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Research ArticleArticles
Open Access

Too Many Men, Too-Short Lives

The Effect of the Male-Biased Sex Ratio on Mortality

View ORCID ProfileSimon Chang, View ORCID ProfileKamhon Kan and View ORCID ProfileXiaobo Zhang
Journal of Human Resources, March 2024, 59 (2) 604-626; DOI: https://doi.org/10.3368/jhr.0420-10845R3
Simon Chang
Simon Chang is a senior lecturer at the University of Western Australia, a research fellow at Institute of Labor Economics (IZA) and a fellow at Global Labor Organization (GLO).
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Kamhon Kan
Kamhon Kan is a research fellow at the Institute of Economics, Academia Sinica.
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Xiaobo Zhang
Xiaobo Zhang is a chair professor at Guanghua School of Management at Peking University and senior research fellow at the International Food Policy Research Institute (IFPRI) ().
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  • For correspondence: [email protected]
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    Figure 1

    National Age-Specific Sex Ratios by Birth Cohort

    Notes: The sex ratio at ages 30 and 35 is the ratio of men to women who were 25–34 and 30–39 when each cohort reached age 30 and 35, respectively.

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    Figure 2

    Age-Specific Sex Ratios by County

    Notes: The figure shows age-specific sex ratios in each county, averaged across birth cohorts 1931–1950. The sex ratio at ages 30 and 35 is the ratio of men to women who were 25–34 and 30–39 when each cohort reached age 30 and 35, respectively. Each age-specific sex ratio is divided into four quarters, with darker shades indicating counties with higher sex ratios. For age 30: first quarter: <1.07; second quarter: 1.07∼1.12; third quarter: 1.12∼1.14; fourth quarter: >1.14. For age 35, the cutoff points are the following: first quarter: <1.02; second quarter: 1.02∼1.11; third quarter: 1.11∼1.15; fourth quarter: >1.15.

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    Figure 3

    Trend in Mortality Rate at Ages 50–64 by Sex and Cohort

    Notes: The authors’ calculation is based on the national death registry maintained by the Ministry of Health and Welfare.

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    Figure 4

    Ordinary Least Squares Estimates of the Sex-Ratio Effect on Age-Specific Mortality Rates

    Notes: The dependent variables are mortality rates at ages 50–54 (Panel A), 55–59 (Panel B), 60–64 (Panel C), and 50–64 (Panel D). Point estimates with 95 percent confidence intervals are shown. Robust standard errors clustered at the county have been used to construct the confidence interval. Circles and crosses indicate point estimates for men and women, respectively. All estimates have been obtained from separate regressions. The sex ratio at ages 30 and 35 is the ratio of men to women who were 25–34 and 30–39 when each cohort turned 30 and 35, respectively. All regressions additionally control for log of prime-age (20–64) men, industry male ratio, share of risky jobs at each county at the corresponding age, and a full set of county and birth cohort dummy variables. The sample includes birth cohorts between 1931 and 1950 across 20 counties. See Online Appendix Table A1 for estimation details.

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    Figure 5

    Two-Stage Least Squares Estimates of the Sex-Ratio Effect on Age-Specific Mortality Rates

    Notes: The dependent variables are mortality rates at ages 50–54 (Panel A), 55–59 (Panel B), 60–64 (Panel C), and 50–64 (Panel D). Point estimates with 95 percent confidence intervals are shown. Robust standard errors clustered at the county have been used to construct the confidence intervals. Circles and crosses indicate point estimates for men and women, respectively. All estimates have been obtained from separate regressions. The sex ratio at age 30 and 35 is the ratio of men to women who were 25–34 and 30–39 when each cohort turned 30 and 35, respectively. The instrumental variable is the log of mainland Chinese men interacted with the gender differential in the estimated global mortality rate at age 20 when each cohort reached age 20. All regressions additionally control for the log of prime-age (20–64) men, industry male ratio, share of risky jobs at each county at the corresponding age, and a full set of county and birth cohort dummy variables. The sample includes birth cohorts between 1931 and 1950 across 20 counties. See Online Appendix Table A1 for estimation details. Mortality rates and sex ratios are the authors’ own imputations. The data relating to mainland Chinese men were drawn from the 1956 Population and Housing Census. Gender differentials in mortality were obtained from various abridged life tables published by the Ministry of the Interior in Taiwan.

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    Figure 6

    Estimates of the Mortality Effect Using Sex Ratios with a Wide Age Range (15–49).

    Notes: Dependent variables are mortality rates at ages 50–54, 55–59, 60–64, and 50–64. Point estimates with 95 percent confidence intervals are shown. Robust standard errors clustered at the county have been used to construct the confidence intervals. Circles and crosses indicate point estimates for men and women, respectively. All estimates have been obtained from separate regressions. The sex ratio at ages 30 and 35 is the ratio of men to women who were 15–49 when each cohort turned 30 and 35, respectively. In Panels E, F, G, and H, the instrumental variable is the log of mainland Chinese men interacted with the gender differential in the estimated global mortality rate at age 20 when each cohort turned 20. All regressions additionally control for the log of prime-age (20–64) men, industry male ratio, share of risky jobs at each county at the corresponding age, and a full set of county and birth cohort dummy variables. The sample includes birth cohorts between 1931 and 1950 across 20 counties. See Online Appendix Table A4 for estimation details. Mortality rates and sex ratios are the authors’ own imputations. The data relating to mainland Chinese men were drawn from the 1956 Population and Housing Census. Gender differentials in mortality were obtained from various abridged life tables published by the Ministry of the Interior in Taiwan.

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    Figure 7

    Ordinary Least Squares Estimates of the Sex-Ratio Effect on Other Health Outcomes

    Notes: The Center for Epidemiologic Studies Depression Scale (CES-D) measures depression with a score ranging from 0 (low depression) to 30 (high depression). All other dependent variables are dummy variables indicating whether a person has the respective medical condition. Point estimates with 95 percent confidence intervals are shown. Robust standard errors clustered at the county have been used to construct the confidence intervals. Circles and crosses indicate point estimates for men and women, respectively. All estimates have been obtained from separate regressions. The sex ratio at ages 30 and 35 is the ratio of men to women who were 25–34 and 30–39 when each cohort turned 30 and 35, respectively. All regressions additionally control for age, age squared, log of prime-age (20–64) men, industry male ratio, share of risky jobs at each county at the corresponding age, a full set of county and birth cohort dummy variables, and a dummy variable indicating the sample drawn in 2003. The sample includes birth cohorts born between 1929 and 1953 across 20 counties. See Online Appendix Table A5 for the estimation details. Health outcome data were drawn from the Health and Living Status of the Middle-Aged and Elderly Survey conducted in Taiwan in 1996 and 2003. Sex ratios are the authors’ own imputations. Gender differentials in mortality were obtained from various abridged life tables published by the Ministry of the Interior in Taiwan.

  • Figure 8
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    Figure 8

    Two-Stage Least Squares Estimates of the Sex-Ratio Effect on Other Health Outcomes

    Notes: The CES-D measures depression with a score ranging from 0 (low depression) to 30 (high depression). All other dependent variables are dummy variables indicating whether a person has the respective medical condition. Point estimates with 95 percent confidence intervals are shown. Robust standard errors clustered at the county have been used to construct the confidence intervals. Circles and crosses indicate point estimates for men and women, respectively. The instrumental variable is the log of mainland Chinese men interacted with the gender differential in the estimated global mortality rate at age 20 when each cohort turned 20. All estimates have been obtained from separate regressions. The sex ratio at ages 30 and 35 is the ratio of men to women who were 25–34 and 30–39 when each cohort reached age 30 and 35, respectively. All regressions additionally control for age, age squared, log of prime-age (20–64) men, industry male ratio, share of risky jobs at each county at the corresponding age, a full set of county and birth cohort dummy variables, and a dummy variable indicating the sample drawn in 2003. The sample includes birth cohorts between 1929 and 1953 across 20 counties. See Online Appendix Table A5 for the estimation details. Health outcome data were derived from the Health and Living Status of the Middle-Aged and Elderly Survey done in Taiwan in 1996 and 2003. Sex ratios are the authors’ own imputations. The data relating to mainland Chinese men were drawn from the 1956 Population and Housing Census. Gender differentials in mortality were obtained from various abridged life tables published by the Ministry of the Interior in Taiwan.

  • Figure 9
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    Figure 9

    Widowhood Effect Test

    Notes: The dependent variables in Panels A and B are women’s mortality rates at ages 50–54 (circle) and 55–59 (cross). The dependent variables in Panels C and D are men’s mortality rates at ages 55–59 (square) and 60–64 (triangle). In the regressions of women’s mortality at ages 50–54 and 50–59, men’s mortality at ages 55–59 and 60–64 has respectively been further controlled to test for the widowhood effect. In the regressions of men’s mortality at ages 55–59 and 60–64, women’s mortality at ages 50–54 and 55–59 has respectively been further controlled to test the widowerhood effect. Point estimates with 95 percent confidence intervals are shown. Robust standard errors clustered at the county have been used to construct the confidence intervals. All estimates have been obtained from separate regressions. The sex ratio at ages 30 and 35 is the ratio of men to women who were 25–34 and 30–39 when each cohort reached age 30 and 35, respectively. All regressions additionally control for the log of prime-age (20–64) men, industry male ratio, share of risky jobs at each county at the corresponding age, and a full set of county and birth cohort dummy variables. In Panels B and D, the instrumental variables are the log of mainland Chinese men interacted with the gender differential in the estimated global mortality rate at age 20 when each cohort turned 20 and the log of mainland Chinese men interacted with the gender differential in the estimated global mortality rate at age 30 when each cohort turned 30. The sample includes birth cohorts between 1931 and 1950 across 20 counties. See Online Appendix Table A6 for the estimation details. Mortality rates and sex ratios are the authors’ own imputations. The data relating to mainland Chinese men were drawn from the 1956 Population and Housing Census. The global estimated mortality rates at age 20 for males and females were obtained from the Abridged Life Table for Males and Females, World Population Prospects 2019, United Nations, Population Division, Department of Economic and Social Affairs.

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Journal of Human Resources: 59 (2)
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1 Mar 2024
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Too Many Men, Too-Short Lives
Simon Chang, Kamhon Kan, Xiaobo Zhang
Journal of Human Resources Mar 2024, 59 (2) 604-626; DOI: 10.3368/jhr.0420-10845R3

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Simon Chang, Kamhon Kan, Xiaobo Zhang
Journal of Human Resources Mar 2024, 59 (2) 604-626; DOI: 10.3368/jhr.0420-10845R3
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