These lectures aim at revisiting the standard approach to several strategic settings in which players’ information is imperfect and/or incomplete. We will first present the relevant solu- tion concepts for extensive form games, and then analyze the scenario in which players may have some commitment power. This allows to cover important issues in incentive theory and mechanism design. Our emphasis will be on economic applications. No background beyond an introductory course in game theory is required.

This course will be held at EIEF.

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Behavioral economics observes regularities in individual decision-making, documents departures from what classical economic theory predicts, and explains these departures by incorporating psychological insights into economic theories. This course covers recent topics in behavioral economics. The first part includes the analysis of deviations from the standard neoclassical model due to imperfect optimization (i.e., limited attention, limited information, limited computational capacity), bounded self-control (i.e., reference dependence, framing, status quo bias), nonstandard preferences (i.e., social preferences, fairness). In the second part, the course gives some applications of behaviorally motivated policy interventions in specific fields, mostly environmental economics but also public economics, household finance, and others.

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One of the central applications of economics is the evaluation of policies and interventions. Causality is important in econometrics because it enables economists to go beyond mere correlations, providing a deeper understanding of how economic variables interact and influence each other. This understanding is essential for making sound economic decisions, designing effective policies, and advancing economic theory. For example, it helps determine whether an increase in the minimum wage directly leads to changes in employment levels. This course delves into advanced topics in causal inference, particularly focusing on 'irregular designs.' Irregular designs represent complex scenarios where the standard assumptions required for estimating causal effects do not apply. Examples of irregular designs include randomized experiments affected by non-compliance, as well as observational studies with unmeasured confounding variables. Additionally, we explore other challenging irregular designs, such as regression discontinuity designs, where treatment assignment relies on specific thresholds, leading to issues of overlap. In the course's second segment, our exploration extends to the realm of spillover effects. Here, we transcend the common assumption of independence between units and investigate how the treatment of one unit may reverberate onto the outcomes of others. We introduce cutting-edge statistical methodologies tailored for estimating spillover or peer-influence effects, particularly within clusters of units or social networks.

This course is shared with the Master of Science in Economics.

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The aim of the course is to introduce the students to the microeconomic analysis of pollution policy. A base model will specifically be presented to address pollution generation and environmental policy design. This model will then be extended in several directions, including (but not limited to) eco-innovation drivers and transboundary/international pollution problems (the latter also featuring a macroeconomic perspective). For the covered topics, a general theoretical analysis will be developed, and then examples of current theoretical and empirical research will be provided.

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Part 1, Gianluca Cubadda

1) Dynamic regression models with many predictors
2) Out-of-sample evaluation
3) Classical methods for large vector autoregressive models (VARs)

Part 2, Stefano Grassi

The objective of this module is to introduce students to advanced topics in macroeconometrics to enhance independent research. Examples of active topic of research will be provided during the lectures.

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This course is centered on a growing literature which extends the traditional theories of incentives and optimal contracting to a competitive framework. Our focus is on strategic approaches. We first provide a methodological introduction, which aims at revisiting the foundations of mechanism design and its recent extensions to competing mechanism games. We next move to competitive settings, covering both moral hazard and adverse selection economies. Hopefully, the lectures will provide new insights to evaluate the effects of financial con- straints due to the combination of agency problems and competition among intermediaries on economic activity and market performances. No background beyond first year graduate microeconomics is required, although familiarity with contract theory and information economics is useful.

This course will be held at EIEF.

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Industrial organisation is the branch of economics that studies the role of imperfectly competitive markets for private and social decisions. The course aims to introduce the students to its fundamental models and results. The course is designed for graduate students who either did not take a course in IO or only took a basic undergraduate IO course. It serves either as a general interest course for those students not wanting to pursue research in IO or as an introduction to more advanced IO courses for those who want to do research in IO.

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The course deals with methods and models for signal extraction and filtering in economics.
It sets off with an introduction to time series analysis in the frequency domain. Frequency domain methods focus on the spectral density function of stationary stochastic process. Inferences are based on the periodogram, which is a transformation of the series, based on the discrete Fourier transform, with interesting properties that bring out features of the series and facilitate inference for classes of time series models. The asymptotic properties of the periodogram will be considered and used for estimating the spectrum of a random process.
For a given time series model, parametric inferences can be based on a large sample approximation to the true likelihood known as the Whittle likelihood. Our illustrations deal with estimation of ARMA, unobserved component models for trend-cycle analysis, parametric and semiparametric long memory models for stochastic volatility, and high-dimensional factor models.
High-dimensional factor models is an approach to high-dimensional time series that plays a pivotal role for signal extraction and forecasting. They are based on a solid representation theory and provide the way of distilling the co-movements in a large set of macroeconomic time series, without incurring in the curse of dimensionality.
We conclude with an introduction to the class of locally stationary processes.

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European economic growth over the long run.
Infrastructure and growth in Europe 1840-2010.  
The Italian regional divide: recent development.

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A large fraction of government spending involves procurement from private contractors. The effectiveness of the procurement process affects crucial government-provided goods and services. Abuses of rules and discretion, their interaction with corruption and collusion and the methods to detect them in large datasets pose the main challenges and will be at the core of the course. Other topics are (ri)emerging, such as if and how to use public procurement as an industrial policy to stimulate innovation and protect the environment, the role played by public buyers’ competences, or if and how to use AI in designing tenders and evaluating public buyers performance. This course will mostly focus on recent empirical studies and will bring students at research frontier on these topics.

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Causality and identification in macroeconomics and finance. Review of stationary models. Causal identification in macroeconomics. Estimation of heterogeneous agent models.

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Introduction to spectral analysis. Inference with weakly dependent data. Functional Central Limit Theorem. Non-stationary models. Long-run variance estimation (time permitting). Impulse response inference (time permitting).

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This is an advanced graduate level course in international macroeconomics and finance. The course is targeted to second-year Ph.D. students in economics and focuses on applied theory and empirical stylized facts. The course assumes familiarity with basic theoretical modeling techniques such as dynamic optimization and general equilibrium modeling. Similarly, the course assumes familiarity with basic numerical-method solution techniques and with econometric softwares of your choice (e.g. matlab, python, ...).

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The course introduces the basic methods for computations based on a posterior distribution. In particular the following topics will be covered: Introduction to Bayesian computation; Basics of Markov chain simulation; Computationally efficient Markov chain simulation.

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This course focuses on New Keynesian model with frictions in the real and financial sectors and on the role of fiscal and monetary policies in mitigating business and financial cycle fluctuations. We will consider among others the role of recent unconventional monetary and macroprudential policies as business cycle stabilization devices and monetary and fiscal policy coordination during the Pandemic. As modern economies are increasingly exposed to shocks of large magnitude, the course will also focus on the role of macroeconomic policies in DSGE models subject to rare disaster shocks.
We will consider Dynamic Stochastic General Equilibrium (DSGE) models where consumers, firms, banks and the public sector (monetary and fiscal policy) interact in the same economic environment and produce choices in terms of consumption, investment, output and monetary aggregates.
Macro models of monetary policy in a DSGE setting typically involve forward-looking behavior. To develop practical research skills students will solve linear rational expectation models using MATLAB.
Focussing in particular on the method proposed by King and Watson (1998) we will then solve a larger DSGE model with a banking sector producing the full constellation of financial and monetary spreads as proposed by Goodfriend and McCallum (2007). We consider the macroeconomic effects of unconventional monetary policy, through variation in the composition of central banks.balance sheets, as compared to the conventional monetary transmission mechanism.

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The course introduces some key topics in Development Economics. It first discusses models with multiple equilibria, where a discrete development effort (a big push) may be required to move the economy away from a low-income, low-growth trap. It then examines the dual structure of labour markets in developing countries and explains migration as a response to the imbalance between different sectors or regions. We shall consider non-ergodic development models, where the long-run growth path of the economy depends on the initial distribution of income and wealth. We shall finally study whether weak states can act as a barrier to economic development.

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The course will focus on determinants of migration and its impact on sending and receiving countries, presenting the main theoretical approaches and the recent empirical evidence. Beside the more classical themes, the course will focus on new areas where research is not yet mature. The course will cover the following topics: data and measurement, theories of migration, selection of migrants, the impact of migration on the labour markets and production structure of receiving and sending, impact on fertility and health, immigration and public finance, the political economy of immigration, understanding refugees flows.

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This course introduces some elements of Network Theory and discusses some of its economic applications. The first part of the course illustrates the basic mathematical tools for the study of networks, including measures to identify the key players. The second part of the course presents applications of the theory, and looks at comparative economic growth, at conflicts, and at the rôle of networks in the enforcement of sanctions.

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Industrial organisation is the branch of economics that studies the role of imperfectly competitive markets for private and social decisions. The course aims to introduce the students to its fundamental models and results. The course is designed for graduate students who either did not take a course in IO or only took a basic undergraduate IO course. It serves either as a general interest course for those students not wanting to pursue research in IO or as an introduction to more advanced IO courses for those who want to do research in IO.

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The course will briefly introduce latent variable models for empirical exercises in economics, finance, and business. We will give an overview of possible specifications of univariate and multivariate latent variable models, with special attention to interpretation and connections with the concept of unobserved heterogeneity. We will mostly focus on latent Markov models with categorical outcomes, but most of the concepts apply in general. The R software for statistical computing will be used throughout.

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This course will be held at EIEF.

1. Credit: Trust and limited commitment; Intermediating trust: the role of banks; Financial fragility.
2. Money: Commodities as money; Assets as money; The terms of trade; Intermediation.
3. Money: The benchmark model with divisible money; Extensions; The cost of inflation; Liquidity in finance.

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This course will be held at EIEF.

This course is an introduction to the study of distributional issues in history and today. History offers a vast catalogue of experience from which to learn: radical technological changes, wars, internationalisation and autarchy, economic miracles and development disasters, and every type of policy regime. And only a historical perspective puts us in a position to identify the operation of long-run laws (or, conversely, the role of contingency) in an economy’s evolution. Equally important in understanding and interpreting the literature on poverty, inequality, and living standards is a sure grasp of the technical issues surrounding measurement. Establishing a poverty line that is comparable across very different circumstances is a theoretical and practical challenge, as is estimating a distribution from microdata (today no less than in the past). Alongside the history of inequality, therefore, the course includes an important component devoted to the econometric theory and practice of measurement.

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The aim of this course is to introduce students to a set of tools for modeling and prediction with complex (long and wide) datasets. This is a recently developed area in statistics and econometrics which blends with parallel developments in computer science, in particular machine learning. The course encompasses a variety of methods, both frequentist and Bayesian, including classical meth- ods for regression and classification; asymptotic approximations vs. resampling methods; model uncertainty and model selection; model averaging; shrinkage estimators; principal components and partial least squares; linear regression smoothers; projection pursuit, generalized additive models, and neural networks; tree-based methods.

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This course will be held at EIEF.

We will present techniques for analysis of textual data. The course discusses at first data engineering, i.e., how to process text and how to obtain a data matrix from a text corpus. Analysis will involve simple descriptive tools for text corpi, summarisation, keyword extraction. We will then discuss the uses of text corpi in supervised and supervised learning tasks. Specific methods will be discussed for topic modeling and sentiment analysis.Case studies will involve both short (e.g., arising from social media) and longer texts (e.g., newspaper articles).

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A look at the data; A Horizontal Innovation Model; A Schumpeterian Model; Semi-endogenous Growth; Skill-Biased Technical Change; Factor Income Taxes in the Endogenous and Semi-endogenous Growth Literature. Growth and Volatility.

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A merger is said to be horizontal when involves firms operating in the same industry. Horizontal mergers are one of the main tools adopted by firms to increase their competitiveness. After an initial review of the seminal contributions discussing the forces leading firms to engage in a horizontal merger, the focus will be on cutting-edge research on the role of Competition Policy in evaluating their social impact.
The course is designed for those students who already took an undergraduate course in Industrial Organization and are therefore familiar with the main models of market competition and the game theoretical solution concepts under static and dynamic interaction.1 The course prepares the student who wishes to pursue academic research on the topic.

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