Showing posts with label Indonesia. Show all posts
Showing posts with label Indonesia. Show all posts

Age distribution by wealth quintile in household survey data

Household survey data may not contain precise ages for all household members. Age heaping, an unusually high share of ages ending in 0 and 5, is especially common in survey data from developing countries. Age heaping can be caused by uncertainty of survey respondents about their own age or the age of other household members, intentional misreporting, or errors during data collection and processing. Errors in age data can affect the estimation of education indicators from household survey data because these indicators are often calculated for specific age groups. Examples include the youth literacy rate and school attendance rates for the population of primary and secondary school age.

An article on age distribution in household survey data on this site demonstrated age heaping in survey data from India, Nigeria and to a lesser extent Indonesia. Data for Brazil showed little to no age heaping. To investigate whether age heaping is more common among certain segments of the population, the survey samples can be disaggregated by household wealth quintile. For this purpose, the households in the sample are first ranked by wealth, from poorest to richest. The population is then divided into five equally sized groups with 20 percent each of all household members in the sample.

Figure 1 shows the age distribution by single year of age and wealth quintile in data from Brazil. The data were collected in 2006 with a Pesquisa Nacional por Amostra de DomicĂ­lios (PNAD) or National Household Sample Survey. No preference for ages ending in 0 and 5 could be observed for the entire survey sample combined and disaggregation does not change the result. The age distribution in each quintile is smooth, with no peaks at ages ending in 0 and 5. The only obvious difference between the population in the different quintiles is that poorer families tend to have more children, indicated by a peak in the age distribution in the younger age groups.

Figure 1: Age distribution in household survey data by single-year age group and household wealth quintile, Brazil
Line graph with age distribution in survey data from Brazil by single-year age group and household wealth quintile
Data source: Brazil PNAD 2006.

Figure 2 shows the age distribution in Demographic and Health Survey (DHS) data from India. The data were collected in 2005-06. In contrast to Brazil, there is considerable age heaping in the Indian data. However, peaks around ages ending in 0 and 5 are more pronounced among poorer households. Increasing household wealth is associated with a decrease in age heaping.

Figure 2: Age distribution in household survey data by single-year age group and household wealth quintile, India
Line graph with age distribution in survey data from India by single-year age group and household wealth quintile
Data source: India DHS 2005-06.

Data from Indonesia, collected with a Demographic and Health Survey in 2007, are shown in Figure 3. At the aggregate level, the survey data from Indonesia exhibit little age heaping. However, disaggregation by wealth quintile reveals that reported ages ending in 0 and 5 are more common among poorer households.

Figure 3: Age distribution in household survey data by single-year age group and household wealth quintile, Indonesia
Line graph with age distribution in survey data from Indonesia by single-year age group and household wealth quintile
Data source: Indonesia DHS 2007.

Finally, Figure 4 displays data from a 2008 Demographic and Health Survey in Nigeria. Similar to India, there is a high percentage of ages ending in 0 and 5 in the combined survey sample. The disaggregated data show that age heaping occurs more frequently among poorer households but also exists in the richest wealth quintile.

Figure 4: Age distribution in household survey data by single-year age group and household wealth quintile, Nigeria
Line graph with age distribution in survey data from Nigeria by single-year age group and household wealth quintile
Data source: Nigeria DHS 2008.

Disaggregation of household survey data from Brazil, India, Indonesia and Nigeria has shown that age heaping occurs more frequently in data collected from poorer households. Wealthier households may have more access to birth registration and therefore may be able to verify their ages with birth certificates. Wealthier households are also likely to be smaller and survey respondents would therefore have to know and report the ages of fewer persons than respondents from larger households.

Age heaping in survey data reduces the accuracy of education indicators that are calculated for single years of age, for example for all children of primary school entrance or graduation age. However, indicator estimates for larger age groups, for example all children of primary or secondary school age, are less likely to be affected by errors in age data.

Related articles
External links
Friedrich Huebler, 30 April 2010, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/04/age.html

Age distribution in household survey data

Indicators in the field of education statistics, such as those defined in the education glossary of the UNESCO Institute for Statistics, are typically calculated for specific age groups. For example, the youth literacy rate is for the population age 15 to 24 years, the adult literacy rate for the population age 15 and over, and the net attendance rates for primary and secondary education are for the population of primary and secondary school age, respectively. The net intake rate is an example for an indicator that is calculated for a single year of age, the official start age of primary school.

For a correct calculation of education indicators it is necessary to have precise age data. In the case of data collected with population censuses or household surveys this means that the ages recorded for each household member should be without error. However, census or survey data sometimes exhibit the phenomenon of age heaping, usually on ages ending in 0 and 5. Such heaping or digit preference occurs when survey respondents don't know their own age or the ages of other household members, or when ages are intentionally misreported.

The presence of age heaping can be tested with indices of age preference such as Whipple's index. Heaping can also be detected through visual inspection of the age distribution in household survey data. Figures 1 and 2 summarize the age distribution in survey data from Brazil, India, Indonesia and Nigeria. The data from Brazil were collected with a Pesquisa Nacional por Amostra de DomicĂ­lios or National Household Sample Survey in 2006. The data for the other three countries are from Demographic and Health Surveys conducted between 2005 and 2008.

Figure 1 shows the share of single years of age in the total survey sample. A preference for ages ending in 0 and 5 is strikingly obvious in the data from India and Nigeria. In the data from Indonesia, age heaping is also present, but to a lesser extent than for India and Nigeria. Lastly, the graph for Brazil is relatively smooth, indicating a near absence of age heaping.

Figure 1: Age distribution in survey data by single-year age group
Line graph with age distribution in survey data by single-year age group
Data source: Brazil PNAD 2006, India DHS 2005-06, Indonesia DHS 2007, Nigeria DHS 2008.

In Figure 2, single ages are combined in five-year age groups, from 0-4 years and 5-9 years to 90-94 years and 95 years and over. Compared to Figure 1, the distribution lines are much smoother, including for India and Nigeria. We can conclude that age heaping is problematic for education indicators that are calculated for single years, for example all children of primary school entrance age, but less so for indicators that are calculated for a larger age group, for example all children of primary or secondary school age or all persons over 15 years of age.

Figure 2: Age distribution in survey data by five-year age group
Line graph with age distribution in survey data by five-year age group
Data source: Brazil PNAD 2006, India DHS 2005-06, Indonesia DHS 2007, Nigeria DHS 2008.

Related articles
External links
Friedrich Huebler, 28 February 2010 (edited 30 September 2010), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/02/age.html