2 On the Concept of Age Heaping and Numeracy
2.7 Applications of the Age Heaping Technique in Economic HistoryHistory
Mokyr (1982) and Mokyr and Ó'Gráda (1982) were the rst to measure 'quantitative sophisti-cation' by the degree of age heaping to approximate education due to the lack of information on literacy. The authors draw on emigrant passenger list to test the assumption that prefamine Ireland suered from brain drain. The emigrant population constituted an important share of laborers and servants, but the levels of age heaping were consistently higher than the levels of age heaping in the Irish census of 1841. The empirical evidence thus suggests that the less edu-cated classes decided to leave the country and that a brain drain has therefore not taken place.
Moreover, lower occupational classes had higher age heaping levels than higher occupational classes.
Using data from the Saudi Arabian social insurance system, Myers (1976) nds pronounced birth year heaping and a negative correlation between individual earnings and age heaping. He
assumes that this is due to the fact that less educated workers earn less. Herlihy and Klapisch-Zuber (1985) study among other things age statements in the Florentine Catastro of 1427. Their main results are that age awareness improved over time, probably in response to government demands for taxes. Additionally, age heaping was higher in rural areas than in Florence itself.
Data from the 1851 and 1881 British censuses suggests a better performance in the labor market of people who reported their age with consistency between the two censuses (Long 2005).
Dillon (2007) reports that being black, being resident in Southern US, living in urban areas, as well as living in the household of a laborer or servant meant a higher likelihood of stating a rounded age in 1870/1871. Clark (2007) nds empirical support for a strong correlation between age awareness correlates and social class. In his study on the biological standard of living in Britain from 1740 to 1865, Cinnirella (2008) uses age heaping as an indicator of individual skills in numeracy. De Moor and van Zanden (2008) estimate gender dierentials in age heaping for the Netherlands. Due to relatively equal position between sexes these dierences were found to be small.
Crayen and Baten (2009b) use age heaping in France and the United States during the 17th to 19th century to study the impact of human capital inequality on subsequent welfare growth.
Occupational groups and anthropometric indicators allow them to distinguish between the lower and the middle/higher economic strata of the society. They nd a clear negative impact of inequality in numeracy between the social groups on subsequent economic growth for the U.S., but less clear eects for France.
The most ample study that investigates the development of age heaping is a study by Crayen and Baten (2009a). They trace long-term trends in numeracy 1820 to 1949 in 165 countries. In a regression on the determinants of age heaping, school enrollment resulted to be the strongest determinant. Comparing the dierent world regions, the industrialized countries, Eastern Eu-rope, and East Asia exhibited low age heaping levels throughout the period considered. Eastern Europe could improve its performance during the 19th century exceptionally to catch up with the industrial countries. In contrast, South Asia and the Middle East had very high age heaping levels (in 1840, South Asia had a Whipple index of 450 and the Middle East of 400 which implies that only 12.5 and 25 percent of the population respectively could state the own age correctly).
Estimates for the Latin American region start only in 1880 and show that the region took a middle position and converged towards the age heaping levels of the industrialized countries.
The following chapters will give a more nuanced overview of this development, also focusing on earlier time periods.
While the above mentioned studies focus on the long-term development of age conscious-ness,Baten, Crayen, and Voth (2007) focus on short-term variations in numeracy levels in Britain during industrialization. They nd slightly increasing age heaping in decades with higher grain prices. Counties which granted higher poor relief payments to their population suered less severe deterioration in age heaping from increasing grain prices.
2.8 Conclusion
The review on the reasons for age misreporting has clearly shown that the dierent reasons for age misreporting have to be taken into account if we use the misreporting patterns to approximate numerical abilities of the population. A dierent cultural background may lead to dierent, more, or less pronounced heaping patterns which have to be controlled for. Generally, the question concerning the age in a census reveals less accurate results than questions for the year of birth, as Gray and Gee (1972, p. 110) nd in a study on age misreporting in England and Wales. Which question is asked to obtain the age data is of crucial importance. Therefore, the circumstances of the census (Have all individuals been asked individually? Did interviewers ask for age or birth year? Did the interviewers estimate the age of the respondents if they did not know their age? Was age information counter-checked with birth certicates?) have to be taken into account when applying age heaping as a proxy variable for human capital. The age heaping technique itself also has limitations which have to be taken carefully into account. Most importantly, it gives only a rough proxy for the educational level of a society or subgroups of a society. Still, this technique is highly valuable to close gaps in existing data sources on human capital. Applications of age heaping in Economic History already exist, but focus mostly on single countries or limited time periods, with the only exception of the study by Crayen and Baten (2009a). Therefore, this thesis aims at providing a broader overview of the development of age heaping in the Iberian world.
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