This paper proposes a framework that examines three levels of access to infrastructure -- nominal, effective, and quality-adjusted access. Most conventional indicators measure nominal access --whether a household has physical access to a service in or near the house.
... See More + By contrast, effective access incorporates functionality and use of service, and quality-adjusted access raises the bar by incorporating quality metrics. The paper illustrates the analytical utility of this conceptual framework by deploying data from a survey of 14,200 households in 15 Kenyan cities in 2012-13. First, the analysis finds that these cities fall far short of delivering universal access to basic infrastructure. Second, for most services there a large gap -- 3 to 41 percentage points—between nominal and effective access. When the bar is raised to include quality of service, the drop-off in the proportion of those with access is even more dramatic. These findings suggest that conventional nominal measures overreport the level of service in urban communities, and that current approaches to infrastructure delivery might be enhancing availability of a service without ensuring that the service is usable -- that is, functional, reliable and affordable. Third, there is an infrastructure access gap between nonpoor and poor households, as well as formal and informal settlements. Fourth, hedonic regression analysis reveals that four services -- electricity, water, toilets, and garbage collection—are associated with higher rents. The analysis has broader implications for understanding and measuring service access. It raises important questions as global discussions turn to indicators for the Sustainable Development Goals.
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Policy Research Working Paper WPS8750 FEB 19, 2019
Gulyani,Sumila; Ryan Rizvi,Andrea C.; Talukdar,DebabrataDisclosed
In the past decade, hundreds of impact evaluation studies have measured the learning outcomes of education interventions in developing countries.
... See More + The impact magnitudes are often reported in terms of "standard deviations," making them difficult to communicate to policy makers beyond education specialists. This paper proposes two approaches to demonstrate the effectiveness of learning interventions, one in "equivalent years of schooling" and another in the net present value of potential increased lifetime earnings. The results show that in a sample of low- and middle-income countries, one standard deviation gain in literacy skill is associated with between 4.7 and 6.8 additional years of schooling, depending on the estimation method. In other words, over the course of a business-as-usual school year, students learn between 0.15 and 0.21 standard deviation of literacy ability. Using that metric to translate the impact of interventions, a median structured pedagogy intervention increases learning by the equivalent of between 0.6 and 0.9 year of business-as-usual schooling. The results further show that even modest gains in standard deviations of learning -- if sustained over time -- may have sizeable impacts on individual earnings and poverty reduction, and that conversion into a non-education metric should help policy makers and non-specialists better understand the potential benefits of increased learning.
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Policy Research Working Paper WPS8752 FEB 19, 2019
This paper explores the effects of a large increase in the national minimum wage in Turkey on firms’ exit rates from the formal economy. The analysis exploits a unique, linked employer-employee panel data set of the universe of registered firms in all sectors of the economy.
... See More + The causal impact of the minimum wage hike is estimated by using pre-policy information on the full distribution of wages in registered firms as a measure of exposure to treatment, and by implementing a difference-in-difference estimation strategy. The minimum wage hike is found to increase firms’ exit rates from the formal economy by 12 percent. This suggests that firm exits attributable to the minimum wage hike could account for up to one-third of the total formal employment destruction that occurred between 2015 and 2016. The minimum wage effect on exit rates is found to be larger among firms with low productivity levels before the policy change, and in sectors where profit margins are low. A range of placebo tests and robustness checks indicate that these findings are not driven by trends in unobservable characteristics correlated with exposure to the minimum wage hike.
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Policy Research Working Paper WPS8749 FEB 15, 2019
Students around the world are going to school but are not learning -- an emerging gap in human capital formation. To understand this gap, this paper introduces a new data set measuring learning in 164 countries and territories.
... See More + The data cover 98 percent of the world's population from 2000 to 2017. The data set will be publicly available and updated annually by the World Bank. The paper presents several stylized facts in a first application of the data: (a) although enrollment has increased worldwide, learning has stagnated; (b) girls outperform boys on learning -- a positive gender gap -- in contrast to a negative gender gap observed for schooling; (c) learning is associated with growth on a global scale; (d) associations with growth are heterogenous; and (e) human capital accounts for up to a third of cross-country income differences -- a middle ground in the recent development accounting literature. These stylized facts demonstrate the potential of the data to reveal new insights into the relationship between human capital and economic development.
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Policy Research Working Paper WPS8742 FEB 14, 2019
Somalia is highly data-deprived, leaving policy makers to operate in a statistical vacuum. To overcome this challenge, the World Bank implemented wave 2 of the Somalia High Frequency Survey to better understand livelihoods and vulnerabilities and, especially, to estimate national poverty indicators.
... See More + The specific context of insecurity and lack of statistical infrastructure in Somalia posed several challenges for implementing a household survey and measuring poverty. This paper outlines how these challenges were overcome in wave 2 of the Somali High Frequency Survey through methodological and technological adaptations in four areas. First, in the absence of a recent census, no exhaustive lists of census enumeration areas along with population estimates existed, creating challenges to derive a probability-based representative sample. Therefore, geospatial techniques and high-resolution imagery were used to model the spatial population distribution, build a probability-based population sampling frame, and generate enumeration areas are to overcome the lack of a recent population census. Second, although some areas remained completely inaccessible due to insecurity, even more accessible areas held potential risks to the safety of field staff and survey respondents, so that time spent in these areas has to be minimized. To address security concerns, the survey adapted logistical arrangements, sampling strategy using micro-listing, and questionnaire design to limit time on the ground based on the Rapid Consumption Methodology. Third, poverty in completely inaccessible areas had to be estimated by other means. Therefore, the Somali High Frequency Survey relies on correlates derived from satellite imagery and other geo-spatial data to estimate poverty in such areas. Finally, the nonstationary nature of the nomadic population required special sampling strategies.
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Working Paper (Numbered Series) 134661 FEB 14, 2019
