No open-access location is known for this record yet.
No open-access location is known for this record yet.
No AccessStand Alone Books1 Feb 2013Proxy means tests for targeting social programsSimulations and speculationAuthors/Editors: Margaret E. Grosh and Judy L. BakerMargaret E. Grosh and Judy L. Bakerhttps://doi.org/10.1596/0-8213-3313-5SectionsAboutPDF (0.2 MB) ToolsAdd to favoritesDownload CitationsTrack Citations ShareFacebookTwitterLinked In Abstract:This paper examines how a proxy means test might work in targeting social programs. The term "proxy means test" is used to describe a situation where information on household or individual characteristics correlated with welfare levels is used in a formal algorithm to proxy household income, welfare or need. Given the administrative difficulties associated with sophisticated means tests and the inaccuracy of simple means tests, the idea of using other household characteristics as proxies for income is appealing. This paper carries out simulations on data sets from Jamaica, Bolivia and Peru to explore what kind of information can best be used in a proxy means test and how accurate such tests might be expected to be. The results show that household characteristics can serve as reasonable proxies for information on income in assessing eligibility for social programs. More information is generally better than less, though there are diminishing returns. The proxy systems all have significant errors of undercoverage, but they cut down leakages so much that the impact on poverty is better with imperfect targeting than with none. Some fine-tuning of the basic system, such as calibrating for the poorest half of the population, improves results considerably. In Jamaica, calibrating separately for rural and urban areas did not improve results. As assumed 25 percent level of distortion of information had no effect at all on targeting outcomes. The paper describes the practical experience with Chile's Ficha CAS system, one of the oldest and best-known proxy means tests in the developing world. It also discusses in qualitative terms some of the strategic choices and implications in setting up proxy means tests of different sorts. The amount of staff time, the amount of training required for staff at different levels, the number of computers, and the transport and communications links required will vary greatly depending on the decision regarding how the system should be set up. FiguresreferencesRecommendeddetailsCited byMachine learning and data augmentation in the proxy means test for poverty targetingStatistical Journal of the IAOS, Vol.39, No.4High-resolution rural poverty mapping in Pakistan with ensemble deep learningPLOS ONE, Vol.18, No.44 April 2023Screening for eligibility: access and resistance in Istanbul's food banksJournal of Cultural Economy, Vol.16, No.21 March 2023Program targeting with machine learning and mobile phone data: Evidence from an anti-poverty intervention in AfghanistanJournal of Development Economics, Vol.161Selective inclusion in cash transfer programs: Unintended consequences for social cohesionWorld Development, Vol.157Geographic microtargeting of social assistance with high-resolution poverty mapsProceedings of the National Academy of Sciences, Vol.119, No.321 August 2022When Poverty Reduction Meets Democracy: An Investigation into the Use of Different Evaluation Methods for Assessing the Effectiveness of a Social ProgramAsian Economic Papers, Vol.21, No.220 June 2022Predicting poverty and malnutrition for targeting, mapping, monitoring, and early warningApplied Economic Perspectives and Policy, Vol.44, No.215 July 2021Machine learning and phone data can improve targeting of humanitarian aidNature, Vol.603, No.790316 March 2022Assessing the Livelihood Empowerment Against Poverty (LEAP) program as a conditional income transfer: a search for a conceptual frameworkInternational Journal of Social Economics, Vol.49, No.45 January 2022Inequity and benefit incidence analysis in healthcare use among Syrian refugees in EgyptConflict and Health, Vol.15, No.12 November 2021Efficiency, Legitimacy, and Impacts of Targeting Methods: Evidence from an Experiment in NigerWorld Bank Economic Review, Vol.35, No.417 November 2021Targeting for Social Safety Nets: Evidence from Nine Programs in the Sahel17 November 2021Productivity and Health: Physical Activity as a Measure of EffortThe World Bank Economic Review, Vol.35, No.311 June 2020Locked down and locked out: Repurposing social assistance as emergency relief to informal workersWorld Development, Vol.139Beyond Manipulation: Administrative Sorting in Regression Discontinuity DesignsJournal of Causal Inference, Vol.8, No.123 December 2020Community-Based versus Statistical Targeting of Anti-Poverty Programs: Evidence from Burkina FasoJournal of African Economies, Vol.29, No.310 December 2019Assesing efficiency of targeting in social services in Federation of Bosnia and HerzegovinaCroatian Review of Economic, Business and Social Statistics, Vol.6, No.18 June 2020Adaptive Safety Nets for Rural Africa: Drought-Sensitive Targeting with Sparse Data24 December 2019Finding the Poor vs. Measuring Their Poverty: Exploring the Drivers of Targeting Effectiveness in IndonesiaWorld Bank Economic Review, Vol.33, No.315 October 2019How Can African Governments Reach Poor Farmers with Fertiliser Subsidies? Exploring a Targeting Approach in GhanaThe Journal of Development Studies, Vol.55, No.924 October 2018A Proxy Means Test for Sri Lanka6 November 2018Retooling Poverty Targeting Using Out-of-Sample Validation and Machine LearningWorld Bank Economic Review, Vol.32, No.313 November 2018Impacts of forests on children's diet in rural areas across 27 developing countriesScience Advances, Vol.4, No.8Proxy Means Tests to Identify the Income Poor: Application for the Case of VietnamJournal of Asian and African Studies, Vol.53, No.429 May 2017Finding the Poor vs. Measuring their Poverty: Exploring the Drivers of Targeting Effectiveness in Indonesia8 March 2018A Poor Means Test? Econometric Targeting in Africa4 January 2017Retooling Poverty Targeting Using Out-of-Sample Validation and Machine Learning5 December 2016Targeting vulnerable households in urban Burkina Faso: effectiveness of geographical criteria but not of proxy-means testingHealth Policy and Planning, Vol.31, No.529 October 2015Evolution of health coverage in Mexico: evidence of progress and challenges in the Mexican health systemHealth Policy and Planning, Vol.31, No.129 March 2015Decentralized versus Statistical Targeting of Anti-Poverty Programs: Evidence from Burkina FasoSSRN Electronic JournalA Comparison of Two Simple, Low-Cost Ways for Local, Pro-Poor Organizations to Measure the Poverty of Their ParticipantsSocial Indicators Research, Vol.124, No.213 November 2014Reducing child poverty and assessing targeting performance: Governmental cash transfers in T aiwanInternational Journal of Social Welfare, Vol.24, No.17 August 2014Who Is Poorest? An Asset‐based Analysis of Multidimensional WellbeingDevelopment Policy Review, Vol.33, No.15 December 2014Housing Consumption and Urbanization16 December 2014Health Information, Treatment, and Worker Productivity: Experimental Evidence from Malaria Testing and Treatment among Nigerian Sugarcane Cutters2 February 2015Estimating Poverty in the Absence of Consumption Data: The Case of Liberia14 October 2014Poverty identification: practice and policy implications in V ietnamAsian-Pacific Economic Literature, Vol.28, No.127 April 2014Selecting a Targeting Method to Identify BPL Households in IndiaSocial Indicators Research, Vol.112, No.216 February 2013Improving the Targeting of Social Assistance in Albania: Evidence from Micro-simulations6 November 2012Leaving the Safety Net: An Analysis of Dropouts in an Urban Conditional Cash Transfer ProgramWorld Development, Vol.40, No.12Operational Models for Improving the Targeting Efficiency of Development Policies: A Systematic Comparison of Different Estimation Methods Using Out-of-sample TestsThe European Journal of Development Research, Vol.24, No.325 August 2011Targeting Cash Transfer Programs for an Older PopulationSSRN Electronic JournalSelecting a Targeting Method to Identify BPL Households in IndiaSSRN Electronic JournalTo target or not to target? The costs, benefits, and impacts of indicator-based targetingFood Policy, Vol.36, No.5Refining Targeting against Poverty Evidence from TunisiaOxford Bulletin of Economics and Statistics, Vol.72, No.3Who wants to work in a rural health post? The role of intrinsic motivation, rural background and faith-based institutions in Ethiopia and RwandaBulletin of the World Health Organization, Vol.88, No.5Agriculture Income Assessment for the Purpose of Social Assistance: The Case of UkraineSSRN Electronic JournalHousehold targeting in practice: The Nicaraguan Red de Protección SocialJournal of International Development, Vol.21, No.11 October 2008Sometimes more equal than others: how health inequalities depend on the choice of welfare indicatorHealth Economics, Vol.15, No.331 October 2005Public Spending, Pro-Poor Growth and Poverty Reduction in Tunisia: A Multilevel AnalysisSSRN Electronic JournalEquity and Policy Effectiveness with Imperfect TargetingSSRN Electronic JournalTargeting Performance of Three Large-Scale, Nutrition-Oriented Social Programs in Central America and MexicoFood and Nutrition Bulletin, Vol.23, No.228 November 2016Foreign aid and poverty in Bosnia and Herzegovina: Targeting simulations and policy implicationsEuropean Economic Review, Vol.45, No.4-6Generating Disaggregated Poverty Maps: An Application to VietnamWorld Development, Vol.28, No.2Needs-based Targeting without Knowing Household Incomes: How Would it Work in Russia?Urban Studies, Vol.36, No.112 July 2016 View Published: July 1995 ISBN: 978-0-8213-3313-6 Copyright & Permissions Related Regions Latin America & Caribbean Related Countries Bolivia Jamaica Related Topics Health Nutrition and Population Poverty Reduction Rural Development KeywordsWELFAREHOUSEHOLD DATAHOUSEHOLD INCOMESOCIAL SERVICESPOVERTYRURAL AREASURBAN AREASTESTSTRAININGTRANSPORTCOMMUNICATIONSIMULATIONSPECULATIONINCOMEMEANS TESTSPOORPOVERTY LINEPOVERTY LINESPOVERTY MEASURESRURALSOCIAL PROGRAMSTARGETINGWELFARE INDICATORS PDF DownloadLoading ...
Loading…
Stored only when both papers are in the corpus — 91 citations exist upstream.
Imported from OpenAlex (CC0) — nothing here is generated.