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Countries are increasingly defining health benefits packages (HBPs) as a way of progressing towards Universal Health Coverage (UHC). Resources for health are commonly constrained, so it is imperative to allocate funds as efficiently as possible. We conducted allocative efficiency analyses using the Health Interventions Prioritization tool (HIPtool) to estimate the cost and impact of potential HBPs in three countries. These analyses explore the usefulness of allocative efficiency analysis and HIPtool in particular, in contributing to priority setting discussions. HIPtool is an open-access and open-source allocative efficiency modelling tool. It is preloaded with publicly available data, including data on the 218 cost-effective interventions comprising the Essential UHC package identified in the 3.sup.rd Edition of Disease Control Priorities, and global burden of disease data from the Institute for Health Metrics and Evaluation. For these analyses, the data were adapted to the health systems of Armenia, Côte d'Ivoire and Zimbabwe. Local data replaced global data where possible. Optimized resource allocations were then estimated using the optimization algorithm. In Armenia, optimized spending on UHC interventions could avert 26% more disability-adjusted life years (DALYs), but even highly cost-effective interventions are not funded without an increase in the current health budget. In Côte d'Ivoire, surgical interventions, maternal and child health and health promotion interventions are scaled up under optimized spending with an estimated 22% increase in DALYs averted-mostly at the primary care level. In Zimbabwe, the estimated gain was even higher at 49% of additional DALYs averted through optimized spending. HIPtool applications can assist discussions around spending prioritization, HBP design and primary health care transformation. The analyses provided actionable policy recommendations regarding spending allocations across specific delivery platforms, disease programs and interventions. Resource constraints exacerbated by the COVID-19 pandemic increase the need for formal planning of resource allocation to maximize health benefits.

We review empirical evidence on the ability of decentralization to enhance preference matching and technical efficiency in the provision of health and education in developing countries. Many influential surveys have found that the empirical evidence of decentralization's effects on service delivery is weak, incomplete, and often contradictory. Our own unweighted reading of the literature concurs. However, when we organize quantitative evidence first by substantive theme, and then—crucially—by empirical quality and the credibility of its identification strategy, clear patterns emerge. Higher-quality evidence indicates that decentralization increases technical efficiency across a variety of public services, from student test scores to infant mortality rates. Decentralization also improves preference matching in education, and can do so in health under certain conditions, although there is less evidence for both. We discuss individual studies in some detail. Weighting by quality is especially important when quantitative evidence informs policy-making. Firmer conclusions will require an increased focus on research design, and a deeper examination into the prerequisites and mechanisms of successful reforms.

The usual approach in disability surveys is to screen persons with disability upfront and then ask questions about everyday problems. The objectives of this paper are to demonstrate the impact of screeners on disability rates, to challenge the usual exclusion of persons with mild and moderate disability from disability surveys and to demonstrate the advantage of using an a posteriori cut-off. Using data of a pilot study of the WHO Model Disability Survey (MDS) in Cambodia and the polytomous Rasch model, metric scales of disability were built. The conventional screener approach based on the short disability module of the Washington City Group and the a posteriori cut-off method described in the World Disability Report were compared regarding disability rates. The screener led to imprecise rates and classified persons with mild to moderate disability as non-disabled, although these respondents already experienced important problems in daily life. The a posteriori cut-off applied to the general population sample led to a more precise disability rate and allowed for a differentiation of the performance and needs of persons with mild, moderate and severe disability. This approach can be therefore considered as an inclusive approach suitable to monitor the Convention on the Rights of Persons with Disabilities.

This paper summarizes the literature on the impact of state subsidized or social health insurance schemes that have been offered, mostly on a voluntary basis, to the informal sector in low- and middle-income countries. A substantial number of papers provide estimations of average treatment on the treated effect for insured persons. We summarize papers that correct for the problem of self-selection into insurance and papers that estimate the average intention to treat effect. Summarizing the literature was difficult because of the lack of (1) uniformity in the use of meaningful definitions of outcomes that indicate welfare improvements and (2) clarity in the consideration of selection issues. We find the uptake of insurance schemes, in many cases, to be less than expected. In general, we find no strong evidence of an impact on utilization, protection from financial risk, and health status. However, a few insurance schemes afford significant protection from high levels of out-of-pocket expenditures. In these cases, however, the impact on the poor is weaker. More information is needed to understand the reasons for low enrollment and to explain the limited impact of health insurance among the insured.

We study the impact of China’s new rural pension program on promoting migration of labor by applying a regression discontinuity analysis to this new pension program. The results reveal a perceptible difference in labor migration among adult children whose parents are just above and below the age of pension eligibility: The adult children with a parent just attaining the pension-eligible age are more likely to be labor migrants compared with those with a parent just below the pension-eligible age. We also find that with a pension-eligible parent, the adult children are more likely to have off-farm jobs. These abrupt changes in household behavior at the cutoff suggest that these households are credit constrained. In addition, we find that the pension’s effect on migration is greater among adult children with a parent in poor health; pension-eligible elderly report that they are more likely to use inpatient services when needed and less likely to rely on adult children for care when they are ill. These results suggest that (expectations regarding) providing care for elderly parents has constrained labor migration from China’s rural areas to some extent, and that the new rural pension program has helped to relax this constraint.

In parts of Asia, the South Caucasus, and the Balkans, son preference is strong enough to trigger significant levels of sex selection, resulting in the excess mortality of girls and skewing child sex ratios in favor of boys. Every year, an estimated 1.8 million girls go “missing” because of the widespread use of sex selective practices in these regions. The pervasive use of such practices is reflective of the striking inequities girls face immediately, and it also has possible negative implications for efforts to improve women’s status in the long term. Recognizing this as a public policy concern, governments have employed direct measures such as banning the use of prenatal sex selection technology, and providing financial incentives to families that have girls. This study reviews cross-country experiences to take stock of the direct interventions used and finds no conclusive evidence that they are effective in reducing the higher mortality risk for girls. In fact, bans on the use of sex selection technology may inadvertently worsen the status of the very individuals they intend to protect, and financial incentives to families with girls offer only short-term benefits at most. Instead, what seems to work are policies that indirectly raise the value of daughters. The study also underscores the paucity of causal studies in this literature.

We examine differential progress on health Millennium Development Goals (MDGs) between the poor and the better off within countries. Our findings are based on an original analysis of 235 DHS and MICS surveys spanning 64 developing countries over the 1990–2011 period. We track five health status indicators and seven intervention indicators from all four health MDGs. In approximately three-quarters of countries, the poorest 40 percent have made faster progress than the richest 60 percent on MDG intervention indicators. On average, relative inequality in these indicators has been falling. However, in terms of MDG outcome indicators, in nearly half of the countries, relative inequality has been growing. Moreover, in approximately one-quarter of the countries, the poorest 40 percent have been slipping backwards in absolute terms on both MDG interventions and outcomes. Despite reductions in most countries, relative inequalities in MDG health indicators are still appreciable, with the poor facing higher risks of malnutrition and death in childhood and lower odds of receiving key health interventions.

To collect, compile and evaluate publicly available national health accounts (NHA) reports produced worldwide between 1996 and 2010. We downloaded country-generated NHA reports from the World Health Organization global health expenditure database and the Organisation for Economic Co-operation and Development (OECD) StatExtract website. We also obtained reports from Abt Associates, through contacts in individual countries and through an online search. We compiled data in the four main types used in these reports: (i) financing source; (ii) financing agent; (iii) health function; and (iv) health provider. We combined and adjusted data to conform with OECD's first edition of A system of health accounts manual, (2000). We identified 872 NHA reports from 117 countries containing a total of 2936 matrices for the four data types. Most countries did not provide complete health expenditure data: only 252 of the 872 reports contained data in all four types. Thirty-eight countries reported an average not-specified-by-kind value greater than 20% for all data types and years. Some countries reported substantial year-on-year changes in both the level and composition of health expenditure that were probably produced by data-generation processes. All study data are publicly available at http://vizhub.healthdata.org/nha/. Data from NHA reports on health expenditure are often incomplete and, in some cases, of questionable quality. Better data would help finance ministries allocate resources to health systems, assist health ministries in allocating capital within the health sector and enable researchers to make accurate comparisons between health systems.

We estimate the impact of changes in unearned income on the height and weight of young children in a developing country. As a source of income variation we use a change in the eligibility criteria for receipt of an unconditional cash transfer in Ecuador. Two years after families lost the transfer, which they had received for seven years, their young children weigh less and are shorter and more likely to be stunted than young children in families that kept the cash transfer. We find no statistically significant effect on young children's height and weight two years after gaining the cash transfer. Information on household expenditures suggests that a reduction of food expenditures by households that lost the transfer is the main mechanism behind this finding.

Estimation of empirical relationships is prone to bias. Economists have carefully studied sources of bias in structural and quasi-experimental approaches, but the randomized control trial (RCT) has only begun to receive such scrutiny. In this paper, we argue that several lessons from medicine, derived from analysis of thousands of RCTs establishing a clear link between certain practices and biased estimates, can be used to reduce the risk of bias in economics RCTs. We identify the subset of these lessons applicable to economics and use them to assess risk of bias in estimates from economics RCTs published between 2001 and 2011. In comparison to medical studies, we find most economics studies do not report important details on study design necessary to assess risk of bias. Many report practices that suggest risk of bias, though this does not necessarily mean bias resulted. We conclude with suggestions on how to remedy these issues.