Application III: Autor (2003) on unjust dismissal doctrine and employment.

5) Regression Discontinuity Design: a) Sharp RD; b) Fuzzy RD; c) Running RD Models; d) Application I: Lee (2008) on U.S. House elections; e) Application II: Angrist & Lavy (1999) on scholastic achievement.

Prerequisites: Econometrics I
Hours:
20
Professors/Lecturers:
Vincenzo Bove (University of Warwick)
Specializing course for:
Economics, Networks and Business Analytics

Finance

Abstract:
This course introduces students to the basic concepts used in quantitative finance, which forms the basis for many applications such as derivatives pricing, financial engineering and asset pricing. Anyone interested in these areas will have to acquire a good grasp of the topics in this course. We will cover: the analysis of complete and incomplete markets in discrete and continuous time models; the discussion and extension of the assumptions of the Black-Scholes-Merton equation and the introduction of common numerical techniques that are widely applied in practice (along with practical lab sessions with real data); the introduction of structured finance products, their use in risk management and valuation techniques, most notably for mortgage-backed securities, credit default swaps and collateralized debt obligations.

Students require an adequate knowledge of mathematics, particularly in matrix algebra and analysis along with stochastic processes and stochastic calculus to follow this course. Appropriate readings to refresh your knowledge are given on request.

Outline:

Part I – Pricing Models
- Hedging of securities;
- No-arbitrage pricing;
- Pricing in multi-period models (Binomial Model);
- Pricing in continuous time (Black-Scholes-Merton Model)

Part II - Numerical techniques
- Beyond Black-Scholes-Merton Model;
- Binomial lattices;
- Monte-Carlo simulation;
- Finite differences

Part III – Structured Finance
- Mortgage-backed securities;
- Modeling and pricing corporate default;
- Credit Default Swaps;
- Designing CDOs and exotic CDOs

Prerequisites: Stochastic Processes and Stochastic Calculus
Hours:
20
Professors/Lecturers:
Tbd
Available for:
Computer Science and System Engineering; Economics, Networks and Business Analytics

Forensic and Legal Psychology

Hours:
24
Professors/Lecturers:
Pietro Pietrini (IMT Lucca)
Available for:
Analysis and Management of Cultural Heritage; Economics, Networks and Business Analytics; Cognitive, Computational and Social Neurosciences

Foundations of Probability and Statistical Inference

Abstract:
This course aims at introducing, from an advanced point of view, the fundamental concepts of probability 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.

Students may be exonerated up to a maximum of 10 hours according to their background.
Hours:
30
Professors/Lecturers:
Irene Crimaldi (IMT Lucca)
Compulsory for:
Economics, Networks and Business Analytics
Also available for:
Computer Science and System Engineering; Cognitive, Computational and Social Neurosciences

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

Abstract:
The 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 a proposal are given.
Hours:
10
Professors/Lecturers:
Marco Paggi (IMT Lucca)
Available for:
Analysis and Management of Cultural Heritage; Computer Science and System Engineering; Economics, Networks and Business Analytics; Cognitive, Computational and Social Neurosciences

Game Theory

Abstract:
The course covers the basics of non-cooperative game theory and information economics. The goal is to equip students with an in-depth understanding of the main concepts and tools of game theory in order to enable them to successfully pursue research in applied areas of economics and related disciplines, and to provide a solid background for students who are planning to concentrate on economic theory.
The course starts with a detailed description of how to model strategic situations as a game. It proceeds by studying basic solution concepts and their main refinements (dominance and iterative dominance, Nash equilibrium, correlated equilibrium, subgame perfect equilibrium, weak perfect Bayesian equilibrium, sequential equilibrium), strategic interaction under incomplete information (Bayesian games, Bayesian Nash equilibrium), and asymmetric information (adverse selection, signaling, screening, moral hazard, and the principal agent problem). The discussion of all theoretical concepts will be accompanied by representative applications from economics.
The course is mostly self-contained, but students should be familiar with basic concepts from calculus, linear algebra, and probability theory.
Hours:
20
Professors/Lecturers:
Kenan Huremovic (IMT Lucca)
Compulsory for:
Economics, Networks and Business Analytics
Also available for:
Computer Science and System Engineering; Cognitive, Computational and Social Neurosciences

Identification, Analysis and Control of Dynamical Systems

Abstract:
The course provides an introduction to dynamical systems, with emphasis on linear systems. After introducing the basic concepts of stability, controllability and observability, the course covers the main techniques for the synthesis of stabilizing controllers (state-feedback controllers and linear quadratic regulators) and of state estimators (Luenberger observer and Kalman filter). The course also covers data-driven approaches of parametric identification to obtain models of dynamical systems from a set of data, with emphasis on the analysis of the robustness of the estimated models w.r.t. noise on data and on the numerical implementation of the algorithms.
Hours:
20
Professors/Lecturers:
Alberto Bemporad (IMT Lucca)
Available for:
Computer Science and System Engineering; Economics, Networks and Business Analytics

International Economics

Abstract:
This course introduces students to the analyses of the most important up-to-date topics in international economics. The objective is to gain an in-depth understanding of the causes and consequences of economic globalization. Emphasis will be given on the internationalization strategies of firms, the organization of production in a global economy, and consequences on labor markets.

Part 1 (F. Serti):
o Overview of Theories of International Trade
o International trade and firm heterogeneity: evidence from firm level data
o Trade and the Labor Market: evidence from local labor markets
o Trade and the Labor Market: evidence from worker and firm level data
o Offshoring and tasks

Part 2 (A. Rungi):
o Gravity Models for International Trade
o The Role of Multinational Enterprises
o Organization of Global Value and Supply chains
o Income inequality and Economic Globalization
o Trade and Investment Policies

Prerequisites: Microeconomics + Econometrics I + Econometrics II
Hours:
20
Professors/Lecturers:
Armando Rungi (IMT Lucca); Francesco Serti (IMT Lucca)
Specializing course for:
Economics, Networks and Business Analytics

Introduction to Cognitive and Social Psyschology

Abstract:
This course will provide an introduction to general themes in Cognitive and Social Psychology. In the first part of the course, we will review seminal findings that had a major impact on our knowledge of cognitive processes and social interactions, as well as more recent studies that took advantage of neuroimaging, electrophysiology and brain stimulation methods to shed new light on decision-making and social behaviors. During the second part of the course, students will be asked to perform a brief presentation of a research article and to critically discuss positive aspects and limitations of the study. The course will include seminars and lectures by renowned researchers in the field and will educate PhD candidates about the influence of social aspects of the human nature on cognitive and brain functioning (and vice-versa) in an intellectually motivating manner.
Hours:
24
Professors/Lecturers:
Pietro Pietrini (IMT Lucca); Emiliano Ricciardi (IMT Lucca)
Available for:
Analysis and Management of Cultural Heritage; Computer Science and System Engineering; Economics, Networks and Business Analytics; Cognitive, Computational and Social Neurosciences

Introduction to Economics

Abstract:
(P. Zacchia): Brief introduction to microeconomics designed for students without previous exposure to it.
This module will cover the following topics, focusing on the interplay between formal models and intuitions:

- Individual choice;
- Equilibrium in competitive markets;
- Imperfectly competitive markets;
- Issues of market failures;
- Concepts of information economics.

(A. Belmonte): This course will provide with a basic introduction of the main notions in Macroeconomics.
Its main goal is to give students a big picture of the macroeconomy and the link between output, employment, and inflation in the short term.
After introducing the fundamentals, the course will then introduce basic macroeconomic models such as the Keynesian AD-AS model and the IS-LM model.
The course will also give some introductory notions of the Phillips curve and its relation with the IS-LM model.
Hours:
20
Professors/Lecturers:
Paolo Zacchia (IMT Lucca); Alessandro Belmonte (IMT Lucca)
Compulsory for:
Economics, Networks and Business Analytics

Introduction to Networks

Abstract:
The course will provide an introduction to the mathematical basis of Complex Networks and to their use to describe, analyze and model a variety of physical and economic situations.

LIST OF LECTURES

Lecture 1 Graph Theory Introduction:
Basic Definitions, Statistical Distributions, Universality, Fractals, Self-Organised Criticality

Lecture 2 Properties of Complex Networks:
Scale-Invariance of Degree Distribution, Small-World Effect, Clustering

Lecture 3 Applications:
Internet, WWW, Socio-technological systems, Economics, Biology

Lecture 4 Communities:
Community Detections, Algorithms to explore Graphs

Lecture 5 Different kind of graphs:
Vertices differences, Layered Vertices, Trees and Taxonomies

Lecture 6 Ranking:
Hierarchies, Spanning Trees,HITS, PageRank,

Lecture 7 Static Models of Graphs:
Erdos-Renyi, Small World

Lecture 8 Dynamical Models of Graphs:
Barabasi-Albert, Configuration models

Lecture 9 Fitness models:
Fitness model and Self-Organised Fitness Model

Lecture 10 Basic Ingredients of Models:
Growth Preferential Attachments, Log Normal Distribution, Multiplicative Noise
Hours:
10
Professors/Lecturers:
Guido Caldarelli (IMT Lucca)
Compulsory for:
Economics, Networks and Business Analytics; Cognitive, Computational and Social Neurosciences
Also available for:
Analysis and Management of Cultural Heritage; Computer Science and System Engineering

Machine Learning

Abstract:
The course provides an introduction to basic concepts in machine learning. Topics include: learning theory (bias/variance tradeoff; Vapnik-Chervonenkis dimension and Rademacher complexity, cross-validation, feature selection); supervised learning (linear regression, logistic regression, support vector machines); unsupervised learning (clustering, principal and independent component analysis); semisupervised learning (Laplacian support vector machines); online learning (perceptron algorithm); hidden Markov models.
Hours:
20
Professors/Lecturers:
Giorgio Stefano Gnecco (IMT Lucca)
Specializing course for:
Economics, Networks and Business Analytics
Also available for:
Computer Science and System Engineering; Cognitive, Computational and Social Neurosciences

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:
30
Professors/Lecturers:
Tbd
Compulsory for:
Economics, Networks and Business Analytics

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:
20
Professors/Lecturers:
Tbd
Compulsory for:
Analysis and Management of Cultural Heritage
Also available for:
Computer Science and System Engineering; Economics, Networks and Business Analytics; Cognitive, Computational and Social Neurosciences

Matrix Algebra

Abstract:
This course is aimed to review the basic concepts of linear algebra:

1. Systems of linear equations: solution by Gaussian elimination, PA=LU factorization, Gauss-Jordan method.
2. Vector spaces and subspaces, the four fundamental subspaces, and the fundamental theorem of linear algebra.
3. Determinant and eigenvalues, symmetric matrices, spectral theorem, quadratic forms.
4. Cayley-Hamilton theorem, functions of matrices, and application of linear algebra to dynamical linear systems.
5. Iterative methods for systems of linear equations.
6. Ordinary lest squares problem, normal equations, A=QR factorization, condition number, Tikhonov regularization.
7. Singular-value decomposition, Moonre-Penrose pseudoinverse.
8. An economic application of linear algebra: the Leontief input-outpul model.
Hours:
10
Professors/Lecturers:
Giorgio Stefano Gnecco (IMT Lucca)
Available for:
Economics, Networks and Business Analytics; Cognitive, Computational and Social Neurosciences

Microeconomics

Abstract:
The course aims at introducing you to graduate-level microeconomic theory. Topics discussed will be:

- Consumer Theory
- Producer Theory
- Choice under uncertainty
- Partial equilibrium and market structure
- General Equilibrium
- Externalities and Public Goods
- Elements of Social Choice Theory (time permitting)

Knowledge of intermediate-level microeconomics is helpful but not necessary. The course will give emphasis to problem solving. For this reason problem sets will be assigned during the course at dates to be communicated in class. Students will then rotate on the board in a following lecture to discuss the problems. There is no required textbook for the course. However, the material presented in class will be taken from Mas-Collel, Whinston, and Green "Microeconomic Theory", which you are encouraged to consult.
Hours:
40
Professors/Lecturers:
Andrea Canidio (IMT Lucca)
Compulsory for:
Economics, Networks and Business Analytics

Neurobiology of Emotion and Behavior

Abstract:
This course will provide an introduction to general themes in Affective and Social Neurosciences, particularly focusing on the neural correlates of emotion and behavior.
Hours:
12
Professors/Lecturers:
Pietro Pietrini (IMT Lucca)
Compulsory for:
Cognitive, Computational and Social Neurosciences
Also available for:
Analysis and Management of Cultural Heritage; Economics, Networks and Business Analytics

Numerical Methods for the Solution of Partial Differential Equations

Abstract:
The course introduces numerical methods for the approximate solution of initial and boundary value problems governed by linear partial differential equations (PDEs) ubiquitous in physics, engineering, and quantitative finance. The fundamentals of the finite difference method and 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. Notions on numerical differentiation, numerical integration, interpolation, and time integration schemes are provided. Special attention is given to the implementation of the numerical schemes in Matlab and in the finite element analysis program FEAP fast intensive computations.
Hours:
20
Professors/Lecturers:
Marco Paggi (IMT Lucca)
Available for:
Computer Science and System Engineering; Economics, Networks and Business Analytics; Cognitive, Computational and Social Neurosciences

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.
An economic application of optimal control: a dynamic limit pricing model of the firm.

Prerequisites: Matrix Algebra
Hours:
20
Professors/Lecturers:
Giorgio Stefano Gnecco (IMT Lucca)
Compulsory for:
Economics, Networks and Business Analytics
Also available for:
Computer Science and System Engineering

Philosophy of Science (long seminar without exam)

Hours:
10
Professors/Lecturers:
Gustavo Cevolani (IMT Lucca)
Available for:
Analysis and Management of Cultural Heritage; Computer Science and System Engineering; Economics, Networks and Business Analytics; Cognitive, Computational and Social Neurosciences

Political Economy

Abstract:
The course is a relatively advanced (i.e. at the beginning graduate level) but essentially self-contained introduction to the methods and some major applications of modern political economy.

Topics:

• Institutions and “exogenous” differences in institutions
• At the origin of institutions: From Social Choice to Political Economics
• Median voter models
• Probabilistic voting models
• Agency models of politics: Electoral accountability and career concerns
• Partisan politicians
• Redistributive politics
• Dynamic policy problems with a focus on economic growth.

Prerequisites: The course assumes a good knowledge of macro and microeconomics (especially some growth theory, elementary taxation theory and game theory, including games with asymmetric/incomplete information and the theory of repeated games), of mathematical and statistical methods (especially static and dynamic optimization), and of econometrics (especially familiarity with the issue of causality in econometrics and IV estimation), at the level of the relevant courses offered at IMT.

In addition, students will be asked to read and present some articles along the way as a part of the final exam.
Hours:
20
Professors/Lecturers:
Alessandro Belmonte (IMT Lucca)
Specializing course for:
Economics, Networks and Business Analytics

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:
Tbd
Compulsory for:
Analysis and Management of Cultural Heritage
Also available for:
Economics, Networks and Business Analytics

Python Programming for Complex Networks

Abstract:
We present in this course the latest results in the field of complex networks. They can solve immediate problems when studying the Internet and the WWW, and they can help sort information on a variety of other systems. This course is structured in such a way as to start with a specific problem and then present the theoretical tools needed to model or to sort out the most relevant information.

In the course we shall follow the various students from the setup of the software in their pc (a basic in Python will be provided in another course) to the application of existing software and the writing of specific one for the personal line of research of the students.
Hours:
20
Professors/Lecturers:
Guido Caldarelli (IMT Lucca)
Compulsory for:
Economics, Networks and Business Analytics
Also available for:
Computer Science and System Engineering; Cognitive, Computational and Social Neurosciences

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

Abstract:
In order to ensure their widest possible dissemination, research results need to be presented in academic publications and in talks. The first goal of this course is to introduce students to basic principles of academic writing and on basic techniques to plan and deliver good academic talks. In addition, the course discusses the key principles of peer review, which is what makes science reliable knowledge. In particular, the course focuses on how to write a professional referee report.
Hours:
8
Professors/Lecturers:
Luca Aceto (Reykjavik University)
Available for:
Analysis and Management of Cultural Heritage; Computer Science and System Engineering; Economics, Networks and Business Analytics; Cognitive, Computational and Social Neurosciences

Socio-Economic Networks

Abstract:
The topic of the course will be the analysis of socio-economic networks. The course will consist of two parts: (1) micro level networks of individuals and firms, (2) macro-level networks of sectors and countries. The first part will focus on social networks and the division of (innovative) labor within and across firm boundaries. The second part on the empirics of macro networks in economics will have a strong focus on international trade, investments and human mobility. Both parts will give you a brief overview on the literature, which predominantly adopted an econometric approach to the analysis of networks.
Hours:
20
Professors/Lecturers:
Massimo Riccaboni (IMT Lucca)
Specializing course for:
Economics, Networks and Business Analytics

Stochastic Processes and Stochastic Calculus

Abstract:
This course aims at introducing some important stochastic processes and Ito stochastic 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 and conditional variance,
- 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, Birth-Death processes,
- Wiener process (definitions, some properties, Donsker theorem, Kolmogorov-Smirnov test) and Ito calculus (Ito stochastic integral, Ito processes and stochastic differential, Ito formula, stochastic differential equations, Ornstein-Uhlenbeck process, Geometric Brownian motion, Feynman-Kac representation formula).

Prerequisites: Matrix Algebra + Foundations of Probability and Statistical Inference
Hours:
30
Professors/Lecturers:
Irene Crimaldi (IMT Lucca)
Specializing course for:
Economics, Networks and Business Analytics
Also available for:
Computer Science and System Engineering; Cognitive, Computational and Social Neurosciences