Statistics

This paper measures and analyzes management practices in the Kenyan health care sector, drawing on a nationally representative survey and linked administrative data. The paper adapts the World Management Survey to measure management quality in primary health care facilities and hospitals, surveying 429 primary health care facilities and 73 hospitals. Primary health care facilities are the primary point of contact for most patients, providing treatment for common infectious diseases and chronic conditions, as well as services related to maternal and child health. Management quality is low on average, and the distribution is highly compressed. The analysis uses administrative data to test the ..

Horizontal inequity occurs when employees and self-employed workers with the same income end up with different effective tax burdens, due to the difficulty of enforcing taxes on the self-employed. Based on detailed micro-tax simulation models integrated with household surveys in 25 developing countries, this paper shows that tax systems incur large horizontal inequities in practice, and reforms that improve vertical equity worsen horizontal equity by a comparable amount. In-person and online surveys across multiple countries reveal widespread concern about horizontal equity. Randomized information treatments heighten this concern but do not shift tax preferences toward addressing horizontal ..

This paper studies how firms respond to the announcement of the European Union’s Carbon Border Adjustment Mechanism (CBAM), focusing on Turkish manufacturing firms with substantial exposure to the EU market. Exploiting variation in firms’ pre-announcement exposure to CBAM-covered exports, the paper estimates difference-in-differences models using detailed firm–product–destination trade data. The findings show that more exposed firms exhibit relatively lower post-announcement exports of CBAM-covered products to the European Union (EU) and relatively higher exports to non-EU destinations, consistent with a market-switching response. These differences are economically meaningful: a one..

This paper examines the effects of drought shocks on unintended pregnancies across 18 countries in Sub-Saharan Africa. The results show that drought exposure increases the likelihood of unintended pregnancy by one to two percentage points (about 3 to 6 percent), depending on the specification. The analysis further finds that children born from unintended pregnancies are less likely to receive antenatal care, less likely to be delivered in health facilities, and more vulnerable to illness. The findings also show that unintended pregnancies have implications for women’s labor market outcomes. Overall, the findings indicate that drought shocks intensify women’s economic and reproductive vul..

Industrial robots are rapidly changing global production processes, with large implications for patterns of foreign direct investments. The impact is ambiguous a priori. On the one hand, robotization may boost foreign direct investments since firms that have invested in robots increase their demand for complementary inputs. On the other hand, robotization may dampen foreign direct investments since firms have weaker incentives to outsource selected inputs and/or tasks. This paper finds that robotization at home boosts foreign direct investments, based on bilateral foreign direct investments data from 2003–21 across 65 countries. To uncover the underlying mechanism, the effect on foreign di..

Social networks are a critical driver of women’s economic empowerment, particularly in contexts where women face mobility and normative constraints. Using baseline data from an impact evaluation in Nigeria, this study examines the association between social capital and labor market outcomes among vulnerable women, including those affected by HIV, survivors of gender-based violence, and caregivers of children living with HIV or exposed to sexual violence. Logistic and OLS models along with the community fixed effects are used to estimate the associations between social network characteristics and four labor market outcomes. The study finds that women with larger networks—specifically, hav..

This paper examines whether automatic credit approval can reduce gender bias in lending to small and medium-sized enterprises. The study team collaborated with a bank in Peru that piloted a new screening tool to generate psychometric credit scores. Applicants who scored above a predefined threshold were automatically offered a loan with a size tied to their score, and those below the threshold were assessed by a loan officer. Using a regression discontinuity design and credit bureau data, the paper compares loan offers and loan sizes of female and male applicants within a narrow window around the automatic approval threshold. The results show that female applicants below the threshold are le..

Accurate and scalable methods for land area measurement are essential for estimating key agricultural indicators, such as crop yields, as well as understanding agricultural relationships. A significant body of literature has demonstrated systematic bias in farmer estimates of land area, the most inexpensive option, and at the same time provided evidence supporting the use of handheld GPS units for objective measurement. Despite the successful adoption of handheld GPS measurement in many survey operations, new tablet-based tools offer potential for smoother, more cost-effective measurement of land area. Using data collected in a methodological experiment in Uganda, this study evaluates the ac..

Fine-grained spatial data are critical for informed decision-making in domains ranging from economic planning to environmental management. However, many statistics are only available for coarse administrative units, necessitating techniques for fine-scale spatial disaggregation. This paper introduces a graph neural network (GNN) based framework for disaggregating aggregated indicators to a finer spatial resolution. The GNN approach leverages graph representations of spatial units to incorporate both feature information and spatial relationships, addressing challenges of heterogeneity and data sparsity. The approach also adopts the H3 hierarchical hexagonal indexing system to define fine-reso..

In many low-income countries, consumption surveys are too infrequent to track poverty during economic shocks. Survey-to-survey imputation can fill this gap, but its reliability depends on whether prediction models estimated in one period remain valid in another. This paper develops a formal identification framework for the transportability of survey-to-survey estimators and shows that failures during crises arise primarily from missing shock-responsive information rather than from insufficient model flexibility. When such information is omitted, both linear models and flexible learners yield biased poverty estimates. When fast-changing proxy variables that track unobserved welfare changes ar..

Energy access in conflict-affected states carries a cost premium — yet there is little evidence of its magnitude and whether it can, at least partially, be mitigated. Analyzing 923 World Bank–financed solar photovoltaic installations across the Republic of Yemen between 2019 and 2025, this analysis finds that project-level learning systematically reduces conflict-linked costs, including in the most volatile regions. The aggregate price decomposition attributes 16.8 percentage points of cost reduction to project-level factors. More generally, a Shapley Machine Learning decomposition of project-level cost variation confirms that project-level learning is the most powerful predictor, explai..

Economic growth is the key driver of poverty reduction. At the same time, economic growth still increases greenhouse gas emissions, which are expected to increase poverty in the future. To quantify the combined effect of these two mechanisms, this paper introduces emissions-adjusted poverty, a new measure that sums a country’s poverty with the future global poverty that the country’s emissions will create. The measure reaches zero when poverty is eliminated within a country and its emissions hit net-zero. Its key parameter is a human-centric analogue to the social cost of carbon, quantifying how current emissions raise future global poverty. The paper estimates that each kiloton of carbo..