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Minimum working age and the gender mortality gap


In 1980, a few years after its democratization process, Spain raised the minimum working age from 14 to 16, while the compulsory education age remained at 14. This reform changed the within-cohort incentives to remain in the educational system. We use a difference-in-differences approach, where our treated and control individuals only differ in their month of birth, to analyze the gender asymmetries in mortality generated by this change. The reform decreased mortality at ages 14–29 among men by 6.4% and women by 8.9%, mainly from a reduction in deaths due to traffic accidents. However, the reform also increased mortality for women ages 30–45 by 7%. This is driven by increases in HIV mortality, as well as by diseases related to the nervous and circulatory systems. We show that women’s health habits deteriorated as a consequence of the reform, while this was not the case for men. The gender differences in the impact of the reform on smoking and drinking should be understood in the context of the gender equalization process that affected women were experiencing when the reform took place. All in all, these patterns help explain the narrowing age gap in life expectancy between women and men in many developed countries while, at the same time, they provide important policy implications for middle-income countries that are undergoing those gender equalization processes right now.

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These figures show the tobacco and alcohol consumption of women and men born between 1944 and 1964 observed in 2009 by level of education. Source: European Survey of Health in Spain (2009)

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  1. Biologically, women are more likely to suffer from acute illness and nonfatal chronic conditions (arthritis, constipation, thyroid conditions, gall bladder conditions, headaches, and migraines), while men are more likely to suffer from life-threatening chronic diseases (coronary heart disease, cancers, cerebrovascular disease, emphysema, liver cirrhosis, and kidney disease) (Bird and Rieker 1999; Case and Paxson 2005). Hormonal, autoimmune, and genetic factors can explain these gender differences (Oksuzyan et al. 2008; Schünemann et al. 2018).

  2. Women also used to eat better (Wardle et al. 2004) and use health care services more often than men (Sindelar 1982; Schünemann et al. 2018).

  3. In the Spanish educational system, all children from the same cohort start school the same year. Consequently, children born at the beginning of the year turn 14 during the final year of primary education, while those born at the end of the year are still 13 years old.

  4. The literature has shown that AIDS (De Olalla García et al. 1999; Gómez-Redondo and Boe 2005), drugs and alcohol abuse (Ribes et al. 2004), and fatal traffic injuries (Saiz-Sánchez et al. 1999; Gine 1992; Puig et al. 1983; Gómez-Redondo and Boe 2005; Serra et al. 2006) all peaked during the late 1970s and early 1980s, especially for young cohorts.

  5. Lleras-Muney (2002) and Goldin and Katz (2011) examine the effects that compulsory schooling and child labor laws from 1910 to 1939 have on educational attainment in the USA. While Lleras-Muney (2002) finds that legislation increased the educational attainment of individuals at the lowest percentile in the distribution of education, Goldin and Katz (2011) report that the reform has only a positive but modest impact on secondary schooling rates. Edmonds and Shrestha (2012) analyze the effect of a statutory minimum school-leaving age on child labor and schooling in 59 mostly low-income countries. However, they find that minimum age regulations are barely enforced in such countries. It is important to note that child labor in low-income countries might be vital for family subsistence. If this is the case, child labor regulations might simply divert children from formal jobs to informal jobs, without reducing their rate of employment.

  6. On the one hand, Lleras-Muney (2005) for the USA, Oreopoulos (2006), for the UK, and Kippersluis et al. (2011) for the Netherlands find that educational attainment has a strong positive impact on mortality rates. Nevertheless, Clark and Royer (2013) using two compulsory schooling reforms in the UK do not find any significant effect of education on such rates. Meghir et al. (2018) and Albouy and Lequien (2009) do not find any causal impact of schooling on mortality rates either in Sweden or in France, respectively.

  7. Oreopoulos (2006) examines two changes in the school leaving age that were enacted in the UK in 1947 and 1957. Clark and Royer (2013) have also explored the UK reform of 1947 and a further reform in 1972. Lleras-Muney (2005) has analyzed two reforms in the USA in 1915 and 1939. Meghir et al. (2018) has estimated the 1-year increase in the length of compulsory schooling that was enacted in Sweden between 1949 and 1962. Finally, Albouy and Lequien (2009) have analyzed two reforms in France in 1923 and 1953.

  8. For more information on this database, please go to the Data Appendix that you can find in our working paper (

  9. Results are mostly robust when comparing individuals born between January and July with individuals born between August and December. Please see Tables 3 and 4, and Tables A10, A11, A12 and A13 in our working paper (that can be found

  10. In Section 4.1, we relax the assumption that the 1964 and 1965 cohorts were not affected at all by the reform.

  11. These results are available upon request.

  12. In Fig. 11, we replicate our main results for the short-term and medium-term effects using different age brackets.

  13. Figure 10 in the Appendix shows the same graphs but for men’s and women’s mortality rate by cause of death.

  14. Note that the pre-reform mortality rate for young individuals differs significantly between genders. There is a mortality rate of 1.1 per 1000 men (aged 14–29) before the reform, while the same rate for women of the same age is 0.39 per 1000 women.

  15. This estimate remains significant even when controlling for the false discovery rate (FDR).

  16. This classification includes deaths due to traffic accidents, other accidents (accidental falls, drowning, accidents with fire, or accidental poisoning), suicide, homicide, surgical and medical complications, and other types of external causes of mortality.

  17. This classification includes deaths due to malignant tumors located in different parts of the body.

  18. This classification includes deaths due to chronic rheumatic heart diseases, ischemic diseases, acute myocardial infarction, heart failure, other heart diseases, influenza, pneumonia, asthma, respiratory insufficiency, and other respiratory diseases.

  19. This classification includes deaths due to infectious intestinal diseases, tuberculosis, meningococcal disease, viral hepatitis, AIDS and HIV, and other infectious diseases.

  20. This classification includes deaths due to meningitis, Alzheimer’s, stomach ulcer, enteritis, non-infectious colitis, and intestinal vascular diseases.

  21. This classification includes deaths due to a heart attack or other abnormal clinical and laboratory symptoms.

  22. This classification includes deaths due to other causes that have not been mentioned above.

  23. Tables 5 and 6 in the Appendix report the corresponding detailed regression results.

  24. Table 9 in the Appendix reports the corresponding detailed regression results.

  25. Table 7 in the Appendix reports the corresponding detailed regression results.

  26. We can also observe that the reform decreased mortality due to abnormal clinical and laboratory symptoms. However, this effect is minimal (one-fifth of the effect on external causes).

  27. Table 10 in the Appendix reports the corresponding detailed regression results.

  28. Table 8 in the Appendix reports the corresponding detailed regression results.

  29. Table 11 in the Appendix reports the corresponding detailed regression results.

  30. In particular, the reform increased deaths due to HIV or AIDS by 13.3% and other types of infections doubled. However, when we control for multiple hypothesis testing, the effect on HIV or AIDS is no longer statistically significant.

  31. The effect of the reform on influenza is no longer statistically significant when we control for multiple hypothesis testing.

  32. For more information on this database, please go to the Data Appendix that you can find in our working paper (

  33. For more information on this database, please go to the Data Appendix that you can find in our working paper (


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The authors thank editor Shuaizhang Feng and two anonymous reviewers for helpful comments. Previously circulated as “The Effects of a Child Labor Law on Mortality,” “Education and Gender Differences in Mortality Rates,” and “Unintended Health Costs of Gender Equalization”.


Jiménez-Martín received financial support from the Spanish Ministry of Economy and Competitiveness, through the Severo Ochoa Programme for Centres of Excellence in R&D (SEV-2015-0563), and Bellés-Obrero from the German Research Foundation (DFG) through CRC TR 224 (Project A02), and the project ECO2017-82350-R.

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Correspondence to Cristina Bellés-Obrero.

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Table 5 Effect of the reform on the mortality rate by cause of death among men aged 14 to 29
Table 6 Effect of the reform on the mortality rate by cause of death among men aged 30 to 45
Table 7 Effect of the reform on the mortality rate by cause of death among women aged 14 to 29
Table 8 Effect of the reform on the mortality rate by cause of death among women aged 30 to 45
Table 9 Effect of the reform on the mortality rate among men aged 14–29 due to external causes
Table 10 Effect of the reform on the mortality rate among women aged 14–29 due to external causes
Table 11 Effect of the reform on the mortality rate among women aged 30–45 due to infectious and parasitic diseases or circulatory and respiratory system diseases
Fig. 10
figure 10

Gender-specific mortality rates by cohort. The dots and triangles represent the average mortality rate of men/women in each cohort, 1961–1971, due to that specific cause of death. The lines are the linear predictions from Regression 1. Source: Mortality Registries (1975–2018), all men and women from cohorts 1961–1965 and 1967–1971

Table 12 Effect of the reform on men’s risky behaviors
Fig. 11
figure 11

Robustness: Gender-specific mortality rates with different age brackets. This figure shows the impact of the reform on the mortality rate of a men aged 14 to the age indicated in the x-axis, b men between the age indicated in the x-axis and 45 years old, c women aged 14 to the age indicated in the x-axis, and d women between the age indicated in the x-axis and 45 years old. The graphs report the point estimates and the 95% confidence interval of the interaction term (Treated* Post Reform) from Regression 1. The dependent variables are the mortality rate (number of men/women that died divided by the total number of men/women born in each cohort and treatment) of men or women in the age bracket that is indicated. All dependent variables are multiplied by 1000. Source: Mortality Registries (1975–2018), all men and women from cohorts 1961–1965 and 1967–1971

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Bellés-Obrero, C., Jiménez-Martín, S. & Castello, J.V. Minimum working age and the gender mortality gap. J Popul Econ 35, 1897–1938 (2022).

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  • Minimum working age
  • Education
  • Mortality
  • Gender equalization

JEL Classification

  • I12
  • I20
  • J10