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  1. Best-response dynamics, playing sequences, and convergence to equilibrium in random games
    Author: Heinrich, Torsten; Jang, Yoojin; Mungo, Luca; Pangallo, Marco; Scott, Alex; Tarbush, Bassel; Wiese, Samuel
    Published: [2021]
    Publisher:  LEM, Laboratory of Economics and Management, Institute of Economics, Scuola Superiore Sant'Anna, Pisa, Italy

    We show that the playing sequence-the order in which players update their actions-is a crucial determinant of whether the best-response dynamic converges to a Nash equilibrium. Specifically, we analyze the probability that the best-response dynamic... more

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    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 203
    Inter-library loan:
    No inter-library loan

     

    We show that the playing sequence-the order in which players update their actions-is a crucial determinant of whether the best-response dynamic converges to a Nash equilibrium. Specifically, we analyze the probability that the best-response dynamic converges to a pure Nash equilibrium in random n-player m-action games under three distinct playing sequences: clockwork sequences (players take turns according to a fixed cyclic order), random sequences, and simultaneous updating by all players. We analytically characterize the convergence properties of the clockwork sequence best-response dynamic. Our key asymptotic result is that this dynamic almost never converges to a pure Nash equilibrium when n and m are large. By contrast, the random sequence best- response dynamic converges almost always to a pure Nash equilibrium when one exists and n and m are large. The clockwork best-response dynamic deserves particular attention: we show through simulation that, compared to random or simultaneous updating, its convergence properties are closest to those exhibited by three popular learning rules that have been calibrated to human game-playing in experiments (reinforcement learning, fictitious play, and replicator dynamics).

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/243498
    Series: LEM working paper series ; 2021, 02 (January 2021)
    Subjects: Best-response dynamics; equilibrium convergence; random games; learning models in games
    Scope: 1 Online-Ressource (circa 58 Seiten), Illustrationen
  2. The potential of big housing data: an application to the Italian real-estate market
    Author: Loberto, Michele; Luciani, Andrea; Pangallo, Marco
    Published: [2018]
    Publisher:  Banca d'Italia Eurosistema, [Rom]

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    VS 450
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    Content information
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Temi di discussione / Banca d'Italia ; number 1171 (April 2018)
    Subjects: big data; machine learning; housing market
    Scope: 1 Online-Ressource (circa 60 Seiten), Illustrationen
  3. Synchronization of endogenous business cycles
    Author: Pangallo, Marco
    Published: [2023]
    Publisher:  LEM, Laboratory of Economics and Management, Institute of Economics, Scuola Superiore Sant'Anna, Pisa, Italy

    Business cycles tend to comove across countries. However, standard models that attribute comovement to propagation of exogenous shocks struggle to generate a level of co-movement that is as high as in the data. In this paper, we consider models that... more

    Access:
    Verlag (kostenfrei)
    Verlag (kostenfrei)

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 203
    Inter-library loan:
    No inter-library loan

     

    Business cycles tend to comove across countries. However, standard models that attribute comovement to propagation of exogenous shocks struggle to generate a level of co-movement that is as high as in the data. In this paper, we consider models that produce business cycles endogenously, through some form of non-linear dynamicsâ€"limit cycles or chaos. These models generate stronger comovement, because they combine shock propagation with synchronization of endogenous dynamics. In particular, we study a demand-driven model in which business cycles emerge from strategic complementarities within countries, synchronizing their oscillations through international trade linkages. We develop an eigen-decomposition that explores the interplay between non-linear dynamics, shock propagation and network structure, and use this theory to understand the mechanisms of synchronization. Next, we calibrate the model to data on 24 countries and show that the empirical level of comovement can only be matched by combining endogenous business cycles with exogenous shocks. Our results lend support to the hypothesis that business cycles are at least in part caused by underlying non-linear dynamics.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: LEM working paper series ; 2023, 01 (January 2023)
    Subjects: Synchronization; Business Cycles; Non-linear dynamics; Networks
    Scope: 1 Online-Ressource (circa 30 Seiten), Illustrationen