nep-evo New Economics Papers
on Evolutionary Economics
Issue of 2023‒11‒13
five papers chosen by
Matthew Baker, City University of New York

  1. Modeling social norms: an integration of the norm-utility approach with beliefs dynamics By Gavrilets, Sergey; Tverskoi, Denis; Sánchez, Angel
  2. Pecuniary Emulation and Invidious Distinction: Signaling under Behavioral Diversity By Junichiro Ishida; Wing Suen
  3. Immigration Restriction and The Transfer of Cultural Norms Over Time and Boundaries:The Case of Religiosity By Fausto Galli; Simone Manzavino; Giuseppe Russo
  4. Slavery, coercion, and economic development in Sub-Saharan Africa By Gardner, Leigh
  5. An evolution strategy approach for the Balanced Minimum Evolution Problem By Gasparin, Andrea; Camerota Verdù, Federico Julian; Catanzaro, Daniele

  1. By: Gavrilets, Sergey; Tverskoi, Denis; Sánchez, Angel
    Abstract: We review theoretical approaches for modeling the origin, persistence and change of social norms. The most comprehensive models describe the coevolution of behaviors, personal, descriptive, and injunctive norms while considering influences of various authorities and accounting for cognitive processes and between-individual differences. Models show that social norms can improve individual and group well-being. Under some conditions though deleterious norms can persist in the population through conformity, preference falsification, and pluralistic ignorance. Polarization in behavior and beliefs can be maintained, even when societal advantages of particular behaviors or belief systems over alternatives are clear. Attempts to change social norms can backfire through cognitive processes including cognitive dissonance and psychological reactance. Under some conditions social norms can change rapidly via tipping point dynamics. Norms can be highly susceptible to manipulation, and network structure influences their propagation. Future models should incorporate network structure more thoroughly, explicitly study online norms, consider cultural variations, and be applied to real-world processes.
    Date: 2023–10–19
  2. By: Junichiro Ishida; Wing Suen
    Abstract: We introduce behavioral diversity to an otherwise standard signaling model, in which a fraction of agents choose their signaling actions according to an exogenous distribution. These behavioral agents provide opportunities for strategic low-type agents to successfully emulate higher types in equilibrium, which in turn reduces the cost for strategic high-type agents to separate from lower types. Behavioral diversity thus improves the equilibrium payoffs to all types of strategic agents. The model also exhibits a convergence property which is intuitively more appealing than the least-cost separating equilibrium of the standard setting.
    Date: 2023–10
  3. By: Fausto Galli (University of Salerno); Simone Manzavino (University of Salerno); Giuseppe Russo (University of Salerno, CSEF, and GLO)
    Abstract: We study the effect of an immigration ban on the self-selection of immigrants along cultural traits, and the transmission of these traits to the second generation. We show theoretically that restricting immigration incentivizes to settle abroad individuals with higher attachment to their origin culture, who, under free mobility, would rather choose circular migration. Once abroad, these individuals tend to convey their cultural traits to their children. As a consequence, restrictive immigration policies can foster the diffusion of cultural traits across boundaries and generations. We focus on religiosity, which is one of the most persistent and distinctive cultural traits, and exploit the 1973 immigration ban in West Germany (Anwerbestopp) as a natural experiment. Through a diff-in-diff analysis, we find that second generations born to parents treated by the Anwerbestopp show higher religiosity.
    Keywords: second-generation immigrants, religiosity, immigration policy, cultural transmission.
    JEL: D91 F22 J15 K37 Z13
    Date: 2023–09–29
  4. By: Gardner, Leigh
    Abstract: Recent debates on the economic history of the United States and other regions have revisited the question of the extent to which slavery and other forms of labor coercion contributed to the development of economic and political institutions. This article aims to bring Africa into this global debate, examining the contributions of slavery and coercion to periods of economic growth during the nineteenth and twentieth centuries. It argues that the coercion of labor in a variety of forms was a key part of African political economy, and thus when presented with opportunities for growth, elites turned first to the expansion of coerced labor. However, while labor coercion could help facilitate short-run growth, it also made the transition to sustained growth more difficult.
    Keywords: Africa; economic development; slavery forced labor
    JEL: J1 R14 J01
    Date: 2023–09–25
  5. By: Gasparin, Andrea (Università degli Studi di Trieste); Camerota Verdù, Federico Julian (Università degli Studi di Trieste); Catanzaro, Daniele (Université catholique de Louvain, LIDAM/CORE, Belgium)
    Abstract: Motivation: The Balanced Minimum Evolution (BME) is a powerful distance based phylogenetic estimation model introduced by Desper and Gascuel and nowadays implemented in popular tools for phylogenetic analyses. It was proven to be computationally less demanding than more sophisticated estimation methods, e.g. maximum likelihood or Bayesian inference, while preserving the statistical consistency and the ability of running with almost any kind of data for which a dissimilarity measure is available. BME can be stated in terms of a nonlinear non-convex combinatorial optimisation problem, usually referred to as the Balanced Minimum Evolution Problem (BMEP). Currently, the state-of-the-art among approximate methods for the BMEP is represented by FastME (version 2.0), a software which implements several deterministic phylogenetic construction heuristics combined with a local search on specific neighbourhoods derived by classical topological tree rearrangements. These combinations, however, may not guarantee convergence to close-to-optimal solutions to the problem due to the lack of solution space exploration, a phenomenon which is exacerbated when tackling molecular datasets characterised by a large number of taxa. Results: To overcome such convergence issues, in this article we propose a novel metaheuristic, named PhyloES, which exploits the combination of an exploration phase based on Evolution Strategies, a special type of evolutionary algorithm, with a refinement phase based on two local search algorithms. Extensive computational experiments show that PhyloES consistently outperforms FastME, especially when tackling larger datasets, providing solutions characterised by a shorter tree length but also significantly different from the topological perspective.
    Date: 2023–07–22

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