Luoto, JillChristiaensen, LucStifel, DavidLanjouw, Peter2012-03-192012-03-192011-06-01https://hdl.handle.net/10986/3447Tracking poverty is predicated on the availability of comparable consumption data and reliable price deflators. However, regular series of strictly comparable data are only rarely available. Price deflators are also often missing or disputed. In response, poverty prediction methods that track consumption correlates as opposed to consumption itself have been developed. These methods typically assume that the estimated relation between consumption and its predictors is stable over time -- an assumption that cannot usually be tested directly. This study analyzes the performance of poverty prediction models based on small area estimation techniques. Predicted poverty estimates are compared with directly observed levels in two country settings where data comparability over time is not a problem. Prediction models that employ either non-staple food or non-food expenditures or a full set of assets as predictors are found to yield poverty estimates that match observed poverty well. This offers some support to the use of such methods to approximate the evolution of poverty. Two further country examples illustrate how an application of the method employing models based on household assets can help to adjudicate between alternative price deflators.CC BY 3.0 IGOABSOLUTE TERMSABSOLUTE VALUEARREARSASSET CLASSASSET CLASSESASSET HOLDINGSBANK POLICYCHANGES IN POVERTYCONSUMER DURABLESCONSUMPTION DATACONSUMPTION EXPENDITURESCONSUMPTION MEASURECONSUMPTION PRICECONSUMPTION SMOOTHINGCOUNTRY LEVELDECLINE IN POVERTYDEPENDENT VARIABLEDEVALUATIONDEVELOPMENT ECONOMICSDEVELOPMENT POLICYDEVELOPMENT RESEARCHDROP IN POVERTYDURABLESECONOMIC GROWTHERROR TERMERROR TERMSESTIMATION TECHNIQUESEXPLANATORY VARIABLESFINANCIAL CRISISFINANCIAL MARKETSFOOD CONSUMPTIONFOOD EXPENDITUREFOOD EXPENDITURESFOOD ITEMSHOUSEHOLD BUDGETHOUSEHOLD CONSUMPTIONHOUSEHOLD DEMOGRAPHICSHOUSEHOLD HEADHOUSEHOLD INCOMEHOUSEHOLD SURVEYHOUSEHOLD SURVEYSHOUSEHOLD WELFAREHOUSINGHUMAN DEVELOPMENTHUMAN DEVELOPMENT REPORTINCIDENCE OF POVERTYINCOMEINCOME ELASTICITYINCOME POVERTYINCOME SHOCKSINEQUALITYINFLATIONINFLATION INDICESINTERNATIONAL BANKINTERNATIONAL DEVELOPMENTLIVING STANDARDSMEASURING POVERTYMEATMODEL SPECIFICATIONSNATIONAL POVERTYNATIONAL POVERTY LINENUTRITIONAL STATUSPENSIONSPER CAPITA CONSUMPTIONPHYSICAL ASSETSPOINT ESTIMATESPOLICY RESEARCHPOORPOOR AREAPOOR AREA DEVELOPMENT PROGRAMPOOR PEOPLEPOVERTY ANALYSISPOVERTY CHANGEPOVERTY CHANGESPOVERTY COMPARISONSPOVERTY DEBATEPOVERTY DECLINEPOVERTY DYNAMICSPOVERTY ESTIMATESPOVERTY GAPPOVERTY HEADPOVERTY INCIDENCEPOVERTY INCIDENCE ACROSS PROVINCESPOVERTY INDICATORSPOVERTY LEVELSPOVERTY LINESPOVERTY MAPPINGPOVERTY MAPSPOVERTY MEASUREPOVERTY MEASUREMENTPOVERTY MEASURESPOVERTY RATEPOVERTY RATESPOVERTY REDUCTIONQUALITY OF LIFEREDUCTION IN POVERTYREGIONAL LEVELSREGIONAL LOCATIONREGIONAL PERSPECTIVERETURNSRURALRURAL AREASRURAL DISTRICTSRURAL HOUSEHOLDRURAL HOUSEHOLDSRURAL VILLAGESSMALLHOLDER FARMERSSTOCKSSTRUCTURAL TRANSFORMATIONTRANSITION ECONOMIESTRANSITORY INCOMEURBAN AREASURBAN POVERTYVEGETABLESWELFARE INDICATORWELFARE INDICATORSWELFARE MEASUREWELFARE MONITORINGWorld Bank10.1596/1813-9450-5683