Key issues for the National Statistical System in Benin
INSAE is the key focal point for official statistics in the country, however it faces several challenges. In terms of capacity, INSAE has approximately 70 employees responsible for everything including data dissemination, survey design, survey sampling, coordinating enumerators, assessing the validity of data published by third parties, census management, macroeconomic indicators such as GDP, labour force statistics, coordination and validation of administrative data.
Another key challenge centres on the availability of administrative data systems and automated data systems. Digitising records such as those used for case management or with administrative data systems within the work of the Ministry of Social Affairs and Microfinance could increase the efficiency of work and provide rich data for analysis on those in the P20. Additional investments in other administrative data – especially vital statistics and civil registration – can significantly improve the sustainability of the data ecosystem in Benin and can provide a better understanding of populations at risk of being left behind.
The benefits of disaggregation
There are many reasons why particular groups of people get left out of progress. The differences according to aspects of identity such as age, gender or disability can be very significant. Where a person lives is often another important factor in terms of the chances and opportunities available to them. The P20 approach recommends using data disaggregated not just by wealth but also by gender, age, geography and disability to gain a better understanding of the inclusion of different groups and assess who is being left behind. Key insights from applying this approach in Benin are outlined in further detail below, alongside recommendations on how existing national statistical systems can be improved and non-traditional sources of data can be used to fill data gaps.
Tools such as satellite imagery, call data records, social media data and other types of non-traditional data clearly hold potential for advancing development and planning. These tools cannot be a substitute for official data sources, but they can complement or provide additional information beyond official sources. INSAE should be at the heart of the official and unofficial statistics. While the poorest may be excluded from many of these new sources of data because they are less likely to have mobile phones or to be on social media, such data sources can highlight other dimensions of exclusion. Furthermore, the digital economy is likely to become an increasing engine for economic growth in Benin which could have broader impacts on the lives of the P20.
Gender
One of the barriers frequently mentioned in Borgou and Alibori was girls being married before the age of 18. Borgou and Alibori have the highest incidence of early marriage, which has implications for human rights and health. Data from the 2017/18 DHS shows that in Alibori, 48% of married women between the ages of 20 and 24 were married before they were 18. In Borgou, the rate was 42.8% (this marked an increase from 39.3% in the 2014 MICS).
It is not just marriage practice that increases the risk of women/girls being left behind; households headed by women are significantly poorer than those headed by men. Nationally, households headed by women are reported to have seen their household consumption decrease by 2.4% between 2011 and 2015, compared to a 14.3% gain among households headed by men.
The ERI-ESI 2018 report also indicates some gender disaggregated data. It reports that 52% of men over 15 are literate compared to 32% of women. However, the data may require further exploration to better understand data that are more complicated. For instance, it reports that 35% of women against 69% of men report having access to electricity at home.
It is worth mentioning that there are a few challenges with gender data. First, many currently defined indicators are better at describing households than people so inequalities within the household are not always visible in the data. This is true for factors such as electrification, clean water, latrines, but also factors such as consumption, income, assets and wealth. Second, there are many issues that are of particular concern to women for which there is relatively little data such as specific security concerns or caregiving or time use. However, Benin does have some useful data on gender through a time use module in EMICOV 2015. This survey found that women report spending 3 hours 35 minutes on domestic activities per day while men average 42 minutes.
Age
Age is a key component linked to exclusion and vulnerability, but it is frequently difficult to find data that is disaggregated by age. The Ministry of Social Affairs and Microfinance is currently developing a digitised database on people benefiting from their programmes, which – if joined with data from ARCH or RAVIP – could provide valuable insights on the status of older people and vulnerable children. Improving death registration rates could also be important in this respect. Better data on disability, illness and death could also provide richer data on how inequalities and age are linked to exclusion.
Indicators on time use also show the intersection of age and gender. The 2015 EMICOV time use section reports that married men over 65 report spending 21 minutes per day on domestic labour compared to three hours for women, a nine-fold difference. Among children aged 6−18, girls report spending 3 hours 34 minutes per day compared to 42 minutes on domestic tasks for boys. [1]
INSAE could collaborate with the UN Statistical Commission’s Titchfield City Group on Ageing Statistics to participate in ongoing discussions on official statistics on ageing and age disaggregation.
Geography
“You can see this 20% of the population in every commune. When you look on the ground, you see that there needs to be more human security, there needs to be more human capital strengthening. There needs to be more activities and resources to ensure that people can participate in our economies and reach their potential.” Nicaise Kotchami Fagnon, Mayor of Dassa-Zoume
The P20 approach can be applied at different levels of government and in different sectors. For instance, it can help those at a departmental level to better understand the wellbeing of their populations, or for ministries (such as the Ministry of Health or the Ministry of Primary and Maternal Education) and civil society organisations to look at the people in the poorest 20% of the populations they aim to serve.
To better understand the relevance of the P20 approach in different contexts, DI visited two departments (Alibori and Borgou) with relatively high P20 headcounts. These visits included discussions and trends with civil society organisations, members of the MdSC who are dedicated to health and education for Borgou and Alibori, as well as key informant interviews with civil society and local officials in health, education, civil registration and welfare. Public and private health clinics, civil registration offices, and a private primary school were visited to better understand key challenges and to better understand data collection procedures.
DI’s latest estimates show that the three northernmost regions have the highest share of their population in the national P20. 33% of Albori’s population is in the P20, and 30% of Borgou’s is. These regions also face other developmental challenges, for instance, only 45% of children aged 6−11 attend school in Alibori. For Borgou, the rate is 62%.
Figure 4: Share of the population in the national P20
A map showing estimates of the share of the population in the P20 in each of Benin’s departments. The southern, coastal region as the lowest rates and the northern region has highest rates, with Alibori, Kandi and Atacora in the north with more than 30 percent of the population in the P20. The southern department Littoral has 0 percent.
Source: Development Initiatives based on Demographic and Health Survey 2017/18 and PovcalNet
With support from the MdSC, we discussed the P20 approach with civil society organisations and local government officials working in health and education.
These conversations helped us identify several major challenges and opportunities in the two departments:
- Support is needed for those not able to afford healthcare while reforms are under way.
- Schools in remote, high poverty areas struggle to recruit and retain adequate numbers of teachers. This may have contributed to the national trend of gross primary enrolment rates decreasing from 97.5% in 2014 to 88.7% in 2017/18. For girls, the rate dropped from 95% to 83.5%.
- Civil registration offices continue to face challenges related to a reliance on paper-based documents and social challenges related to parents being unwilling to register their children’s births but there have been some significant gains in digitisation.
- Administrative data for the health sector and for vital statistics benefits from a strong database at the ministry level; however, data at the facility level is frequently recorded in generic notebooks, raising the possibility of errors in data transmission and recording.
- The government’s new national identification campaign, RAVIP, provides significant potential to ensure that those in need are counted and their progress is monitored. RAVIP is distinct from CRVS but can be a powerful tool for ensuring that all births and deaths are registered.
Geographic disaggregation allows for much more targeted interventions and can permit closer monitoring of progress among those most at risk of being left behind. Averages, even at the department level, can mask significant variation. Monitoring progress at a highly disaggregated level will be required to ensure no one is left behind. This will require the assimilation of non-traditional data sources, such as big data, citizen-generated data or data from other actors.
A recent trend in poverty research has sought to provide granular estimates of poverty based on satellite imagery (using both daytime and nighttime images). Such assessments can be a powerful complement to data collected on the ground but cannot be considered as a viable substitute for engagement with the population on the ground.
Figure 5: P20 headcount by survey cluster in Alibori and Borgou
A map of Alibori and Borgou departments covered with dots indicating where populations have been surveyed. There is a wide range of the share of households in a survey cluster in the P20. The dots show that some pockets have very high shares of the population in the P20 while others do not. Generally, densely populated areas have fewer people in the P20 but in urban areas there are also areas with more people in poverty.
Source: Development initiatives calculations based on the 2017/18 DHS
Disability
People in Benin with disabilities are eligible for benefits through several programmes. Eligibility is determined following the legal definition of disabilities. Comprehensive data on disabilities in Benin is limited. The 2013 Population and Household Census reports that about 92,495 Beninese people have a disability. Disabilities follow the legal definition and are described as being motor disabilities, visual, audio-visual, intellectual or mental illness.
One particularly useful approach from a statistical perspective is to use the UN Statistical Division’s Washington Group on Disability Statistics’ set of six questions to collect data on disability levels. These questions have been used in dozens of countries to provide useful, reliable methods for disaggregating data. They have been included in several household surveys including DHS, MICS, censuses, administrative data or household income/expenditure surveys. These questions have been designed to avoid potentially biases responses to questions due to stigma against the term ‘disability’. To date, these questions have not been used to collect data in Benin. Adding the Washington Group questions to surveys and censuses would be a low-cost intervention with significant improvements in the data available for leaving no one behind.
“In giving voice to civil society organizations on the ground, the challenges of the population can be elevated to the national level. I think the P20 gives us an opportunity. We are going to accelerate the adoption of the approach by civil society organizations.” Fiacre Nouwadjro, Director of Programming, Maison de la Société Civile
Notes
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1
INSAE, 2015, https://www.insae-bj.org/images/docs/insae-publications/autres/Enquete-emploi-du-temps/EMICOV%202015%20VOLET%20EMPLOI%20DU%20TEMPS.pdf (accessed 28 January 2020).Return to source text