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Left-handedness and economic development

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Abstract

This paper studies the interplay between left-handedness and economic development, thereby contributing to our understanding of the relationship between evolutionary forces, human diversity and growth. We propose a novel theoretical framework in which economic development influences the prevalence of left-handedness through structural change and a genetic mechanism driven by differential fertility. In particular, the emergence of the industrial sector puts left-handers at a reproductive disadvantage, because of their lower manual ability and wages. This fertility differential changes sign as soon as the income-fertility relationship is reversed, and eventually fades away when the rise of human capital makes manual skills irrelevant. Our model thus explains the decline and subsequent recovery of left-handedness observed over the last few centuries in the Western world. We further explore the possibility that left-handedness in turn influences growth: despite their lower productivity in manual tasks, left-handers may enhance technological progress through cognitive skills that are conducive to innovation, and through their contribution to the diversity of the workforce. This implies that the link between handedness and economic performance varies across stages of development. We present empirical evidence that lends credence to the core differential-fertility mechanism of our model and suggests that left-handedness can positively contribute to growth, once the economy has reached a sufficiently high level of human capital.

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Change history

  • 25 September 2022

    The original online version of this article was revised: The style, spacing and fonts in text, equations and figures were set incorrectly in the article, the stye, font and spacing issues have now been corrected.

Notes

  1. Great apes like chimpanzees and bonobos are only mildly lateralized, as observed by Hopkins et al. (2011) and Marchant and McGrew (2013), who claim that “human handedness seems to be unique among living hominoids”.

  2. Moreover, the corpus callosum, which connects the two hemispheres and regulates the speed of interhemispheric processing, is on average 11% larger among left-handed individuals (Witelson 1985). Heilman (2005) argues that a larger corpus callosum may translate into higher levels of creativity.

  3. Environmental factors, such as fetal stress in utero or at birth and prenatal exposure to testosterone, may also shape the differential brain structure of right- and left-handers (Medland et al. 2009; Vuoksimaa et al. 2009).

  4. A locus is a specific position on a chromosome where a particular gene is located.

  5. A recent study by Hermans, Ahn, and Rousseau (2020) has also detected much higher levels of the highly heritable Lipoprotein(a) in left-handed persons.

  6. In particular, Halpern, Haviland, and Killian (1998) find that left-handed students significantly outperform right-handed ones in MCAT tests, while Faurie et al. (2008) report that left-handers are over-represented among individuals holding managerial, high-level position in the French electricity and gas company EDF–GDF.

  7. Two archival studies conducted on British cricketers (Aggleton, Kentridge, and Neave 1993; Aggleton et al. 1994) find strong evidence that left-handed men were more likely to die prematurely in accidents or in action (during World War I), probably due to the use of equipment adapted to right-handers.

  8. Perhaps not coincidentally, the 18th century saw the invention of machines such as the circular saw and the power press, which still injure left-handers disproportionately today (Taras, Behrman, and Degnan 1995).

  9. Our research is also linked to papers emphasizing the role of evolutionary mechanisms in defining human outcomes, behaviors or traits with some economic relevance: see for instance Robson (2001), Horan, Bulte, and Shogren (2008), Alger and Weibull (2010). Some other studies, such as Gören (2017), take the prevalence of genetically-determined traits as exogenous, but explore their implication for economic growth.

  10. Coren and Porac (1977) provide indirect estimates based on hand use in unimanual activities, as displayed in artworks. Osteoarcheological evidence speaks of left-handedness rates in the 10–19% range between the 9th and the 16th century (Steele and Mays 1995; Cuk, Leben-Seljak, and Stefancic 2001; Kujanová et al. 2008), but is in general built on small samples.

  11. There is evidence of hand-switching practices, with left-handed pupils being forced to write with their right hand (see for instance Kushner 2012 and Guber 2019). The vertical difference between the solid and the dashed lines in Fig. 1, which measures the share of people who write with the right hand but throw with the left one, can be thought of as an approximation of the share of constrained left-handers. As it is bell-shaped, it suggests that coercion into right-handedness did participate in the U-shaped trajectory of left-writing. However, repression cannot account for the U-shaped pattern of the share of people who write and/or throw with their left hand, which is a better proxy for natural left-handedness.

  12. In particular, Ellis et al. (1998) study forced dextrality on a sample of about 6,000 respondents in Lancashire, U.K. Consistent with the NGSS data, their results point to a much lower prevalence of left-handedness among older respondents (born at the end of the 1920s) than among younger respondents (born at the end of the 1970s). They find, however, that less than 20% of this difference can be explained by forced right-hand writing.

  13. Other studies discussing (and finding no evidence of) differential mortality by handedness include Harris (1993), Salive, Guralnik, and Glynn (1993), Persson and Allebeck (1994), Steenhuis, Østbye, and Walton (2001) and Martin and Freitas (2002).

  14. For instance, casualties in WWI and WWII – as reported by Chambers (2000) – amounted to 0.11\(\%\) and 0.31\(\%\) of the U.S. population measured in 1920 and 1940, respectively. This depends on U.S. soldiers having relatively low odds of death in war: 1.1% in WWI, 1.8% in WWII and 0.6% in the Korean War (Hobbes 2004).

  15. In addition, family studies – which do not suffer from time-varying reporting bias, as the handedness of parents and children is reported by the same person – point to a similar increasing pattern for left-handedness rates in the U.S. during the 20th century (see for instance Spiegler and Yeni-Komshian 1983 or Risch and Pringle 1985).

  16. An individual characteristic that could be correlated with both left-handedness and the propensity to be a reader of the National Geographic is gender, as men are more likely to be left-handed than women (McManus 2004). However, about 55% of the NGSS respondents were women, and computing gender-weighted left-handedness rates based on the sex ratio at birth yields U-shaped patterns that are very close to those of Fig. 1.

  17. The NLSY questionnaire asks respondents whether they were born naturally left-handed, right-handed, or ambidextrous. Our narrow definition of left-handedness treats self-declared ambidextrous respondents as missing observations, while we pool them with left-handers in our inclusive definition.

  18. Historical evidence for the U.K. is collected from Ogle (1871), Mayhew (1907) as cited by Crichton-Browne (1907), Annett (1973) and Burt (1937). We further rely on two recent longitudinal surveys: the National Child Development Study (NCDS58) and the British Cohort Study (BCS70), which track people born in Great Britain in March 1958 and April 1970, respectively.

  19. In Appendix A, we report additional evidence suggesting a non-monotonic cross-country relationship between left-handedness and development.

  20. In fact, we have that \(\displaystyle \frac{\partial n_{ij,t}}{\partial w_{ij,t}}= - \frac{\gamma (1-\beta )(\theta -\tau )}{(1-\gamma )( \tau +\phi w_{ij,t} -\theta )^2}\).

  21. Whether or not a Malthusian segment characterized fertility in the U.S. at the end of the 19th century is still debated. See for instance Reher (2004), Jones and Tertilt (2006) and Baudin, de la Croix, and Gobbi (2015).

  22. In Appendix D, we develop an alternative version of the model, where the traditional sector is characterized by decreasing returns to both the number of workers and working time.

  23. Individual productivity must be observable, for workers to receive their marginal product.

  24. The idea is that there are always a few intellectual, skilled workers, even in pre-industrial societies.

  25. That handedness runs in families is a well-known fact, as explained in the Introduction. As far as monozygotic discordance is concerned, McManus and Bryden (1992) and Vuoksimaa et al. (2009), among others, have shown that 10 to 20% of monozygotic twins display different handedness. The higher degree of randomness associated with left-handedness is revealed, for instance, by the fact that only 5–6% of right-handers have right-hemisphere dominance for language, compared to 30–35% of left-handers (McManus 2009). In addition, Hepper, Wells, and Lynch (2005) have found that all right-hand thumb-sucking fetuses remain right-handers postnatally, while 34% of left-hand thumb-sucking fetuses become right-handers.

  26. In our model, like in Moav (2005), heterogeneity among agents implies that in each period, different subgroups might be at different stages of the demographic transition, so that Malthusian behavior can subsist in the modern regime and vice versa.

  27. As long as there is no investment in education, we have the same share of left-handers among skilled and unskilled workers, so if unskilled left-handers are poorer, left-handers have a lower fertility rate on average. When people start investing in education and the income-fertility relationship is eventually reversed, left-handers – if poorer – are over-represented among the unskilled, who also have the highest fertility rate. Therefore, in the post-Malthusian regime left-handers have higher fertility on average, because (i) they are under-represented in the lowest-fertility group (the skilled), and (ii) unskilled left-handers have more children than unskilled right-handers, because they are less productive.

  28. Notice that, for simplicity, the conditions defining regions within stage (1) and (3) are expressed in terms of \(P_{U}\) and \(P_{LU}\). In the model however, there is a one-to-one mapping from these variables to P, which is the variable in the y axis in Fig. 5, for given \(\lambda \) and \(x_i\). It can indeed be proven that

    $$\begin{aligned}P_t=\frac{P_{U,t}}{1-x_{L,t}\lambda _t-x_{R,t}\left( 1-\lambda _t\right) }=\frac{P_{LU,t}}{\left( 1-x_{L,t}\right) \lambda _t}. \end{aligned}$$
  29. If all agents are skilled, some of them must end up in the traditional sector – as marginal productivity in that sector tends to infinity, when employment tends to zero.

  30. This (sufficient) condition is obtained by imposing that minimum fertility, in both the Malthusian and modern regimes, must not be lower than 1.

  31. One may also ask how the initially stationary rate of left-handedness is reached, before the perturbation brought about by industrialization, and why it is not equal to 50%. Although this goes beyond the scope of our model, a possible explanation – based on a frequency-dependent selection mechanism leading to stable polymorphism in the long-run – is provided in Appendix F (see also Billiard, Faurie, and Raymond 2005).

  32. In the literature, the parameter \(\alpha \) is typically calibrated making reference to the rent share of output. In our model, as in Lagerlöf (2006), workers in the traditional sector earn the average product of labor, so that rents are, so to speak, redistributed to the workers.

  33. The values for \(\beta \) and \(\gamma \) are chosen to set a reasonable upper bound for Malthusian fertility, and the limit behavior of post-Malthusian fertility. In practice, we proceed as follows. We compute the \(\lim _{w_{ij,t}\rightarrow \infty }n_{ij,t}\) for both the corner and interior solutions in Eq. (8). We thus obtain \(\overline{n}=\gamma /(\phi (1+\gamma ))\) and \(\underline{n}=(1-\beta )\gamma /((1+\gamma )\phi )\). \(\overline{n}\) is a hypothetical upper bound to fertility under the Malthusian regime, should the demographic transition never occur. Relying on the literature, we estimate \(\overline{n}=5\), i.e. midway between Clark and Hamilton (2006) (according to whom the richest married testators in England between 1535 and 1628 left 4 to 5 surviving kids, so that \(\overline{n}=2.5\)) and Pensieroso and Sommacal (2019) (who suggest \(\overline{n}=7.5\), by looking at children-ever-born for women aged more than 64 from the U.S. census data, 1900-1990). Given that \(\phi =0.075\), we thus obtain \(\gamma =0.6\). We set \(\underline{n}\) equal to 1, so that population in the post-Malthusian regime is stationary in the long run. Given the chosen values of \(\phi \) and \(\gamma \), from \(\underline{n}=1\) we can residually determine \(\beta = 0.8\), which lies in the range generally accepted by the literature.

  34. Our parametrization has an illustrative purpose and is not meant to gauge the quantitative importance of the genetic mechanism relative to alternative or complementary drivers of left-handedness.

  35. In Galor and Michalopoulos (2012), the frequency of genetically determined traits can also significantly change over (relatively) short periods of time. In that paper, although the selection of entrepreneurial traits may have taken the whole Malthusian epoch, the recovery of risk-averse traits is a recent feature of mature economies.

  36. In Appendix G, we use the NLSY data to show that the distribution of wages for individuals with more than 16 years of education favors left-handers.

  37. A further similarity with Galor and Michalopoulos (2012) is that economic development implies a non-monotonic evolution of the trait under study over the course of human history.

  38. This formulation may also reflect the disruption or lack of coordination induced by the presence of left-handers in production, which can hamper the learning-by-doing process.

  39. By replacing \(a \lambda _{t}\) with \(a\lambda _{t}(1-\lambda _{t})\) in Eq. (48), we could bring our modelization even closer to Ashraf and Galor (2012, 2013), and identify a growth-maximizing left-handedness rate. By replacing \(a \lambda _{t}\) with \(a x_{L,t}\lambda _{t}\), one may instead introduce the realistic feature that only educated left-handers contribute positively to technological progress. None of these alternatives, however, would change the main implications of our analysis, namely that the correlation between left-handedness and growth changes across stages of development.

  40. More precisely, the growth rate of GDP per capita in both models increases substantially as structural change emerges. However, in early periods, the low productivity of left-handers in the modern sector hampers growth, and delays the accumulation of human capital, while the dynamics of the population under the Malthusian regime takes away some of the benefits of the additional growth. As soon as the demographic transition unfolds, the left-handedness rate stops decreasing, while the disruptive effect of left-handers on productivity becomes less and less important, since human capital accumulates and the average wage gap shrinks. The growth rate of GDP per capita increases in both models. When the share of skilled agents in the population is sufficiently high, the contribution of human capital accumulation to the growth rate of GDP becomes less and less important, and the latter converges asymptotically to its stationary value.

  41. The countries in the sample are: Austria, Belgium, Denmark, France, Germany, Greece, Israel, Italy, the Netherlands, Spain, Sweden, and Switzerland.

  42. This pattern is robust to regressions without controls, and to alternative cutoff years. As shown in Appendix H, setting the cutoff to 1922 provides the most precise estimate.

  43. In Appendix I, we show that our results are robust to alternative definitions of the age group used to compute the prevalence of left-handedness.

  44. Output per worker is also used by other papers concerned, like ours, with the growth effects of specific factors – such as financial development and liberalization (Henry 2003; Jerzmanowski 2017) and health (Bloom, Canning, and Sevilla 2004).

  45. This concern is further assuaged when we consider shorter age brackets, as in Table I.1 of Appendix I.

  46. Ager and Brueckner (2018) find that a one s.d. increase in immigrants’ genetic diversity in 1870 translates into a 20% higher growth rate over the 1870-1920 period, which corresponds to around 0.2 s.d. and to +0.37% per annum. In our case, a one s.d. increase in the 1990 left-handedness rate is associated with a 2.6% higher growth rate over the following decade, which corresponds to around 0.4 s.d. and to +0.26% per annum.

  47. In 1980, 10 states still exhibited an average level of education lower than the threshold (Alabama, Arkansas, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, West Virginia).

  48. Using alternative age groups to measure left-handedness yields similar results.

  49. Left-handedness prevalence in the previous generation is a good predictor of left-handedness prevalence in the current one. Specifically, the first-stage coefficient of interest is equal to 0.767, with a p-value lower than 1% and, as shown in Table 5, the first-stage F-test is well above the rule-of-thumb critical value of 10.

  50. All these papers take advantage of panel data to study the empirical relevance of possible growth-enhancing factors, and use growth regressions very similar to our Eq. (51).

  51. In columns (2) and (3), we use the second to fifth lags (both in differences and in levels) as instruments. In column (4), we use the second to fourth lags. Using the second to fifth lags yields very similar results but generates 63 instruments, which is relatively high given the standard rule of thumb that the number of instruments should not exceed the number of cross-sectional units (Roodman 2009). In all specifications, we apply the two-step procedure which corrects for a nontrivial covariance matrix, the small-sample adjustments, and the Windmeijer (2005) correction of downward-biased standard errors in finite samples. The usual GMM validity tests, such as the Hansen test for the joint validity of the instruments and the Arellano-Bond first- and second-order residual autocorrelation tests, are satisfactory. In addition, the difference-in-Hansen tests for the validity of instrument subsets confirm that the stationarity restrictions on initial conditions required for the validity of sGMM are satisfied (see Roodman 2009).

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Acknowledgements

We acknowledge the financial support of the Belgian French-speaking community (ARC project 15/19-063 on “Family Transformations”). We thank Ingela Alger, Matteo Cervellati, Bastien Chabé-Ferret, David de la Croix, Klaus Desmet, Matthias Doepke, James Fenske, Cecilia Garcia Peñalosa, Sudhanshu Handa, Mariko Klasing, Justin Johnson Kakeu, Petros Milionis, Romain Wacziarg, as well as participants to the workshop on “The importance of elites and their demography for knowledge and development” in Louvain-la-Neuve, the PET conference in Rio de Janeiro, the ARC workshop in Durbuy, the 5th Toulouse Economics and Biology Workshop, the WEAI and SEHO conferences in San Diego, the ASSET meeting in Florence, the CREA workshop on “Culture and Comparative Development” in Luxembourg, the workshop on “Deep-rooted Factors in Comparative Development” in Brown, and seminar participants at AMSE, the University of Bonn and the University of Paris Nanterre for their comments. The Editor of this Journal, Oded Galor, and two anonymous referees provided several suggestions that helped us improve the paper. We would also like to express our gratitude to Michal Jerzmanowski for sharing his U.S. data with us, and Gilbert Wysocki, who gave us access to the National Geographic’s “Smell Survey” data.

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Mariani, F., Mercier, M. & Pensieroso, L. Left-handedness and economic development. J Econ Growth 28, 79–123 (2023). https://doi.org/10.1007/s10887-022-09212-6

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