Publications by authors named "Marco Pangallo"

Article Synopsis
  • The text discusses the ongoing debate about the economic and public health effects of mandated interventions versus voluntary behavior changes during the COVID-19 pandemic.
  • A new agent-based model is introduced that simulates how different industries, occupations, and income levels are impacted, validated against the first wave of COVID-19 in New York.
  • The study finds that the main connection between epidemic spread and economic outcomes is the decrease in consumer spending driven by fear of infection, particularly affecting low-income workers in face-to-face jobs the most.
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We analyze the performance of the best-response dynamic across all normal-form games using a random games approach. The playing sequence-the order in which players update their actions-is essentially irrelevant in determining whether the dynamic converges to a Nash equilibrium in certain classes of games (e.g.

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Agent-Based Models (ABMs) are used in several fields to study the evolution of complex systems from micro-level assumptions. However, a significant drawback of ABMs is their inability to estimate agent-specific (or "micro") variables, which hinders their ability to make accurate predictions using micro-level data. In this paper, we propose a protocol to learn the latent micro-variables of an ABM from data.

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We introduce a dynamic disequilibrium input-output model that was used to forecast the economics of the COVID-19 pandemic. This model was designed to understand the upstream and downstream propagation of the industry-specific demand and supply shocks caused by COVID-19, which were exceptional in their severity, suddenness and heterogeneity across industries. The model, which was inspired in part by previous work on the response to natural disasters, includes the introduction of a new functional form for production functions, which allowed us to create bespoke production functions for each industry based on a survey of industry analysts.

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Game theory is widely used to model interacting biological and social systems. In some situations, players may converge to an equilibrium, e.g.

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Online activity leaves digital traces of human behavior. In this paper we investigate if online interest can be used as a proxy of housing demand, a key yet so far mostly unobserved feature of housing markets. We analyze data from an Italian website of housing sales advertisements (ads).

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