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Article

Janine Barden-O'Fallon and Erin McCallum

Monitoring and evaluation (M&E) can be defined as the systematic collection, analysis, and use of data to answer questions about program performance and achievements. An M&E system encompasses all the activities related to setting up, collecting, reporting, and using program information. A robust, well-functioning M&E system can provide program stakeholders with the information necessary to carry out a responsive and successful program intervention and is therefore a critical tool for program management. There are many tools and techniques needed for successful M&E of sexual and reproductive health (SRH) programs. These include frameworks to visually depict the organization of the program, its context and goals, and the logic of its M&E system. Essential practices of M&E also include continuous stakeholder engagement, the development of indicators to measure program activities and outcomes, the collection and use of data to calculate the indicators, and the design and implementation of evaluation research to assess the benefits of the program. Over time, language around “M&E” has evolved, and multiple variations of the phrase are in use, including “MEL” (monitoring, evaluation, and learning), “MER” (monitoring, evaluation, and reporting), and “MERL” (monitoring, evaluation, research, and learning), to name but a few. These terms bring to the forefront a particular emphasis of the M&E system, with an apparent trend toward the use of “MEL” to emphasize the importance of organizational learning. Despite this trend, “M&E” continues to be the most widely known and understood phrase and implicitly includes activities such as learning, research, and reporting within a robust system.

Article

Maya Chandrasekaran, Joseph Cook, and Marc Jeuland

Improved access to safe and reliable water, sanitation, and hygiene (WASH) services in the developing world has many positive health and economic impacts. Two of the key channels through which such impacts manifest are (a) the reduced time burden for the household members, usually women, who are responsible for water collection and transportation, and (b) time saved from not having to defecate in the open, far away from living areas. WASH interventions can produce time savings for low-income households via several specific pathways—for example, through access to closer, more convenient, better quality water and sanitation sources; reduced cost of water delivery to the home; direct conveyance of water via reliable piped supply; or improvements that reduce the time costs of coping with unreliable supply. In existing studies, time savings arising from WASH interventions have primarily been elicited using one of three methods. The first is the time diary approach, which aims to reconstruct an individual’s time use on a recent or typical day. A second approach is direct questioning, where the time spent on a specific activity in a recent (or typical) time period—in this case water collection and WASH management—is recorded. Finally, researchers have begun to use the Global Positioning System and smartphones to track information related to individuals’ movements throughout the day and to determine how those locations map to community water and sanitation facilities. The time savings estimated in published works vary greatly, which may be due to differences in intervention evaluation methods, time elicitation strategies, geographical context, households’ baseline water situation, and the type of improved technology considered. Then, the value of time saved by individuals from use of improved WASH services depends on the opportunity cost of time—that is, the value of the next best use of that time. From a development perspective, alternative time uses for education or income generation may be of particular interest, but other time use (e.g., for leisure, other domestic work, or rest) may also contribute to enhanced household and individual welfare. Unfortunately, in contrast to a fairly robust time valuation literature, especially regarding transportation choices, there is relatively sparse literature on the reallocation of time savings, and its value, from WASH interventions. Many economic analyses therefore fall back on “rule-of-thumb” methods that assume that time savings are worth some fraction, typically approximately 50%, of the prevailing market wage rate. Two methods for time valuation could be used more extensively for valuing WASH-related time savings and burdens in middle- and low-income countries: (a) revealed preference methods based on choices made by individuals between time and other burdens and (b) structured stated preference trade-offs that yield time values based on respondents choices in hypothetical games. Given the shortcomings of the literature, researchers working in this domain should devote greater attention to reporting the nature of the pre-intervention WASH situation in their study setting, describing and validating time use elicitation methods, including, when possible, with objective measures, and more thoroughly considering how time savings are reallocated or contribute to household well-being and reduced poverty. Finally, when conducting cost–benefit analysis of WASH interventions, analysts should use their judgment and knowledge about the specifics of a particular water project when specifying time savings; however, 60% of baseline time spent appears to be a reasonable base case estimate for water supply improvements. For sanitation improvements, the evidence base is thin, but per person time savings of 5–10 minutes per day appears reasonable as a starting point. In each case, sensitivity analysis is recommended around these base case values. Specifically, the value of that time is unlikely to be worth 100% of the household after-tax wage in the policy site, so the analyst should test whether the outcome of a project appraisal would change if time is valued between 25% and 75% of the average after-tax wage rate or, absent that data, the local unskilled wage rate. If the project recommendation changes within this range, the analyst should consider investing in primary research in the policy site, most likely using a stated preference approach. Primary research may also be warranted if distributional consequences of the project (e.g., on women or on the poor) are a central focus of the intervention.