1973
DOI: 10.2307/1402833
|View full text |Cite
|
Sign up to set email alerts
|

Digit Preference and Avoidance in the Age Statistics of Some Recent African Censuses: Some Patterns and Correlates

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

3
21
0

Year Published

1978
1978
2025
2025

Publication Types

Select...
9

Relationship

0
9

Authors

Journals

citations
Cited by 28 publications
(24 citation statements)
references
References 0 publications
3
21
0
Order By: Relevance
“…Mokyr (1983) was the first to apply age heaping as a proxy variable for the educational level of a population in order to investigate whether there was a brain drain from prefamine Ireland. Studies find a strong negative correlation between age heaping and literacy or schooling, such as Crayen and Baten (2009) for the 19 th and 20 th centuries, A 'Hearn, Baten and Crayen (2009) for the 19 th century U.S. states and the countries of Europe during the early modern period, Manzel and Baten (2008) for Argentina during the 19 th century, and Nagi, Stockwell and Snavley (1973) for African countries of the mid-20 th century. To measure the degree of age heaping, various indices can be used.…”
Section: Methodsmentioning
confidence: 99%
“…Mokyr (1983) was the first to apply age heaping as a proxy variable for the educational level of a population in order to investigate whether there was a brain drain from prefamine Ireland. Studies find a strong negative correlation between age heaping and literacy or schooling, such as Crayen and Baten (2009) for the 19 th and 20 th centuries, A 'Hearn, Baten and Crayen (2009) for the 19 th century U.S. states and the countries of Europe during the early modern period, Manzel and Baten (2008) for Argentina during the 19 th century, and Nagi, Stockwell and Snavley (1973) for African countries of the mid-20 th century. To measure the degree of age heaping, various indices can be used.…”
Section: Methodsmentioning
confidence: 99%
“…Practically, however, the variety of ultimate contextual factors is likely to affect such patterns. In their pioneering studies, Nagi, Stockwell and Snavley (1973), and Stockwell and Wicks (1974), found that the magnitude of error in age reporting in a population is closely related to the latter's level of modernization as measured by a host of socio-economic indicators (e.g. the proportion of persons economically active, the percentage literate and the proportion of people working in the non-agricultural sector).…”
Section: Age Heaping In Contextmentioning
confidence: 99%
“…2,5 Despite the common use of self-report measures, bias may arise in using these measures. Digit bias or, heaping, which is a clustering of reported estimates around rounded values 6–8 is common and has been well documented in the literature. 1,915 …”
mentioning
confidence: 97%