构建可比较的全球贫困趋势

GLOBALPOVERTYMONITORINGTECHNICALNOTE45AbstractCountries frequentlyrevisehow they measure income or consumptiondue to changesin data collectionandquestionnaire design. Thesechangescreate comparability breaksin poverty trends over time. This paperdevelopsthree methods to create global,regional, and country-level povertytrendsthat are comparable within countries overtime.It does so by usingnational accounts growth to bridge non-comparable sequences.Accounting for comparability breakscreateslarge differences insome country-levelpoverty trends,buttheglobal extreme poverty trend built fromthesecomparablepoverty series remains largely unchanged.All authors are with the World Bank.Corresponding author:Daniel Gerszon Mahler(dmahler@worldbank.org).The authors aregrateful for feedback received from the Global PovertyMonitoring Working Group.The authors gratefully acknowledge financial support from the UKgovernment through the Data and Evidence for Tackling Extreme Poverty(DEEP) ResearchProgramme.The Global PovertyMonitoringTechnical Note Series publishes short papers that document methodological aspects ofthe World Bank’s global poverty estimates. The papers carry the names of the authors and should be cited accordingly.The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do notnecessarily represent the views of the International Bank for Reconstruction and Development/World Bank and itsaffiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. GlobalPoverty Monitoring Technical Notes are available athttps://pip.worldbank.org/publication. 1.IntroductionIn low-andmiddle-incomecountries, monetary poverty is measuredusing datafromhouseholdsurveysthat elicit the income or consumption patterns of a representative sample of householdsinacountry. If a household’s income or consumption falls short of a given poverty line, the householdis classified as being poor.Numerous studies have shown that the design of household surveysimpacts the data collected,measuredincome orconsumption, and therefore also measured povertyrates(Beegle et al. 2012, De Weerdt et al 2020, Jolliffe 2001, Friedman et al. 2017, Kilic et al.2019).For example, when measuring food consumption, it matters whether households are askedto keep a diary of their consumption or to recall their consumption. In the latter case, it is ofconsequence whether they are asked to recall their consumption over thepast seven days or 30days. For both food and non-food consumption, it matters how disaggregated the elicitedcategoriesof consumptionare, for example whether households are asked to report their riceconsumption in aggregate,or brown and white rice separately.Hence, systematic differencesintroduced by alternative survey instruments imply that welfare and poverty indicators producedunder one design are not directly comparable with those generated under another.Guidelines for data collection and questionnaire design have changed over time as moreinformation aboutthe accuracy and bias of variousmeasurementapproaches areuncoveredand asconsumption patterns in countrieschange(Deaton and Grosh2000,Deaton and Zaidi 2002,Mancini and Vecchi 2022).To ensure that household surveys are on the frontier of povertymeasurement, theunderlyingdata collection and questionnaire designoccasionally need to berevisited.Though this creates morereliablepoverty estimates, it also results in comparabilitybreaksin estimated poverty rates. At times,measured consumption increasesby over 50% becauseof changes to the survey design andconstruction ofconsumption aggregates, which biases povertytrendsusing fixed poverty linesif unaccounted for (Mahler et al. 2024).For single countries, solutions to this problem are well known andfrequentlyapplied, and includesurvey-to-survey imputations that predict the distribution of consumption had there been nochange to the questionnaire design (Dang et al. 2017, Dang et al. 2019,Mathiassen and Wold 2021,Roy and Van der Weide 2025)or bridge surveys thatcollect an old consumption aggregate on asubsample in a newer survey. Yet the problem extends beyond single countries.Tounderstandhow poverty is evolving globally and by regions, such methods cannot be appliedconsistently.Asa result, the problem is most often ignoredin the measurement ofglobalpoverty.In this paper, we developthree methodstoaddresstheincomparabilityofhow consumption ismeasured within countries over time.The methods usegrowthinnational accountsdatato bridgecomparability breaksandusevarying degrees of information from surveys of olderdesign.Weapply themethodsto the World Bank’s global poverty numbers in the Poverty and InequalityPlatform (PIP) toshed light onwhether thetrendsin poverty are robust to differences in howconsumption is measured.We find large changes formanycountries,but relatively muted changesat the regional and global levels. When changes are apparent at theregional and global