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 Domicílios (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

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

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

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

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

• Age distribution in household survey data
• Educational attainment in Brazil since 1920
• School attendance in Brazil
• Educational attainment in India, 1950-2000
• Primary school completion in India, 1950-2000
• Age and level of education in Nigeria
• Adult literacy in Nigeria
• Youth literacy rates
• Official school ages: primary, secondary, and compulsory education

External links

• Demographic and Health Surveys (DHS)
• Brazil National Household Sample Survey 2006
• Education glossary by the UNESCO Institute for Statistics

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

Baidu's Q1 2010 profits rose 167% Y-o-Y

"Total revenues in the first quarter of 2010 were RMB1.294 billion ($189.6 million), a 59.6% increase from the corresponding period in 2009.
Operating profit in the first quarter of 2010 was RMB530.8 million ($77.8 million), a 167.4% increase from the corresponding period in 2009.
Net income in the first quarter of 2010 was RMB480.5 million ($70.4 million), a 165.3% increase from the corresponding period in 2009. Diluted earnings per share ("EPS") for the first quarter of 2010 was RMB13.77 ($2.02); diluted EPS excluding share-based compensation expenses (non-GAAP) for the first quarter of 2010 was RMB14.33 ($2.10)."
Source: Baidu press release, 28th April 2010

Music streaming site we7 pays between £2,000 and £4,000 to the music industry per 1m song plays

"In comments to Digital Music News, we7 chief executive Steve Purdham clarified that ads are now covering royalties (both recording and publishing) and bandwidth costs, but not broader operational costs. The rest of the P&L is on its own.
Purdham also colored an earlier figure. Specifically, the company calculated that one million song plays now translate into "payments to the music industry" of between "2,000 to 4,000" pounds, or roughly $3,000 to $6,000. That is based on per-play rates, not "miniscule or non-existent revenue share" arrangements, and the payouts run the gamut of "unsigned" to "major label"."
Source: Digital Music News, 28th April 2010

50,000 websites implemented Facebook social plugins in the first week

"At f8, we also launched new tools called social plugins — including the Like button, Activity Feed, and Recommendations — on more than 75 websites. Already, just one week since launch, more than 50,000 sites across the Web have implemented the new plugins. We are thrilled by the strong adoption so far as developers realize how easy social plugins are to use and how powerful they are in engaging users in a frictionless experience without requiring them to share any personal information."
Source: Facebook blog, 28th April 2010

240m Chinese internet users watch videos online

"According to its annual 2009 research report on online video applications in China, the China Internet Network Information Center (CNNIC) announced today that as of the end of 2009, online video users in China reached 240 mln.
According to the report, 66.8% of respondents reported time spent watching television had decreased, with 23.7% of those users stating they basically no longer watch television programs on TV. 56.7% of respondents said they are more dependent on the Internet than TV.
Films and television programs were the most commonly named content when respondents were asked what their favorite type of content was, garnering 77% and 70.5% of users respectively.
71.6% of respondents said they used regular search engines to find video content; 53.9% of respondents found content through word of mouth or SNS websites, while 43.8% used on-deck search on specific online video websites.
Over 98% of respondents said they used broadband connections to watch online videos, while only 0.9% said they used narrowband connections.
47.9% of respondents watched online video content every day.
62.9% of respondents reported that advertising on online video services is acceptable."
Source: Online video report from the CNNIC, reported by Marbridge Consulting, 7th April 2010

More young Chinese go online through mobile phones than desktop computers

"The report found that China's Internet penetration rate has reached 54.5 percent among young people, much higher than the national average of 28.9 percent among the country’s total population. In addition, the number of young Chinese netizens increased by 28 million in 2009.
Mobile netizens constitute the majority of the newly-added young Internet users. The number of young mobile Internet users rose 73.5 percent to 144 million from the end of 2008 to 2009, accounting for 74 percent of the total young netizen population, above the national average of around 61 percent. The proportion of young people who surf the Internet via their desktops dropped to about 70 percent, indicating that mobile phones have overtaken desktops for the first time as the first choice for young Chinese Internet users to access the Internet."
Source: CNNIC "2009 Report on the Behavior of China's Young Internet Users", reported by People's Daily, 27th April 2010
Note - Young Chinese are defined as age 6 to 25.

There are 195m internet users under the age of 25 in China

"The China Internet Network Information Center (CNNIC) issued its "2009 Report on the Behavior of China's Young Internet Users" in Beijing today, showing that as of the end of 2009, China had reached a total of 195 mln young internet users, up 16.8% from the previous year, accounting for 50.7% of all internet users in China. Internet penetration among youth reached 54.5%, and 74% of all young internet users accessed the internet via mobile phone, up 24.3% from the previous year.
Young internet users spent a weekly average of 16.5 hours online, 1.9 hours longer than in 2008.
Most marked was young internet users' use of entertainment services, with usage of online music (88.1%), online video (67%), online literature (47.1%) and online gaming (77.2%) all higher than that of overall internet users. Young internet users also used online communication tools at higher rates than overall internet users, including blogs (68.8%), instant messaging (77%), social networking sites (50.9%) and BBS (31.7%). 73.9% of young Chinese internet users used search engines. In general, young Chinese internet users were less active on commerce-related internet applications, with online shopping and payment used by 26.5% and 22.9% of users, respectively.
85.7% of university students and 69.3% of middle- and high-school students who went online did so via mobile phone. Overall, young internet users were relatively active in usage of most mobile internet applications: 87.3% of young mobile internet users used online chat services, 60.8% used mobile search, and 54.5% used mobile music.
CNNIC defines internet users as Chinese nationals over the age of 6 who have used the internet within the past half year. Young internet users refers to those under the age of 25."
Source - CNNIC "2009 Report on the Behavior of China's Young Internet Users", reported by Marbridge Consulting, 26th April 2010