Nicolas Baumard explains the origins of the Industrial Revolution on the basis of Life History Theory (LHT). As presented by Baumard, LHT makes two important predictions. First, the relationship between wealth and the rate of innovation is monotonously positive and probably exponential (because wealth gives rise to innovations that further increase the wealth of the population). Second, there is a uniform relation between affluence, innovation rate, quality of life, prosocial behavior, optimism, long-term investments (e.g., education), social trust, and several other variables, all being negatively correlated with violence and materialist views.
I agree that both predictions may be perfectly true for some populations or some epochs of human development, but they are false in general. Counterevidence can be found even in the target article itself. Thus, optimism and open-mindedness tend to decrease in contemporary Western society despite its affluence (sect. 6.1). Ironically, Baumard uses this fact to argue against “cognitive” explanations of the Industrial Revolution without noticing that they work even harder against his own explanation. The supposed negative correlation between affluence and materialism (sect. 5.4) implies that the richest people do not even want to be rich.
Every nonmonotonous function contains monotonous segments; when we look at one of such segments, we can believe we are observing a monotonous function. This is what LHT does. The prediction of monotonicity can be questioned in several ways. In many societies the largest cultural achievements have been realized by the second-wealthiest social group but not by the wealthiest one. As Baumard rightly notices, most inventions and discoveries were made by representatives of the wealthy middle class – but much less by people from the high class. To my knowledge, only 1.5% of Nobel Laureates in the natural sciences were of noble origin, although very many of them received nobility on account of their scientific achievements.
An obvious nonmonotonous factor is urbanization. At the transition from pre-industrial to industrial society, the growth of towns was accompanied by increasing morality and decreasing violence; now, however, large cities are characterized by rates of crime and violence that dramatically increase with city size. Another intervening variable may be maternal care. In present-day affluent societies, more women realize their human potential in their jobs. On the other hand, maternal absence (calculated as the percentage of mothers who regularly work) is positively related to the rate of murder (e.g., Huang Reference Huang1995).
The relationship between wealth and subjective well-being (or “happiness”), albeit monotonously positive, does not fully agree with LHT predictions. Within the upper income range, further increases in income result in ever smaller increments of happiness; the function demonstrates a curvilinear trend with a tendency to saturation (e.g., Diener et al. Reference Diener, Sadndvik, Seidlitz and Diener1993).
Baumard rightly argues that affluence may have given rise to Protestant Work Ethics (PWE: sect. 6.1), but it can also cause three other kinds of ethics: Wealth Ethics, which does not correlate with PWE, and Leisure Ethics and Welfare Ethics, which are negatively related to PWE (Furnham & Rose Reference Furnham and Rose1987). In a similar vein, Adler (Reference Adler1997) indicated that economic growth can result in a “doing-oriented” culture (which facilitates innovations), but also in a “being-oriented” culture (which hampers innovations). The same society can be doing-oriented at a certain step of its economic development but became being-oriented at a later step.
Halpern (Reference Halpern2001) showed that antisocial morality contains two different factors, called “self-interest” antisociality (e.g., tolerance to cheating on tax, to keeping money found, to self-interest lying) and “illegal” antisociality (e.g., tolerance to driving under alcohol, littering, political assassinations). Only the former factor significantly correlated with the national crime rate and with behavioral variables predicting the crime rate (young age, male gender, city size); the latter did not. Both factors did not correlate with income, and the correlations of the “self-interest” antisocial factor with social trust and education level were significant but very low (–.08 and .04, respectively). These data clearly contradict LHT's predicting that prosocial behavior (both factors), high income, high education, high social trust, and low crime rate all should go hand-in-hand. This prediction of uniform relationship is further in conflict with the data of Tang and Koveos (Reference Tang and Koveos2004), who showed that innovation entrepreneurship is differently related to economic growth rate in high-, middle-, and low-income countries.
The societal predictors of innovation rate appear to be much less simple than Baumard suggests on the basis of LHT. Dakhli and De Clercq (Reference Dakhli and De Clercq2003) performed a large-scale investigation of three innovation indices (number of patents, research and development [R&D] investments, high-tech exports) as functions of human capital (i.e., skills), social trust, cooperation, country size, income gap, and norms of prosocial behavior (the same items as in the two factors of Halpern, see above). First, social trust was not a single variable; rather, trust in one's fellows (generalized trust) did not correlate with trust in social institutions. Generalized trust had a positive impact on R&D expenditures but not on high-tech exports, whereas the opposite was true for institutional trust. In agreement with LHT, all innovation indices were robustly related to human capital. In strong contrast to LHT, however, high-tech exports were negatively related to prosocial behavior (standardized β = –.51, p < .001). To explain this finding, the authors question the monotonicity assumption. They suggest that moderate prosocial behavior might facilitate innovative activity, but too much of it is related to social conformity. Strong innovations can require the ability to violate norms.
To summarize, I admit that LHT can explain a lot about what happened in Northern Europe in the eighteenth century, but attempts to generalize the explanation result in inconsistencies. According to an old joke, the shape of a cow can, in a first approximation, be regarded as a simple sphere. However, by the next step, we see that her tail, ears, and hooves do not fit into the oversimplified theoretical framework. A good theory is not one that meets many confirming cases but, rather, one that does not meet any disconfirming case (Popper Reference Popper1963). Therefore, LHT is not a good theory.
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Nicolas Baumard explains the origins of the Industrial Revolution on the basis of Life History Theory (LHT). As presented by Baumard, LHT makes two important predictions. First, the relationship between wealth and the rate of innovation is monotonously positive and probably exponential (because wealth gives rise to innovations that further increase the wealth of the population). Second, there is a uniform relation between affluence, innovation rate, quality of life, prosocial behavior, optimism, long-term investments (e.g., education), social trust, and several other variables, all being negatively correlated with violence and materialist views.
I agree that both predictions may be perfectly true for some populations or some epochs of human development, but they are false in general. Counterevidence can be found even in the target article itself. Thus, optimism and open-mindedness tend to decrease in contemporary Western society despite its affluence (sect. 6.1). Ironically, Baumard uses this fact to argue against “cognitive” explanations of the Industrial Revolution without noticing that they work even harder against his own explanation. The supposed negative correlation between affluence and materialism (sect. 5.4) implies that the richest people do not even want to be rich.
Every nonmonotonous function contains monotonous segments; when we look at one of such segments, we can believe we are observing a monotonous function. This is what LHT does. The prediction of monotonicity can be questioned in several ways. In many societies the largest cultural achievements have been realized by the second-wealthiest social group but not by the wealthiest one. As Baumard rightly notices, most inventions and discoveries were made by representatives of the wealthy middle class – but much less by people from the high class. To my knowledge, only 1.5% of Nobel Laureates in the natural sciences were of noble origin, although very many of them received nobility on account of their scientific achievements.
An obvious nonmonotonous factor is urbanization. At the transition from pre-industrial to industrial society, the growth of towns was accompanied by increasing morality and decreasing violence; now, however, large cities are characterized by rates of crime and violence that dramatically increase with city size. Another intervening variable may be maternal care. In present-day affluent societies, more women realize their human potential in their jobs. On the other hand, maternal absence (calculated as the percentage of mothers who regularly work) is positively related to the rate of murder (e.g., Huang Reference Huang1995).
The relationship between wealth and subjective well-being (or “happiness”), albeit monotonously positive, does not fully agree with LHT predictions. Within the upper income range, further increases in income result in ever smaller increments of happiness; the function demonstrates a curvilinear trend with a tendency to saturation (e.g., Diener et al. Reference Diener, Sadndvik, Seidlitz and Diener1993).
Baumard rightly argues that affluence may have given rise to Protestant Work Ethics (PWE: sect. 6.1), but it can also cause three other kinds of ethics: Wealth Ethics, which does not correlate with PWE, and Leisure Ethics and Welfare Ethics, which are negatively related to PWE (Furnham & Rose Reference Furnham and Rose1987). In a similar vein, Adler (Reference Adler1997) indicated that economic growth can result in a “doing-oriented” culture (which facilitates innovations), but also in a “being-oriented” culture (which hampers innovations). The same society can be doing-oriented at a certain step of its economic development but became being-oriented at a later step.
Halpern (Reference Halpern2001) showed that antisocial morality contains two different factors, called “self-interest” antisociality (e.g., tolerance to cheating on tax, to keeping money found, to self-interest lying) and “illegal” antisociality (e.g., tolerance to driving under alcohol, littering, political assassinations). Only the former factor significantly correlated with the national crime rate and with behavioral variables predicting the crime rate (young age, male gender, city size); the latter did not. Both factors did not correlate with income, and the correlations of the “self-interest” antisocial factor with social trust and education level were significant but very low (–.08 and .04, respectively). These data clearly contradict LHT's predicting that prosocial behavior (both factors), high income, high education, high social trust, and low crime rate all should go hand-in-hand. This prediction of uniform relationship is further in conflict with the data of Tang and Koveos (Reference Tang and Koveos2004), who showed that innovation entrepreneurship is differently related to economic growth rate in high-, middle-, and low-income countries.
The societal predictors of innovation rate appear to be much less simple than Baumard suggests on the basis of LHT. Dakhli and De Clercq (Reference Dakhli and De Clercq2003) performed a large-scale investigation of three innovation indices (number of patents, research and development [R&D] investments, high-tech exports) as functions of human capital (i.e., skills), social trust, cooperation, country size, income gap, and norms of prosocial behavior (the same items as in the two factors of Halpern, see above). First, social trust was not a single variable; rather, trust in one's fellows (generalized trust) did not correlate with trust in social institutions. Generalized trust had a positive impact on R&D expenditures but not on high-tech exports, whereas the opposite was true for institutional trust. In agreement with LHT, all innovation indices were robustly related to human capital. In strong contrast to LHT, however, high-tech exports were negatively related to prosocial behavior (standardized β = –.51, p < .001). To explain this finding, the authors question the monotonicity assumption. They suggest that moderate prosocial behavior might facilitate innovative activity, but too much of it is related to social conformity. Strong innovations can require the ability to violate norms.
To summarize, I admit that LHT can explain a lot about what happened in Northern Europe in the eighteenth century, but attempts to generalize the explanation result in inconsistencies. According to an old joke, the shape of a cow can, in a first approximation, be regarded as a simple sphere. However, by the next step, we see that her tail, ears, and hooves do not fit into the oversimplified theoretical framework. A good theory is not one that meets many confirming cases but, rather, one that does not meet any disconfirming case (Popper Reference Popper1963). Therefore, LHT is not a good theory.