Timor-Leste has made impressive progressover the past decade in reducing national poverty levels.Geographically, however, this progress has been highlyuneven across the country. In addition, concerns existregarding gender gaps based on broader socioeconomicdimensions, such as access to economic activities,education, health, and power and agency. In response, theGovernment of Timor-Leste has set a goal of eradicatingextreme poverty by introducing more socially inclusive andgender sensitive policies and programs. However, theexisting sex-disaggregated statistics and consumption basedpoverty estimates resulting from the 2014 Survey of LivingStandards only provide district-level disaggregation. Thislimits the government’s ability to identify and targetpockets of extreme poverty and gender disparity across thecountry below the district level. To address this gap, theWorld Bank, in close collaboration with the GeneralDirectorate of Statistics Timor-Leste, has generated a newset of sex-disaggregated poverty statistics at the village(suco) level. This work takes a more thoughtful approach togender-sensitive poverty analyses, beyond the usualhousehold headship, by employing individual-levelcharacteristics of education, health, employment, and powerand agency. The analyses employ a small-area estimation(SAE) approach to link the data in the 2015 Population andHousing Census with the 2014 Survey of Living Standards andthe 2016 Demographic and Health Survey. The suco-levelpoverty maps confirm an already known pattern that povertyheadcount rates are much higher in western areas of thecountry. The maps also reveal new findings that were notpreviously known, namely that there is far more variation inpoverty rates within than between districts. For example,while the Dili district-level poverty rate is 29 percent,its suco-level rates range from 8 to 80 percent. Analyzingpoverty and gender equality by the gender of the householdhead, female-headed households are less likely to be poorthan those headed by males. However, if poverty andgenderequality are assessed using spatially disaggregatedevidence of five individual-level gender indicators(education, health, labor force, and power and agency), twointeresting patterns emerge. First, poorer areas have higherlevels of abuse and domestic violence against women, andfemales are at a greater educational disadvantage, despitenarrowing gaps in the literacy rate among school-agedchildren and school enrollment. Second, there is an inverserelationship between gender-related labor force gaps andpoverty rates: the prevalence of a female labor forcedisadvantage is higher in more economically developed sucos.However, women do not appear to be disadvantaged in terms ofhealth measures and this pattern has no correlation withpoverty. Poverty does not appear to be related to women’sautonomy to make decisions. The overall findings suggest theimportance of using sex-disaggregated individual levelanalysis, beyond the male/female household headship, tobetter assess poverty of women and men and gender disparity.This analysis goes beyond traditional consumption-basedpoverty analysis by integrating a gender dimension to bettercapture the standard-of-living and gender disparities in thecountry. These findings can be used to inform the design ofpolicies and programs that target poverty at the suco level,and to improve resource allocation designed to raise theliving standards of the poor, balance the targeting of poorareas and poor people, and close gender gaps in the fivedimensions studied here. The poverty maps could also providea cost-effective way to add value to existing census andsurvey data, and also serve as a substitute for fieldingexpensive new censuses or surveys.
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