Economics

This course explores the architecture and politics behind global finance, and how it can be reformed to address the world's most urgent needs: climate change, inequality, debt sustainability, and beyond. The challenge today isn't just what we fund, but how we fund it. Through a mix of academic literature, case studies, student-led presentations, and guest lectures by senior experts from leading institutions, the course explores which actors shape the global economy, how they wield their influence, and what it would take to reform them.

The course develops students' understanding of the classical linear econometric model (ordinary least squares). It covers a range of topics, including estimation and inference in multivariate regression models; the use of limited dependent variables; large sample properties of OLS estimators; multicollinearity and heteroskedasticity. The course develops students' applied skills through the use of appropriate econometric software.

This course introduces key economic principles such as trade-offs, opportunity cost, supply and demand, and market structures. Students learn how markets function, how government policies influence economic outcomes, and how macroeconomic indicators like national income and trade shape the global economy. Emphasis is placed on applying economic reasoning to real-world issues and thinking critically about the limits of economic models.

At a time when liberal democracies are weakened by ideological polarization and the rise of populist movements challenging institutional checks and balances as well as the foundations of rational debate (Trumpism, the Bolsonaro episode, the AfD, etc.), it is becoming vital for future political, administrative, and academic leaders—who are often unfamiliar with scientific fundamentals, particularly in statistics—to acquire a basic grasp of such tools in order to define a framework for contributing to informed debate and evidence-based decision-making. This course provides them with that foundation through the lens of mathematical modeling. Concretely, it offers a rigorous methodology and a practical introduction to statistical modeling, taught through its logical application in structuring arguments and fostering debate. The objective is to equip students with practical tools that will allow them to analyze, interpret, and critically assess the use of data in their future professional environments, whether in strategy, economics, consulting, or public affairs management. With the help of AI-assisted applications, students learn to build, and interpret simple economic models, while developing a critical stance on the limitations and biases inherent in these models. The econometric article by Daron Acemoglu, recipient of the 2024 Nobel Prize, serves as one of the course's central threads, alongside more operational examples drawn from the corporate world and public sector. Through these applications, the course also offers students keys to understanding the mathematical foundations behind how artificial intelligence operates. The overarching ambition of this course is to enable students to become autonomous, clear-sighted, and critical actors in the use of data—capable of shaping the framework of public debate and decision-making at a time when perceptions of reality are increasingly influenced and polarized by the subjective interpretations of both populist opinion leaders and the prophets of artificial intelligence and big data.

This course is part of the Laurea Magistrale degree program and is intended for advanced level students. Enrollment is by permission of the instructor. By the end of this course students are able to: master all the necessary tools and knowledge to interpret modern phenomena relative to international economics evolution; understand the role of optimal currency areas and the most important theories on exchange-rate determination.

This course provides all necessary tools and knowledge to interpret modern phenomena relative to international economics evolution. The focus of the course is on monetary aspects of international economics. In particular, we study the role of optimal currency areas and the most important theories on exchange-rate determination. Moreover, attention is devoted to the analysis of balance of payment crisis as a mechanism derived from the internal economic policy contradiction of a given country. Therefore, what is going to be the optimal exchange-rate regime? How an inadequate choice about exchange-rate regime will translate into a Balance of Payment Crisis?

The long-run economic development of countries, as well as inequality within countries are the major topics of this course. The course reviews the major conceptual approaches to economic development and applies those to the actual experience of countries. In this way, the global variety of development experiences becomes a central topic of the course, addressing topics such as investment, trade, building institutions, population dynamics, education, health, and migration. The material that we cover suggests that inequality of the distribution of income resulting from differences across the population in terms of access to education, health services, or infrastructure can be a major obstacle to economic development. Throughout the course, public policy options for stimulating development are made central, especially in the assignment that students carry out.  Prerequisite SSC1027 Principles of Economics. Knowledge of basic quantitative concepts such as reading and working with graphs and simple equations is also a prerequisite

The course is designed to introduce students to the latest developments in behavioral finance and to broaden their understanding of modern finance. Behavioral finance introduces psychological insights and more realistic assumptions to guide and advance the theory of financial markets. We will examine how behavioral finance complements traditional paradigms and study trading behavior, asset price dynamics, and corporate financial decisions in a behavioral context.

This course covers the tools required to evaluate and carry out empirical data analyses and introduces students to various regression methods that empirical researchers (economists, social scientists, data scientists, etc.) use for estimating, testing, and forecasting causal relationships.  Frontier research papers with various economic data sets are covered, and the course discusses how machine learning and econometrics can be used together to improve causal inference.  

Topics include basic regression models, advanced topics in panel data, time series analysis, difference-in-differences models, and discrete choice models 

Prerequisites: Basic knowledge of linear algebra, probability, and statistics is expected. If you are not sure whether you meet the prerequisites, please consult with the instructor.  

This course provides an intermediate level introduction to the application of modern time series methods that may be used to analyze economic data. The initial part of the course includes a review of techniques that can be used to identify the dynamic properties of time series data. Thereafter, a selection of the popular modelling frameworks is introduced (i.e. autoregressive integrated moving average models, distributed lag models, and vector autoregressive models). Extensions to these frameworks, which allow for aspects such as cointegration and error correction representations, are also covered, before attention is directed towards the application of model misspecification tests and forecasting exercises. Course entry requirements: ECO4006F, ECO4007F and ECO4016F.

This course examines the internal organization of firms and other organizations. It provides a rigorous introduction to foundational theories, and then discusses applications to real-world managerial problems. It looks at the following questions: How should incentives be designed in organizations? How should conflict within an organization be resolved? When should organizations outsource and when should they produce internally? Why do organizations arise in market economies?