Individual-disaggregated survey data on economic outcomes—including employment, time use, asset ownership, and access to financial services—are critical to understanding and addressing mutually reinforcing gender inequities in economic and social life. However, substantial data gaps persist in these areas, particularly in multi-topic household surveys that would otherwise allow an in-depth analysis of different factors affecting individuals’ welfare and economic opportunities.
To address these gaps, the World Bank Living Standards Measurement Study‐Plus (LSMS+) program has been working to enhance the availability and quality of individual-disaggregated survey data collected in low- and middle-income countries —initially with a focus on men’s and women’s ownership of and rights to physical and financial assets and labor market outcomes. Since its inception, LSMS+ has been working in three tracks:
- supporting national statistical offices (NSOs) in operationalizing international recommendations on individual-disaggregated survey data collection—with an emphasis on conducting intra-household, private interviews with adult household members and minimizing the use of proxy respondents,
- improving methods and providing guidance for individual-disaggregated survey data collection, including on asset ownership and time use, and
- conducting and disseminating policy-oriented research to highlight the value of improved individual-disaggregated survey data.
Table 1 presents an overview of national surveys supported by the LSMS+ thus far. The anonymized unit-record survey data and documentation from these surveys are publicly available on the World Bank Microdata Library, and can be accessed HERE.
Notes: (1) Surveys also received technical and financial support from LSMS-ISA and LSMS+; and using the World Bank Survey Solutions Computer-Assisted Personal Interviewing (CAPI) platform. (2) All surveys, as well as the sample size for individual interviews supported by LSMS+, are nationally representative.
Recently, LSMS+ launched three new reports tied to these activities:
- Findings from LSMS+ supported surveys in Sub-Saharan Africa (Malawi, Tanzania, and Ethiopia),
- Findings from LSMS+ supported survey in Cambodia,
- Program overview and recommendations for intra-household, individual-disaggregated survey data collection on asset ownership and labor market outcomes, building on existing international recommendations on these topics.
Below are selected findings from these publications:
(1) Privately interviewing adults on asset ownership, versus interviewing a single, most knowledgeable household member as commonly done in surveys, can lead to marked differences in how asset ownership is measured among men and women.
In Malawi, for example, the LSMS+/IHPS was conducted concurrently with another national survey, the Fourth Integrated Household Survey (IHS4) that asked only one “most knowledgeable” respondent about household members’ asset ownership and rights. Kilic et al. (2020a) found that the IHS4 resulted in higher rates of exclusive ownership of agricultural land among men, and lower rates of joint ownership among women, compared to the IHPS.
On financial inclusion, scaling up individual-level data collection on financial account ownership in the Malawi LSMS+ also leads to higher household-level estimates of account ownership, compared to the IHS4—with greater differences for better-off households as measured by consumption expenditure.
Figure 1. Malawi: share of households with financial account in LSMS+ and comparison survey (IHS4), by percentile of per capita expenditure
One concern with intra-household level data collection on assets is that household members may disagree over who owns or has rights to specific assets such as land. Among married couples interviewed separately in the LSMS+, however, there was a relatively high share of agreement over joint and exclusive ownership of land: for about 90% of land parcels in Cambodia and Ethiopia, and about 70% of parcels in Malawi and Tanzania.
(2) A greater emphasis placed on eliciting self-reported information and conducting private interviews with adult household members has implications for men’s and women’s reporting of work and employment.
Proxy reporting of labor in both the Tanzania and Malawi LSMS+ surveys were substantially lower than other national surveys in these countries (Figure 2). In the Cambodia LSMS+ as well, more than 90% of respondents self-reported in the labor module. Kilic et al. (2020b) also show that, in Malawi, these differences lead to significantly higher reporting of employment in the IHPS (the LSMS+) compared to IHS4 (business-as-usual), with stronger effects for women and for a longer (12‐month) recall period.
Figure 2. Share of respondents reporting by proxy in the labor module, LSMS+ versus other recent national surveys
(3) The labor and time use modules in the LSMS+ supported surveys cast a brighter light on unpaid work.
In Malawi, Tanzania, and Ethiopia, the LSMS+ highlights greater time spent by both men and women in non-market work such as water and fuel collection than other recent national surveys in these countries. Additionally, the 24-hour time-use diary in Cambodia, where all respondents self-reported, reveals important connections to other areas of individual-level data collection. Figure 3 shows the incidence of unpaid work during working hours is much higher for employed women than men. Additional findings from the Cambodia LSMS+ show that ownership of assets (specifically, financial accounts and vehicles) is associated with less unpaid activity for women, especially among those in off-farm work—underscoring the importance of individual-level data collection across both of these areas to better understand women’s economic opportunities and mobility.
Figure 3. Cambodia LSMS+: share of men and women reporting time in unpaid work in the time use module, in 15-minute increments, and for different labor categories
(4) Additional data on nuances of land ownership and rights reveal important gender inequalities.
The enumerator training for the LSMS+ surveys underscored that household members’ responses to different constructs of ownership and rights questions should not necessarily be the same—just because an individual has the right to make improvements to/invest in a parcel does not necessarily mean they have the right to sell it. The LSMS+ supported surveys revealed some gender differences in land ownership, but wider gender inequalities among landowners in rights to sell and bequeath. Figure 4 shows that this is particularly the case in Sub-Saharan Africa.
Figure 4. Share of landowners that do not have sell or bequeath rights
Overall, the LSMS+ supported surveys have highlighted important gender inequalities in economic opportunities, and, in turn, avenues for gender-sensitive policy design. Looking forward, we are continuing to:
- Support NSOs in individual-disaggregated survey data collection on asset ownership and labor—with the Sudan Labor Market Panel Survey being the first survey supported by LSMS+ in 2021 in partnership with the Sudan Central Bureau of Statistics and the Economic Research Forum,
- Conduct methodological research to develop improved methods and guidance for individual-disaggregated survey data collection on asset ownership and time use—with the activities over the next 12 months being mostly based on the existing LSMS+ survey data and a new methodological survey experiment on time use measurement that will be fielded later in 2021 in Malawi, and
- Undertake research based on the existing LSMS+ survey data to highlight the value of improved individual-disaggregated survey data for development research and policymaking—with the short-term research agenda being focused on wealth inequality and gender wealth gap, and links between intra-household differences in bargaining power and time use.
For more information on LSMS+, please click HERE. For additional country-level sex-disaggregated data and gender statistics on access to economic opportunities, please visit the World Bank Gender Data Portal along with a tip sheet to help guide you through the statistics available.
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