Publication: Small Area Estimation of Poverty and Wealth Using Geospatial Data: What Have We Learned So Far ?
Loading...
Date
2023-07-18
ISSN
Published
2023-07-18
Author(s)
Editor(s)
Abstract
This paper offers a nontechnical review of selected applications that combine survey and geospatial data to generate small area estimates of wealth or poverty. Publicly available data from satellites and phones predicts poverty and wealth accurately across space, when evaluated against census data, and their use in model-based estimates improve the accuracy and efficiency of direct survey estimates. Although the evidence is scant, models based on interpretable features appear to predict at least as well as estimates derived from Convolutional Neural Networks. Estimates for sampled areas are significantly more accurate than those for non-sampled areas due to informative sampling. In general, estimates benefit from using geospatial data at the most disaggregated level possible. Tree-based machine learning methods appear to generate more accurate estimates than linear mixed models. Small area estimates using geospatial data can improve the design of social assistance programs, particularly when the existing targeting system is poorly designed.
Link to Data Set
Citation
“Newhouse, David. 2023. Small Area Estimation of Poverty and Wealth Using Geospatial Data: What Have We Learned So Far ?. Policy Research Working Papers; 10512. © World Bank. http://hdl.handle.net/10986/40028 License: CC BY 3.0 IGO.”
Associated URLs
Associated content
Other publications in this report series
Journal
Journal Volume
Journal Issue
Collections
Related items
Showing items related by metadata.
Publication Small Area Estimation of Poverty in Four West African Countries by Integrating Survey and Geospatial Data(Washington, DC: World Bank, 2024-09-05)The paper presents a methodology to generate experimental small area estimates of poverty in four West African countries: Chad, Guinea, Mali, and Niger. Due to the absence of recent census data in these countries, household-level survey data are integrated with grid-level geospatial data, which are used as covariates in model-based estimation. Leveraging geospatial data enables reporting of poverty estimates more frequently at disaggregated administrative levels and makes estimation feasible in areas for which survey data are not available. The paper leverages the availability of a recent census in Burkina Faso for evaluation purposes. Estimates obtained with the same survey instruments and candidate geospatial covariates as the other four countries are compared against estimates obtained using recent census data and an empirical best predictor under a unit-level model. For Burkina Faso, the estimates obtained using geospatial data are highly correlated with the census-based ones in sampled areas but moderately correlated in non-sampled areas. The results demonstrate that in the absence of recent census data, small area estimation with publicly available geospatial covariates isPublication Small Area Estimation of Non-Monetary Poverty with Geospatial Data(World Bank, Washington, DC, 2020-09)This paper uses data from Sri Lanka and Tanzania to evaluate the benefits of combining household surveys with geographically comprehensive geospatial indicators to generate small area estimates of non-monetary poverty. The preferred estimates are generated by utilizing subarea-level geospatial indicators in a household-level empirical best predictor mixed model with a normalized welfare measure. Mean squared errors are estimated using a parametric bootstrap procedure. The resulting estimates are highly correlated with non-monetary poverty calculated from the full census in both countries, and the gain in precision is comparable to increasing the size of the sample by a factor of three in Sri Lanka and five in Tanzania. The empirical best predictor model moderately underestimates uncertainty, but coverage rates are similar to standard survey-based estimates that assume independent outcomes across clusters. A variety of checks, including adding noise to the welfare measure and model-based and design-based simulations, confirm that the main results are robust. The results demonstrate that combining household survey data with subarea-level geospatial indicators can greatly increase the precision of survey estimates of non-monetary poverty at comparatively low cost.Publication Updating Poverty Estimates at Frequent Intervals in the Absence of Consumption Data : Methods and Illustration with Reference to a Middle-Income Country(World Bank Group, Washington, DC, 2014-09)Obtaining consistent estimates on poverty over time as well as monitoring poverty trends on a timely basis is a priority concern for policy makers. However, these objectives are not readily achieved in practice when household consumption data are neither frequently collected, nor constructed using consistent and transparent criteria. This paper develops a formal framework for survey-to-survey poverty imputation in an attempt to overcome these obstacles, and to elevate the discussion of these methods beyond the largely ad-hoc efforts in the existing literature. The framework introduced here imposes few restrictive assumptions, works with simple variance formulas, provides guidance on the selection of control variables for model building, and can be generally applied to imputation either from one survey to another survey with the same design, or to another survey with a different design. Empirical results analyzing the Household Expenditure and Income Survey and the Unemployment and Employment Survey in Jordan are quite encouraging, with imputation-based poverty estimates closely tracking the direct estimates of poverty.Publication Estimating Poverty in the Absence of Consumption Data : The Case of Liberia(World Bank Group, Washington, DC, 2014-09)In much of the developing world, the demand for high frequency quality household data for poverty monitoring and program design far outstrips the capacity of the statistics bureau to provide such data. In these environments, all available data sources must be leveraged. Most surveys, however, do not collect the detailed consumption data necessary to construct aggregates and poverty lines to measure poverty directly. This paper benefits from a shared listing exercise for two large-scale national household surveys conducted in Liberia in 2007 to explore alternative methodologies to estimate poverty indirectly. The first is an asset-based model that is commonly used in Demographic and Health Surveys. The second is a survey-to-survey imputation that makes use of small area estimation techniques. In addition to a standard base model, separate models are estimated for urban and rural areas and an expanded model that includes climatic variables. Special attention is paid to the inclusion of cell phones, with implications for other assets whose cost and availability may be changing rapidly. The results demonstrate substantial limitations with asset-based indexes, but also leave questions as to the accuracy and stability of imputation models.Publication Small Area Estimation of Monetary Poverty in Mexico Using Satellite Imagery and Machine Learning(World Bank, Washington, DC, 2022-09)Estimates of poverty are an important input into policy formulation in developing countries. The accurate measurement of poverty rates is therefore a first-order problem for development policy. This paper shows that combining satellite imagery with household surveys can improve the precision and accuracy of estimated poverty rates in Mexican municipalities, a level at which the survey is not considered representative. It also shows that a household-level model outperforms other common small area estimation methods. However, poverty estimates in 2015 derived from geospatial data remain less accurate than 2010 estimates derived from household census data. These results indicate that the incorporation of household survey data and widely available satellite imagery can improve on existing poverty estimates in developing countries when census data are old or when patterns of poverty are changing rapidly, even for small subgroups.
Users also downloaded
Showing related downloaded files
Publication Four Decades of Poverty Reduction in China(Washington, DC : World Bank, 2022)Regardless of the poverty line used, the speed and scale of China’s poverty reduction are historically unprecedented. Over the past 40 years, the number of people in China with incomes below US$1.90 per day—the international poverty line as defined by the World Bank to track global extreme poverty—has fallen by close to 800 million, accounting for almost three-quarters of the global reduction in extreme poverty. In 2021, China declared that it had eradicated extreme poverty according to its national poverty threshold, and that it had built a “moderately prosperous society in all respects.” However, a significant number of people remain vulnerable, with incomes below a threshold more typically used to define poverty in upper-middle-income countries. China has set a new goal of approaching common prosperity by 2035, which can help keep the policy focus on the vulnerable population. Four Decades of Poverty Reduction in China: Drivers, Insights for the World, and the Way Ahead explores the key drivers of China’s poverty alleviation achievements and considers the lessons of China’s experience for other developing countries. The report also makes suggestions for China’s future policies. China’s approach to poverty reduction was based on two pillars. The first aimed for broad-based economic transformation to open new economic opportunities and raise average incomes. The second was the recognition that targeted support was needed to alleviate persistent poverty; this support was initially provided to disadvantaged areas and later to individual households. The success of China’s economic development and the associated reduction of poverty also benefited from effective governance, which helped coordinate multiple government agencies and induce cooperation from nongovernment stakeholders. To illustrate the role of broad-based economic transformation for poverty alleviation, separate sections of the report analyze growing agricultural productivity, incremental industrialization, managed urbanization and rural-to-urban migration, and the role of infrastructure.Publication Argentina Country Climate and Development Report(World Bank, Washington, DC, 2022-11)The Argentina Country Climate and Development Report (CCDR) explores opportunities and identifies trade-offs for aligning Argentina’s growth and poverty reduction policies with its commitments on, and its ability to withstand, climate change. It assesses how the country can: reduce its vulnerability to climate shocks through targeted public and private investments and adequation of social protection. The report also shows how Argentina can seize the benefits of a global decarbonization path to sustain a more robust economic growth through further development of Argentina’s potential for renewable energy, energy efficiency actions, the lithium value chain, as well as climate-smart agriculture (and land use) options. Given Argentina’s context, this CCDR focuses on win-win policies and investments, which have large co-benefits or can contribute to raising the country’s growth while helping to adapt the economy, also considering how human capital actions can accompany a just transition.Publication Classroom Assessment to Support Foundational Literacy(Washington, DC: World Bank, 2025-03-21)This document focuses primarily on how classroom assessment activities can measure students’ literacy skills as they progress along a learning trajectory towards reading fluently and with comprehension by the end of primary school grades. The document addresses considerations regarding the design and implementation of early grade reading classroom assessment, provides examples of assessment activities from a variety of countries and contexts, and discusses the importance of incorporating classroom assessment practices into teacher training and professional development opportunities for teachers. The structure of the document is as follows. The first section presents definitions and addresses basic questions on classroom assessment. Section 2 covers the intersection between assessment and early grade reading by discussing how learning assessment can measure early grade reading skills following the reading learning trajectory. Section 3 compares some of the most common early grade literacy assessment tools with respect to the early grade reading skills and developmental phases. Section 4 of the document addresses teacher training considerations in developing, scoring, and using early grade reading assessment. Additional issues in assessing reading skills in the classroom and using assessment results to improve teaching and learning are reviewed in section 5. Throughout the document, country cases are presented to demonstrate how assessment activities can be implemented in the classroom in different contexts.Publication The Growth Elasticity of Poverty(Washington, DC: World Bank, 2024-02-01)On current trends, the future of global poverty reduction will be determined by Sub-Saharan Africa. Yet even during Sub-Saharan Africa’s period of high economic growth — roughly corresponding to the first decade and a half of the 2000s — the extent to which this growth translated into improved living standards for African households was hotly debated. This paper revisits the issue of Sub-Saharan Africa’s relatively low growth elasticity of poverty using a sample of 575 successive and comparable growth spells between 1981 and 2021. The findings confirm that, even controlling for initial differences in poverty, income levels, and inequality, Sub-Saharan Africa consistently had a significantly lower growth elasticity of poverty relative to other regions over this period. The lower growth elasticity of poverty, which has remained unchanged over time, is due to a lower passthrough between growth in gross domestic product per capita (or growth in household final consumption expenditure as measured by national accounts) and growth in household consumption expenditures as measured from surveys. Given the low passthrough of economic growth to households, Africa thus needs higher rates of economic growth than its peer countries in other regions to achieve equal rates of poverty reduction. Given the challenge of achieving this in the current global economic environment, success in reducing global poverty will require a focused effort to strengthen the effect of aggregate economic growth on household welfare in Sub-Saharan Africa. The results suggest that this will require (i) improved provision of basic education services and basic infrastructure, (ii) faster structural transformation, and (iii) a decrease in the occurrence and persistence of violent conflicts.Publication Minimum Wage Policy and Poverty in Indonesia(Published by Oxford University Press on behalf of the World Bank, 2025-02-13)This paper investigates whether the minimum wage policy significantly reduced poverty in Java Island, Indonesia, between 2002 and 2014. Its identification strategy exploits variation in minimum wages over time within pairs of geographically proximate districts. The study finds that the minimum wage has a distributional impact on wage workers just below the 20th percentile up to those in the middle of the wage distribution, with no overall loss of employment. However, the minimum wage policy has no distributional impact on per capita household expenditure and a limited effect on changes in poverty status.