nep-evo New Economics Papers
on Evolutionary Economics
Issue of 2021‒04‒12
four papers chosen by
Matthew Baker
City University of New York

  1. Left-Handedness and Economic Development By Mariani, Fabio; Mercier, Marion; Pensieroso, Luca
  2. Quantitative economic geography meets history: Questions, answers and challenges By David Krisztián Nagy
  3. When Did Growth Begin? New Estimates of Productivity Growth in England from 1250 to 1870 By Paul Bouscasse; Emi Nakamura; Jón Steinsson
  4. Evolutionary Strategies with Analogy Partitions in p-guessing Games By Aymeric Vie

  1. By: Mariani, Fabio (Université catholique de Louvain); Mercier, Marion (Université Paris-Dauphine); Pensieroso, Luca (IRES, Université catholique de Louvain)
    Abstract: This paper studies the interplay between left-handedness and economic development. To explain the decline and subsequent recovery of left-handedness observed over the last few centuries in the Western world, we propose a theory in which economic development influences the prevalence of left-handedness through structural change and a genetic mechanism driven by differential fertility. We further explore the possibility that the prevalence of left-handedness influences growth, finding that the link between handedness and economic performance varies across stages of development. Consistent with the implications of our model, the analysis of US data suggests that left-handedness can positively contribute to growth, once the economy has reached a sufficiently high level of human capital. Our research provides an example of how economic development can shape evolutionary forces, thus improving our understanding of the growth-diversity link.
    Keywords: handedness, economic growth, evolution, diversity, unified growth theory
    JEL: O11 O14 O33 O40 J13 J24 Q57
    Date: 2021–03
  2. By: David Krisztián Nagy
    Abstract: A rapidly growing literature uses quantitative general equilibrium models of economic geography to study the economic impact of historical events such as the railroad revolution, industrial take-off, structural transformation and wars. I identify three key challenges facing this literature: the tractability of model structure, the availability of historical data, and issues related to identification. I review the literature by discussing how it has been addressing each of these challenges. While doing so, I point out the rich set of questions that this literature can address, as well as the methodological innovations it has conducted to answer these questions.
    Date: 2021–03
  3. By: Paul Bouscasse; Emi Nakamura; Jón Steinsson
    Abstract: We provide new estimates of the evolution of productivity in England from 1250 to 1870. Real wages over this period were heavily influenced by plague-induced swings in the population. We develop and implement a new methodology for estimating productivity that accounts for these Malthusian dynamics. In the early part of our sample, we find that productivity growth was zero. Productivity growth began in 1600—almost a century before the Glorious Revolution. Post-1600 productivity growth had two phases: an initial phase of modest growth of 4% per decade between 1600 and 1810, followed by a rapid acceleration at the time of the Industrial Revolution to 18% per decade. Our evidence helps distinguish between theories of why growth began. In particular, our findings support the idea that broad-based economic change preceded the bourgeois institutional reforms of 17th century England and may have contributed to causing them. We also estimate the strength of Malthusian population forces on real wages. We find that these forces were sufficiently weak to be easily overwhelmed by post-1800 productivity growth.
    JEL: N13 O11 O47
    Date: 2021–03
  4. By: Aymeric Vie
    Abstract: In Keynesian Beauty Contests notably modeled by p-guessing games, players try to guess the average of guesses multiplied by p. Convergence of plays to Nash equilibrium has often been justified by agents' learning. However, interrogations remain on the origin of reasoning types and equilibrium behavior when learning takes place in unstable environments. When successive values of p can take values above and below 1, bounded rational agents may learn about their environment through simplified representations of the game, reasoning with analogies and constructing expectations about the behavior of other players. We introduce an evolutionary process of learning to investigate the dynamics of learning and the resulting optimal strategies in unstable p-guessing games environments with analogy partitions. As a validation of the approach, we first show that our genetic algorithm behaves consistently with previous results in persistent environments, converging to the Nash equilibrium. We characterize strategic behavior in mixed regimes with unstable values of p. Varying the number of iterations given to the genetic algorithm to learn about the game replicates the behavior of agents with different levels of reasoning of the level k approach. This evolutionary process hence proposes a learning foundation for endogenizing existence and transitions between levels of reasoning in cognitive hierarchy models.
    Date: 2021–03

This nep-evo issue is ©2021 by Matthew Baker. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.