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Psychological origins of the Industrial Revolution

Published online by Cambridge University Press:  11 April 2018

Nicolas Baumard*
Affiliation:
Institut Jean Nicod, Département d'Etudes Cognitives, ENS, EHESS, CNRS, PSL Research University, 75005 Paris, France. nbaumard@gmail.comhttps://nicolasbaumards.org

Abstract

Since the Industrial Revolution, human societies have experienced high and sustained rates of economic growth. Recent explanations of this sudden and massive change in economic history have held that modern growth results from an acceleration of innovation. But it is unclear why the rate of innovation drastically accelerated in England in the eighteenth century. An important factor might be the alteration of individual preferences with regard to innovation resulting from the unprecedented living standards of the English during that period, for two reasons. First, recent developments in economic history challenge the standard Malthusian view according to which living standards were stagnant until the Industrial Revolution. Pre-industrial England enjoyed a level of affluence that was unprecedented in history. Second, behavioral sciences have demonstrated that the human brain is designed to respond adaptively to variations in resources in the local environment. In particular, Life History Theory, a branch of evolutionary biology, suggests that a more favorable environment (high resources, low mortality) should trigger the expression of future-oriented preferences. In this paper, I argue that some of these psychological traits – a lower level of time discounting, a higher level of optimism, decreased materialistic orientation, and a higher level of trust in others – are likely to increase the rate of innovation. I review the evidence regarding the impact of affluence on preferences in contemporary as well as past populations, and conclude that the impact of affluence on neurocognitive systems may partly explain the modern acceleration of technological innovations and the associated economic growth.

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Copyright © Cambridge University Press 2019 

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