Data Sources

Starting with the complex Visita General of the Viceroy Francisco de Toledo in 1572, population counts in the New World were carried out regularly. The rst counts were intended to obtain a detailed overview of the territory and its inhabitants and did not contain systematic age statements. Most visitas focused on small regional units and repeated within ve to ten years. In the 17^thcentury, there followed the empadronamientos de tributarios, population counts to determine the taxes of individuals. Padrones de

13Although they had lower educational levels than immigrants in the United States.

población (population counts with a limited geographical or social scope) and partial censuses were carried out during the 18^th and 19^th centuries, covering larger regions and a larger share of the population (Mellafe 2004, pp.148-170). In the late 18^th century, the Council of the Indies started a series of systematic census records (Platt 1998, p.8). By means of this information, the Spanish Crown estimated the amount of taxes and learned about the number of men able to ght in the army. For the post-colonial period, censuses of the republics are available, although most of them stem only from the late 19^th and 20^th centuries. Therefore, information on the rst decades after independence is scarce.

Latin America is actually the only continent in the developing world for which popu-lation enumerations are widely available for such an early period (Platt 1998, p.7). An advantage of the surviving original records is the detailed amount of information they provide. Some of the population enumerations not only list names but also ages and information on the ethnicity, profession, place of birth, number and age of children, and the number of slaves in a household.¹⁴This information allows an in-depth study of age heaping already during colonial rule, and up until the 20^th century. Our data covers Argentina, Brazil, Colombia, Mexico, Peru, and Uruguay¹⁵and represents therefore, a large part of the Latin American subcontinent. All in all, these countries today represent around 80% of the Latin American population.¹⁶An important question is whether our various sources are representative of the whole society during the period under study. The population enumerations were supposed to have universal coverage in the whole area con-sidered, as well as in all social strata. Nevertheless, ocials of the Spanish Crown were seen as invaders by the native population and the reasons for the enumeration (taxes, military recruitment) led to fear and distrust. Therefore, demographers are convinced that most of the census data is subject to underenumeration. Gootenberg (1991) even assumes that all population estimates of Peru are wrong due to a severe underenumera-tion. In particular, men aged 16 to 36 attempted to avoid the military draft (Orozco y

14In some cases, the census schedules also contain information on the wealth of a family.

15While borders changed during the colonial and post-colonial period, we always refer to today's borders here.

16Central America had not a similarly dense population and no mineral resources, so that the Spanish Crown was less interested in this area (Mabry 2002, p. 58) and there exist only few population enumerations for these countries.

Berra 1980). The famous Censo de Revillagigedo (1790-1794) in Mexico City, for example, shows an overrepresentation of widows. Women tended to declare themselves as widows or solteronas (spinsters) in order to protect their husbands and sons (Arrom 1985).The avoidance behavior of younger males underestimates the overall number of inhabitants.

But it does not actually bias our numeracy estimates as long as it is uncorrelated with their educational status. The available evidence suggests that military draft avoidance was spread across a large part of the population, except perhaps the very rich (Orozco y Berra 1980, p. 72). Consequently, even data which suers from underenumeration can provide relatively unbiased information on the development of education in terms of nu-merical abilities in the colonial society of Iberian America. Some biases are unavoidable;

therefore, the strategy we will follow is to compare dierent samples wherever possible.

An important question is whether the household heads reported the age for all house-hold members or whether all people in the age range studied here (age 23-62) were asked individually. One might expect that the household head was certain about his or her own age, but did not know the exact age of other household members. Hence, there might be an exaggerated age heaping among those who were not household heads. We compared male household heads and other male members of the household in the census of 1744 of Buenos Aires and found that there was actually no substantial dierence, even though one might expect that the other members had a lower educational status. We conclude that potential reporting by a household head on other male members of the household was not a large problem in case that this census was representative. In addition, a few padrones contain personal notes of census takers that a certain person states his or her age as 30, 'but looked considerably older' (see for instance Cook 1968, p.34). This implies that census takers asked each person individually for census-specic information. Thus they did not rely only on the information provided by the household head and did not adjust for obviously erroneous age statements.

Table 1 and Appendix A contain detailed additional information on the sources that were used to construct a numeracy series for colonial and post-colonial Latin America.

Some of our sources were restricted to the capital, others to some regions of a country.

The most special data sets come from prison records. Sometimes prison samples have a strong concentration of ages 23 and 24, which results in a skewed age distribution.

Therefore the ABCC index is sometimes upward biased for the youngest prisoners.

In order to assess the representativeness of our samples in detail, we compare the ethnic composition of our census samples with the ethnic composition of the whole population for all cases for which information was available from the literature. Table 2 lists the results. It is noteworthy that the skin-color classication was abolished in most countries after Independence and we are therefore not able to compare the later samples by these characteristics. The Argentinean samples of 1744 and 1771 reect the population of Buenos Aires generally quite well, with the exception of blacks and mulattos, who are slightly underrepresented in 1744.¹⁷ In sum, while not all census samples reect the exact share of each ethnic group in the colonial society, our data reveal no severe biases. But there is one major exception: The Peruvian data is clearly not representative as we only possess data for Lima until the 1880s and the population of the capital is probably biased towards the higher social classes. For this reason, we will estimate a numeracy trend for Lima only (not for Peru) and bear in mind that the level of numeracy will be upward biased.

Finally, an important point for Latin America in particular is whether migrants should be included in the individual samples. Here, we are mainly interested in the long-term human capital formation of countries, and permanent migrants were an important part of the population. Therefore, we decided to include migrants as well. This also makes individual and aggregated samples comparable, because in the aggregated data migrants were included anyways. However, we have to expect some shifts in the numeracy graphs during periods of mass immigrations, assuming that the immigrants to Latin America were more numerate than the native population.

17During the 19^th century, the share of blacks and mulattos declined. Their share in the censuses of Buenos Aires was around 25% in 1810, 1822 and 1838. In 1887 it had declined to only 1.8% (Andrews 1989).