COURSES

Numerical Methods for Time Inconsistency, Private Information and Limited Commitment (W1)

Antonio Mele, University of Surrey


The aim of this course is to give an overview of state-of-the-art computational methods for non-recursive model with time inconsistency, private information and limited commitment. At the end of the course the student will be able to solve these models with a batch of techniques that combine generalized recursive methods and global approximation theory. This course is indicated for economists working on applied game theory, industrial organization, macroeconomic theory, labour economics, mechanism design.

Course outline

The course is taught in 4 sessions of 4 hours each. The material will be self-contained.
  • Lecture 1: Introduction. Recursivity in Economics and Computational Methods.
  • Lecture 2: Non-recursive Models: Examples of Time Inconsistency, Private Information and Limited Commitment. Numerical Techniques.
  • Lecture 3: The Promised Utilities Approach.
  • Lecture 4: The Lagrangean Approach. Wrap up.

Social and Economic Networks (W2-A)

Angelo Mele, Johns Hopkins University


In this course we will introduce the literature on social and economic networks. Special attention will be devoted to the modeling and estimation of network formation, the econometrics problems related to network effects and the computational issues. At the end of the course, you will be familiar with the trade-offs of using strategic vs random network models, the empirical challenges of estimation and the standard computational tools for network analysis. This course is useful for students and scholars that want to start working on network models, or those wanting a short introduction to the literature.

Course outline

The course is taught in 4 sessions of 4 hours each. The material will be self-contained.
  • Lecture 1: Examples of Social Network Analysis.
  • Lecture 2: Models of network formation, random vs strategic.
  • Lecture 3: Estimation of network models: econometrics and computational challenges.
  • Lecture 4: Estimating the effect of networks.

Dynamic Models of the Family (W2-B)

Matthias Kredler, Universidad Carlos III de Madrid


This course provides an overview on models of the family that are used in dynamic economic environments, including the collective and unitary model as well as non-cooperative models. We will discuss the advantages of these frameworks for addressing different economic questions.

Course outline

The course is taught in 4 sessions of 4 hours each. The material will be self-contained.
  • Lecture 1: Altruistic Preferences.
  • Lecture 2: Commitment Models.
  • Lecture 3: Relaxing Commitment.
  • Lecture 4: Dynamic No-Commitment Models.

Introduction to simulation and estimation of Dynamic Stochastic General Equilibrium models (W3-A)

Cristiano Cantore, University of Surrey


The aim of this course is to provide a hands-on introduction to construction, simulation and estimation of DSGE models using the free software Dynare. Dynare offers a user-friendly and intuitive way of describing these models. It is able to perform simulations of the model given a calibration of the model parameters and is also able to estimate these parameters given a dataset.

Course outline

The course is taught in 4 sessions of 4 hours each. The material will be self-contained.
  • Lecture 1: Introduction to Matlab and Dynare
  • Lecture 2: DSGE model solution and simulation: An application to the RBC model
  • Lecture 3: NK Models
  • Lecture 4: Bayesian Estimation of DSGE models: An application to the New Keynesian model and to a medium scale DSGE model

Continuous-time Methods for Economics and Finance (W3-B)

Galo Nuño, Banco de España


The aim of this course is to provide an introduction to the state-of-the-art continuous-time techniques in economics and finance. At the end of the course the student will be familiar with the theoretical foundations of stochastic calculus and its application to option pricing and general-equilibrium macroeconomics models with financial frictions, default or heterogeneity, as well as with the recent numerical techniques to solve them.

Course outline

The course is taught in 4 sessions of 4 hours each. The material will be self-contained.
  • Lecture 1: Introduction to Stochastic Calculus: Application to Option Pricing.
  • Lecture 2: Stochastic control: Application to Macro-Finance and Sovereign Default.
  • Lecture 3: Numerical techniques.
  • Lecture 4: Heterogeneous-Agents in Continuous Time and Social Planning and Games with Heterogeneous Agents.

An Introduction to Computational Finance (W4)

Vincenzo Merella, University of Cagliari


The aim of this course is to illustrate the most widely used quantitative techniques to price financial instruments. We will develop the main numerical methods to evaluate: hedging strategies (Greeks and stop-loss); options, both vanilla style (European and American) and exotic style (Asian, Bermudan, Barrier, Exchange); and corporate debt, with a particular focus on the risk structure of interest rates.

Course outline

The course is taught in 4 sessions of 4 hours each. The material will be self-contained.
  • Lecture 1: The Binomial Model: basic theoretical elements of arbitrage pricing
  • Lecture 2: Numerical methods: Binomial tree
  • Lecture 3: A More General Framework: arbitrage pricing with infinite states and time periods
  • Lecture 4: Numerical methods: Monte Carlo

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