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- Almost 6 in 10 respondents were satisfied with how things were going in their life, with career, family and health being key drivers of satisfaction. Less than a fifth felt their career or financial situation had exceeded expectations.
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1) Over 83% of households are male-headed and 16.3% are female-headed, with some women taking on responsibility after husband's death or abandonment.
2) 64 households have 5-8 members but only one earning member, making it difficult to escape poverty. Some families believe more children will result in male earners.
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We also asked questions about new offerings, such as residential solar energy and electric vehicles. We explored the level of customer trust in utilities. We identified growing fault lines beneath the utility, especially with investor-owned utilities. We determined that the assumptions around reliability, equity, and ownership may be outdated. Like all fault lines, it is necessary to dig to see them. In this case, we began to ask the tough questions of consumers to get their input
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1) Access to PSNP and timely transfers vary between regions, with improvements seen in Tigray but declines in Oromia.
2) Graduation outcomes are mixed, with some households graduating without readiness. Appeal systems are underutilized due to lack of confidence.
3) Constraints to graduation include low wages, delayed payments, insufficient credit access. Market challenges like price fluctuations also hinder livelihood improvement.
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Discover the videos and other sessions from the OECD Disrupted Futures 2023 conference at https://www.oecd.org/education/career-readiness/conferences-webinars/disrupted-futures-2023.htm
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- Respondents in the Republic of Ireland reported significantly better general health than those in Northern Ireland, with over 90% in ROI reporting very good or good health.
- The proportion of the population providing unpaid care was much higher in Northern Ireland at 11.8% compared to 4.2% in the Republic of Ireland.
- Both jurisdictions saw an increase in unpaid care between 2001-2011, with the highest growth rates among those aged 65 and over.
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- Nearly 50% of consumers used restaurant reservation platforms/apps, with immediacy and planning being attractive features for different generations.
- Google reviews and recommendations from friends/relatives were the top sources for restaurant information. Official websites were preferred more by older consumers compared to younger ones.
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The document provides a final report on a community survey conducted in three villages in Cambodia between February and May 2016. Key findings include:
1) Households with migrating adults working away for over 9 months per year had higher ownership of assets like televisions but lower scores on land quality and food security compared to households without migrating adults.
2) Analysis by village found differences in areas like water access, quality of farming land, and perceived ability to recover from disasters. Sompov Kert generally scored highest while K'Downg scored lowest.
3) Over 40% of households had one or more adults working away, most commonly in manufacturing or construction in Thailand, suggesting migration is a significant issue for
- The survey found that 93% of rural households in Andhra Pradesh are indebted, with most debt from informal sources like moneylenders, friends, and employers. Informal loans accounted for the largest share of total loan amounts.
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2. INTRODUCTION
The Poverty Assessment Tool was implemented in Sovann Phoum in 2010, in order to:
- appraise the partners’ households’ poverty level from a general point of view (the several
indicators in the assessment are totaled into a maximum score of 100 for each
household, with 0 representing extreme poverty and 100 representing emerging from
poverty);
- depict a household’s economic status with six different factors: demography, finance,
housing, assets, nutrition and health;
- and assess the evolution of the poverty situation of households in time (by conducting an
assessment of the partners every three loan cycles, i.e. approximately every year).
This is the second time that a complete analysis has been completed on the PAT data
collected in the past four years.
EXECUTIVE SUMMARY
It is interesting to note the significant disparities between the different areas where
Sovann Phoum operates. Some areas such as Ahr Sor and Sen Sok 5 systematically
register poorer scores for most questions with the overall score of these places raising
doubts about Sovann Phoum’s capability to serve areas of great poverty.
The main evolutions noted on partners’ situation of poverty as they progress through loan
cycles are on the level of assets, and more significantly school attendance of children.
There were no notable evolutions either on nutrition or on how they deal with health issues
when they arise. There were also varied results in the level of partners’ business capital as
they move through loan cycles.
Such an analysis gives interesting insight on the level of poverty of the partners served by
Sovann Phoum and can provide valuable input under the condition that the PAT data
collected on the field is done in an accurate and consistent manner.
CONTENTS
Main characteristics of Sovann Phoum partners’ households.......................... 3
Poverty level of households .............................................................................................. 3
Analysis by area of operation ............................................................................................ 4
Indicators of Poverty.............................................................................................. 4
Education .......................................................................................................................... 4
Assets................................................................................................................................ 5
Housing conditions ............................................................................................................ 6
Nutrition ............................................................................................................................. 7
Access to health services.................................................................................................. 7
Comparison between cycles 1, 4 and 7................................................................ 8
Poverty Situation Evolution................................................................................... 9
Improvements noted.......................................................................................................... 9
Varied Results ................................................................................................................. 11
Partners with decreased PAT scores .............................................................................. 12
3. Main characteristics of Sovann Phoum partners’ households
The analysis is based the 1370 PAT questionnaires from July 2011-October 2014 (40
weeks), of which 1112 are for 1st
cycle loans, 199 for 4th
cycle, 48 for 7th
cycle loans, and for
8 for 10th
cycle loans
Poverty level of households
The average PAT Score for all households is 47.2, and scores are spread as follows:
Average size of households
The average size of the households is 3.8 persons per home, which compares with a
national average of 4.7 based on the 2008 census. There seems to be no correlation
between the size of the households and their total PAT score.
Analysis by area of operation
There is a noticeable disparity among the different geographical areas in which Sovann
Phoum operates, with average scores ranging from 41.1 to 52.7. Please note that some
areas did not have a significant number of questionnaires administered (less than 10), and as
a result, were taken out of the analysis below:
4.
Average
PAT
score
The differences between the areas with the highest and the lowest scores were noted on
most criteria, as shown in the details of the analysis below.
Indicators of Poverty
Education
Almost half of the children in the surveyed households do not attend school, however there
are some areas that exhibit more promising results.The best score is in Chumpos
Kaak
and
Praek
Tapov,
where 50% of the households have all their children attending school.
Official statistics on 2008 census data state that over 80% of the children between 6 and 16
attend school – Sovann Phoum’s partners fall considerably below that average.
In addition, in 43.5% of the households, none of the children of a school going age attend
school. In Sen
Sok
2,
Chungruk,
Trea,
Sopor
Thmei,
Dey
Thmey,
Sen
Sok,
Beoung
Salang,
Toul
Kork, over 55% of the households do not send any of their children to school.
177
Questionnaires
124
Questionnaires
98
Questionnaires
89
Questionnaires
88
Questionnaires
86
Questionnaires
81
Questionnaires
81
Questionnaires
73
Questionnaires
47
Questionnaires
38
Questionnaires
38
Questionnaires
34
Questionnaires
33
Questionnaires
27
Questionnaires
24
Questionnaires
22
Questionnaires
22
Questionnaires
18
Questionnaires
17
Questionnaires
16
Questionnaires
14
Questionnaires
13
Questionnaires
12
Questionnaires
12
Questionnaires
12
Questionnaires
12
Questionnaires
11
Questionnaires
10
Questionnaires
10
Questionnaires
10
Questionnaires
10
Questionnaires
5. Almost half of the households assessed have attended secondary school (or primary
school with technical training). In about 24% of the households, high school (or secondary
school with technical training) is the highest education obtained.
Arh
Sor
and
Changruk
have significantly lower levels of education than the other areas, as
practically two thirds of the households have not surpassed primary school. On the other
hand, almost 20% of households in Trea attend University (or High school with technical
training).
Assets
Business capital
Over half of the partners assessed have a business capital of less than 100 US dollars –
24% are below 50 USD.
In Sopor
Thmei, 83% of the partners’ business capital is less than 50 USD; in Arh
Sor,
Chumpos
Kaak,
Toul
Kork.and
OU
Andong
over
45%
of
households
fall
in
this
range.
6. Household assets
Motorbike: 75% of the partners have at least one motorbike and just over 25% of the
households’ motorbikes are worth more than $500. Arh
Sor
and
Praek
Tapov
are
both
outliers
to
this
observation
as
in
these
areas,
60%
of
households
do
not
own
a
motorbike.
Mobile phone: 88% of partners assessed have at least one mobile phone with the exception
of households in Ahr Sor where 80% do not own a mobile phone. Almost none of the
households had mobile phones worth $60 or more.
Housing conditions
Almost all households lived in houses with roofs made from sturdy material (i.e. not leaves,
thatch or tarpaulin).
A majority of households assessed have their own home in legal areas, but again there are
significant differences depending on the areas surveyed:
- Overall, 16% of households rent their home, however more than 50% of the
households in Damnak Thom and Boeung Salang pay rent for their homes.
Overall, 6% of the families reside in illegal areas, however households in Sen
Sok
5
and
Prey
Tear
fall below the norm with 30% of partners living in illegal areas.
-
78% of households assessed own their own concrete toilets; in Prey Tear however, 31%
have no concrete toilets (vs. 4% on average), and in Trea, more than 75% of the households
share concrete toilets (vs. 18% on average).
7. Nutrition
Almost every single household has at least 2 meals a day, with over 40% of the households
eating 3 meals a day.
In
Sopor
Thmei,
Dey
Thmey,
and
Sen
Sok
5,
very few households declare eating three meals a
day (less than 5% of the partners interviewed, vs. 53% on average).
A clear majority of partners assessed buy a 50kg bag of rice only once in awhile, indicating
that their level of income does not enable them to benefit from economies of scale by
purchasing this staple food at wholesale prices.
Access to health services
On average almost half of the households go to the doctor or a health centre; however in
certain areas such as Praek
Tapov
and
Deoum Slearng none of the families seek this type of
treatment. In those areas, it seems that the only alternative is going to the chemist.
- In Ahr Sor, Chungruk, and Dey Thmey, over 90% of the families go to a doctor or
health centre; this is interesting as these areas had lower scores on most other
questions.
Fortunately, only 1.3% of partners’ families do not seek any form of modern medical advice
when ill (8% in Sen Sok 7).
A clear majority of partners assessed do not have health insurance (99.6%).
8. Comparison between cycles 1, 4 and 7
This section helps to identify the most volatile indicators based on the number of loans that
partners have received from Sovann Phoum.
Please note that the figures below do not represent the same group of partners who have
moved from cycle 1 to 4 to 7, as they only portray the various economic situations of partners
in each cycle individually.
A general trend of increasing PAT Scores is observed as the partners progress from Cycle 1
to 4 to 7.
Number of questionnaires 1112 199 48
The analysis does not consider the partners in cycle 10 as there were only 8 questionnaires
administered, which is not considered a significant sample.
Of note, the business capital of individual partners increases from cycle 1 to 7. For cycle
1, most partners are found to have a business capital of between 50 and 99 USD. For cycle
4, the largest group is found in the range of 100 to 200 USD, and for cycle 7, partners who
have business capital of more than 100 USD make up the largest numbers.
9. There are also progressively more households who own at least one mobile phone in higher
cycles. The percentage increases from 83% in Cycle 1 to 86% in Cycle 4 to 92% in Cycle 7.
The same trend can be observed in the ownership of motorbikes as well (from 70% in Cycle
1 to 76% in Cycle 4 to 85% in Cycle 7).
With regard to housing, roughly the same percentage of partners own homes in legal areas
regardless of their loan cycle.
The last indicator of note is health insurance subscription: almost no partners had health
insurance regardless of their loan cycle.
Poverty Situation Evolution
This section contains the analysis of figures for 64 partners who were assessed with the PAT
at least twice, illustrating a more accurate picture of the changes in the partners’ poverty
situation. 52 partners were assessed in Cycles 1 and 4 and 10 partners were assessed in
cycles 4 and 7. Only 2 partners in the data set were assessed in cycles 1,4 and 7.
- On the one hand, 47 out of 64 of these partners had an increase in PAT score after 3
cycles, averaging an increase of 8.2 points.
- On the other hand, 15 partners registered a decrease in score, averaging a decrease of
6.4 points.
Improvements noted
16 families (25%) showed an improvement in the level of school attendance of their
children.
10. A 7% increase was also noted in the percentage of partners who own at least one mobile
phone. Please note that 76% of the sample already owned one mobile phone when they first
joined.
Similarly, 13 partners who had no motorcycle when they joined Sovann Phoum owned one
by the time they took their 4th
loans. The percentage of partners who own at least one
motorcycle increased by 11%.
11. Another clear improvement was noticed in the type of toilets that the partners’ households
use. There was a significant increase of 24% in the number of households who own concrete
toilets.
Varied Results
With regard to the number of meals eaten every day, only four families noted improvement,
two families went from having 2 to 3 meals a day to having 3 meals every day, one family
went from having 1 to 2 meals a day to having 2 to 3 meals every day, and one family even
went from not having a meal every day to having three meals every day; the rest remained
the same.
Access to health facilities improved slightly, fifteen families went from visiting a chemist for
treatment to going to the doctor, three families upgraded from going to a chemist to going to
the hospital/clinic, and two families went from going to the doctor for treatment to going to the
hospital/clinic. Most families, however, did not change the way they seek medical treatment
(most of them go the chemist). Ten families even reported a degraded score.
The change in business capital between cycles varied greatly for this group of partners: for
39%, the business capital increased, for another 23%, it decreased – while it remained stable
for the other 38%.
Partners with decreased PAT scores
The 15 partners who registered a drop in PAT score, had decreases in the following
indicators:
o Partner A: one less mobile phone
o Partner B: regressed from owning a toilet in cycle 1 to sharing a toilet in cycle 4, went
from seeking treatment from a hospital in cycle 4 to going to a chemist in cycle 7, and
experienced a decrease in capital from cycle 4 to 7
o Partner C: decrease in capital
o Partner D: regressed from going to a doctor when ill to going to a chemist
o Partner E: regressed from owning home in a legal area to renting a home
o Partner F: decrease in capital from cycle 1 to 4, regressed from seeking treatment from
a doctor in cycle 4 to going to a chemist in cycle 7 and had one less source of income
from cycle 4 to 7
o Partner G: 5 less sources of income, 3 less mobile phones, 1 less motorbike, 2 less
bicycles and regressed from usually buying a big bag of rice to sometimes buying a big
bag of rice
12. o Partner H: regressed from going to the hospital when ill to going to a doctor, went from
having 3 meals a day to having 2 to 3 meals a day, and went from owning home in a
legal area to renting a home
o Partner I: decrease in capital and regressed from having 3 meals a day to having 2 to 3
meals a day
o Partner J: decrease in capital
o Partner K: decrease in capital and regressed from having 3 meals a day to having 2 to
3 meals a day
o Partner L: regressed from having 2 to 3 meals a day to having 1 to 2 meals a day
o Partner M: one less mobile phone, one less bicycle, one less source of income
o Partner N: regressed from having 3 meals a day to having 2 to 3 meals a day
o Partner O: decrease in capital, one less bicycle, once less source of income, and
regressed from going to a doctor when ill to going to a chemist