Social Security in Low and Middle-Income Countries: The Role of Household Survey Data

Author(s):  
Agnieszka Sowa ◽  
Christina Behrendt
2022 ◽  
Vol 119 (3) ◽  
pp. e2113658119
Author(s):  
Guanghua Chi ◽  
Han Fang ◽  
Sourav Chatterjee ◽  
Joshua E. Blumenstock

Many critical policy decisions, from strategic investments to the allocation of humanitarian aid, rely on data about the geographic distribution of wealth and poverty. Yet many poverty maps are out of date or exist only at very coarse levels of granularity. Here we develop microestimates of the relative wealth and poverty of the populated surface of all 135 low- and middle-income countries (LMICs) at 2.4 km resolution. The estimates are built by applying machine-learning algorithms to vast and heterogeneous data from satellites, mobile phone networks, and topographic maps, as well as aggregated and deidentified connectivity data from Facebook. We train and calibrate the estimates using nationally representative household survey data from 56 LMICs and then validate their accuracy using four independent sources of household survey data from 18 countries. We also provide confidence intervals for each microestimate to facilitate responsible downstream use. These estimates are provided free for public use in the hope that they enable targeted policy response to the COVID-19 pandemic, provide the foundation for insights into the causes and consequences of economic development and growth, and promote responsible policymaking in support of sustainable development.


2018 ◽  
Vol 33 (3) ◽  
pp. 436-444 ◽  
Author(s):  
John E Ataguba ◽  
Augustine D Asante ◽  
Supon Limwattananon ◽  
Virginia Wiseman

Abstract Financing incidence analysis (FIA) assesses how the burden of health financing is distributed in relation to household ability to pay (ATP). In a progressive financing system, poorer households contribute a smaller proportion of their ATP to finance health services compared to richer households. A system is regressive when the poor contribute proportionately more. Equitable health financing is often associated with progressivity. To conduct a comprehensive FIA, detailed household survey data containing reliable information on both a cardinal measure of household ATP and variables for extracting contributions to health services via taxes, health insurance and out-of-pocket (OOP) payments are required. Further, data on health financing mix are needed to assess overall FIA. Two major approaches to conducting FIA described in this article include the structural progressivity approach that assesses how the share of ATP (e.g. income) spent on health services varies by quantiles, and the effective progressivity approach that uses indices of progressivity such as the Kakwani index. This article provides some detailed practical steps for analysts to conduct FIA. This includes the data requirements, data sources, how to extract or estimate health payments from survey data and the methods for assessing FIA. It also discusses data deficiencies that are common in many low- and middle-income countries (LMICs). The results of FIA are useful in designing policies to achieve an equitable health system.


2013 ◽  
pp. 96-113 ◽  
Author(s):  
David Goldberg ◽  
Graham Thornicroft ◽  
Nadja van Ginneken

Demography ◽  
2019 ◽  
Vol 56 (5) ◽  
pp. 1899-1929 ◽  
Author(s):  
Stephanie R. Psaki ◽  
Erica Soler-Hampejsek ◽  
Jyotirmoy Saha ◽  
Barbara S. Mensch ◽  
Sajeda Amin

Abstract Global investments in girls’ education have been motivated, in part, by an expectation that more-educated women will have smaller and healthier families. However, in many low- and middle-income countries, the timing of school dropout and first birth coincide, resulting in a rapid transition from the role of student to the role of mother for adolescent girls. Despite growing interest in the effects of pregnancy on levels of school dropout, researchers have largely overlooked the potential effect of adolescent childbearing on literacy and numeracy. We hypothesize that becoming a mother soon after leaving school may cause the deterioration of skills gained in school. Using longitudinal data from Bangladesh, Malawi, and Zambia, we test our hypothesis by estimating fixed-effects linear regression models to address the endogeneity in the relationship between childbearing and academic skills. To our knowledge, this is the first study to examine the effects of adolescent childbearing on academic skills in low- and middle-income countries. Our results indicate that among those with low levels of grade attainment, first birth has a negative effect on English literacy and numeracy. Among those with higher levels of grade attainment, we find little evidence of effects of childbearing on academic skills. Childbearing also has little effect on local language literacy. Beyond the immediate loss of English literacy and numeracy, if these skills lead to better health and more economic productivity, then adolescent childbearing may have longer-term repercussions than previously understood. In addition to ongoing efforts to increase educational attainment and school quality in low- and middle-income countries, investments are needed to strengthen the academic skills of adolescent mothers to secure the demographic and economic promise of expanded education for girls and women.


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