Economics, Networks and Business Analytics

Microeconomics

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)

Matrix Algebra

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.

Macroeconomics

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.

Introduction to Economics

(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.

(F. Serti): This course will provide with a basic introduction of the main notions in Macroeconomics.

Decision-Making in Economics and Management

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.

Critical Thinking (long seminar without exam)

Constructing and evaluating arguments is fundamental in all branches of science, as well as in everyday life. The course provides the basic skills and tools to recognize correct forms of inference and reasoning, detect the unsound or fallacious ones, and assess the strength of various kinds of argument. The toolbox includes elementary deductive logic, patterns of inductive and abductive inference, the basics of statistical and probabilistic reasoning, and the analysis of heuristics and biases in cognitive psychology.

Analytics in Economics and Management

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.

Advanced Topics in Network Theory: Statistical Mechanics of Networks

Information theory, Exponential Random Graphs.
Hypothesis testing on networks.
Reconstruction of networks.

Lecture 1: Basics of Information Theory
Lecture 2: Complex Networks Randomization
Lecture 3: Exponential Random Graphs
Lecture 4: maximum Likelihood Estimation
Lecture 5: Hypothesis testing on networks
Lecture 6: Early warnings in economic and financial networks
Lecture 7: Gravity Models of Trade
Lecture 8: Reconstruction algorithms I
Lecture 9: Reconstruction algorithms II

Strategies and Business Behavior

Teaching contents:

1. Market and strategy
2. Business and behavioral strategy
3. A new dimension for space and time in organization and strategy
4. Optimization and decision modeling on strategic decision making
5. Skills, competence and a new role of the human being
6. Business behavior as managerial evidence
7. Business plan: the role and function
8. Big data & decision-making process
9. Big data, machine learning for Management science
10. A multidisciplinary approach to business behavior