Gender-Sensitive Poverty Mapping for Timor-Leste : Policy Note
Timor-Leste has made impressive progress over the past decade in reducing national poverty levels. Geographically, however, this progress has been highly uneven across the country. In addition, concerns exist regarding gender gaps based on broader...
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| Language: | English |
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World Bank, Washington, DC
2019
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| Online Access: | http://documents.worldbank.org/curated/en/143891560928616596/Gender-Sensitive-Poverty-Mapping-for-Timor-Leste-Policy-Note http://hdl.handle.net/10986/32015 |
| Summary: | Timor-Leste has made impressive progress
over the past decade in reducing national poverty levels.
Geographically, however, this progress has been highly
uneven across the country. In addition, concerns exist
regarding gender gaps based on broader socioeconomic
dimensions, such as access to economic activities,
education, health, and power and agency. In response, the
Government of Timor-Leste has set a goal of eradicating
extreme poverty by introducing more socially inclusive and
gender sensitive policies and programs. However, the
existing sex-disaggregated statistics and consumption based
poverty estimates resulting from the 2014 Survey of Living
Standards only provide district-level disaggregation. This
limits the government’s ability to identify and target
pockets of extreme poverty and gender disparity across the
country below the district level. To address this gap, the
World Bank, in close collaboration with the General
Directorate of Statistics Timor-Leste, has generated a new
set of sex-disaggregated poverty statistics at the village
(suco) level. This work takes a more thoughtful approach to
gender-sensitive poverty analyses, beyond the usual
household headship, by employing individual-level
characteristics of education, health, employment, and power
and agency. The analyses employ a small-area estimation
(SAE) approach to link the data in the 2015 Population and
Housing Census with the 2014 Survey of Living Standards and
the 2016 Demographic and Health Survey. The suco-level
poverty maps confirm an already known pattern that poverty
headcount rates are much higher in western areas of the
country. The maps also reveal new findings that were not
previously known, namely that there is far more variation in
poverty 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. Analyzing
poverty and gender equality by the gender of the household
head, female-headed households are less likely to be poor
than those headed by males. However, if poverty and
genderequality are assessed using spatially disaggregated
evidence of five individual-level gender indicators
(education, health, labor force, and power and agency), two
interesting patterns emerge. First, poorer areas have higher
levels of abuse and domestic violence against women, and
females are at a greater educational disadvantage, despite
narrowing gaps in the literacy rate among school-aged
children and school enrollment. Second, there is an inverse
relationship between gender-related labor force gaps and
poverty rates: the prevalence of a female labor force
disadvantage is higher in more economically developed sucos.
However, women do not appear to be disadvantaged in terms of
health measures and this pattern has no correlation with
poverty. Poverty does not appear to be related to women’s
autonomy to make decisions. The overall findings suggest the
importance of using sex-disaggregated individual level
analysis, beyond the male/female household headship, to
better assess poverty of women and men and gender disparity.
This analysis goes beyond traditional consumption-based
poverty analysis by integrating a gender dimension to better
capture the standard-of-living and gender disparities in the
country. These findings can be used to inform the design of
policies and programs that target poverty at the suco level,
and to improve resource allocation designed to raise the
living standards of the poor, balance the targeting of poor
areas and poor people, and close gender gaps in the five
dimensions studied here. The poverty maps could also provide
a cost-effective way to add value to existing census and
survey data, and also serve as a substitute for fielding
expensive new censuses or surveys. |
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