nep-neu New Economics Papers
on Neuroeconomics
Issue of 2015‒10‒25
four papers chosen by
Daniel Houser
George Mason University

  1. The Effect of Intelligence on Financial Development: A Cross-Country Comparison By Kodila-Tedika, Oasis; Asongu, Simplice
  2. Be smart, live long: the relationship between cognitive and non-cognitive abilities and mortality By Öhman, Mattias
  3. Beyond Qualifications: Returns to Cognitive and Socio-Emotional Skills in Colombia By Acosta, Pablo A.; Muller, Noel; Sarzosa, Miguel
  4. Brain Types and Wages By Drydakis, Nick

  1. By: Kodila-Tedika, Oasis; Asongu, Simplice
    Abstract: We assess the correlations between intelligence and financial development in 123 countries using data averages from 2000-2010. Human capital is measured in terms of IQ, cognitive ability & cognitive skills, while financial development is appreciated both from financial intermediary and stock market development perspectives. Short-term financial measures are private and domestic credits whereas long-term financial indicators include: stock market capitalization, stock market value traded and turnover ratio. The following findings are established. (1) With respect to private credit, the positive correlations of IQ and cognitive ability are broadly similar while that of cognitive skills is substantially higher in terms of magnitude. (2) The correlation between intelligence and other financial variables are broadly similar. (3) The underlying findings are broadly confirmed in terms of sign of correlation, though the magnitude of correlation is higher (lower) with the addition of social capital or ethnic fractionalization (institutions or income). (4) When continents are excluded to control for extreme effects, baseline results are confirmed and the following on order of continental importance in financial development is established in increasing magnitude: Africa, Americas, Oceania, Europe & Asia.
    Keywords: Financial development, Intelligence, Skill, Human Capital
    JEL: E01 G20 I20 I29
    Date: 2015–02–01
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:67295&r=all
  2. By: Öhman, Mattias (Department of Economics, Uppsala University)
    Abstract: I study the association between cognitive and non-cognitive abilities and mortality, and investigate how well income and education act as proxy measures for ability. The risk of premature mortality is estimated using Cox proportional hazard models with a dataset of 692,303 Swedish men aged 18-20 years, enlisted between the years 1969-1983, and deaths between the years 1969 and 2009. Results suggest that both cognitive and non-cognitive abilities are strongly associated with mortality, independently and through income and education. Non-cognitive ability is a stronger predictor of the risk of mortality than cognitive ability. For middle and high income earners, and individuals with a college education, there are no associations between the abilities and mortality. However, for low income earners and individuals without a college education, cognitive and non-cognitive ability have strong associations with mortality. Results are mainly driven by the bottom of the measured ability distributions.
    Keywords: Cognitive ability; non-cognitive ability; mortality; education; income
    JEL: I12 J24
    Date: 2015–09–30
    URL: http://d.repec.org/n?u=RePEc:hhs:ifauwp:2015_021&r=all
  3. By: Acosta, Pablo A. (World Bank); Muller, Noel (World Bank); Sarzosa, Miguel (University of Maryland)
    Abstract: This paper examines the relationship between individuals' skills and labor market outcomes for the working-age population of Colombia's urban areas. Using a 2012 unique household survey, the paper finds that cognitive skills (aptitudes to perform mental tasks such as comprehension or reasoning) and socio-emotional skills (personality traits and behaviors) matter for favorable labor market outcomes in the Colombian context, although they have distinct roles. Cognitive skills are greatly associated with higher earnings and holding a formal job or a high-qualified occupation. By contrast, socio-emotional skills appear to have little direct influence on these outcomes, but play a stronger role in labor market participation. Both types of skills, especially cognitive skills, are largely associated with pursuing tertiary education. The analysis applies standard econometric techniques as a benchmark and structural estimations to correct for the measurement error of skill constructs.
    Keywords: returns to skills, cognitive skills, socio-emotional skills, personality traits, latent skills, unobserved heterogeneity, labor market outcomes, Colombia
    JEL: J24 J31 I24
    Date: 2015–10
    URL: http://d.repec.org/n?u=RePEc:iza:izadps:dp9403&r=all
  4. By: Drydakis, Nick (Anglia Ruskin University)
    Abstract: We examine the association between brain types and wages using the UK Behavioural Study dataset for the period 2011 to 2013 (four waves). By applying Empathising-Systemising Theory (E-S), the estimations suggest that, for men and women, systemising traits are associated with higher wage returns than empathising traits and that a Type-S brain (also known as a Male-brain, entailing greater skills in directing systems) is associated with higher wage rewards than a Type-E brain (also known as a Female-brain, entailing more social skills). In addition, wage decompositions suggest that systemising traits can explain greater differences in the assigned gender wage gap compared to empathising traits. Interestingly, the estimations suggest that the wage returns of empathising and systemising traits vary by occupation and that each trait might provide an absolute wage-return advantage in certain occupations. Whilst men and women in certain occupations might face positive wage rewards when they have empathising and systemising traits and work atypical of those common to their gender, it would appear that evaluating individuals' empathising, systemising and brain type is perceived to be important for employees' wage returns.
    Keywords: brain-type, empathising-systemising theory, segregation, wages, wage-gap
    JEL: J24 J31
    Date: 2015–10
    URL: http://d.repec.org/n?u=RePEc:iza:izadps:dp9426&r=all

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