This paper finds that the Great Chinese Famine of 1959–1961 reduced lifetime educational attainment by up to 3.8 years for people who lived in areas most severely hit by the famine. Using geographical variation in famine intensity, information about place of residence during the famine, and educational attainment recorded in the China Health and Retirement Longitudinal Study, the paper demonstrates that the decline in educational attainment was particularly sharp for women. This decline interrupted substantial gains in schooling achieved in China during the middle part of the twentieth century.
This work was supported by the NICHD (T32 HD007339, Funder ID: http://dx.doi.org/10.13039/100000071) and NIA training grant (T32 AG000221) as part of the University of Michigan Population Studies Center training program. The authors gratefully acknowledge the use of the services and facilities of the Population Studies Center (funded by NICHD Center Grant R24 HD041028, Funder Id: http://dx.doi.org/10.13039/100000071). The authors also gratefully acknowledge the National Bureau of Statistics, China, for providing the census data used in this research. The opinions and conclusions expressed herein are solely the authors’ and do not represent the opinions or policy of these funders or agencies.
A Delayed Schooling
In Section 5.2, we show that women aged 13–15 in 1959 were less likely to complete primary school if they experienced severe famine. Given the standard schooling schedule, this finding is surprising. A child who begins the 6 years of primary school at age 6 should be done by age 12. Departure from this normal schooling schedule could leave a child in primary school past her twelfth birthday. In order for a child to still be attending primary school after age 12, she would either need to have begun primary school after age 6 or to have intervals during which her schooling was interrupted. We cannot use the CHARLS to measure the frequency of these departures from the normal schooling schedule because the survey does not record age at first schooling and does not record schooling interruptions. We similarly do not know of another data source that records sufficiently detailed schooling histories for these cohorts.
Instead, we use data from the 1982 census, the earliest available census for which microdata are publicly available, to calculate the frequency of departures from this normal schooling schedule in the early 1980s (Minnesota Population Center 2019). The 1982 census records the highest level of schooling completed by each person aged 6 and older, and identifies whether each person aged 15 and older is currently attending school. Although this information does not identify the age at which a person started school, we can use it to identify people aged 16 who are in school but have not yet completed junior high school. A person who began primary school at age 7 and continued without interruption should complete junior high school by age 16. A substantial share of people departed from this normal schedule: 9.1% of children who were aged 16 and attending school in 1982 had not yet completed junior high school. This share was slightly higher for boys than girls, 9.7% versus 8.0%. These rates were similar in the 1990 census, 10.2% and 8.3%. Again, although these calculations do not directly demonstrate that children aged 13 and older were still attending primary school at the start of the famine, they suggest that departures from standard progress through school were somewhat common in China during the last half of the twentieth century.
Figure 6 presents the main education findings by sex. The estimates in this figure are calculated using as a measure famine intensity the ratio of each prefecture’s population in 1982 who were born between 1950 and 1952 to the population in 1982 who were born between 1959 and 1961, and using 3-year birth cohorts between 1941 and 1961 (with 1938–40 as the omitted cohort). In this section, we demonstrate the robustness of these estimates to alternative construction of the famine intensity measure and alternative definitions of the cohorts.
B.1 Famine Intensity Measure
First, we use the population born between 1953 and 1955 as the numerator in the famine intensity measure. Figure 9 repeats the estimates in Figure 6 using this new intensity measure. The estimates change only slightly, if at all. For example, using either famine intensity measure, women born between 1944 and 1946 who experience severe famine complete about 0.55 fewer years of schooling than do women in the control (1938–40) cohort who experience severe famine. This comparison suggests that the particular choice of 1950–52 as the reference cohort, although somewhat arbitrary, does not drive the findings.
Second, we use the cohort born between 1956 and 1958 as the denominator of the famine intensity measure. Figure 10 repeats the estimates in Figure 6 using this new intensity measure. The estimates are generally closer to zero, and every 95% confidence interval includes zero. If cohort sizes in 1959–61 simply followed pre-existing trends in cohort sizes, then the choice of denominator would matter little to the estimates. The weakening of the findings when an earlier cohort is used indicates that the particular 1959–61 cohort is meaningful and reflects the unique mortality and fertility conditions during the famine.
B.2 Cohort Definition
First, we define cohorts by normal progress through school in 1959, the year the famine began. The omitted birth cohort remains 1938–40, people aged 19 and older at the start of the famine and likely done with high school. The first two cohorts, 1941–43 and 1944–46, are the same as in the main findings, and represent people of senior high school age (aged 15–18) and junior high school age (aged 12–15) at the start of the famine. The third cohort consists of people, born between 1947 and 1952, who are primary school age (aged 6–12) at the start of the famine. The fourth cohort, born between 1953 and 1958, is too young to attend school at the start of the famine. The final cohort is born during the famine. The estimates in Figure 11 have the same interpretation as those in Figure 5: Years of completed schooling declines, especially for girls of high school age during the famine. Primary and junior high school completion rates decline, although this decline is statistically significant only for girls of junior high school age during the famine. Senior high school completion rates decline most substantially for girls born during the famine.
Second, we use the same seven 3-year birth cohorts between 1941 and 1961 as in the main analysis, but with people born immediately after the famine between 1962 and 1964 as the omitted cohort, instead of 1938–40. As depicted in Figure 12, the estimates for boys change little relative to Figure 5, suggesting that the famine had little effect on the schooling of boys born after the famine. However, the estimates for girls all shift upwards. For example, all cohorts between 1941 and 1955 now have a positive interaction effect with famine severity, relative to the omitted post-famine cohort’s interaction effect with famine severity. This comparison suggests that the negative consequences of the famine may have continued for girls born after the famine ended.
Ampaabeng, Samuel K., and Chih Ming Tan. 2013. “The Long-term Cognitive Consequences of Early Childhood Malnutrition: The Case of Famine in Ghana.” Journal of Health Economics 32(6): 1013–27.10.1016/j.jhealeco.2013.08.001Search in Google Scholar
Attané, Isabelle, and Christophe Z. Guilmoto, editors. 2007. Watering the Neighbour’s Garden: The Growing Demographic Female Deficit in Asia. Paris: Committee for International Cooperation in National Research in Demography.Search in Google Scholar
Brown, Philip H., Erwin Bulte, and Xiaobo Zhang. 2011. “Positional Spending and Status Seeking in Rural China.” Journal of Development Economics 96(1): 139–249.10.1016/j.jdeveco.2010.05.007Search in Google Scholar
Chen, Y., and L. Zhou. 2007. “The Long-term Health and Economic Consequences of the 1959–1961 Famine in China.” Journal of Health Economics 26(4): 659–81.10.1016/j.jhealeco.2006.12.006Search in Google Scholar
Das Gupta, Monica, Jiang Zhenghua, Li Bohua, Xie Zhenming, Woojin Chung, and Bae Hwa-Ok. 2003. “Why is Son Preference so Persistent in East and South Asia? A Cross-Country Study of China, India, and the Republic of Korea.” Journal of Development Studies 40(2): 153–87.10.1080/00220380412331293807Search in Google Scholar
Deng, Z., and D. J. Treiman. 1997. “The Impact of the Cultural Revolution on Trends in Educational Attainment in the People’s Republic of China.” American Journal of Sociology 103(2): 391–428.10.1086/231212Search in Google Scholar
Fung, Winnie, and Wei Ha. 2010. “Intergenerational Effects of the 1959–61 China Famine.” In Risk, Shocks, and Human Development, edited by Ricardo Fuentes-Nieva, and Papa A. Seck, 222–54. New York: Palgrave MacMillan.10.1057/9780230274129_10Search in Google Scholar
Guilmoto, Christophe Z. 2012. Sex Imbalances at Birth: Current Trends, Consequences, and Policy Implications. Bangkok, Thailand: UNFPA Asia and the Pacific Regional Office.Search in Google Scholar
Haddad, Lawrence J., and Howarth E. Bouis. 1991. “The Impact of Nutritional Status on Agricultural Productivity: Wage Evidence from the Philippines.” Oxford Bulletin of Economics and Statistics 53(1): 45–68.10.1111/j.1468-0084.1991.mp53001004.xSearch in Google Scholar
Hannum, E., and Y. Xie. 1994. “Trends in Educational Gender Inequality in China: 1949–1985.” Research in Social Stratification and Mobility 13: 73–98.Search in Google Scholar
Hernández-Julián, R., H. Mansour, and C. Peters. 2014. “The Effects of Intrauterine Malnutrition on Birth and Fertility Outcomes: Evidence from the 1974 Bangladesh Famine.” Demography 51(5): 1775–96.10.1007/s13524-014-0326-5Search in Google Scholar
Intergovernmental Panel on Climate Change. 2012. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. Edited by Christopher B. Field, Vicente Barros, Thomas F. Stocker, Qin Dahe, David Jon Dokken, Kristie L. Ebi, Michael D. Mastrandrea, et al. Cambridge: Cambridge University Press.Search in Google Scholar
Jiang, Quanbao, Isabelle Attané, Li Shuzhuo, and Marcus W. Feldman. 2007. “Son Preference Aht eMarriage Squeeze in China: An Integrated Analysis of First Marriage and the Remarriage Market.” In Watering the Neighbour’s Garden: The Growing Demographic Female Deficit in Asia, edited by Isabelle Attané, and Christophe Z. Guilmoto, 347–63. Paris: Committee for International Cooperation in National Research in Demography.Search in Google Scholar
Jowett, A. J. 1984. “The Growth of China’s population, 1949-1982 (With Special Reference to the Demographic Disaster of 1960-61).” Geographic Journal 150(2): 155–70.10.2307/634995Search in Google Scholar
Jurges, Hendrik. 2013. “Collateral Damage: the German Food crisis, Educational Attainment and Labor Market Outcomes of German Post-war Cohorts.” Journal of Health Economics 32(1): 286–303.10.1016/j.jhealeco.2012.11.001Search in Google Scholar
Kim, Seonghoon, Quheng Deng, Belton M. Fleisher, and Shi Li. 2014. “The Lasting Impact of Parental Early Life Malnutrition on Their Offspring: Evidence from the China Great Leap Forward Famine.” World Development 54: 232–42.10.1016/j.worlddev.2013.08.007Search in Google Scholar
Kim, Seonghoon, Belton Fleisher, and Jessica Ya Sun. 2017. “The Long-term Health Effects of Fetal Malnutrition: Evidence from the 1959–1961 China Great Leap Forward Famine.” Health Economics 26(10): 1264–77.10.2139/ssrn.2655041Search in Google Scholar
Kiros, Gebre-Egziabher, and Dennis P. Hogan. 2001. “War, Famine and Excess Child Mortality in Africa: The Role of Parental Education.” International Journal of Epidemiology 30(3): 447–55.10.1093/ije/30.3.447Search in Google Scholar
Lardy, N. R. 1987. “The Chinese Economy under stress, 1958–1965.” In The Cambridge History of china, Volume 14: the People’s Republic of China Part I: The Emergence of Revolutionary China 1949–1965, edited by R. MacFarquhar, and J. K. Fairbank, 360–97. Cambridge: Cambridge University Press.10.1017/CHOL9780521243360.009Search in Google Scholar
Lary, Diana. 1999. “The ‘Static’ Decades: Inter-provincial Migration in Pre-Reform China.” In Internal and International Migration: Chinese Perspectives, edited by Frank N. Pieke, and Hein Mallee, 29–48. Surrey: Curzon Press.Search in Google Scholar
Meng, X., and N. Qian. 2009. “The Long Term Consequences of Famine on Survivors: Evidence from a Unique Natural Experiment Using China’s Great Famine.” NBER Working Paper.10.3386/w14917Search in Google Scholar
Minnesota Population Center. 2019. "Integrated Public Use Microdata series, International: Version 7.1 [Dataset]." Minneapolis, MN: IPUMS. Accessed August 15, 2019. https://doi.org/10.18128/D020.V7.2.Search in Google Scholar
Mu, Ren, and Xiabao Zhang. 2011. “Why Does the Great Chinese Famine Affect the Male and Female Survivors Differently? Mortality Selection versus Son Preference.” Economics and Human Biology 9(1): 92–105.10.1016/j.ehb.2010.07.003Search in Google Scholar
Neelsen, Sven, and Thomas Stratmann. 2011. “Effects of Prenatal and Early Life Malnutrition: Evidence from the Greek Famine.” Journal of Health Economics 30(3): 479–88.10.1016/j.jhealeco.2011.03.001Search in Google Scholar
Pepper, S. 1987. “New Directions in Education.” In The Cambridge History of china, Volume 14: the People’s Republic of China Part I: The Emergence of Revolutionary China 1949–1965, edited by R. MacFarquhar, and J. K. Fairbank, 398–431. Cambridge: Cambridge University Press.Search in Google Scholar
Price, R. F. 1979. Education in Modern China. New York: Praeger.Search in Google Scholar
Seaman, J., G. Sawdon, J. Acidri, and C. Petty. 2014. “The Household Economy Approach. Managing the Impact of Climate Change on Poverty and Food Security in Developing Countries.” Climate Risk Management 4: 59–86.10.1016/j.crm.2014.10.001Search in Google Scholar
Sen, Amartya. 1990. “More than 100 Million Women are Missing.” The New York Review of Books 37(20): 61–66.Search in Google Scholar
Steckel, Richard H. 1986. “A Peculiar Population: The Nutrition, Health, and Mortality of American Slaves from Childhood to Maturity.” Journal of Economic History 46(3): 721–41.10.1017/S0022050700046842Search in Google Scholar
Ulimwengu, John. 2009. “Farmers’ Health and Agricultural Productivity in Rural Ethiopia.” African Journal of Agricultural Economics 3(2): 83–100.Search in Google Scholar
Valenzuela, M. J., and P. Sachdev. 2006. “Brain Reserve and Cognitive Decline: A Non-Parametric Systematic Review.” Psychological Medicine 36(8): 1065–73.10.1017/S0033291706007744Search in Google Scholar
Waldron, I. 1983. “The Role of Genetic and Biological Factors in Sex Differences in Mortality.” In Sex Differences in Mortality, edited by A. D. Lopez, and L. T. Ruzicka, 141–64. Canberra: Department of Geography, Australian National University.Search in Google Scholar
Weir, D., M. Lay, and K. Langa. 2014. “Economic Development and Gender Inequality in Cognition: A Comparison of China, India, and of SAGE and the HRS Sister Studies.” Journal of the Economics of Ageing 4(1): 112–25.10.1016/j.jeoa.2014.08.002Search in Google Scholar
Wu, Xiaogang. 2010. “Economic Transition, School Expansion and Educational Inequality in china, 1990–2000.” Research in Social Stratification and Mobility 28(1): 91–108.10.1016/j.rssm.2009.12.003Search in Google Scholar
Yaffe, K., A. J. Fiocco, K. Lindquist, E. Vittinghoff, E. M. Simonsick, A. B. Newman, S. Satterfield, et al. 2009. “Predictors of Maintaining Cognitive Function in Older Adults: The Health ABC Study.” Neurology 72(23): 2029–35.10.1212/WNL.0b013e3181a92c36Search in Google Scholar
Zhao, Yaohui, John Strauss, Gonghuan Yang, John Giles, Peifent (Perry) Hu, Yisong Hu, Xiaoyan Lei, et al. 2013. “China Health and Retirement Longitudinal Study.” International Journal of Epidemiology 43 (1): 61–68. Accessed January 30, 2019. http://charls.pku.edu.cn/en.10.1093/ije/dys203Search in Google Scholar
Zhao, Yaohui, Yisong Hu, James P. Smith, John Strauss, and Gonghuan Yang. 2014. “Cohort Profile: The China Health and Retirement Longitudinal Study (CHARLS).” International Journal of Epidemiology 43(1): 61–68.10.1093/ije/dys203Search in Google Scholar
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