nep-evo New Economics Papers
on Evolutionary Economics
Issue of 2022‒02‒07
three papers chosen by
Matthew Baker
City University of New York

  1. Sophistication about Self-Control By Deborah A. Cobb-Clark; Sarah C. Dahmann; Daniel A. Kamhöfer; Hannah Schildberg-Hörisch
  2. Evolutionary correlation, regime switching, spectral dynamics and optimal trading strategies for cryptocurrencies and equities By Nick James
  3. Men Are from Mars, and Women Too: A Bayesian Meta-Analysis of Overconfidence Experiments By Bandiera, Oriana; Parekh, Nidhi; Petrongolo, Barbara; Rao, Michelle

  1. By: Deborah A. Cobb-Clark (The University of Sydney, School of Economics); Sarah C. Dahmann (Melbourne Institute: Applied Economic & Social Research, the University of Melbourne); Daniel A. Kamhöfer (Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics); Hannah Schildberg-Hörisch (Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics)
    Abstract: We propose a broadly applicable empirical approach to classify individuals as time consistent versus naive or sophisticated regarding their self-control limitations. Operationalizing our approach based on nationally representative data reveals that self-control problems are pervasive and that most people are at least partly aware of their limited self-control. Compared to naïfs, sophisticates have higher IQs, better educated parents, and are more likely to take up commitment devices. Accounting for both the level and awareness of self-control limitations has predictive power beyond one-dimensional notions of self-control that neglect awareness. Importantly, sophistication fully compensates for self-control problems when choices involve immediate costs and later benefits. Raising people's awareness of their own self-control limitations may thus assist them in overcoming any adverse consequences.
    Keywords: self-control, sophistication, naïveté, commitment devices, present bias
    JEL: D91 D01
    Date: 2021–08
  2. By: Nick James
    Abstract: This paper uses new and recently established methodologies to study the evolutionary dynamics of the cryptocurrency market, and compares the findings with that of the equity market. We begin by applying random matrix theory and principal components analysis (PCA) to correlation matrices of both collections, highlighting clear differences in the eigenspectra exhibited. We then explore the heterogeneity of both asset classes, studying the time-varying dynamics of underlying sector behaviours, and determine the collective similarity within each collection. We then turn to a study of structural break dynamics and evolutionary power spectra, where we quantify the collective affinity in structural breaks and evolutionary behaviours of underlying sector time series. Finally, we implement two algorithms simulating `portfolio choice' dynamics to compare the effectiveness of stock selection and sector allocation in cryptocurrency portfolios. There, we highlight the importance of both endeavours and comment on noteworthy implications for cryptocurrency portfolio management.
    Date: 2021–12
  3. By: Bandiera, Oriana (London School of Economics); Parekh, Nidhi (J-PAL Africa); Petrongolo, Barbara (University of Oxford); Rao, Michelle (London School of Economics)
    Abstract: Gender differences in self-confidence could explain women's under representation in high-income occupations and glass-ceiling effects. We draw lessons from the economic literature via a survey of experts and a Bayesian hierarchical model that aggregates experimental findings over the last twenty years. The experts' survey indicates beliefs that men are overconfident and women under-confident. Yet, the literature reveals that both men and women are typically overconfident. Moreover, the model cannot reject the hypothesis that gender differences in self-confidence are equal to zero. In addition, the estimated pooling factor is low, implying that each study contains little information over a common phenomenon. The discordance can be reconciled if the experts overestimate the pooling factor or have priors that are biased and precise.
    Keywords: gender gaps, over-confidence, Bayesian meta-analysis
    JEL: C91 J16
    Date: 2021–12

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