Nigeria’s National Bureau of Statistics (NBS) is taking huge strides forward in improving its labor market statistics. With a new methodology that matches international best practices – in terms of questionnaire design, sampling, fieldwork management, and data quality monitoring – NBS is leapfrogging to the frontier of global labor market statistics. The new Nigeria Labour Force Survey (NLFS) will provide policymakers with reliable, timely, and frequent data – not just on whether people are employed, but more importantly on the quality of their work. This is crucial for designing policies that can set Nigeria on a pathway to poverty reduction.
Labor is people’s main vehicle for escaping poverty, especially in low- and middle-income countries. It often contributes the largest share of household income. Collecting accurate labor market statistics is essential for understanding the structure and dynamics of the labor market. This is key to inform poverty-reducing policies. Such policies are particularly important in Nigeria, where about 4 in 10 people live below the national poverty line.
However, labor market statistics are not just about measuring unemployment. In fact, unemployment is not necessarily a good predictor of whether someone is poor. In Nigeria, poor and non-poor Nigerians are about equally likely to work. This is not only the case in Nigeria. In Nigeria’s neighbors and in other global comparators, unemployment – defined as not being employed but actively searching and being available for work – is typically very low, even when poverty is high (Figure 1). Just knowing whether people are employed or unemployed is not enough.
Figure 1. Poverty and unemployment in Nigeria’s neighbors and other comparator countries
Note: Poverty rate calculated using the latest available data and the 2.15 USD 2017 PPP per person per day international poverty line. Unemployment rates shown are the ILO Modelled estimates.
Source: Poverty and Inequality Platform, ILOSTAT, and World Bank estimates.
Instead, knowing about the quality of people’s jobs is much more important. In Nigeria, the wage jobs most able to lift workers out of poverty are extremely rare. Workers also differ in the number of hours they work, their willingness and availability to take on additional work, the specific occupations and activities in which they engage, and whether their work is informal. All of these characteristics are important to understand the types of jobs that are available, which workers can take advantage of them, and how this affects livelihoods – and, in turn, whether someone lives in poverty.
Against this backdrop, NBS – in collaboration with the World Bank and following guidance from the International Labour Organisation (ILO) – has invested strongly in improving labor market statistics. This has culminated in the new NLFS, which deploys an improved methodology that matches international best practices. The survey started collecting data in October 2022. The first results will be made available soon, and will then regularly follow each quarter of data collection. The new NLFS methodology enhances Nigeria’s labor market statistics in at least four ways.
First, the questionnaire now matches the standards put forward by the ILO. This brings Nigeria in line with at least 25 other countries in Sub-Saharan Africa, which have adopted the standards set out by the ILO at the 19th International Conference of Labour Statisticians. The standards include more detailed and consistent indicators of job quality, underemployment, and subsistence agriculture – all of which are essential for policy design. Additionally, following the international standards allows for more meaningful comparisons of Nigeria’s labor market with those of its peers. In particular, the new questionnaire will measure search and availability more explicitly: combined with Nigeria now adopting the one-hour criterion (whereby someone is classed as employed if they worked for pay or profit for at least one hour in the last seven days, or would normally do so), this will produce a more precise, and likely lower, unemployment rate estimate than Nigeria’s previous labor force surveys.
Second, the new methodology reduces non-response. To select households to be interviewed, enumerators need to list all households in randomly pre-selected areas, called enumeration areas or clusters. The new methodology redefined the process of listing, which is now implemented (at most) a few months before the households are actually interviewed. This helps to avoid missing households, which have recently moved into the cluster, or households who have left.
Third, the NLFS fieldwork is organized continuously throughout the year as in many high-income countries, but rarely in Sub-Saharan Africa (Figure 2). This permits smaller field teams that are easier to manage to cover the full sample. It also balances better information coming from different seasons. Moreover, fieldwork implementation has been changed to run each week from Wednesday to Sunday. The helps to reduce proxy responses, whereby one household member responds to the questionnaire on behalf of another. This is important in the context of labor force surveys as unemployment status depends on whether someone searched for a job in the last four weeks and whether they are available in the next two weeks – information that individuals can provide more accurately themselves.
Figure 2. Periodicity in national labor force surveys, 2018
Note: Data labels refer to the number of countries. Bar sizes capture percentages. Not all countries in each region are covered.
Source: International Labour Organisation (ILO) review of national plans to implement the 19th International Conference of Labour Statisticians (ICLS) standards in labor force surveys (July-August 2018).
Fourth, the new NLFS is using state-of-the-art technology that enables real-time monitoring of data quality. By using Computer-Assisted Personal Interviewing – conducting data collection through tablets – it is possible to assess data quality just seconds after the interview is submitted. Automatic dashboards flag any data quality concerns, which can be resolved the same day by communicating directly with the field teams. For example, digital maps of enumeration areas allow households to be georeferenced and enumerators can be tracked to ensure that they are conducting interviews in the correct location. This approach improves data quality considerably by moving the data assurance process “into the field.”
While these improvements are vital for a better understanding of the labor market, they come with one crucial caveat: it will not be possible to compare the new NLFS statistics with previous labor market statistics in Nigeria. Yet the new methodology places Nigeria’s labor market statistics on a more sustainable footing. It also shows how national statistical offices can leapfrog and provide timely, high-frequency, accurate, and detailed statistics on par with more advanced economies. The NLFS can be a shining example – creating inspiration to push the frontier of statistics in all countries.
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