
Still to be written

Raffaello Seri
Professor of Econometrics
My research interests include statistics, numerical analysis, operations research, psychology, economics and management.
Related
Publications
How many times should one run a computational simulation?
This chapter is an attempt to answer the question “how many runs of a computational simulation should one do,” and it gives an answer by means of statistical analysis. After defining the nature of the problem and which types of simulation are mostly affected by it, the chapter introduces statistical power analysis as a way to determine the appropriate number of runs. Two examples are then produced using results from an agent-based model. The reader is then guided through the application of this statistical technique and exposed to its limits and potentials.
Analytical Approaches to Agent-Based Models
The aim of this article is to present an approach to the analysis of simple systems composed of a large number of units in interaction. Suppose to have a large number of agents belonging to a finite number of different groups: as the agents randomly interact with each other, they move from a group to another as a result of the interaction. The object of interest is the stochastic process describing the number of agents in each group. As this is generally intractable, it has been proposed in the literature to approximate it in several ways. We review these approximations and we illustrate them with reference to a version of the epidemic model. The tools presented in the paper should be considered as a complement rather than as a substitute of the classical analysis of ABMs through simulation.
Talks
Nonparametric moment-based estimation of simulated models without optimization
International conference
Dec 19, 2020 — Dec 21, 2020
London, United Kingdom (online)
Analyzing the gender pay gap with Agent-Based Modeling
International conference
Dec 4, 2020 — Dec 6, 2020
Dublin, Ireland (online)
Nonparametric moment-based estimation of simulated models via regularized regression
International conference
Sep 14, 2020 — Sep 18, 2020
Milano, Italy (online)
A complex adaptive approach to the gender pay gap
International conference
Jul 2, 2020 — Jul 4, 2020
Hamburg, Germany (online)
Calibration of Agent-Based simulation Models via Model Confidence Sets
Seminar
Jun 9, 2020
Varese, Italy (online)
Counterfactual evaluation in history-friendly models: limits and perspectives
Jan 17, 2020 2:00 PM — 2:30 PM
Ispra, Italy
Model calibration and validation via confidence sets
International conference
Dec 14, 2019 — Dec 16, 2019
London, United Kingdom
Spot the differences! The Simulated Minimum-Distance Method
International conference
Jun 26, 2019 — Jun 28, 2019
Lisbon, Portugal
A simulated minimum-distance method for the calibration of ABMs
International conference
Jun 3, 2019 — Jun 6, 2019
Brighton, United Kingdom
A simulated minimum-distance method for the calibration of ABMs
International conference
May 3, 2019 — May 4, 2019
Bolzano, Italy
A minimum-distance estimator for the calibration of simulation models
International conference
Dec 14, 2018 — Dec 16, 2018
Pisa, Italy
Emergence and Causation in Simulation Models in Social Sciences
Guest lecture
Jul 23, 2018 — Jul 24, 2018
Como, Italy
A power primer for Agent-Based simulation Models. Determining the number of runs in linear and polynomial regressions
International conference
Jun 20, 2018 — Jun 23, 2018
Reykjavík, Iceland
When Finding Appropriate Parameter Values is Challenging: Response Surface Methodology
International conference
Jan 25, 2018 — Jan 26, 2018
Huddersfield, United Kingdom
Controlling for 'false negatives' in agent-based models of organizational behavior: A review of power analysis
International conference
Jun 17, 2015 — Jun 20, 2015
Warsaw, Poland
An approach to tax evasion with social peers and reference dependent preferences
International conference
May 7, 2015 — May 8, 2015
Slagelse, Denmark
Analytical approaches to the analysis of agent-based models
International conference
Jan 27, 2014 — Jan 28, 2014
Bournemouth, United Kingdom