yemen social fund for development 2003 impact evaluation ... · and recall questions in the project...

Yemen Social Fund for Development

2003 Impact Evaluation Study

Final Report

ESA Consultores International

December 2003

Client: World Bank

Yemen SFD Impact Evaluation Study -2003 Final Report

ESA Consultores International, December 2003 i

Index Acknowledgements.......................................................................................1 Introduction .................................................................................................4 1 Methodology..........................................................................................5

1.1 Sample design..................................................................................5 1.1.1. The sample of completed projects ....................................................5 1.1.2. The sample of pipeline projects ........................................................6 1.1.3. Household sample..........................................................................7 1.1.4. Household selection procedure.........................................................7 1.1.5. Qualitative survey sample................................................................8 1.2 Evaluation instruments.......................................................................9 1.3 Survey/study problems and results ......................................................9

1.3.1 Implementation process ...............................................................9 1.3.2 Project survey ..........................................................................10 1.3.3 Household survey .....................................................................10 1.3.4.Working database.........................................................................11

2 SFD’s Operational efficiency...................................................................13 2.1 Number and type of projects/amount of funding ..................................13 2.2 Number of beneficiaries ...................................................................13 2.3 Project cycle performance ................................................................15

3 Cost – Efficiency of SFD Investments ......................................................18 Cost per beneficiary .................................................................................18

4 SFD’s Targeting Outcomes.....................................................................19 Benefit Incidence Analysis.........................................................................19

5 Consultation, Participation, Ownership and SFD’s Impact on Social Capital....24 5.1 Consultation on project design ..........................................................24 5.2 Community contribution to the project ...............................................25 5.3 Consensus on priority of SFD Project .................................................27 5.4 “Ownership” of project ....................................................................28 5.5 Social Capital .................................................................................30

6 Service production and sustainability of SFD Projects. ................................34 6.1 Education Projects ..........................................................................34 6.2 Health Projects ...............................................................................37 6.3 Water projects................................................................................42 6.4 Sewerage projects ..........................................................................45 6.5 Rural road projects ..........................................................................46 6.6 Micro Finance Projects.....................................................................48 6.7 Projects for Special Needs Groups .....................................................54 6.8 Organizational support .....................................................................56 6.9 Training.........................................................................................57

7 SFD Contribution to National Stock of Infrastructure ..................................59 7.1 Education Projects ..........................................................................59 7.2 Health Projects ...............................................................................59 7.3 Water and Sanitation Projects ...........................................................60 7.4 Rural roads Projects ........................................................................60 7.5 Overall financial investment..............................................................60

8 SFD Impact on Household-level Development Indicators..............................62 8.1 Methodology..................................................................................62


ESA Consultores International, December 2003 ii

8.2 Education ......................................................................................63 8.2.1 SFD’ impact on the probability of being enrolled in a primary school .64 8.2.2 The impact of SFD on grade for age in primary education................68

8.3 Health ...........................................................................................71 8.3.1 SFD impact on access to medical attention for health problems .......72 8.3.2 SFD impact on vaccination coverage............................................75 8.3.3 SFD Impact on the take-up of antenatal care.................................76

8.4 Water projects................................................................................77 8.5 Characteristics of the survey population ..........................................79 9 Conclusions and Recommendations .........................................................81

9.1 Conclusions ...................................................................................81 9.1.1 SFD outputs and its contribution to the national stock of infrastructure in the social sectors ..............................................................................81 9.1.2 Targeting outcomes...................................................................82 9.1.3 Consultation, participation, ownership and impact on social capital...82 9.1.4 Service production and sustainability ...........................................83 9.1.5 Impact on household-level development indicators .........................84

9.2 Recommendations...........................................................................85 Annexes....................................................................................................87


ESA Consultores International, December 2003 1

Acknowledgements The analysis of the 2003 Impact Evaluation Survey of the Yemen Social Fund for Development (SFD) and the writing of this report were completed by the following members of ESA Consultores International:

Ian Walker Study Director

Vincent David Principal Analyst

Fidel Ordoñez Statistician

Freddy Velásquez Data Processing and Tabulation

This report is not conceived to represent in any way the views of the Word Bank, the Government of the Republic of Yemen, or the management of the Social Fund for Development. The study team would like to acknowledge the comments on earlier drafts of this report received from Yasser El-Gamal (World Bank), from Judith Brandsma (consultant) and from our colleagues from the Yemeni team. We have tried to incorporate those comments and suggestions in the final report, when they brought a significant contribution to the interpretation of the findings. Any omission, error in the reproduction of the data provided to us and, in the end, the analysis and interpretation of those findings remain the responsibility of the study team.

The study team would like to extend its special gratitude to the Yemeni team in charge of the field work, data collection and data entry for the survey, as well as the processing of selected data from the program’s MIS and the forwarding of information obtained from other sources in Yemen.



The Yemeni Team

A. Study Management

Lamis Abass Al- Iryani, Head of Programming and Evaluation Unit, SFD

Tareq Yeslam Awadh, Impact Evaluation Officer, SFD

B. Household and Project Survey

Abdo -Nasser Al-Qubatie, Statistics National Expert, SFD

Abdul-Raqeeb Abdo Saif, Programming Officer, SFD

Ahmed Mohamed Noaman Al-Barakani, Field Manager, SFD

Anwar Farhan, Data Processing Consultant, CSO

1- Sana’a Team:

Team leader: Abdul Hakeem Saeed Mohamed Al-Mudieh

Interviewers: Ranwa Ali Al-Saroury, Dekrah Taha Noaman, Takwoa Abdul-Gabar Alessi, Miysoon Ali Al-Saroury

2- Sana’a , Al Amana, and Al-Mahweet(1) Team

Team leader: Ameen Hasson Al Banna

Interviewers: Waffa Abdul-Rahman Ahmed, Zumuzm Mohamed Al-Harthi, Sameera Abdul-Rahman Ahmed, Magedah Ali Al-Karni

3- Hajja & Al Mahweet(2) Team

Team leader: Mohamed Ahmed Ghumthiem

Interviewers: Mofiedah Ahmed Abdul-Khalequ, Mariem Saleh Abduh, Nada Ahmed Bin Ahmed, Ashwaq Abduh Malek

4- Al Hodeidah Team

Team leader: Mohamed Ali Haza’a

Interviewers: Fareedah Hamed Al-Soofi, Dekra Abdullah Moqbel Al-Shargabi, Riya Hussian Hagwan, Alla Manssor Al-Babily

5- Amran Team

Team leader: Abdulah Moqbael Al Kudssi

Interviewers: Abdul -Kareem Mohamed Ali Al-Sabri, Susan Hamood Al-Kamel, Bushra Abdul-Fard Noaman, Amt-Alteef Al-Babeli

6- Marib, Sa’ada , and Al Jowf Team:

Team leader: Mohamed Khaleel Al Mubrazi

Interviewers: Fatehia Hamood Al-Hamadi, Ebtisam Ahmed Abdul-Galeel, Ehlam Ahmed Abdul-Khaleq, Nabeelah Ahmed Al-Abessy



7- Dhamar & Al Baidhah Team

Team leader: Mohamed Saif Abdulla Al-Barkani

Interviewers: Susan Abdullah Shamsan, Samiah Mohamed Yahya Al-Akwa’a, Muna Mohamed Al-Harithie, Nawal Abduh Ali Al-Ga’addie

8- Taiz Team:

Team leader: Abdul Raqeeb Mohamed Nasser

Interviewers: Nugood Kasem Ahmed Muhsain, Ashwaq Abu-Baker Abdul-Haq, Amel Ghalaeb Abdulah, Buthienah Ahmed Moqeable

9- Ibb & Al Dhaleh Team

Team leader: Mohmed Abdul Razaq Ali

Interviewers: Ateqah Mohamed Ali Al-Masswary, Assrar Abdul-Wali Abdul-Gabar, Nagla Nasser Nasser, Riela Abdul-Kareem Qasem

10- Hadhramout & Al Mahrah Team:

Team leader: Qaid Ahmed Haidrah

Interviewers: Kareemah Ali Al Turkie, Nadieha Ali Al-Shaikh, Sabah Abdul-Salam Abdulah, Snaa Salman Nagie

11- Shabwah, Abyan , Aden and Lahj Team

Team leader: Mohamed Ameen Al Gabrie

Interviewers: Susan Abu-Baker Radman, Lina Taher Malaek, Waliyah Ahmed Thabet Saeed, Randah Hussain Ahmed Haidar

C. Qualitative Survey

Dr. Abdul-Wahed Al-Seroury, Study Manager

Thabet Bagash, Focus Group Discussion Trainer

Facilitators & Reporters:

Musaid Al- Maghibi Mana Mohamed Al-Kindi

Muna Derhim Magedah Bakohail

Abdo Yassin Saleh Foad Taleb Abdo Hamna



Introduction This report presents the findings of the impact evaluation of the Yemen SFD carried out during 2003. The report is based primarily on the results of a survey of 97 projects completed by the SFD between 1999 and 2002 and 2,028 households. At the same time, a new baseline survey of 101 projects in the SFD pipeline and 2,029 households was carried out, to provide the basis for the 2005 evaluation.

Comparators used in the study for making inferences about the SFD’s impact include: baseline household data drawn from the 1999 National Poverty Survey for the same communities; institutional records of the SFD and government ministries; and recall questions in the project and household surveys. A summary of the key elements of the methodology is presented in Chapter 1. The detailed methodology for the study is described in the SFD’s Impact Monitoring and Evaluation Manual and in the prior report on the study methodology, submitted in December 2002.

Chapter 2 presents the study’s findings regarding the SFD’s operational efficiency, in terms of the number of projects funded and investment amounts mobilized, the number of beneficiaries reached, and the time taken in the project cycle. Chapter 3 looks at the available evidence on the SFD’s cost efficiency, in terms of costs per beneficiary.

Chapter 4 analyses targeting outcomes at household level, using the benefit incidence analysis approach1. Chapter 5 documents the process of consultation and participation in SFD projects at community level and the resulting impacts on “ownership” and on social capital. Chapter 6 reports on the service production record of these projects and evidence on their sustainability in terms of the coverage of operating costs.

Chapter 7 summarizes the SFD’s contribution to the national stock of infrastructure in the areas of education, health and water. Finally, Chapter 8 presents household-level evidence for the impact of the SFD investments on key development indicators such as educational enrollment and attainment, the take up of health services, vaccination status, and access to water and sanitation services. This section presents direct comparisons of before and after status in the relevant population based on the 1999 NPS and 2003 impact evaluation survey databases. It also uses multivariate analysis to control for changes in other independent variables (such as income trends) that might affect the study (dependent) variable, and for the possible impact of sampling differences between the two surveys.

Chapter 9 summarizes the conclusions and recommendations made by the study team.

1 A detailed analysis of the targeting outcomes at community level was presented in a prior report presented in December 2002; these findings remain valid.



1 Methodology The Impact Monitoring and Evaluation Manual provides a detailed definition of the study questions that the evaluation should address and indicators to be reported.

There are five main data sources: household survey, facility (or project) survey; qualitative evaluation; SFD program data (Management Information System); and secondary statistical sources such as national household surveys and Ministerial registers, many of which are available in the SFD Geographic Information System.

The study draws on baseline data collected in 1999 as part of the National Poverty Survey (NPS) – including an expansion of the survey into areas of SFD intervention that were not in the NPS sample - together with a purpose-designed ex-post project and household survey carried out in 2003, and SFD Management Information System (MIS) registers. Where the 1999 NPS did not provide useable ex-ante data, recall questions were used in the 2003 survey to establish the situation prior to the SFD intervention.

1.1 Sample design

As outlined in the SFD Impact Monitoring and Evaluation Manual (see Table 4 on page 10 of the IMEM), the program’s evaluation strategy is based on two sorts of comparisons:

• The comparison of conditions in a sample of households and communities that had already benefited from different sorts of SFD projects, with those of otherwise similar communities and households who had not yet benefited from the projects. This analysis, based on the data generated in the 1999 National Poverty Survey (NPS) was presented in December 2002.

• The comparison of conditions before and after the SFD intervention in a sample of projects and households in the program’s “intervention group”. This analysis forms the central axis of the present study. Baseline data from the 1999 NPS are compared with ex-post data collected for the same households in 2003.

1.1.1. The sample of completed projects

The point of going back in 2003 to projects implemented in 1999-2002 is to observe changes in those communities and households, compared with the situation that existed beforehand. This is made possible by the existence of a baseline dataset from the 1999 NPS for 117 SFD beneficiary communities. The study universe for this part of the survey is the communities and households that benefited from SFD investments in 1999-2002. However, since the baseline data had already been generated, sampling for the ex-post exercise was limited to the sub-set of SFD projects for which we had baseline data.



Table 1.a presents data for the total number of projects in the universe, the number of projects for which we have baseline data at household level, and the planned distribution of the sample of projects in the 2002/3 survey.

Due to the small number of projects for which baseline data were available, it was proposed that the 2003 survey return to the whole set of 24 water and 23 health projects for which there is baseline data.

A sub-sample was taken of the 30 of the 70 education projects, using systematic sampling with an equal probability of selection for each project, and based on – first – a rural / urban grouping and within each group, a geographical ordering of the projects. Additionally, all 13 completed roads projects and 11 established micro finance projects were selected; no baseline data exist in either of these two cases.

1.1.2. The sample of pipeline projects

The second sub-universe of the 2003 survey is the set of projects and communities that will receive SFD support in the future, but where the services are not yet being delivered.

There are two points of comparison for the data gathered in these 100 projects and communities. The main purpose of these observations is to provide new baseline data that will be updated in the next Impact evaluation survey in 2005. However, immediately, they also provide a second comparison set for the “ex-post” part of the sample (that is, in addition to the comparison with the baseline data for the ex-post set that were collected in 1999).

Table 1.a – Universe of projects implemented in 1999-2002 and distribution of the 2003 Ex-Post sample, by sub project type

Sector

Value of projects

implemented by SFD in 1999-

2002 (US$)

Number of projects

implement-ted by SFD in 1999-

2002

Projects with 1999

baseline data (NPS)

Planned “ex

post” sample in 2003 survey

Education 35,569,704 688 70 30 Water 13,400,783 225 24 24 Health 7,219,751 143 23 23 Roads 1,692.121 16 0 13 Micro-finance

656,892 16 0 11

Total 66,869,853 1,283 117 101



For the purposes of sample selection, the projects were stratified by sector. Within each stratum, these projects were selected using systematic random sampling, based on a geographically ordered list of projects, with an equal probability of selection for each project in the project pipeline. Annex A presents the lists of the selected samples of projects in the “ex-post and “pipeline” components of the study. At a later stage, a decision was made that no “pipeline” sample could be made for micro finance projects, as there were no client households yet; thus, the 15 project sites were “re-distributed” to water, health and roads sub-projects (see table 1.d).

1.1.3. Household sample

In both the ex-post and pipeline samples, a sample of 20 households was drawn from within the area of influence of each project.

a) Ex-post sample

To ensure comparability with the 1999 data, the Ex-Post sample of households for education, health and water projects were taken from the same censal segments sampled in the 1999 NPS.

For micro finance projects, the household sample was selected from a list of all present borrowers of the program. The list was ordered systematically (either alphabetically or by geographical location of the borrower).

b) Pipeline sample

To ensure that the observed households are all potential beneficiaries from the SFD investment, the sample of households was selected on the basis of the CSO cartography for the censal segment where the project is (or will be) physically located.

1.1.4. Household selection procedure

In each case, the procedure for selection of households for education, health, water and roads projects was the same used by the 1999 NPS survey:

1. The starting point is established by drawing a random number between 0 and 1 and multiplying it by the number of dwellings in the segment.

2. The sampling interval, x, is equal to the number of dwellings in the updated segment divided by 20.

Table 1.b - Universe of projects in Pipeline (approved, but not completed) at December 2002, by sub project type and distribution of the Pipeline sample

Sector

Value of projects (US$)

Number of

projects

Distribution of “pipeline”

sample Education 65,200,089 711 30 Water 19,158,567 303 20 Health 9,082,582 133 20 Roads 9,592,745 86 15 Micro-finance

3,233,609

21 15

Total (all types)

127,374,396 1,537 100



3. The sampled dwellings are the dwelling selected as the starting point and then every xth dwelling. If x is not a whole number the selected dwelling is that which is nearest to x.

4. The sampled dwellings were identified (highlighted) on listing sheets by project area. Sketches were provided to the field teams in order to help identifying the location of sampled dwellings.

5. The selected sample of households included all households that live in the sampled dwellings.

6. There was no substitution of empty dwellings or of households that refuse to be interviewed. Households that were absent from the dwelling were revisited at least twice before being registered as absent.

For Micro finance projects, the selection procedure was based on a list of the names and addresses of all the active borrowers of the project (people with loans currently outstanding). The list was ordered geographically and the sampling interval equal to the number of borrowers, divided by 20. Otherwise, the same procedures applied as for the other projects.2 The micro finance sample is a clustered sample of six active consecutive (living in the same neighborhood) beneficiaries in each cluster of beneficiaries.

1.1.5. Qualitative survey sample

The qualitative survey covers a sub-set of the projects in the project and household survey. Table 1.c summarizes the qualitative sample. Annex B lists the projects included in the sample.

The sample for the five major sectors was divided equally between urban and rural projects. The others were selected from the full list of completed projects in the quantitative project sample, with equal probability of selection for each project.

2 If the microfinance project had no centralized register of the names of borrowers, a two-stage procedure was used, with the first step being to select four of each program’s promoters, from a list ordered by geographical scope, with probability of selection proportional to the number of clients each promoter managed. Then, from each selected promoter’s list of clients, a sample of 6 borrowers was selected, with equal probability of selection for each client, using a sampling interval given by the number of clients of each promoter divided by 6; the expected number of interviews was thus 244 (11 x 4 x 6).

Table 1.c – Qualitative sample for 2003 survey Sector Urban Rural Total

Education 2 2 4

Water 2 2 4

Health 2 2 4

Roads 2 2 4

Micro-finance 2 2 4

Environment 3

Special needs 3

Org.Strengthening 3

Training 3

Total 32



The qualitative study was carried out in each community shortly after the quantitative field team had completed its work.

Table 1.d summarizes all the components of the sample for the 2003 study.

1.2 Evaluation instruments

Project types covered by the quantitative survey work include the following: education, health, water, roads and microfinance. Qualitative studies were carried out of a sub sample of the surveyed projects and also of SFD interventions in environment, special needs, organizational strengthening and training projects which absorbed a relatively small proportion of the Fund’s investments and therefore did not merit quantitative treatments. The study questions covered the following broad areas; SFD’s operational efficiency; cost efficiency, targeting, consultation and participation (including impacts on social capital); service production and sustainability of the services SFD has invested in; and household-level impacts for key development indicators such as educational enrollment and effective access to health care facilities. The Survey instruments are available from the authors.

1.3 Survey/study problems and results

1.3.1 Implementation process

Fieldwork teams were formed and had intensive training for ten days. Each team included one male team leader and four female interviewers, and was provided with a four-wheel drive vehicle and all necessary equipment. Each team was assigned a number of areas in the sample, taking into account the difficulty and the roughness of the some districts, and the spread of the selected clusters in other districts. Data collection process started on 1/15/2003 and lasted for about one month. The field teams interviewed in total 3,804 households (distributed within 187 project areas) and 253 micro-finance beneficiaries (distributed in 45 clusters).

Table 1.d - Summary of sample components for 2003 Impact Evaluation

EXPOST NEW BASELINE

Sector Project survey

House-holds

Qualitative

Project survey

House-holds

Education 30 600 4 30 600

Water 24 480 4 25 500

Health 23 460 4 25 500

Roads 13 260 4 20 400

Micro-finance 11 220 4

Environment 3

Special needs 3 Org.Strength-ening 3

Training 3

Total 101 2,020 32 100 2,000



1.3.2 Project survey

During fieldwork, a number of changes in project’s status were observed: three water projects and one road project were found to be still at the baseline stage (whereas they had been listed as ex-post in the sampling frame). Conversely, two road projects listed as “baseline” were found to have been already completed, and were accordingly re-classified and transferred for analysis purposes to the ex-post sample. One of the intended baseline health projects could not be investigated because of insecurity linked to a tribal conflict situation. The following table shows the intended distribution of projects by category before the initiation of fieldwork and the actual distribution, which is used for analysis:

Table 1.e. Distribution of sub-projects in the survey sample by category, before and after fieldwork

Baseline Ex-post Total Before

field work

After field work

Before field work

After field work

Before field work

After field work

Education 31 31 32 32 63 63 Health 25 24 21 21 46 45 Water 24 27 22 19 46 46 Roads 20 19 13 14 33 33 Microfinance 0 0 11 11 11 11 Total 100 101 99 97 199 198

1.3.3 Household survey

A number of sampling and data collection problems were also encountered for the household survey.

• Some SFD project areas (that is, the location of specific projects in villages and sub-villages) did not correspond to the enumeration areas listed in the 1999 NPS sample frame provided to the field team. Ten such projects were found (three in education, two in health, five water projects, one road project, all parts of the ex-post sample). In these cases, field teams were instructed to draw a sample from the appropriate area (really covered by the project), by making a list of 150 households in the actual project area and then drawing a systematic random sample of 20 households from this new frame (see Annex A for detailed list of these projects).

• Some enumeration areas included households that were not considered – or did not consider themselves - as potential beneficiaries of projects, e.g. because of distance. This arose in the case of 19 projects (five water projects and one health project in the baseline sample; five education, two health and six water projects in the ex-post sample). There were a total of such139 households in the 19 projects, and in five of these projects 10 or more households were not potential beneficiaries. Investigators were instructed to identify those households so they could be excluded from the analysis wherever it was appropriate to do so (see Annex A for detailed list of these projects).



In the analysis phase, these two types of projects were excluded as appropriate, in particular for the evaluation of household level indicators (see Chapter 9).

• In some disperse rural communities benefiting form road projects, the field manager decided to increase the household sample from 20 to 25, to ensure that the incidence of absent households and refusals did not overly reduce the sample available for analysis. However, this increase was not systematic. Eleven of the 14 ex-post road project samples included 25 households, thus leading to a total of 335 households visited. But only one of the 19 baseline road project sample included 25 households, leading to a total of 385 households visited.

The following table shows, for each survey type (baseline/ex-post) and each project type, the number of projects for which household samples were drawn, the number of visited households and the number of households for which the questionnaire was indicated as completed.

Table 1.f - Distribution of surveyed projects, visited households and completed questionnaires Households Projects

Total sample Completed sample Sector Base

line Ex-post

Total Base line

Ex- post

Total Base line

Ex- post

Total

Education 31 32 63 620 640 1,260 586 598 1,184 Health 24 21 45 480 420 900 461 388 849 Water 27 19 46 544 380 924 516 345 861 Roads 19 14 33 385 335 720 366 308 674 Micro-finance 11 11 263 263 234 234 Total 101 97 198 2,029 2,038 4,067 1,929 1,873 3,802

The completion rate overall (proportion of visited households for which the questionnaires were completed) was 93.5%, slightly higher for the baseline survey (95.1%) than for the ex-post survey (91.9%). Sector specific completion rates were 94.0% (education), 94.3% (health), 93.2% (water), 93.6% (roads) and 89.0% (micro finance).

1.3.4.Working database

The field work and data processing (including translation) was a carried out by the SFD. Analysis was undertaken by the study team.

The information remitted to the study team related to project and household surveys was initially located in three databases: the project survey’s database and the household survey’s household database and person database. The impact evaluation analysis, which implies the interpretation of project-related benefits on the basis of different household or personal characteristics, requires that those separate databases be related, a process which entails some additional loss of information linked to the need to obtain complete datasets for all observations.



Thus, the following are the final outputs of the quantitative surveys that constitutes the core observations for the impact analysis3:

- number of households: 3,790, distributed as follows: education projects – 1,179, health projects – 847, water projects – 855, road projects – 670, micro finance projects – 239 (actually 232 households, since some beneficiaries were found in the same households);

- number of persons: 28,203 (down from 28,270 in the initial database), including 4,113 women in reproductive age, 1,914 children under two years of age and 5,519 persons indicating a source of income.

3 That is, before taking out the problematic enumeration areas mentioned above.



2 SFD’s Operational efficiency

2.1 Number and type of projects/amount of funding

As of July 2003, the Social Fund for Development has committed a total of US$213 millions in 3,034 projects, of which 1,685 (US$94M) have been completed, 1,232 (US$111M) are under implementation and 117 (US$8M) have been approved pending implementation (see Table 2.a, budget in US$).

Table 2.a - SFD Investments by sector to July 2003

Compared with the program’s situation in December 2002, as reported in the Phase 2 Report, the proportion of completed projects has gone up from 45.5% to 55.5%, while the proportion of the total investment spent in completed projects has gone from 34.4 to 43.9%. The SFD’s main commitment remains with education projects (1,524), which account for 54% of the total investment, followed by water projects (530) for 15% of the total budget, health projects (281) for 8% of the budget, and rural roads (100) with 5% of the total investment. Those four categories still represent 79% of all projects. Of more recent interest and implementation are projects for special needs groups and environment projects, both with 5% of the total program’s investment.

2.2 Number of beneficiaries

A simple way to assess the impact of a program is to look at the number of persons who benefit from the program. The SFD’s Management Information System records, through the Project Appraisal forms, the number of beneficiaries for each project, as defined in the Impact Monitoring and Evaluation Manual.

Table 2.b summarizes the number of direct and indirect beneficiaries of SDF projects by type of project and by year of completion. Education, health, water and road projects generate 79% of all direct beneficiaries, a figure which goes up to 97% if environment projects are included in the group. Indirect beneficiaries add only 19% to the number of direct beneficiaries. The number of direct beneficiaries varies by type of project, from small-scale ventures such as training (55 beneficiaries per project) or special needs groups projects (302) to wider-scaled

Number of projects Budgeted value of investmentApproved Underway Completed Total Approved Underway Completed Total

Education 59 577 888 1,524 4,167,302 56,630,861 53,452,350 114,250,513 50 54Water 28 218 284 530 1,616,404 14,694,706 16,743,512 33,054,622 17 15Health 11 93 177 281 548,281 7,236,693 9,385,550 17,170,524 9 8Roads 3 65 32 100 306,657 7,641,489 2,984,188 10,932,334 3 5Special Need 3 102 41 146 65,000 8,508,334 2,416,324 10,989,658 5 5Environment 4 36 41 81 563,711 5,105,128 4,273,255 9,942,094 3 5Cultural Herit 3 26 8 37 453,680 4,618,825 654,370 5,726,875 1 3Micro Credit 16 26 42 2,698,838 1,417,463 4,116,301 1 2Organization 5 53 86 144 650,057 1,852,086 1,234,140 3,736,283 5 2Training 29 96 125 1,084,271 1,166,441 2,250,712 4 1Integrated In 1 16 4 21 76,000 1,037,890 85,813 1,199,703 1 1Small Entreprises 1 2 3 126,000 13,706 139,706 0 0Total 117 1,232 1,685 3,034 8,447,092 111,235,121 93,827,112 213,509,325 100 100

3.9% 40.6% 55.5% 4.0% 52.1% 43.9%

% of projects

% of investment



road (9,630) or environment (14,348) projects, through medium-size developments in education (713) or water (2,867)4.

Table 2.b - Summary of direct and indirect beneficiaries of SFD projects by type of project and year of completion

Source: MIS

It seems, from the figures above, that the data reported by the MIS are overestimating the number of beneficiaries in some cases. For instance, the MIS reports around 600,000 direct beneficiaries for education projects, which in total built or refurbished 5,396 classrooms (also according to the MIS). This would give an average of more than 100 beneficiaries per classroom. However, the estimation of number of beneficiaries is made difficult by the summarization of the corresponding data, regardless of the type of intervention (construction of new classes, completion or rehabilitation of existing classes or provision of furniture). If one only looks at projects where the intervention was limited to building of new classes (about 40 projects, table not shown), the average number of beneficiaries per class varies between 25 and 239 (with an average of 51.6)5, a more likely figure.

Information from the evaluation’s qualitative survey reveals that, even after SFD intervention, overcrowding remains a major problem. However, the project survey shows that in the sampled sites, the number of students per classroom rose from 29 in 1997-8 to 33 in 2002-3, a figure more compatible with the national average of 36, even considering that some schools may have two daily shifts, as will be seen in chapter 6.

4 Those figures are consistent with the number of beneficiaries estimated by the main respondents of the project survey, as seen in chapter 6. 5 Eliminating this one outlier showing 239 beneficiaries per classroom, the average becomes 46.7.

Completion Year

Cultural Heritage Education

Environment Health

Integrated

Interventi

Micro Credit

Projects

Organizational

Support Roads

Special Need

Groups Training WaterGrand Total

1997 900 5,200 784 6,8840 1,006 0 1,006

1998 48,848 1,523 91,958 782 97 64,277 207,48513,778 0 5,000 0 0 7,400 26,178

1999 129,530 10,500 182,075 40 442 223 124,895 447,70519,498 0 27,000 0 0 0 0 46,498

2000 34,249 10,770 139,863 9 3,657 2,964 5,000 200 477 40,472 237,6613,515 0 9 0 8,040 2,720 3,000 0 0 724 18,008

2001 14,900 95,694 105,877 144,710 939 1,846 4,260 61,409 8,791 1,229 219,257 658,9120 21,339 0 17,500 0 10,833 155 26,494 45,377 4,500 1,200 127,398

2002 950 249,631 278,040 165,238 51 662 11,214 157,869 2,909 1,783 274,029 ########4,900 25,967 36,000 6,006 112,270 3,738 2,074 39,980 3,591 22,900 89,555 346,981

2003 46,893 181,540 57,631 245 3,513 83,876 498 1,504 81,876 457,6761,838 7,000 650 5,060 524 37,028 903 10 159 53,172

Total Direct 15,850 605,745 588,250 786,675 999 6,450 23,175 308,154 12,398 5,313 805,590 ########Total Indirect 4,900 85,935 43,000 57,171 112,270 27,671 5,473 106,502 49,871 27,410 99,038 619,241# projects 8 849 41 177 4 26 86 32 41 96 281 1,641Direct beneficiaries by project 1,981 713 14,348 4,444 250 248 269 9,630 302 55 2,867 1,936



Gender distribution, as calculated through project statistics shows that the distribution is more or less equal by gender except in the case of indirect beneficiaries of education projects (table 2.c). A likely explanation for the latter issue is that the construction of new classrooms for female students, a focus of the program, actually converts predominantly male students who were sharing mixed classes before the intervention into indirect beneficiaries.

Figure 2.a shows the cumulative number of direct beneficiaries by year and by type of project, evidencing the strong increase in program performance during the second phase of the SFD, in particular for water, education and environment projects. The second phase (2000- ) also shows the growing importance of road projects and other types of projects (cultural heritage, special needs groups, etc.) in the Fund’s portfolio.

Figure 2-a - Cumulative number of direct beneficiaries

2.3 Project cycle performance

The concept of project cycle performance refers to the relative speed of the different steps needed to complete the project. The are five milestones that define the major steps in the process: request for project funding, approval of the project by the committee, signature of a contract with the requesting community, adjudication of construction contract, completion of works. The measure used in this section is the median time, rather than the average, which can be strongly influenced by very few outliers. From the data available from 1,035 completed projects including civil works, the overall duration of the process is 576 days, that is 19.2 months, distributed as follows:

Table 2.c - Proportion of female beneficiaries by type of sub-project Proportion of women beneficiaries

Direct Indirect

Education 43.3 34.7 Health 50.3 52.8 Water 50.1 49.9 All projects 48.9 47.8

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

900,000

1997 1998 1999 2000 2001 2002 2003

Education Water Health

Roads Environment Others



- from request to committee approval: 221 days (38.4% of total time) - from committee approval to contract with community: 16 days (2.8%) - from contract with community to construction contract: 102 days

(17.7%) - from construction contract to completion: 237 days (41.1%)

There are, however, some internal differences: for instance, water projects are quicker to approve and, along with health projects, have a shorter civil works time, resulting in an overall median duration of 520 days. On the other hand, road projects take longer to approve and complete, for an overall median duration of 648 days (the corresponding figures are 562 days for health projects and 580 days for education projects).

Although the above statistics are calculated only on the basis of the completed projects, it is important to note that SFD accepts new requests whether or not there is availability of funding at the time. Managing those requests – about 20,000 since the starting date in 1997, including those not funded or implemented, takes time and energy away from the implementation of selected projects. The sector of feeder roads is a point in case, as it was not an area of intervention for the SFD in the beginning and funding only came through by 1999.

Figure 2-b - Project cycle performance – by sector

Another interesting difference is related to the year of implementation. Figure 2.c below, shows the distribution of median duration of the same main four steps, with the projects distributed according to the year when they were completed. The overall picture over time is that of an increasing length of the project cycle, from 282 to 631 days. However, the increase in total time taken is almost entirely attributable to the first stage (from request to approval). This is likely to be related in part to the increase in the number of project requests to be processed, as the SFD become better known and more accessible, due to the decentralization of the program. It is also linked to increased stringency in the appraisal and monitoring norms of the SFD as the institution matured.

��

��

��

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��

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��

0 100 200 300 400 500 600 700

Education

Health

Roads

Water

All sectors

Number of days (median)Request to approval

��Approval to community contract��Community contract to construction contractConstruction contract to completion



Figure 2-c -Project cycle performance – by year

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0 100 200 300 400 500 600 700

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Number of days (median)Request to approval��Approval to community contract��

Community contract to construction contracConstruction contract to completion



3 Cost – Efficiency of SFD Investments

Cost per beneficiary

The average cost per direct beneficiary was calculated from data provided by the Fund’s MIS for completed sub-projects. The results, presented in Table 3.a, range between US$7.26 for environment projects to US$220.91 for training ventures6. Projects with larger number of beneficiaries tend to be less expensive on a per capita basis.

The outcome for this indicator is closely in line with the expected parameters that were anticipated in the project’s design. The Project Appraisal Document for the Second Phase of the SFD quoted the costs of education projects at US69-134, those of health projects at US$6-15, those of water projects at US$17-32, and those for roads projects at US$12, for the period 1997-1999.

Table 3.a - Cost of SFD completed sub-projects per beneficiary

6 Those estimates are conditional on the accuracy of the other inputs in the equation, in particular the average number of beneficiaries.

Type of sub-projectAverage cost per project

(US$)

Number of direct beneficiaries per

projectAverage cost

per beneficiaryEnvironment 104,226 14,348 7.26Roads 93,256 9,630 9.68Health 53,026 4,444 11.93Water 58,956 2,867 20.56Cultural Heritage 81,796 1,981 41.29Organizational supprt 14,350 269 53.35Education 60,194 713 84.42Integrated Interventions 21,453 250 85.81Special Needs groups 58,935 302 195.15Micro credit 54,518 248 219.83Training 12,150 55 220.91

55,684 1,934 28.79



4 SFD’s Targeting Outcomes

Benefit Incidence Analysis

The interim impact evaluation report presented in December 2002 presented both a community-level and household-level analysis of targeting. In the present report, the household-level analysis is repeated using data from the new household survey. It should be noted that the community level analysis already presented, remains valid, as it used data for project locations and costs up to the end of 2002 and the most recent available data on relative poverty conditions in different geographical locations in Yemen from the 1999 National Poverty Survey. It is not, therefore, repeated here.

The analysis of targeting outcomes at household-level is based on data for the real beneficiaries of the program’s investments. This approach requires the use of urvey data to document the income of beneficiary households. It shows what proportion of program resources benefit each decile of the population, based on data for the per-capita income of each household and the amount of the SFD’s investment in each community and project.

The 2003 Impact Evaluation Survey (IES) database includes information on household per capita income for all households in the survey sample, that is households included in the area of influence of the SFD projects (in this case, both the ex-post sample and the baseline sample are included in the analysis). The 1999 NPS database provides a reference frame for the national per capita income distribution, permitting the insertion of each household in the area of influence of these 198 SFD projects into the national per capita income decile to which it belongs. This reference frame was updated to 2003 values using the official retail price index.

For each project covered by this survey, the value of the investment was found from the SFD’s MIS. In the absence of detailed household-level data on the utilization of the facility, it was supposed that each potential beneficiary derived equal benefit from the project. The value of the investment was therefore imputed to the deciles of the expenditure distribution, pro-rata with the distribution of its beneficiary households. For example, if a 15% of a project’s potential beneficiary households were in the third decile of the income distribution, 15% of its value was attributed to that decile, and so on.7

In this way, the investment in the 63 education projects was allocated between household income deciles, with each project in the sample having a weight proportional to its value. The distribution of the investment in water, health, roads and microfinance projects was established in the same way. Annex C contains the spreadsheets used for these calculations.

The next step in the analysis was to estimate the total resource distribution. This was estimated as a weighted sum of the resource distributions for each sub-project

7 The deciles for the household level analysis of targeting reported in the present section are based on equal numbers of people (population deciles), not equal number of households.



type, where the weights are given by the total SFD investment to date in each of these types of sub-project, based on MIS data. Education has a weight of 0.62, water 0.20, health 0.10, roads 0.07 and microfinance 0.02.

The result is an estimate the proportion of total SFD funding going to each decile of Yemen’s population, by type of project and globally for all SFD projects. Table 4.a shows the results of this analysis, and figure 4.a illustrates them graphically in the form of a cumulative distribution curve.

Table 4.a - Benefit incidence of SFD – 198 projects with data from MIS of SFD and the IES 2003

The results are very positive, showing that a high proportion of SFD resources are benefiting the poorest households in Yemen. 17% of SFD funds go to the poorest decile, 31% to the poorest quintile and 44% to the poorest three deciles. Only 4% of resources are received by households in the top decile. These figures are considerably better than those found in other Social Investment Funds where similar analytical procedures have been applied. It is especially to the credit of the Yemen SFD that it has achieved this effective bias towards the poorest households, notwithstanding the very high level of poverty across the whole population and the relatively flat income distribution in Yemen (with a Gini coefficient of 0.38). These factors might have been expected to make it more difficult to target the relatively poorer households.

These findings are graphed in the cumulative distribution curve shown in Figure 4.a, in which the population is accumulated in deciles from poor to rich along the horizontal axis and the resources assigned to each decile are accumulated along the vertical axis. If the cumulative distribution curve lies entirely above the 45% dotted line, the distribution is unambiguously progressive, as is the case here; while if it lies below the line, it is regressive.

Populations deciles from poor (1) to rich (10)/11 2 3 4 5 6 7 8 9 10 Total

Total program resources SFD

Distribution Index /4

Education 102,769,793 16.8 14.5 12.1 10.9 11.7 6.1 8.8 8.8 6.3 4.0 100.0 0.201Water 32,559,350 18.2 13.9 14.1 10.5 10.8 9.9 7.0 6.9 6.5 2.3 100.0 0.176Health 16,302,332 15.6 14.4 12.8 9.6 12.0 7.8 7.9 7.8 5.2 7.0 100.0 0.242Rural Roads 11,284,867 15.2 18.9 14.2 10.9 10.9 8.9 6.5 6.6 2.3 5.5 100.0 0.256Micro Credit 3,890,501 8.2 7.0 9.8 10.5 7.5 14.1 7.7 14.1 7.6 13.6 100.0 -0.072Total /3 166,806,843 16.6 14.5 12.6 10.7 11.4 7.4 8.2 8.3 6.0 4.3 100.0 0.204

% of resources based on potential beneficiary population/2 for education, water, health, rural roads and micro credit

Notes1/National Population deciles based on income data from NPS 1999 ajusted to january 2003 with CPI, acumulating population in order of percapita income with cut-off points determined by the accumulated population of the households and set at 10%, 20% etc of the total population.2/ Potential beneficiaries are the population located in the IES 2002 sample considered to be within the area of influence of the 198 SFD projects analyzed.3/ Total for the project types analysed here to december 2002. Other projects account for 14.1% of 194,244,249 SFD resources in total . The total is based on the sector-specific estimates weighted by the investment amount in each sector for the whole SFD program. It is valid only for the project types reported here.4/ See text for definition.



Figure 4-a - Household-level targeting outcome: 198 Yemen SFD Projects in education, health, water, rural roads and micro credit

The distributive impact is also summarized in the final column of Table 4.a, where an index number is reported for the distribution of the resources. This number is defined in such a way that it takes the value of zero when every decile gets exactly 10% of the resources; it is > 0 when the distribution is progressive and < 1 when it is regressive. The limit values are -1 and +1. The distribution index number for the total of the project types analyzed here is above zero, at 0.204, indicating a significant positive impact.

It's also noteworthy that the pattern is consistent across sub-project types (with distribution indexes ranging between 0.176 and 0.256. The only exception is micro finance where the distribution index of –0.072 shows a regressive pattern, maybe linked to the fact that people benefiting from micro loans are self-selected and tend to be more “entrepreneur”, and thus less likely to be poor, than the average target population. This is a normal finding for this sort of project. However, this group of project has a small weight in the total distribution. It should also be mentioned that the project sample for micro finance was small, but was virtually a census of all SFD micro finance projects, so it is representative of those projects.

These results differ from the findings based on the analysis of 1999 NPS data that were presented in the Phase 2 Report of this study, which found less favorable results. There are various possible explanations for this. It might reflect an improvement in targeting by project officials since 1999. It also might reflect methodological problems in the analysis of the 1999 dataset related to the link of projects' areas of influence to household data observations (so that non-beneficiary households were wrongly classified as SFD beneficiaries, or vice-versa).

For the 2003 IES study, the definition of primary sampling units (project’s areas of influence) was directly controlled by the study team, whereas in the 1999 exercise the data collected by the NPS teams might have covered households that were not really beneficiaries. As mentioned above, in some cases, when the study team got in to the field for the 2003 IES, they found that the censal segment supposedly related to the SFD project according to the 1999 NPS database was in fact wrongly identified. For this reason, the study team is confident that the 2003 findings on targeting are more reliable than the 1999 findings.

Another methodological change is that the estimation of benefit incidence for the 1999 NPS used household expenditures as a proxy for income while the 2003 study (for survey cost reasons) used estimated per capita income based on direct

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statements of income received. As is well known, properly collected expenditure data are normally likely to give a better absolute proxy estimate for income than direct statements of income by interviewees. However, there is much less likely to be a significant non-random difference in the ordinal ranking of households between these two methodologies. Therefore, in the opinion of the study team, it is unlikely that non-parallel variations in the distribution of the population for these two variables could be responsible for the observed differences in the targeting outcomes between the two datasets8, and Figures 4.b show the resource distribution for each type of project. Road, water, education and health projects, in this order, have progressive distributions, while the microfinance projects show a cumulative distribution of project’s benefits below the 45% line.

Table 4.b - Comparison of benefit incidence between the 1999 NPS and the 2003 IES

1999 NPS 2003 IES Distribution

Index #

projects Distribution

Index #

projects Education -0.022 1,399 0.201 1,524 Water 0.038 528 0.176 530 Health 0.078 276 0.242 281 Road 0.256 100 Micro Finance -0.072 42 Total 0.002 0.204

Figure 4-b - Household level targeting outcome: results by type of project

8 So long as the data has been carefully collected, household expenditure is generally held to be the best proxy for household income (it is a proxy for “permanent income” on which households are theorized to base their expenditure decisions, according to Milton Friedman’s “Permanent Income Hypothesis”).

Household level targeting outcom e: 45 Yem en SFD health projects

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5 Consultation, Participation, Ownership and SFD’s Impact on Social Capital

5.1 Consultation on project design

One of the development objectives of the SFD is to promote innovative approaches to community development by involving beneficiaries in project identification, preparation and implementation, while encouraging NGOs, government agencies and other institutions to assist communities where needed. This section reviews the extent and nature of community involvement in the sub-projects evaluated, and the perceptions of those communities with regards to the works undertaken. To widen the perspective, it uses information from three different sources: interviews with key respondents from the project survey; opinions gathered during the household survey in the area of influence of the sub-projects; and comments from the qualitative survey.

From the qualitative survey, it is clear that the first step in most projects is often taken by a key individual, most often a local sheikh or member of Parliament who is made aware of the need and forwards the initial request to the SFD. In a few cases, a local agricultural association may be involved (Al Shammayateen, Taiz). Finally, specially in the case of health units, the initial step may come from prospective visits made by the SFD, sometimes along with officials from the Health Office (Gashen, Al Meerah and Al Habilane, Lahj).

Respondents in the project survey were asked to estimate the extent of community involvement in the discussions held prior to project implementation. The results are presented in Table 5.a.

Table 5.a - Proportion of main respondents, community leaders and community representatives who were involved in sub-project discussions

Education Health Water Road EP BL EP BL EP BL EP BL Main respondents informed 91 95 95 92 100 96 100 85 Leaders/persons involved in the discussion Shaikh 76 74 80 59 84 92 79 77 Member of Parliament 66 50 45 36 61 33 43 45 Staff of institution 59 61 45 45 16 8 Local Council 21 43 20 23 21 31 29 29 District Gvt. Office 21 25 20 23 12 Governorate Office 7 32 25 41 NGO 10 4 15 18 21 20 14 12 Community beneficiaries 90 86 100 86 100 92 100 94

Source: IES 2003 – Project survey

The respondents themselves, in most case managers of the sub-project or otherwise involved in its current work, were overall well informed about the project design. Their answers with regards to other persons’ involvement indicate the frequent occurrence of involvement of individual political leaders (shaikh or Parliament member), either to initiate or to support the project, a traditional way for politicians or customary leaders to maintain their status. Staff members of the beneficiary



institutions were consulted in more than half of the cases for education and health projects. The district and governorate-level offices of the line ministries seem to be only peripherally involved which may indicate the effectiveness of the Fund’s interventions in bypassing common administrative barriers and bottlenecks, and establishing itself as an action-minded organization. On the other hand, it may also reflect a lack of inter-sectorial coordination, which may be prejudicial to the future operation and maintenance of the sub-project.

Although the project survey shows that in almost all cases, some members of the community were consulted, that is not the same as all members of the community being informed of or consulted about the project. The evidence from the household survey shows that between a third and two-fifths of the populations knew about the SFD project (40.2% in the ex-post group and 36% for the baseline group). When households in the ex-post group were asked which kind of project was supported by the SFD, those who knew there was one mentioned the correct type in 91% to 96% of the cases.

The qualitative survey indicates a clear gender difference: while most participating men knew about the sub-project and the SFD, almost all women said they were not consulted and did not know about SFD and its performance in project implementation.

“Men don’t tell women.” (Al Hegrh, Amran)

“I asked my husband and he told me don’t be curious.” (Adood, Taiz)

“We are women, we don’t put our nose.” (Al Munirah, Hodeidah)

“We are women, we don’t know about anything.” (Al Ramady, Ibb)

Yet, in a number of cases, specially water projects, where community participation in terms of labor is minimal, the consultation is more on the technical side and even men become aware when the workers arrive on site. However, when they take place, these consultations with community leaders or community members at large sometimes lead to changes in the design of the project (different location of building, increased size of water tank, etc.).

5.2 Community contribution to the project

Communities’ direct participation can take several forms: donation of money or working days, donation of materials for construction of the main building, etc. Table 5.b shows, for each type of participation and each type of project, the proportion of communities that participated in the projects and the average amount (money-equivalent) of this participation, according to the main respondents.

Between two-thirds and four fifths of the communities contribute money to the sub-project, the easiest way to participate, provided there is some money available in the community. Direct labor contribution is highest in the road sub-projects (57.1%) as well as contribution in materials (stones). Using an average exchange rate of YR 160 per US$, the community contribution estimated by the main respondent corresponds to 6.9% of the completed project costs (as assessed by the SFD, see Table 2.a) for education projects; 7.3% for health projects; 16.5% for water projects and 11.3% for roads projects. These figures are above the 5% that



constitutes one of the requirements for SFD funding. Their relative size could also indicate the grade of priority that communities give to each type of sub-project.

Table 5.b - Frequency and average amount of community contribution to SFD sub-projects

Education Health Water Roads Type of participation

% Amount (YR)

% Amount (YR)

% Amount (YR)

% Amount (YR)

Money 71.9 445,750 77.8 376,389 83.3 1,066,666 64.3 425,143

Working days 37.5 61,515 44.4 54,889 33.3 138,444 57.1 201,071

Stones 34.4 68,125 33.3 133,472 11.8 150,000 57.1 655,721

Sand 28.1 28,125 0.0 22.2 9,036 7.1 7,143

Water 25.0 15,000 22.2 13,333 27.8 7,333 14.3 10,000

Other materials 18.8 24,000 33.3 29,167 47.1 2,612,292 14.3 35,714

Other 15.6 21,594 5.6 11,111 26.7 41,111 7.1 357,143

Total N=32 664,109 N=18 618,361 N=18 4,024,903*

N=14 1,691,935

Source: IES 2003 – Project survey Note: one isolated contribution for YR40M in “other materials” has a large impact on the average water project community contribution. Discarding this outlier, the average total contribution for water projects would be: YR1,558,504, similar to that of the road projects. All figures in nominal YR.

Of the surveyed households, 38.7% said they had contributed to the sub-project. Individual contributions by categories show similar patterns, as seen in Table 5.c, with money contribution being the most common. As sub-projects get under way, the labor and materials contribution make up an increasing share of community contribution, as opposed to financial contributions, which predominate before the beginning of a sub-project.

The average household contribution is estimated, in the ex-post group, between six and twenty five thousands Yemeni

Table 5.c - Proportion of households contributing to SFD sub-projects by type of contribution

Ex-post Type of contribution Educ. Health Water Roads

Percentages Donating labor 32.8 45.9 32.8 42.6 Donating materials 6.7 23.5 22.7 16.3 Donating money 67.2 50.6 67.2 54.7 Donating or lending tools 2.1 2.4 2.5 4.7 Other 6.7 3.6 2.5 11.1 Memo item: Number of observations 238 84 119 190

Table 5.d - Average household contribution to sub-projects by category Monetary value of household contributions (in YR)

Education Health Water Roads # h/hlds donating

Donated labor 4,997 2,241 2,177 3,265 237 Donated materials 1,203 1,362 1,682 3,851 94 Donated money 5,190 1,683 3,432 7,766 387 Donating or lending tools 143 71 32 319 19 Other ways 13,917 1,250 25 2,732 42 Total 25,450 6,607 7,348 17,933 Number of observations 238 84 119 190 Source: Household survey. Note: averages calculated on the basis of all households in project groups (nominal YR)



Riyals, as seen in Table 5.d. Education and rural road sub-projects have the highest level of household contribution.

For all type of sub-projects, individual household contribution is important. In some cases, it goes without saying:

“The contribution was easy on us; it was great to contribute; it was for our benefit; there was no disadvantage for contribution.” (Jabal Henwab, Taiz)

“We built the foundation, but we did not pay one ryal.” (Al Zerai, Hodeidah)

For others, it comes at a higher cost, be it in time and energy or in cash:

“We work on it till our hair whitens.” (Beir Al Aros, Lahj)

“The tractor driver was not paid, so they had to give him gold and weapons as guarantee; but until now he has not given us back our gold.” (This is because he had not yet been fully paid at the time of the survey.

“We sold rocks extracted from the old cistern and sold a generator to a member of the community.” (Al Ramady, Ibb)

In general, women express the same willingness to contribute as men, either through money from the household or in form of a more specific input:

“We provided workers with food for the whole period they were working on the road.” (Beir Al Aros, Lahj)

“In the rural area, you know that women have a different job from men; they look after children and prepare the food for the family. They do not interfere or react with the men who also do not listen to women. We contribute with food and water.” (Al Hegrh, Amran)

In any case, even if it brings hardship to the household, people are willing to cooperate, either for project implementation or for operations and maintenance, provided the services are actually delivered:

“We are willing to cooperate, if we receive services from this project.” (Gashen, Al Mahra)

5.3 Consensus on priority of SFD Project

In assessing the participation of the community in the development of a project, the perceived level of priority for the SFD project gives an idea of the consensus between the SFD and beneficiaries on what the issues really are. The respondents in the project survey and the interviewees in the household survey were asked whether they thought the project really was a priority; the results are shown in Tables 6.e and 6.d.

Table 5.e - Sub-project priority as perceived by project survey respondents (ex-post)

Level of priority Education Health Water Roads High 90.6 100.0 100.0 100.0 Worthwhile 9.4 0.0 0.0 0.0 Not a priority 0.0 0.0 0.0 0.0



As one would expect, the project survey respondents, most of them currently involved in the projects, are virtually unanimous that the project chosen was the main priority of the community. The only cases where other priorities were cited were two education projects, where the stated priorities were water and health.

The household perspective is slightly more diverse, but there is still a clear majority of 60% to 89% of interviewees concurring that the project implemented by SFD was the highest priority, with the best ranking going to micro finance projects. For those who stated other priorities, water projects were the preferred alternative in 52.2% of the cases, health in 17.1%, education in 13.2% rural roads in 5.6% and electricity projects in 7.8%.

Table 5.f - Priority of sub-project as perceived by households (household, ex-post survey)

Level of priority Education Health Water Roads Microfinance Would have chosen same project 60.0 74.2 73.8 78.9 88.8 Would have chosen other project 32.8 18.9 19.5 17.9 8.6 Did not know 7.2 7.0 6.7 3.2 2.6 Number of households 595 387 344 308 233

Participants in the qualitative survey’s focus groups and interviews were almost unanimous in agreeing on the high priority of the project implemented in their village. Water projects benefits are expressed mainly in terms of time saved by the women to fetch water and the rationale for road projects is often linked to being able to bring sick patients to hospital:

“Our daughters do not have to carry and fetch water any more.” (Al Shammayateen, Taiz)

“We go down the valley at dawn and come back at noon; it takes us about six hours to go and fetch water.” (Al Ramady, Ibb)

“We were transporting sick patients on our backs for hours to get to the nearest hospital.” (Beir Al Aros, Lahj)

“In the past, if somebody was in a medical emergency, he might die on the road, or at least his condition might worsen, because the road was so rough.” (Jabal Henwab, Taiz)

The priority of health projects is generally agreed on, but results are sometimes below expectations, as most of the new or rehabilitated facilities only provide first aid and immunizations; the Governorate Health Office often assigns a Medical Assistant but no physician or midwife. Thus, antenatal care and delivery are often still excluded from the service mix offered at the facility.

“Only if they provide a doctor for delivery, it will be a true facility … now it is just a lie.” (Al Hegrh, Amran)

5.4 “Ownership” of project

One way to assess ownership of the project by the community is to investigate the perceived quality of the work done, under the assumption that community members will cherish and better maintain a facility they deem to be of acceptable quality. Again, the same question was asked from the main respondents in the project survey and the interviewees in the household survey.



Table 5.g -Perceived quality of SFD work among main respondents (project survey)

Perceived quality of work Education Health Water Roads Excellent 71.9 85.7 57.9 71.4 Average 25.0 14.3 26.3 7.1

Bad 3.1 0.0 15.8 21.4

For education projects, reasons for perceived bad quality included: bad quality of the stones employed in the construction; presence of surface cracks or roof leakages; absence or low quality of doors and fences. For water projects, reasons for dissatisfaction with quality included: water leakage; shortage or bad quality of cement; not abiding by standards; the well not being dug deep enough. For rural road projects, they included: road still narrow; delay in implementation by the contractor, not meeting the standards.

Stories obtained from the qualitative survey are diverse: a number of them praise the contractor; a similar number complains about him, accusing him of cheating on the inputs, delaying work, not respecting the standards. The SFD and the communities, however, have their own way of reacting to perceived deficiencies in contractors’ performance:

“The Sheikh has complained to the district manager about the contractor, and he was put in jail.” (Al Ramady, Ibb)

“He wanted to manipulate but he was put under observation, the SFD was informed and replaced him.” (Warzan – Al Raheda, Taizz)

Table 5.h - Perceived quality of SFD work among ex-post household members (household survey)

Perceived quality of work Education Health Water Roads Excellent 61.6 56.3 42.7 53.6 Average 7.1 15.0 15.7 20.6

Bad 3.0 4.7 13.1 9.2 No opinion / no response 28.3 24.0 28.5 16.6 Number of observations 594 387 344 306

Another approach to assessing ownership of project and likelihood of community participation in its running and maintenance is asking about the perceived value of the finished product as compared to the resources (both theirs and the project’s) invested in its development (value-for-money).

Table 5.i - Perceived value for money of the SFD works among main respondents (project survey)

Value for money Education Health Water Roads Good 75.0 85.7 84.2 78.6 Medium 21.9 4.8 5.3 0.0 Low 3.1 9.5 10.5 21.4

In the case of education projects, the cases of perceived low value for money were linked to a still insufficient number of classrooms and the lack of fences. For water projects, respondents felt that in some cases, the consultants and contractors changed the standards, or that the community did not really benefit from the project. Reasons for low value perception of the road projects included the fact that the work was sometimes not completed or not up to standards.



With regards to the last type of project, it should be remembered that the concept of feeder roads was introduced in Yemen by the SFD, as a category of roads to be built according to simplified economic and technical standards, aiming at keeping roads open all over the year, with minimal improvements focusing on critical sections and introduction of rain water drainage and soil slide prevention components. The simplified design and implementation techniques, especially dry stone paving and retaining walls, which are labor intensive, compare poorly in terms of image, with the government agencies’ intervention involving heavy machinery, asphalt pavement, bigger concrete bridges and culverts, etc. However, the simplified specifications are well known to be more cost effective for rural roads projects.

Finally, one can simply ask households in the area of influence of the sub-projects if they do actually feel that they are beneficiaries of this project. The left-side part of Table 5.j shows that the proportion of ex-post households feeling that they actually do benefit from the sub-project implemented is highest for road projects and lowest for water projects; an overall proportion of 60.6% consider themselves beneficiaries Others would like to see more water available, and delivery directly to the dwelling. In the new baseline group (where sub-projects are planned or under way but are not completed), the proportion of households defining themselves to be beneficiaries is lower, and can be expected to rise when implementation is complete.9

However, the proportion of respondents who perceive themselves as definitely not being a beneficiary also tends to increase from the baseline group to the ex-post group. This is probably due to it being much clearer after a project is finished, who are really the beneficiaries; ex-ante, some people may expect to benefit, who turn out later not to benefit. This could lead to some discontent with the SFD project among the households who do not benefit, for whatever reason. SFD should attempt to provide clear information as early as possible about the scope of coverage and the character of services to be provided, in order to avoid such confusions.

Table 5.j – Households’ perception of their beneficiary status in relation to SFD projects

Ex-post Baseline Education Health Water Roads Education Health Water Roads Beneficiary now 56.1 69.3 41.0 80.2 9.2 12.0 0.8 16.4 Beneficiary in the future

13.3 17.6 20.6 13.0 78.1 80.7 72.9 72.9

Not beneficiary 30.6 13.2 38.4 6.8 12.7 7.4 26.4 10.7 Source – 2003 IES

5.5 Social Capital

Social capital is usually disaggregated into two components: structural social capital, which includes the extent and intensity of associational links or activity, and

9 Note that this comparison is with the new baseline sample; a comparison cannot be made with the baseline situation of projects that are now completed, as the 1999 NPS survey did not include this question.



cognitive social capital, which covers perceptions of support, reciprocity, sharing and trust in the community. The cognitive component of social capital in the survey population was explored through asking whom would households in financial needs turn to for support.

The present (pre-existing) levels of social capital are likely to affect directly the success of any given project, since greater trust between community members, or stronger functional relationships between those members can facilitate the planning, implementation and operation of the SFD sub-projects. Conversely, the community’s experience of planning, implementing and operating an SFD sub-project may, depending on the quality of this experience, create or erase social capital in the community. The impact of an SFD project on social capital is expected to be an important determinant of the overall impact of the project on a community’s development.

We do not have data on social capital for the ex-ante situation of the communities in the ex-post sample, and so are only able to compare here the ex-post social capital situation with the ex-ante situation in the new baseline sample. It is important to stress that the comparison of these two groups is not necessarily a good indicator of SFD’s impact on social capital, as the social capital status of the new “Baseline” group might have been different from that of the pre-intervention status of the “ex-post group”. Also, the preparatory phase of the SFD intervention (which had already happened in these communities, in order for the project to be firmly approved for implementation by SFD) would be expected to affect (positively) their social capital status. Nevertheless, we report here the findings for the two groups.

The fact that the levels of structural social capital appear to be generally rather low in both datasets is some indication that the SFD is not yet having a major impact in this area. Only 4.0% of the households in the ex-post group (and 2.3% in the baseline group) mentioned that they had members affiliated with any association, with an average of 1.6 members affiliated per family with affiliation.

Another measure of structural social capital is respondents’ knowledge of organizations that work for the benefit of the community (Table 5k). But once again there is little sign that there is more organizational presence in the communities in the ex-post than in the ex-ante (new baseline) group. A similar proportion of households (13.9 and 14.1%) seemed to know about such organizations.

Table 5.k - Service-providing organizations in the community (multiple answers) Ex-

post Base-line

Local societies (cooperatives/charitable)

56.4 38.2

Office of Post & Communications Services

10.0 32.4

Water/Electricity Corporations 23.6 30.1 Local Councils 24.3 19.1 Hospitals/health facilities 5.8 18.8 Social Security Fund 17.8 8.5 Education/illiteracy offices 14.7 11.8 Other government agencies 5.8 11.4 Schools 0.4 11.0 Private Sector Corporations 5.8 11.0 Foreign donors 2.7 9.6 Security/Civil Affaires 0.8 9.6 Social Fund for Development 5.8 5.5 Number of observations 259 272



Local charitable or cooperative societies are mentioned most often (by 56 and 38% of the respondents respectively), followed by public services (communications, water and electricity), local councils and health facilities. The Social Fund for Development was only mentioned by six percent of the respondents in each group, a potential source of worry in terms of communications strategies for the Fund. In general, local charitable or cooperative societies seem to be the prevalent form of structural social capital present in the surveyed communities.

In this listing, SFD ranks second behind local societies, but with a much lower score. Yet the qualitative survey showed a much better appreciation of the Fund, even though the opinions gathered through interviews could be tainted by an apprehension bias (“One should not bite the hand that feeds him.”)

“The SFD was the only authority that was honest with us and did something for us.” (Al Zahra, Saadah)

“It is considered as the greatest gift provided from the SFD.” (Warzan – Al Raheda, Taiz)

“(SFD had played a) very positive and effective role that solves many problems for the communities.” (Beir Al Aros, Lahj)

An important insight provided by the qualitative survey is that related to the capacity of people to undertake and follow-up projects. The image given is mainly that of poor households so immersed in their daily survival and the repetitive chores linked to getting enough food and water that they lack the initiative and mostly rely on selected individuals to take care of innovations and project follow-up:

“We can’t do anything, and we can’t follow up anything. We are poor.” (Jabal Henwab)

“There is nobody from our area in the higher authorities.” (Mojib, Shabwah)

“The quest for resources in the area depends on the prominent figures – personal social position in the community, as people are hopeless.” (Warazan – Al Raheda, Taiz)

Given this cultural setting, it would be utopian to expect the SFD’s projects to transform community dynamics. Leadership figures such as the Shaikh or the Parliament Member ensure the link between the community, the SFD and other authorities, and often make personal financial contributions during project implementation. Nevertheless, in several cases, it is possible to observe the beginning of a change in some of the affected communities:

Table 5.l - Ranking of local organizations by their perceived importance for community development (multiple answers) Ex-post Baseline % Rank % Rank Local societies 79.4 1 52.2 1 SFD 14.7 2 9.0 6 Local Councils 13.2 3 9.0 6 Education (schools) 7.4 4 29.9 2 Health facilities 7.4 4 25.4 4 Water/ electricity corporations

4.4 6 26.9 3

International organizations

2.9 7 20.9 5

No. of observations 68 67



“[Participation] creates trust and cooperation among the community.” (Al Hegrh, Amran)

“The people of this committee are really good: they are better than the rest. We will support the Hope committee, so that they can request more projects.” (Jabal Henwab, Taiz)

“People started to care about the interest of the community as a whole.” (Al Shamaayateen, Taiz)

“But the sense of contribution is there: people have contributed one million YR for the school. Also the community has created a fund to gather contributions for emergencies.” (Sayhoot, Al Mahra)



6 Service production and sustainability of SFD Projects. This section presents findings on the production of services and sustainability indicators taken from the 2003 IES project survey component. Data are presented for the ex-post group and for the new baseline sample.

The same caveats already expressed should be borne in mind regarding the comparability of these data. The new baseline data set from the 2003 IES was collected in order to provide a comparator for ex-post data to be collected in 2005, rather than as a comparator for the ex-post data collected in 2003. It is possible that there are systematic differences between present service production and sustainability conditions in the new baseline group and the pre-intervention status of the projects that SFD has already completed.

Therefore, the data for the ex-post set should be interpreted independently, as indicating the sustainability level of projects where SFD has already finished its work, but not normally allowing us to reach inferences about whether SFD’s intervention has been associated with an improvement in that sustainability. However, where possible, administrative registers were reviewed to establish pre-intervention data for service coverage and recall data were collected from survey respondents. These comparators allow us to reach conclusions on this point.

6.1 Education Projects

(32 schools in ex-post group, 31 in baseline group)

Table 6.a shows for the number of schools, number of classrooms and number of students by type of classes (boys only, girls only or mixed classes) in the ex-post survey sample for 2002/3 and for 1997/8, taken from the written records in the school archive. These observations allow us to see changes in these indicators over the period covering the SFD intervention. The number of students increased by 29% in the ex-post group; the increase was highest for girl-only classes (38%). The increase in number of classrooms was 12% (29% for girl-only classrooms). The average class-size rose by 38% in (but only 8% in girl-only classes). Overall, the proportion of girls enrolled rose from 48% to 50%. We can conclude that the SFD investments in these schools were associated with an increase in enrollment, which is particularly strong for girl students, whose teaching conditions were favored by the building of new classrooms, so class sizes for girls remained stable. Figure 6-a – Schools opening in 6 days before survey

Figure 6.a, shows that schools in the ex-post group tended to be more frequently opened over the week before the survey than those from the baseline group,

0%

20%

40%

60%

80%

100%

1 2 3 4 5 6 1 2 3 4 5 6

All open Some closed All closed

Ex-Post Baseline



although the main reason invoked was similar in both cases, that is the middle-of-the-year vacations.

The survey also looked at the status of the school infrastructure as an element of sustainability, in terms of status of buildings and furniture, decoration and overall cleanliness of the school.

Figure 6.b shows these results in a graphical way, classifying status as good, moderate or poor for each of the four areas of assessment in three categories of classrooms in the ex-post group: built by the SFD (New), completed or refurbished by the SFD (C/R), or untouched by the program (Old). SFD intervention, as would be expected, resulted in improved building status (one quarter of the new classrooms were already deemed not in good shape after a maximum of five years of existence). Cleanliness and decoration status were also slightly improved by the SFD intervention, whereas its impact on the status of furniture was probably diluted by the time gone since its provision, or by the redistribution of existing furniture to new classes.

Fig. 6.b: Maintenance of SFD supported schools

Staffing patterns also influence the availability and quality of services: the following table shows the data for the two surveyed groups in this respect (see table 6.b). In each case, there is a relatively high proportion of qualified and permanent teachers, suggesting that the availability of staff (and funding for their employment) is not a serious limiting constraint to the

Table 6.a - Enrolment ratios (project survey ex post sample)

Boys classes

Girls classes

Mixed classes

Total

1997/8 Number of schools 6 7 15 28 Number of classes 50 84 126 260 Number of students Male 1,596 2,254 3,850 Female 2,849 723 3,572 Both 1,596 2,849 2,977 7,422 # students/class 32 34 24 29 # classes/school 8 12 8 9 # students/school 266 407 198 265 2001/2 Number of schools 6 7 18 31 Number of classes 52 108 163 323 Number of students Male 1,887 3,404 5,291 Female 3,946 1,341 5,287 Both 1,887 3,946 4,745 10,578 # students/class 36 37 29 33 # classes/school 9 15 9 10 # students/school 315 564 264 341 % change # students 18.0 38.5 59.4 42.5 # students/class 13.7 7.7 23.2 14.7 # classes/school 4.0 28.6 7.8 12.2 # students/school 18.2 38.5 32.8 28.7

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0%10%20%30%40%50%60%70%80%90%

100%

Good 74.1 63.4 18.2 58.1 9.1 61.9 38.7 37.2 9.1 77.4 44.4 64.1

Moderate 22.6 22.0 45.5 19.4 18.2 19.0 25.8 23.3 36.4 22.6 55.6 25.6

Poor 3.6 2.4 18.2 3.2 27.3 0.0 19.4 4.7 27.3 0.0 0.0 11.4

N/A 0.0 12.2 18.1 19.3 45.4 19.1 16.1 34.8 27.2 0.0 0.0 0.0

New C/R Old New C/R Old New C/R Old New C/R Old

Building Furniture Decoration Cleanliness



effectiveness of investments in the expansion of education coverage in the communities where SFD has invested and plans to invest in the future. However, the gender composition of the teaching staff may still be a problem in rural areas. Absenteeism of staff is very low, with attendance rates of 94-96% in the ex-post schools and 96-97% in the baseline schools for which records were available for the day of the survey and the previous five days.

Nor does textbook supply appear to be a problem. The availability of textbooks was assessed by grade for 5 subjects: Arabic, Mathematics, Sciences, Arts, and Islamic Studies (tables not shown). Ex-post schools had an average of 1.0 book per student per subject (except 0.7 for Arts) while baseline schools had an average of 1.3-1.4 book per student per subject (except 1.1 for Arts). The ex-post schools have 0.87 seats per student (the figure is1.12 in baseline schools). But this appears to be due to multiple shift use of the facilities, rather than indicating a need for more investment in this area10.

There is also evidence of a reasonably high level of parental involvement in the schools SFD is supporting. A parents’ maintenance committee exists in 63% of the ex-post schools and 60% of the baseline schools. In the last twelve months this committee has met on average three and 3.5 times respectively.

Table 6.c summarizes the issues most commonly mentioned as problematic in the schools, issues that the committees should address.

The same concern for persistent overcrowding of schools and lack of qualified – particularly female – teachers is felt by participants in focus group discussions and individual interview, demonstrating that the Fund and other similar institutions have a long way to go to correct the current problems of school conditions in Yemen.

10 Evening shifts increase the number of students by 57% in the baseline schools, but only by 23% in the ex-post schools. Thus, taking this into account, ex-post schools may now have approximately the right amount of space, provided they continue with the two shift system, while baseline schools may be able to welcome even more students.

Table 6.b - Staffing patterns for SFD schools Ex-

Post Base-line

Number of staff (average) 16.7 31.9 % qualified/all teachers 83.6% 77.6% % permanent/all teachers 95.0% 97.1% % qualified & permanent 80.0% 75.8% % teachers/ all staff 83.8% 86.8% % female teachers 17.9% 39.4% % administrative staff 13.8% 9.1%

Table 6.c - Operating problems identified in schools Problem identified (% mentioned) Ex-

post Base-line

Crowded classes 56.3 46.4 Insufficient number of teachers 40.6 25.0 No fence 31.3 Scarcity of water 21.9 No administrative building 15.6 No school/office furniture 15.6 53.6 No teacher residence 12.5 No library 12.5 14.3 No support for school activities/laboratories

12.5 17.9

No concern for maintenance 14.3



“Although there are two shifts, there is overcrowding; the students come from everywhere.” (Al Zahra, Saadah)

“They provide male teachers! How can male teachers teach females?” (Al Munirah, Hodeidah)

6.2 Health Projects

(21 in ex-post group, 24 in baseline group) Health centers in the baseline survey tend to serve a wider population (13,497 people on average) than facilities in the ex-post group (10,155 persons), and more communities (51.7 vs 18.611). This suggests that SFD is now intervening in somewhat larger facilities than it did in the early years of its operations, but these remain located in dispersed rural populations.

In the ex-post group, as for the education projects, the SFD contribution included building new rooms from scratch, and rehabilitating or amplifying existing ones, as shown in Table 6.d, below:

Table 6.d: Type of support provided by SFD to health facilities New Rehab./

Amplified Untouched Total

Clinical rooms (consultation, child care/imm., pregnancy/FP, delivery) 30 32 11 73 Rest rooms (male, female, mixed) 22 32 4 58 Other rooms (waiting, admin., pharmacy, store) 18 17 13 48

Assessing the status of the facilities covered by the SFD intervention with regards to the same four areas considered for schools yields good results in terms of the overall status of the buildings, as seen in Figure 6c, below. While better furniture and improved decoration could increase both worker’s productivity and patients’ attendance, cleanliness of health facilities is an area that needs special attention, in order to aim for an ideal 100% “good” status, especially in the clinical sections.

Fig. 6.c: Status of building, furniture, decoration and cleanliness of SFD supported health facilities

11 Four health facilities surveyed in the baseline group were reported as serving between 100 and 400 villages or sub-villages and may correspond to large urban settlements.

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20%

40%

60%

80%

100%

Good 86.2 89.7 81.8 72.4 61.5 51.8 49.2 21.1 35.7 69.6 51.3 62.5

Moderate 6.9 10.3 12.7 19.0 15.4 19.6 18.6 0.0 17.9 16.1 23.1 17.9

Poor 3.4 0.0 3.6 6.9 2.6 8.9 13.6 10.5 17.9 8.9 12.8 5.4

N/A 3.4 0.0 1.8 1.7 20.5 19.6 18.6 68.4 28.6 5.4 12.8 14.3

Clinical

Rest Other

Clinical

Rest Other

Clinical

Rest Other

Clinical

Rest Other

Building Furniture Decoration Cleanliness



Water supply remains an important problem in many health facilities, that certainly contributes to the previous situation, and it has not been resolved in all the SFD-supported facilities. Only 50% of the ex-post clinics had water supply within the building or the compound and for those without water, the next source was 2.3km away (a 47 minutes walk on average). A similar proportion of clinics had electricity from a main line, but 62% of the ex-post facilities could benefit from a generator located in the clinic (only 4% of the baseline clinics could do that), suggesting that SFD has helped in this regard.

Table 6.e shows the average staff composition of the health facilities surveyed. Once again, the pattern is similar between the two surveyed groups and generally suggests that staffing has not been an undermining constraint to the effectiveness of SFD investments in this area.

Roughly half (48%) of the facilities in the ex- post group have a doctor (57% in the baseline group) and 57% have a midwife in each group. Two-thirds of the doctors are male. Medical assistants (all male) are present in 71% of the ex-post facilities and 57% of baseline clinics. Professional and auxiliary nurses (all female) are only present in between 19% and 29% of facilities, in proportion similar in both groups. Overall, the average ex-post facility has 4.3 professional health staff while this number is 5.9 for the baseline facilities (again the difference is consistent with the projects’ location).

However, there is some evidence of a greater use of temporary and volunteer staff in the ex-post than in the new baseline sample, suggesting the need for a further effort to provision the necessary budget for the hiring of permanent staff. In the Ex-post facilities, 16% of staff is temporary and 10% are volunteers. The corresponding figures for the baseline facilities are 4% and 7%. The proportion of permanent staff is lowest for physicians and professional nurses in both groups.

As in the education sector, staff absenteeism (for the persons assigned to the facilities) does not appear to be a major problem. Over the five previous days (including the day of the survey), the proportion of staff presence by category, calculated over a maximum number of potential days of presence, in the ex-post and the baseline group respectively, was as follows:

- physicians: 98 and 77% - professional nurses: 100 and 98% - midwives: 91 and 94% - medical assistants: 100 and 97% - auxiliary nurses: 100 and 100%

The presence of selected categories of staff apparently enhances the capacity of facilities to provide a wider range of services. Table 6.f shows the proportion of each type of service being provided by all facilities, then by facilities with physicians

Table 6.e - Staffing patterns of health facilities Category of staff Ex-post Baseline Physicians 0.9 1.9 Professional nurses 0.3 0.9 Midwives 1.8 1.3 Auxiliary nurses 0.3 0.8 Medical Assistants 1.0 1.0 Others (health guides, cleaners, escorts, others)

4.6 4.5

Total 8.9 10.4 Number of facilities observed

21 14



and facilities with midwives (10 and 8 respectively). As can be seen in the table (and in Figure 6.d, for the ex-post group), the presence of physicians and/or midwives is associated with a 10-30 percentage point increase in the availability of specific services.

Figure 6.d - Variations in service mix by presence of selected staff (ex-post group)

Table 6.f: Proportion of health units providing selected services by availability of providers

Health facilities start their morning shift between 7.30 and 8.30 am (80 and 85% start at 8.00 am respectively); the evening shift is more variable, with about 50% of the facilities starting between 3.00 and 4.00 pm. In the week before the survey, where data were available, there did not seem to be a major problem related to closing of facilities: one out of 21 ex-post clinics was closed during three days for an immunization campaign, while 2 of the 14 reporting baseline facilities had a one-day closing linked to staff vacations.

However not all services are provided every day. In the 35 clinics where data were available (105 days for 21 ex-post and 70 days for 14 baseline facilities), the

0.0%

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100.0%

Morbidit

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Prenata

l care

Delivery

(at f

acility

)

Delivery

at home

Family

planning

Growth Monito

ring

MCH

TT Immun

izatio

n

Child Vacc

inations

Hepati

t is Vacc

ination

Lab ser

vice

X ray se

rvice

other ser

vice

All

With Physician

With Midwife

Ex-post BaselineType of Service All With Physician With Midwife All With Physician With MidwifeMorbidity 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%Prenatal care 57.1% 80.0% 80.0% 64.3% 87.5% 87.5%Delivery (at facility) 61.9% 100.0% 70.0% 50.0% 62.5% 75.0%Delivery at home 66.7% 80.0% 70.0% 64.3% 75.0% 75.0%Family planning 57.1% 70.0% 80.0% 50.0% 75.0% 62.5%Growth Monitoring 47.6% 60.0% 60.0% 35.7% 62.5% 50.0%MCH 47.6% 70.0% 70.0% 50.0% 87.5% 75.0%TT Immunization 76.2% 80.0% 90.0% 100.0% 100.0% 100.0%Child Vaccinations 76.2% 80.0% 90.0% 92.9% 87.5% 87.5%Hepatitis Vaccination 61.9% 80.0% 80.0% 78.6% 87.5% 87.5%Lab service 57.1% 80.0% 70.0% 42.9% 62.5% 75.0%X ray service 14.3% 30.0% 30.0% 14.3% 25.0% 25.0%other service 38.1% 40.0% 30.0% 35.7% 50.0% 62.5%



following are the proportions of days when the services were offered during the day of the survey and the four previous working days:

As can be seen from the table above, the daily, integrated, delivery of services, especially of preventative services, is far from being ensured, implying that people/families with the need for those services may have to come on several occasions to the facility in order to satisfy those needs. The production figures, partially as a consequence of this lack of availability of integrated services, is still low, especially in the ex-post clinics (again, the difference may be linked to the preferentially rural location of SFD projects): assuming that the surveyed facility is the only source for the provision of health services, that the flux of patients observed at the time of survey is representative of the overall utilization, that services are delivered 260 days per year, and using the average number of population served, the resulting utilization rate is 0.28 consultations per year per person for the ex-post facilities and 0.55 for the baseline facilities, a very low rate by all standards.

Information related to equipment and drug supplies in the health centers was also available for 21 ex-post facilities and 13 baseline facilities. From a list of 18 basic pieces of equipment, an average of 15.6 (86.5%) was found in the ex-post facilities and 11.3 (that is 62.8%) in the baseline facilities. Table 6.h below shows the pieces of equipment most frequently missing in both groups:

Table 6.h - Stock outs of essential equipment in health facilities % facilities without item Type of equipment

Ex-post Baseline Bassinet (baby cots) 38.1 84.6 Adult scales 23.8 75.0 Catheters 23.8 61.5 Fetal stethoscopes 9.5 53.8 Infant scales 14.3 46.2 Boiling set for instruments 0.0 46.2 Bed screens (for privacy) 33.3 46.2 Kelly Haemostatic Forceps 42.9 46.2 Forceps jar 23.8 38.5 Folding examination tables 0.0 30.8 Number of facilities observed 21 13

Of the equipment available in the facilities, 83% was deemed in good condition, 15.2% in medium condition and 1.9% in poor condition for the ex-post group. Corresponding figures for the baseline group were 61.5, 32.4 and 6.1% respectively. Items most often in a state of disrepair included infant scales, sphyngmomanometers and stethoscopes in the ex-post group and refrigerators, thermometers and scissors in the baseline group.

Table 6.g - Frequency of health services provided Ex-post Baseline

Service provided % of days when service is offered

Morbidity consultation (OPD) 97 91 Prenatal care 28 31 Child Development Clinic 18 16 Family Planning 37 19 Vaccinations 48 31 Deliveries 35 26 Average number of patients/day

10.9 28.3



As the main project respondents had observed that they knew the project had supplied medical equipment in 20 out of 21 ex-post facilities, it seems that this provision has been effective in improving the situation of beneficiary facilities to this respect.

Availability of drug supplies constitutes an essential element of the perceived quality of health services and a powerful motivator for increased use of services. The evaluation process surveyed the availability of a sample of 42 essential drugs, vaccines and medical supplies. Ex-post facilities had on average 55% of the products available, while baseline facilities had 51.8%. Most often stocked-out drugs and supplies included dermatological products (calamine lotion, benzoic salicylate), contraceptives (combined pills and condoms), folic acid, oral penicillin tablets. Items such as aspirin and paracetamol tablets, cotrimoxazol, chloroquine, ferrous sulphate, metronidazole, ORS and tetracycline ointment were found more consistently. However, none of the facilities had a perfect score (zero stock out) nor was any specific drug available in all visited facilities. Each type of vaccine was out of stock in one quarter to one third of the sampled facilities. Curiously, the lack of medicines does not appear as one of the main concerns of the respondents, as manifested below in Table 5.h.

There are health committees in 67% of the ex-post clinics and 46% of the baseline clinics. Those committees had met on average 4.9 and 5.4 times over the previous twelve months. The problem issues mentioned by the informants are tabulated in Table 6.i.

Table 6.i - Operating problems identified in health facilities project survey (% that mentioned each problem)

Problem Ex-post Baseline Non availability/shortage of staff 66.7 47.6 No water/water far from facility 28.6 9.5 Low level of health awareness 9.5 28.6 Non availability/shortage of medical equipment 23.8 14.3 No laboratory/operations theater 23.8 9.5 Financial problems (no incentives, no budget, etc) 23.8 19.0 Non availability/shortage of furniture/equipment 4.8 19.0 Delay in completing project 4.8 19.0 Non availability/shortage of medicines 14.3 0.0 No guard 14.3 0.0 Building not completed 4.8 14.3

Clearly, shortage of staff is the main concern. Water supply is the second-ranked problem in the ex-post group, while baseline facilities are worried about the lack of awareness with regards to health matters, which probably accounts for not having yet an ongoing health project, and several complained about delays in the start of the project. Ex-post facilities are more concerned about operational issues for their new/renovated buildings. Lack of drugs is not perceived as a major problem in either group. It is, however, raised as a frequent concern in the qualitative survey:

”Drugs that come from the Health Office finish rapidly and are only sufficient for 3-4 days… When there is some money, the medical assistant goes to the



city and buys some drugs. If there is no money those who are going to die will die and those who are going to be cured will be cured.” (Adoob, Taiz)

“These drugs (from Health Office) and should be sold to the attendees, and they are insufficient.” (Al Hegrh, Amran)

“At the hospital they just give us a paper (prescription) for the external pharmacy.” (Al Habilane, Lahj)

One of the major concerns expressed with regards to health sub-projects is the perceived lack of cooperation with the governorate or district health office. The usual HO contribution is to dispatch a medical assistant (who may have to wait some months before actually being on the payroll) and send (limited amounts of) essential drugs. Usually no maintenance budget is provided:

“The refrigerator has broken down and the doctor, director and staff donated 18,000 YR and repaired it.” (Adood, Taiz)

However, of more relevance for the mid-term perspective and the sustainability of SFD actions, is the institutional estrangement between the Health Office and the SFD:

“In immunization, we get the second position in the whole district… HO staff deals with us differently and always says to us: You are belonging to SFD, and they do not provide us with drugs or running budget, in spite of following up with them monthly.”

6.3 Water projects

(19 projects in ex-post group and 27 projects in baseline group)

Water projects in the ex-post group are of two types: piped water systems (42%) and water harvesting systems (58%). However, projects in the pipeline, that is, in the baseline group are almost exclusively water harvesting projects (92%), which correspond more to the emphasis on the needs of the poorest communities. Most of the projects do not treat water (only 3 out of 19 in the ex-post group do so, using either sand filter, chlorine).

Electromechanical equipment is used in 9 (47%) of the ex-post sites, with 72% of the pumps reported in good shape. Only four baseline sites currently use pumps, which are in good conditions.

For piped water projects, pumps, pipes and other supplies are provided by the SFD; beneficiary households are asked to pay for the meter (between 1,000 and 1,500 YR), which may constitute an obstacle to access, sometimes solved through community support:

“We help our neighbors, and the Sheikh paid for the poor households.” (Al Shammayateen, Taiz)

Payment for water is a feature of the newly completed projects, with 8 projects charging for water (42%): payments were found to be timely in 61% of the cases or with a 2-4 month delay in 29% of the cases. Payment is sometimes made at the harvest season, when households have cash on hand. Only one project in the baseline group is currently charging for water.



Water systems, after intervention, have a staff of 6.4 persons on average, of which 2.4 are professionally qualified, as seen in Table 6.j.

Table 6.j - Staffing patterns for water sub-projects Ex-post (situation observed

directly in 2003 project survey)

Baseline (Recall data for pre-intervention situation)

Average # of staff Average # of staff Category of staff

Total Qualified % days of presence* Total Qualified

% days of presence*

Manager 0.9 0.5 74 1.0 0.5 30 Engineer 0.1 0.1 100 Plumber/technician 0.6 0.3 86 Accountant 0.7 0.4 93 Bill distributors/ collectors

1.0 0.2 91

Operations and maintenance technician

1.7 0.6 67 1.0 0.5 40

Other admin. Staff 1.2 0.3 157 Other 0.2 100 1.0 1.0 0 Total 6.4 2.4 79 3.0 2.0 23

The SFD projects have had a very positive impact on coverage of the water systems. The water benefits on average 9.8 communities in the ex-post group and 7.7 in the baseline group. Reports from 18 of the 19 ex-post projects showed that the number of persons covered increased on average from 1,251 to 3,251 per project (a 160% increase) while the number of covered households increased from 109 to 328 (201%). The proportion of households with tap water in their dwelling was reported (from 15 projects) to increase from 3.4 to 26.0% (drinking water) while the proportion of those with a tap available less than 100m from their dwelling increased from 7.5 to 15.8% (water for domestic use). The SFD intervention also led to a clear increase in per-capita consumption of water and frequency of supply, according to recall data for the situation prior to intervention gathered in the project survey (Table 6.k).

Table 6.k - Changes in water production and service outputs Ex-post (situation observed directly

in 2003 project survey) Baseline (Recall data)

Before After # projects Before Daily per capita consumption last year 26.6 63.1 18 36.8 Daily per capita consumption last mth 26.4 35.1 18 67.8 # operating hrs/day in rainy season 2.6 6.8 9 2.0 # operating days/mth in rainy season 8.2 21.0 9 20.0 # operating hrs/day in dry season 2.7 7.9 9 1.0 # operating days/mth in dry season 10.7 21.9 9 12.3 # operating hrs/day last month 0.9 14.8 9 1.7

The findings of the study on sustainability are also positive. As one would expect, the upgrading of the systems led to an increase in their running costs, by 200% on average, due to the use of electromechanical pumps and the need to buy spare parts for those pumps. However, average revenue generation rose by a much greater factor, of 500%. There is still a shortfall of revenue: on average, revenue is



65% of the total cost. However, before the SFD intervention, on average, revenues were only 34% of estimated costs (table 6.l). These findings suggest that the electromechanical – network systems that were supported by SFD in the early period of its work were relatively sustainable. This might justify a reconsideration of the SFD’s decision to concentrate almost exclusively on non-mechanized water harvesting schemes. However, two findings from the qualitative survey point at some of the difficulties faced by the communities in maintaining their systems:

- in Al Shammayateen, Taiz, the maintenance costs include salaries for the manager, the accountant and the technician, but the system is threatened by the imminent collapse of the 15-year old pump;

- in Warzan - Al Raheda, Taiz, where 40% of potential revenues are still not perceived, repeated breakdown of the pumps and residence expenses for the engineers and his workers have led to high costs that have been born by the project manager. “I was forced to procure a new pump… I presented this problem to the people but they did not respond, thinking that the project is profitable and can cover its expenses… At present, I am drowned in debts, above one million ryals.” (Project Manager) This also leads to the suggestion of using new materials (pumps, tanks, etc…) rather than completing what already exists.

Table 6.l – Operating costs and revenues for water systems Before After # Projects Operating & Maintenance costs Staff 33,666 40,100 6 / 10 Electricity 0 44 6 / 10 Diesel/gasoline 37,733 47,422 6 / 10 Chemicals 0 0 6 / 10 Spare parts 0 185,906 6 / 10 Other 34,667 24,940 6 / 10 Total 106,666 298,412 6 / 10 Revenues # beneficiaries 183 1,219 9 Charge per cubic meter 117.2 170.7 9 Total bill value for last month 57,902 102,841 9 Total revenues for last month 36,337 191,937 9 All figures in nominal YR.

There is also positive evidence regarding the creation of community water committees. In the ex post sample, 84% and in the new baseline sample, 74% of the projects are managed by a Community Water committee. Table 6.m summarizes the operating problems encountered with the water systems, according to the project survey informant.



Table 6.m - Operating problems identified in water sub-projects Problem identified (% mentioned) Ex-post Baseline

Project location far from beneficiaries 0.0 23.1 Water leakage 21.1 11.5 Defects in finishing of cistern walls/bottom 21.1 0.0 Cistern/well without cover 21.1 0.0 Non availability of other equipment 21.1 0.0 Delay in implementation 0.0 19.2 Low capacity due to low depth/low # of wells 15.8 11.5 Community unable to contribute/different opinion 10.5 15.4 Cistern above water level 10.5 3.8 Pipe network deteriorated 10.5 3.8 Pipe network insufficient to cover all households 10.5 3.8 Insufficient/misuse of financial resources 10.5 7.7

The qualitative survey in general confirms the findings of the project and household surveys regarding from the perspective of users and community leaders. It also underlines the problems with collecting user fees from very poor families:

“We have cut water from 350 houses (who have not paid) but nobody came as they are poor and have no money to pay for water. We used to have exemption for the very poor (around 300 households), but the Local Council has stopped this.” (Sayhoot, Al Mahra).

6.4 Sewerage projects

Three sewerage projects were visited for the qualitative survey. Those projects, located in the main towns of Sana’a, Taiz and Aden, included the installation of a main sewage network with individual household connections. Two of the projects were driven by the community needs; one had an additional motivation in its location close to a tourist area, where the cleanliness obtained by improved excreta disposal would increase – or at least not deter – tourist attraction. Work was mostly done by the Water and Sanitation Agency (WASA), which participated to the costs of the projects, but asked a community contribution (usually around YR5,000 per household) for the household connection. As for other community-related projects, the presence and role of a key leader (shaikh or MP) was essential for the initiation and follow-up of the project. The SFD involvement was often thought providential, as not many other funding agencies are interested in this type of work, less visible than the building of schools or health centers.

“Kind people (i.e. philanthropists) prefer to support mosques or schools.” (Al Memdarah, Aden)

Some consultations have occurred between the Fund, WASA and the community leaders, leading in some cases in significant changes in design (site of the pump, for instance); however, the majority of the population was not really associated in this process.

The main benefits obtained from the new system include improved landscape (both in terms of sights and odors), improved sanitation (less mosquitoes, decrease in malaria and other diseases), improved safety for children (who do not fall any more in sewage pits), decreased damage to building walls and foundations, and increase



in the prices of the houses located in the drained areas. The main problems encountered included:

- during implementation: difficulties in locating the system’s pump on a specific land, discussions between WASA and contractors, high perceived price of household connection for some families, leading to illegal – and less safe – connections.

“Some are connected illegally.” “It was like a mountain on my head.” (Wadi-al-Muassel, Taiz)

- afterwards: persistence of bad odors and spills where pits have not been dug deep enough; location of pipes above some households, leading to overflow in those households in case of blockage of the pipes; extension of the network insufficient to cover new or peripheral areas.

While this type of projects does not seem to have increased the technical or organizational capacity of the community, it is generally very well received, as it brings tangible benefits and makes people more ready to participate in other community initiatives.

“Even if an enemy like [Israeli PM] Sharon is going to support sanitation, nobody will oppose.” (Assad, Sana’a)

“[It is] completely different. Now [it is] so clean!” (Al Memdarah, Aden)

“Communities in the neigbourhood became more prepared to participate to solve their problems.” (Wadi-al-Muassel, Taiz)

6.5 Rural road projects

(14 projects in ex-post group, 19 projects in baseline).

SFD support mainly consists of building or upgrading rural access roads (13 out of the 14 ex-post projects and 13 out of the 19 intended projects in the baseline group).

Other interventions include drainage work and road widening. The average length of the roads being supported is 16.8km in the ex-post

Table 6.n - Operating problems identified in rural roads sub-projects Problem identified (% mentioned)

Ex-post sample (2003)

New baseline sample (2003)

Road exposed to rain/flood damage

61.5 84.2

Difficulty/roughness of the area 15.4 47.4 Road not maintained/paved 15.4 31.6 Road not fully completed (parts without pavement)

30.8 15.8

Lack of walls, trenches, water outlets

23.1 21.1

Narrow/not widened road 23.1 5.3 Road does not reach many places 15.4 10.5



group and 8.5km for the pipeline projects. Road projects serve on average 19.5 communities12 and 16,771 people in the ex-post groups, and 29.2 communities and 40,261 persons in the baseline group. The problems identified with the current status of the access roads in the sampled sites are summarized in Table 6.n.

Notwithstanding the persistence of problems, the survey results suggest that these projects have had a very positive impact on journey times (reducing them on average by 40%, from 201 ro 122 minutes).13 (Table 6.o). Household level data from dwellers living in sub-project confirm that travel times have been greatly reduced. According to their responses, the time needed to get to the nearest town market has decreased due to the SFD intervention from 289 to 193 minutes, a 33% reduction (based on observations from 304 households).

“We were traveling eight hours to the nearest town, now it is one and a half hour.” (Beir Al Aros, Lahj)

The key informant interviews suggest some change in the nominal cost of journeys:

“We used to pay 200YR to go down the village and another 200 to go up; now it is only 200 to go up and down.” (Jabal Henwab, Taiz)

Household level responses also suggest a significant reduction in the cost of travel, from YR488 to 290 (a 40% reduction). There is evidence of some amount of reduction in the cost of basic commodities imported to the villages (key informant interview data):

“One sack of wheat used to cost 1,650YR, now it costs us 1,600YR. A cylinder of gas used to cost us 350YR, now it costs 300YR…. In the past, we used to pay sugar 150YR per kilo, now we only pay 100YR per kilo.” (Jabal Henwab, Taiz)

Table 6.o - Outputs of rural roads sub-projects Ex-post sample 2003 New baseline

sample 2003 Before

(Recall data)

After (Observed in project survey)

Before

Cost of transport to nearest city/suq 200.00 178.32 233.20 Time spent (in minutes) 201.5 121.8 112.1 Vehicles using the road/day 15.9 45.6 30.5 Cost of one bottle of LPG gas 367.90 260.66 388.40 Cost of one sack of wheat 2,110.70 1,821.97 2,534.20

Source: Project survey. 2003 prices (After) are expressed in 1999 YR, deflated using the CPI which rose 38%.

12 Average number of communities served is given after eliminating one outlier project allegedly serving 2,000 communities in the ex-post group and two projects serving 250 communities in the baseline group. 13 These findings are based on interviewee’s recall in the completed projects, which might be thought less reliable than baseline data collected prior to the project’s implementation.



The reduction in travel time and cost has led to a sharp increase in the number of trips per day, which is up, on average, by 180%, according to the key informant interview. Household level data were collected for the weekly number of trips to the nearest market/town undertaken by each family member before and after the intervention, classifying those trips according to their motive, for better recall. These data show an increase of 120% in the number of trips (Table 6.p). It is particularly heartening that much of the increase in trips is due to visits to market local production to town, which should contribute to poverty reduction.

Table 6.p - Number of weekly trips to main town by category of trip Average # of weekly trips for: Now Before Difference Shopping 0.8 0.5 0.3 Marketing 1.9 0.2 1.8 Working 0.7 0.6 0.2 Learning 0.3 0.2 0.1

The findings on sustainability are also positive. There is an agreement with the community for road maintenance in 86% of the ex-post projects and 58% of the baseline group. A maintenance follow-up committee has been formed in 8 ex-post projects, but training has only occurred in one. Community leaders (shaikhs) and more rarely local councils or a charitable organization can also be responsible for maintenance. Three projects mention that beneficiaries contribute YR100 per month for the maintenance costs. Maintenance of the road is performed most often in a periodic fashion (75% of projects in the ex-post group).

The qualitative survey observed an interesting format in Jabal Henwab, Taiz, where the beneficiary committee has divided the new road in segments, with groups of twenty households responsible for the maintenance of this segment. But this is still a relatively isolated finding, maybe more applicable to roads projects which have a very intensive community involvement in terms of labor from the very start. Communities where school and health sub-projects were implemented rather see the government or the school/health unit itself as responsible for maintenance, often leaving the committed staff to do it on their own, and statements such as the following are not the majority:

“We are not going to neglect it. We will repair it and ask community to contribute.” (Al Hegrh, Amran)

6.6 Micro Finance Projects

(11 projects in the ex-post group).

Eight out of the 11 micro finance projects are run by an NGO and two by a cooperative. The SFD has financed grants for technical assistance and training in 4 of these projects, and has provided grants for seed capital and loans for on - lending in all 11 (Table 6.q).

Table 6.q - Type and amount of support received by SFD # of projects Average amount

received (YR) Grant for TA and training 4 160,945 Grant for seed/capital 11 3,484,725 Loans for lending 11 13,747,216



Other support 10 1,853,993 Total 11 19,246,879

The governance of the supported microfinance organizations is generally adequate, although the frequency of board meetings is rather low in some cases. Board members are normally nominated by the General Assembly of the sponsoring agency/cooperative. Information obtained from ten of the projects shows that project boards have an average of 7.4 members, with a mean age of 42 years and a majority of female members (4 versus 3.4 men). The boards meet annually in 7 projects and quarterly in 3 projects. Board members do not receive salary or attendance fees; in two cases, they receive transportation allowance or reimbursement of expenses; in one case, they get an incentive on the fund’s production.

Micro finance projects have an average staff of nine (Table 6.r). Staff salaries range from YR15,070 to 74,938 for men and form YR5,573 to 38,416 for women, with a variation factor of 1.3 to 2.4 for the same staff category.

None of the projects surveyed had an ongoing training program. Six of the projects have a saving component; saving is a prerequisite for getting a loan and savers get priority in obtaining the loan. There are on average 502 saving accounts per project for a total amount of YR 958,614, that is an average saving account of YR1,910. The interest rate of the saving accounts varies between 6 and 10%. Savings are used for financing program loans (3 projects) or deposited in a bank (5 projects).

However, the record of the MF institutions in saving mobilization is not strong: only 1.5% of the loan portfolio is funded by members’ savings. SFD loans and grants and 96% is funded by SFD loans or grants (Table 6.s).

The current value of the loan portfolio is estimated at YR 11,257,736. The average number of loans is 383 (range 120 - 1,385), and the average value of the loans is YR 29,394 (US$184). Six of the 11 projects work with the “murabaha” (profit sharing) type loan, while one is using the “musharaka” modality (provision of inputs on a credit basis); five projects use ordinary interest mechanisms. In Hodeidah, the initial opposition from religious political parties (Islah) to charging an interest on loan was overcome by “…making this interest a type of Islamic interest, which is Al Murabaha – sharing in

Table6.r – Staffing patterns of micro finance sub-projects Staff category # Male # Female Total Manager 0.6 0.5 1.1 Accountant 0.6 0.2 0.8 Credit officer 2.8 2.4 5.2 Other 0.7 0.3 1.0 Ancillary 0.5 0.7 1.2 Total 5.2 4.1 9.3

Table 6.s – Source of funds for micro finance projects #

projects Average

amount (YR) Beneficiary savings 4 294,400 Grant from sponsoring agency

2 107,265

SFD loan 11 13,646,366 SFD grant 11 4,565,759 Other 3 395,259 Total 19,005,049



the profit – and we supported that by asking some religious figures to explain that this kind of credit is permitted in Islam.”

The maximum amount of the first loan ranges from YR 20-100,000, while subsequent loans may reach YR 250,000. The minimum term for the loans is 6 months (190 days on average), while the maximum is just over a year (374 days on average), with a mean loan duration of 279 days (9 months). Loans are used for trade (11 projects), manufacturing (9), animal raising (5), agriculture (4), family and personal consumption (1) and other activities including services and maintenance.

All projects have credit regulations available and all but one also have program statutes. The six projects that have a saving component also have savings regulations. Accounting documents include cash book, loan and saving books, as well as shareholder register (in 4 projects). Four of the projects use accounting software, mostly an Excel-based package. All but one of the projects had up-to-day accounts at the time of the survey. However, the qualitative survey in the largest project in Hodeidah reveals a history of fake contracts (with ghost clients) made by credit officers for their own benefit; this experience led to a strengthening of the Fund’s administrative control over the program (improved information system, limited authority of the credit officers, procurement committee involving beneficiaries).

Sanctions are applied to loan defaulters including fines (7 projects), exclusion from future loans (all projects) and execution of the guarantee (8 projects; all projects require a guarantee before they provide a loan). Only one project allows refinancing of loans that have run in arrears and has a total of 51 such loans, for a total amount of YR364,018. Seventy five percent of loans made by these projects have been fully repaid; of those that are still outstanding, half are being repaid on time and half are in arrears (Table 6.t).

Table 6.t - Status of project loans Status of loans Number of loans % Total amount % Fully repaid 708 67 29,279,619 75 Being paid on time 172 16 4,854,759 12.5 In arrears 172 16 4,869,455 12.5 Total 1,052 100 39,003,833 100

The following section summarized the financial and administrative records of the micro finance projects obtained during the project survey. The structure of the balance sheet and profit and loss statement for 2002 is drawn from information on 11 projects reporting for this year; the percentage of change from 2001 to 2002 is calculated from only five projects that reported for both years. We report separately for the large micro credit program in Hodeidah (#98-003-0006) and for the other ten projects, which are much smaller and would have their average figures distorted by the inclusion of the Hodeidah project. 2002 YR have been converted to their 2001 value, using the CPI provided by the Central Statistics Office. The individual figures for the eleven projects are attached in Annex E.



Table 6.u shows the number of scheme members in 2002 for the Hodeidah project and for the other 10 projects, as well as the percentage of change from 2001 to 2002 (the later figure on the basis of 4 projects only in the last column). While the Hodeidah project is going through a moderate decrease in its number of borrowers, especially female ones, the other projects are seeing an increase of both borrowers and savers (Hodeidah does not have a saving scheme), mostly benefitting women.

Table 6.v shows the consolidated accounts, again for the Hodeidah project on the left hand side and for the other projects on the right hand side.

The profit and loss statements show an operating loss of YR4.5 million in 2002 for Hodeidah and YR0.5 million for the other projects, figures slightly better than those observed in 2001. The balance sheet shows a slight decrease in assets for the Hodeidah project (-19%), but a significant rise for the other projects (60%); however, in both cases, the loan portfolio has decreased significantly from 2001 to 2002 (52 and 36% respectively), thus showing a contraction in operations. However, the balance sheet totals for the “other projects” group do not sum properly (the total of assets is not equal to the sum of liabilities and capital) and –for the four cases where data are available for two years - the movement in total assets between 2001 and 2002 is not consistent with the profit and loss results of 2001. In addition, the increase in number of borrowers and savers observed for the four smaller projects (excluding Hodeidah) does not seem consistent with the decrease in the loan portfolio observed here.

These incongruencies lead us to suppose that there are still weaknesses in the accounting procedures (above all for capital accounts) being used by the MF institutions, but that their profit and loss performance has somewhat been improved by cost reductions in 2002. However, it is also clear that the capacity of the MF institutions to mobilize savings is modest; they are really operating essentially as intermediaries to on-lend the capital received from the SFD (registered mainly under “other capital contributions”) to final users. They still lose money in this operation, and are not therefore financially sustainable.

Table 7.u: Distribution of borrowers and savers by project

Year 2002Hodeidah

% change 2001-2002

Other projects (average)

% change 2001-2002

Borrowers - male 1,519 -12.6% 88 15.4%Borrowers - female 204 -31.5% 119 206.5%Borrowers - total 1,723 -15.4% 207 52.0%Savers - male 12 70.5%Savers - female 199 215.8%Savers - total 211 183.2%



Note: amount and structure % for Other Projects based on 10 projects; % change 2000-1 based on 4 projects only

The findings reported above suggest the need for continued careful study of options to improve the business performance of the MF institutions supported by SFD before this area of activity is significantly expanded.

The household survey asked loan beneficiaries to assess whether their standards of living had changed as a result of receiving the loan and the results, shown in Table 6.w, are generally positive, as 62% of the responding borrowers said their

Table 7.v: Financial statements from micro finance projectsBalance sheet

Hodeidah Other projects (average)

Amount% by

category% change

2001-2002 Amount% by

category

% change 2001-2002

AssetsCash and bank 35,572,075 30.0% 215.5% 3,129,843 19.3% 28.9%InvestmentsLoan portfolio 45,421,771 38.3% -52.4% 5,172,220 31.9% -35.5%Reserves for bad loansFixed assets 10,912,931 9.2% -8.0% 1,056,459 6.5% -6.4%Other assets 26,676,842 22.5% -1.4% 6,871,085 42.3% 655.7%Total Assets 118,583,619 -18.6% 16,229,607 59.8%LiabilitiesMembers savings 563,490 18.8% 99.0%Other savingsLoan from financial institutions 707,090 23.6%Other liabilities 25,833,829 100.0% -29.3% 1,721,855 57.5% 21.4%Total Liabilities 25,833,829 -29.3% 2,992,435 25.1%CapitalStart up capital 10,512,931 11.4% -24.2% 2,643,998 23.7% -4.7%Other capital contributions 70,000,000 75.8% -15.2% 7,061,080 63.3% 6.1%Accumulated profitsDonations and grants 11,836,860 12.8% -7.2% 1,446,384 13.0% -5.6%Capital reservesTotal Capital 92,349,791 -15.4% 11,151,462 1.6%

Profit and loss statementHodeidah Other projects (average)

Amount% by

category% change

2001-2002 Amount% by

category

% change 2001-2002

Operating IncomeIncome from interest on loan 9,591,294 77.3% -28.1% 974,775 85.6% 37.2%Income from other charges to clients 20,500 0.2% -84.5% 71,010 6.2% 13.0%Income from investment outside loan 2,798,338 22.5% 298.5% 92,872 8.2% 83.5%Total operating income 12,410,132 -12.4% 1,138,657 38.5%Operating Expenses - Interest paid to saversProvision for bad debts 0.0% 3,746 0.2%Administrative costs - staff 11,295,369 67.0% -13.7% 1,052,790 62.8% 1.8%Other operating expenses 5,571,253 33.0% -14.5% 619,915 37.0% -13.2%Total operating expenses 16,866,622 -13.9% 1,676,450 -4.1%Net result of operations -4,456,490 -537,793

Non operational income/expensesDonations and Grants 0 0Other non operational income 612,275 -47.8% 3,456Non operational expenses 771,151 121.8% 43,225 -100.0%

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standards of living were now better than before, this proportion being higher for women (70%) than for men (53%). Interestingly, only very few women (5%) experienced a decrease in their standards of living after receiving the loan14.

The effect of the SFD loan on the perception of changes in the standards of living does not seem to be affected by the level of income of the person who received the loan, as shown in Figure 6.e.

Figure 6.e: Changes in perceived standards of living after SFD loan by level of annual income

The qualitative survey confirms the initial easiness of working with the SFD and the positive impact of the loan program on beneficiaries:

“In a bank, a person needs a recommendation or a bribe. Here, the first loan is given in a week, the third one in a day.” (Hais, Hodeidah)

“It’s released us from the poverty’s sink; it’s rescued us from doing bad things such as robbery.” (Dar Saad, Aden)

“Women without supporters (those whose husband has died or gone mad), they took loans and created a living for themselves.” (Hais, Hodeidah)

“The one who had a motorcycle now has a car; those who had a shop now have two.” “One [woman] used to sell incense; now she makes it herself and has four employees.” (Al Hodeidah, Hodeidah)

“All poor [people] moved towards it. It saved us.” (Al Maraweah, Hodeidah)

However, people do recognize that very poor people, unable to repay the loans in time or to buy fodder for the animals they would raise with the credit program, or

14 It should be remembered, however, that a perceived decrease in the standards of living may not be due to the impact of the loan only, but may represent an overall change in the socio-economic situation of the population occurring during the same period.

Table 6.w: Changes in standards of living (before and after SFD loan) Standards of living Male Female Total Now better 52.7 69.8 61.9 Same as before 25.5 24.0 24.7 Now worse 21.8 5.4 13.0 N 110 129 239

0%

20%

40%

60%

80%

100%

Annal income (YR)

Worse

Same

Better



people without previous skills or job, are usually unable to benefit from the program. This feeling is increased by the perception of tightening of the rules from the SFD:

“In the beginning, they used to help people, but now they are very picky about the repayments.” “The sponsoring agency is doing its job, but now they need a guarantee, and if you don’t repay, they take you to the police with the guarantor.” (Al Hodeidah, Hodeidah)

“Loans were supposed to be offered to poor people to develop their means of income and alleviate poverty. But what can people do? We are not pleased with the many fees and the short period.” “SFD is exerting pressure on them [program officers]; they have a program and they fear senior officals.” “SFD’s required guarantees are overestimated, along with complicated bureaucratic procedures. If a participant encounters difficult circumstances, they will not tolerate.” “It becomes a commercial, not a service.” (Hais, Hodeidah)

Common problems perceived and mentioned by the borrowers include:

- the small amount of the loans which has them need to obtain additional money from alternative sources,

- the short repayment terms

- the dependency on the compliance of all members of a borrowers’ group in order to get subsequent loans

- the autocratic stance of the Fund when dealing with the managing NGO and its board

- and, as mentioned above, the increasingly commercial and bureaucratic attitude of the program’s officers.

Yet, beneficiaries also recognize that, while the micro credit program does not formally develop the community’s organization capacity, it does contribute to developing team spirit and group work and getting people to learn how to use resources.

“The program gave us a value and a personality.” (Dar Saad, Aden)

6.7 Projects for Special Needs Groups

Three special needs groups projects were covered by the qualitative survey:

- one supported the rehabilitation of premises, the provision of computers and the relevant training for a Handicapped Association near Aden



- the second supported the integration of deaf and mute children in a regular government school in Dhamar by building two special classes, a kindergarden, providing furniture and facilitating special teacher training and technical assistance

- the third provided accounting training and training to the Administrative Board of a charitable association serving marginalized groups of migrants peasants from Hodeidah governorate to Sana’a.

While those projects have limited scope – only 60 out of 379 known deaf or mute children could be integrated within the regular classes – they have contributed to breaking the isolation of the beneficiary groups and helping them to contribute more meaningfully to the society’s life and to their own well being. Integrating deaf children into regular schools relieved their sense of isolation, contributed to eliminate social shame, reduced their hostility and enhanced their capacity for studying. Handicapped persons trained in computer skills were able to find job opportunities. The Board of the charitable association was able to prepare better proposals and to obtain funds from local councils, German and Dutch cooperation.

“We are now able to prepare contracts and proposals.” “In the past, there was a confusion [in accounting], now everything is clear.” (Al Amanah, Sana’a)

The projects also contributed to the organizational development and growth of the managing NGOs. The Association for the Deaf and Mute in Dhamar has become a consultant in integration. The Handicapped Association also uses its computers to provide training for non-handicapped (for a fee) and has opened an Internet Café.

“Before the training, when we attend workshops, we stay silent; but now we discuss, comment and reply. Many NGOs come to learn from our experience.” (Al Amanah, Sana’a)

Problems encountered include the insufficient scope of the support – no transport provided for handicapped, only two special classes built, etc. (from the recipients’ perspective, this will always be an issue), the lack of supplies to put in application the skills learned (registers for accounting), the difficulties in finding jobs after training.

“I can learn computers, but it is not easy to find a job. But if I learn sewing, I can work at home.” (Al Mansourah, Aden)

Also present were problems with the contractors, but with communities learning from the experience:

“We have benefited a lot, but the believer should not be stung in the same place twice.” (Al Mansourah, Aden)



6.8 Organizational support

The qualitative survey reviewed three women charitable organizations or cooperatives in Sana’a Governorate. In all cases, the project included support for rehabilitation of the association’s offices, provision of furniture and equipment (sewing machines, food processing equipment), training of members. All members have to pay a fee for training sessions (usually YR 200-1,000 per course), which, although low, is still a deterrent for a number of interested persons. Another obstacle is the reluctance of fathers to let their daughter go out and learn:

“Some fathers did not allow their daughters (to attend).” (Sanhan, Sana’a)

“There are girls who are not allowed to leave the house.” (Al Amanah, Sana’a)

The projects usually face a number of operational and financial difficulties in terms of being able to bring teachers from the town and pay them, which does not leave many resources for buying materials and being able to apply the skills learned during training. Many trainees do not have the equipment needed at their home and have to come to the association to practice. The lack of materials and the fees decrease the number of potential trainees and thus the resources available for the associations to bring teachers and buy supplies, etc. Marketing of products is also an issue. This may bring the question of following-up this kind of training with some kind of micro-credit project (or facilitating trained members of the association to join an existing micro-credit scheme).

Additional income generated by the project is not yet generalized. Yet again, benefits are felt by a number of trainees:

“The training did not benefit the trainees themself only, but also their families.” (Sanhan, Sana’a)

“Women sew and feed their children; they do not have anyother source [of income].” (Bani Al Arith, Sana’a)

“Thanks God, we can now help our children in studying their lessons.” (Bani Al Arith, Sana’a, after literacy classes)

Finally, a number of voices are heard, this time in favor of computer training, at the expense of craft training:

“Today training on computers and in English is more important.” (Sanhan, Sana’a)

“The computer is the first thing; it is the language of the era.” (Al Amanah, Sana’a)



6.9 Training

By July 2003, the SFD had completed a total of 167 training projects: those represented a total of 680 organizations involved with an overall number of trainees of 31,250, including 50.9% of women (see tables in Annexes F-1 and F-2). Training topics included specific technical skills (Agriculture, Health Administration, TBA & PHCW training), training for community development, organizational support for women associations and life skills (Community Participation, Home economics, Marketing/Product design, Skills and vocational training), project support training (PTC training, Means & methods in Illiteracy Eradication, Operations & Maintenance for water projects, SFD mechanisms). 59% of the trainees received training in health and environment, mostly through Integrated Interventions. The next most common topics were health administration with community participation, and agriculture, the latter being a mostly men-oriented training.

During the qualitative study, three training projects were observed:

- training of contractors and consultants for the Fund’s projects, including topics such contracting and tender rules, relationships between contractor and engineer, engineering drawing, standards (3 days, 40 people, out of 300 potential attendants)

- marketing training for members of the Agricultural Cooperative Union from Hodeidah, Hadramawt, San’a governorates), on packaging and marketing agricultural products (2 weeks)

- marketing training for members of nine NGOs producing crafts, clothes, etc., in Sana’a

Training was overwhelmingly well received, with good appreciation of the trainers’ technical capacity; in two instances, those trainers were brought from Egypt.

“The father and the mother of the NGOs is the SFD.” “Even if we knock at other doors, nobody will give us like the SFD gives.” (Marketing training, Sana’a)

Knowledge and skills were developed, although a number of participants requested more time, a more even level of trainees, and more practical training. Technical hints about making better steps for building and on cement proper mixing were examples of the very specific contents of the consultant/contractor course.

“We know how to avoid mistakes before it happens.” (Consultant/contractor course, Taiz)

“We knew the types of packing, sorting, marketing and the offer and need rule.” (Marketing training, Taiz)

However, it seems that there is not much follow-up and evaluation of the training, thus not allowing for modifying content or format according to actual results.



Those results are still mixed in the mid-term. SFD program officers have seen actual improvement in the relationships with sub-project contractors:

“The relationship between contractors and engineers has improved and became integrative, instead of the previous enemy relationship.” (Consultant/contractor training, Taiz)

Yet the long term impact from the trainees’ perspective may not be so rosy. Quality improvement comes at a later cost:

“We became more confident in applying for tenders, but there are new contractors who do not care and win the tenders as they put less estimates.” (Consultant/contractor training, Taiz)

”In spite of the fact that we improved our products after the training, we did not find a market. There is no tourism and the locals do not accept our products.” (Marketing training, Sana’a)

This latter group went out of its way to find new outlets for its products, looking – without success - for a selling space in the traditional Al Samsarah market and discussing with the local council. As for training and support provided by the Fund to special needs groups or women organizations (see sub-sections above), beneficiaries point out to the need for follow-up actions, such as support to a marketing foundation, micro credit, etc…



7 SFD Contribution to National Stock of Infrastructure After assessing elements of effectiveness and sustainability at individual project level, it is now important to take a bird’s eye view towards the overall impact of the program in relation to each sector’s dynamics at national level. In other terms, does the Social Fund for Development reach a critical mass of effects where we can say that it is really changing something in Yemen, or does it stay at the stage of experience or pilot project, even with the most desirable qualities at local level? This section of the evaluation relies on information from the program’s MIS, as well as secondary data mostly obtained from the Central Statistical Office (CSO) through SFD management.

7.1 Education Projects

From its starting date to July 2003, the Social Fund for Development, through its 886 education projects, has built a total of 3,869 new classes, has completed 324 previously unfinished classes and rehabilitated 1,203 classes. In addition, it has built 244 fences and 2,129 toilets. Table 7.a shows information on the number of classrooms in Yemen as a whole for the year 2,000 (from the Ministry of Education), and the number of classrooms built by the SFD, as well as the proportion this input represents in terms of national infrastructure stock:

Table 7.a: SFD contribution to national stock of school classes Yemen stock

(2001-2) SFD inputs

(1997-2003) %

Classes – new 3,869 5.0 Classes – finished/rehabilitated 1,527 2.0 Classes – all 77,165 5,396 7.0

Thus it can be seen that the SFD, in the last five years, has made functional 7% of the national stock of classrooms. Since the national stock of classrooms in the Basic cycle had increased 13.8% from the number of 67,808 registered for the school year 1998/9, a more significant figure to point out is that SFD contributed to 41.3% of all new classroom construction occurred in the country since 199815.

7.2 Health Projects

By July 2003, the SFD had built 71 new health units, that is a 3.6% contribution to the national stock of 1,955 (CSO, 2002); it had also built 12 new health centers, that is 2.2% of the national stock of 536. In the same period (1997-2002), the number of health units at national level had gone from 1,311 to 1,955 (+49.1%) and the number of health centers from 421 to 536 (+27.3%). Thus the SFD

15 It should be noted, however, that there is a time difference between the two sources of information at the beginning (1998/9 for the school census and 1997 for the SFD) and at the end of the period considered (2001/2 for the school census and 2003 for the SFD). Nevertheless, it is probably safe to place the coverage share of SFD in terms of increase in classroom construction in the range of 30-40%.



contribution in terms of new health facilities represents 11.0% and 10.4%, respectively, of the increase in the national stock during the same period.

In addition, the SFD rehabilitated/completed 23 health units (1.2% of the national stock in 2002) and 25 health centers (4.7%).

The 21 health projects covered in the Project survey (see Table 6.a) yielded a total of 30 new clinical rooms (consultation, MCH, delivery) and 30 other rooms (stores, administration, rest rooms). Based on these data, together with MIS data for the total number of health projects funded, we estimate that the SFD contributed 120 new clinical rooms and 120 other rooms to the national stock of 3,078 rooms used in health units and 3,179 rooms used in health centers16, that is, a 3.8% increase in the total.

7.3 Water and Sanitation Projects

No information was available to the study team on the national stock of water systems, water tanks or household connections, thus preventing the estimation of the SFD contribution in this respect.

7.4 Rural roads Projects

At the end of 2003, the SFD is expected to have built or rehabilitated 705.5km of roads, that is a 3.5% contribution to the national stock of 20,126.2 (CSO, 2002).17 At the data collection stage for this survey, however, the completed projects totalled only 130.9km (18.6%). Finally, works including rehabilitation only (that no new road, or completion of an ongoing work) yield a total of 448.6km of roads, that is 63.6% of the SFD contribution.

7.5 Overall financial investment

The overall contribution of SFD to investment in the social sectors at national level can also be seen from Table 7.b, showing the contribution of SFD in the health and education sectors to the corresponding national sectors for the period 1998-2002. While the Fund’s actual contribution has been lower than the committed amount, the proportion of funds disbursed by SFD in the

16 Figures from the Comprehensive Health Survey for Public facilities (1998) database. 17 According to data supplied by the Government, between 1997-2002, the national network of asphalted and paved roads grew from 8,307.4 to 20,126.2km (+142.3%). However, this growth is clearly not credible, it is likely to reflect improved inventory taking. Therefore, we cannot calculate the SFD’s contribution to the increase in road network coverage for this period.

Table 7.b: Overall financial contribution of SFD to the health and education sectors in Yemen – 1998-2002 Education Health Committed funds National Investment (US$) 321,124,233 142,310,920 SFD Investment (US$) 102,157,422 15,606,312 SFD Contribution (%) 31.8 11.0 Disbursed funds National Investment (US$) 303,404,966 145,293,782 SFD Investment (US$) 59,487,454 10,862,031 SFD Contribution (%) 19.6 7.5



education sector represents one fifth of the total investment in that sector over the period; the corresponding figure for the health sector is lower, around 7.5%.

In addition, this contribution, in terms of actually disbursed funds, has increased over the years, moving from 3.5% in 1998 to 48.3% in 2002 for the education sector, and from 1.3 to 25.1% in the health sector, as seen in Figure 7.a.

Fig. 7.a: SFD share of social sector investment 1998-2002

0

10

20

30

40

50

60

70

80

90

1998 1999 2000 2001 2002 1998 1999 2000 2001 2002

Mill

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s U

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SFD

Education Health



8 SFD Impact on Household-level Development Indicators

8.1 Methodology

This section is based on the analysis of indicators gathered through the household survey, indicators pertaining to households included in the area of influence of specific projects (the impact on school enrollment is estimated only for households living within the area of education projects, for instance).

The main comparison is made between the ex-ante (1999) and ex-post (2003) data for projects undertaken between 2000 and 2002 in communities that are covered by the 1999 NPS dataset (which is the source of the baseline data). The chapter reports the changes from 1999 to 2003 in the household-level indicators attributable to the SFD’s projects completed in this interval, for key variables such as enrollment rates and uptake of medical care in the event of illness.

It also presents multivariate analysis, to control for the possibility that there are either trend changes in other independent variables – such as income – that might explain the observed changes in status of the study variable; and also to control for possible differences in the composition of the household sample taken in 1999 and 2003. Either of these might give rise to changes in the reported value of the dependent variables that are not related to the project intervention of the SFD.

The data collection process initially covered a total of 109 “pipeline” projects from the 1999 NPS database18 and 72 completed projects for which suitable information was available in the 2003 household survey dataset. However, following the field work, a number of problems arose related to the location of the project area with regards to the corresponding enumeration area or to the distance of potential beneficiaries’ houses from the project site (see Methodology section). The information corresponding to these areas was thus taken out of the database used for the evaluation of impact and the regression analyses:

- the substitute communities that were surveyed in the right project’s place in 2003 but in an enumeration area different from that initially sampled were eliminated because we had no matching 1999 ex-ante data for those communities and cannot assume that the average ex-ante conditions of the other areas surveyed in 1999 are properly representative of the places that were not covered;

- as for the villages identified as non-beneficiaries (because sampling was done in the whole enumeration area and not only in the expected area of influence of the project – an issue specifically relevant for water projects, the area of influence of which is limited by the location of the cistern or the extension of the pipe system -, the corresponding areas were removed from both the ex-post and the baseline datasets; the rationale for that was that, in search of an impact, sampled households should have a fair chance of being impacted by the project, that is, their

18 The original database contained information from 117 project areas (education: 70, water: 24, and health: 23) but eight areas with very low number of households were eliminated.



beneficiary status should not depend on the distance and access to the project site. While it would have been possible to only remove those “non-beneficiary” households from the ex-post database, a similar process was not possible for the baseline dataset, thus leading to a decision to remove whole segments from both databases. While yielding a lower number of observations available for the analysis, it provides a stronger and more consistent dataset for the evaluation of impact.

Table 8.a shows the distribution of projects and the number of household level observations by study group and by type of project, before and after the removal of problem sites.

Table 8.a –Dataset for the SFD impact evaluation Completed projects

“Ex-post group” 2003 Pipeline projects

“Baseline group” 1999 Initial dataset Sector Projects Households Projects Households Education 32 598 66 1,207 Health 21 388 21 393 Water 19 345 22 396 Total 72 1,331 109 1,996 Dataset after removal of problem sites Sector Projects Households Projects Households Education 23 424 57 1,036 Health 18 332 18 337 Water 10 184 13 219 Total (% loss)

51 (-29.2%)

940 (-29.4%)

88 (-19.3%)

1,592 (-20.2%)

The results presented here are those from this reduced, but more consistent dataset. However, we also conducted all computations with the initial dataset (results not shown) and obtained results that were quite consistent with those shown in this document.

8.2 Education

SFD investments in building or improving primary schools should have a positive impact on the gross enrollment rate (that is, on educational coverage) and on the grade-for-age statistics, which show what proportion of children are in the grades they should have reached a their age, compared with the situation in similar places where SFD had not yet intervened. The improvement in grade-for-age is the expected product of improved enrollment rates, coupled with reduced desertion and failure rates due to the improved quality of the educational environment. In each case, the positive impacts should be most notable amongst girls, whose enrollment rates and grade-for-age attainment are both markedly inferior to those of boys in Yemen.

The specific indicators chosen for analysis are the same as those used in the Phase 2 Report analyzing 1999 NPS data and are the following:

• % of boys and girls aged 6 to 14 years enrolled in school, in the households “with” and “without” project, based on the household survey data; and



• % of boys and girls with a satisfactory grade-for-age performance, defined as follows: a child of 8 years of age should have completed at least the first grade; a child of nine, the second grade; a child of ten, the third grade, etc. Once again, the evaluation is based on a comparison of households “with” and “without” project, based on the household survey data.

8.2.1 SFD’ impact on the probability of being enrolled in a primary school

Yemen has a low gross enrollment rate for primary education, especially in rural areas and especially among girls, as shown in the following table, obtained form the Yemen Demographic and Health Survey (DHS), 1997.

Table 8.b - Yemen gross enrollment rates (%) Urban Rural Total Age Boys Girls Boys Girls Boys Girls 6-10 80.2 75.9 63.4 31.5 67.1 41.2 11-15 90.2 74.6 81.4 25.7 83.6 38.4 Total 85.1 75.3 71.5 29.0 74.8 39.9 Source: Demographic and Health Survey (DHS) 1997

In this context, the SFD’s school building investments aim to increase enrollment rates in the beneficiary communities. The study hypothesis is that the SFD intervention would result in an increase the gross enrollment rate for children between the ages of 7 to 14.

Table 8.c reports the enrollment rate for children aged 7 to 14 found in the 1999 NPS and the 2003 IES surveys in the beneficiary communities of the SFD’s education projects. The comparison between the ex-post and baseline enrollment rates in the 1999 dataset has already been reported in the previous Impact Evaluation study presented in December 2002, showed that there was a much higher female enrollment rate in beneficiary communities than in those still waiting for the SFD investment and this led to an increase of about 5% in the overall enrollment rate. Multivariate analysis suggested that this difference was attributable to the SFD intervention and not to sampling differences.

The 2003 IES allows us to compare the enrollment rate before and after the SFD intervention in the group of communities that was in the 1999 baseline sample. This comparison once again indicates a very clear and statistically significant increase in the enrollment rate for girls where the SFD investments were made, from 41.7% in 1999 to 58.3% in 2003 (95% CIDiff = 6.1, 16.3%)19. There is also a smaller increase in male enrollment (from 75.0% to 80.9% and the overall rate rises from 59.2% to 70.4%, the later figure statistically significant. This is a very

19 When reporting results comparing proportions in the ex-post and baseline datasets, we report the statistics p and Cldiff. The statistic p reports the result of a one-tailed significance test for the difference between the two proportions: if p < 0.05 the observation is reliable at the 95% level; if p < 0.1 it is reliable at the 90% level. If p > 0.1 we report that the observation is Not Significant (NS). For significant observations, we report the Confidence Interval for the Difference, CIdiff, which reports the possible range of values for the difference between the intervention and pipeline comparison groups. If the range covered by the two numbers given for Cldiff does not pass through zero, we are 95% sure that we are not wrongly rejecting hypothesis of no difference between the groups. The detailed calculations are shown in Annex D.



positive finding, reconfirming that the SFD is making an important difference to one of the most critical development indicators in Yemen. Table 8.d shows the enrollment rates by age and sex for both surveys.

Table 8.c - Comparison of enrollment statistics between 1999 and 2003

Ex-post Baseline M F T M F T

1999 NPS analysis

78.2 49.9 64.7 75.0 41.7 59.2 Ex-post Baseline M F T M F T

2003 IES

80.9 58.3 70.4 82.4 62.8 72.9

Table 8.d - SFD Impact on gross enrollment rates Ex-Post 2003 Baseline 1999

Age Boys Girls Total Boys Girls Total 7 66.7 63.5 65.4 54.5 32.9 44.0 8 78.1 58.5 68.8 59.4 43.5 51.1 9 81.6 71.1 76.6 79.0 43.4 63.3 10 92.1 73.4 83.6 82.9 45.7 65.0 11 89.4 64.9 78.6 83.5 52.9 70.1 12 81.2 47.4 65.9 82.1 42.9 64.5 13 85.1 47.3 64.7 82.7 44.4 65.2 14 76.6 40.4 58.5 78.2 30.8 54.9 Total 80.9 58.3 70.4 75.0 41.7 59.2 Observations 486 422 908

1,174 1,051 2,225

Of particular note is the increase in female enrollment rates observed between the 1999 baseline and the 2003 ex-post (heavy lines in Figure 8 a) during the first years of basic schooling, corresponding to the time frame of the project implementation. The motivation for keeping girl children in school starts with the initial years of schooling and the observed pattern will create a dynamics of its own that will contribute to better achievements up to the end of the basic schooling and beyond.

Figure 8-a - Girls school enrollment rate

0%

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80%

7 8 9 10 11 12 13 14

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% e

nrol

led 1999-EP

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Table 8.c also reports the ex-ante status for the enrollment rate in the new baseline dataset gathered for the purpose of future comparison. It should be noted that this group has a generally higher enrollment rate than obtained in the 1999 baseline dataset. There are various possible explanations for this. The SFD may have changed the balance of its interventions towards places with higher enrollment rates – that is, by placing more emphasis on helping increase the capacity of overcrowded urban schools. Other projects and programs may also have contributed to an overall improvement in enrollment rates in the country during the timeframe considered.

Multivariate analysis

Multivariate analysis was undertaken to check for the impact of changes in other independent variables that might differ systematically between the ex-post and baseline groups. To this end, a logistical regression was run including a variety of independent variables that might be expected to affect the probability that a child attends school (the dependent variable).

The variables analyzed were: SFD ex-post/baseline community school (dummy); the socio-economic level of the household20, education and sex of the household head, age and sex of the pupil, and urban or rural location.21

The results of the multivariate analysis (Table 8.e) confirm that – ceteris paribus - the SDF investment has been a significant factor in increasing school enrollment, even after taking into account the effect of the other independent variables (Exp B = 1.87).22 This impact is statistically highly significant (Sig = 0.000)23. The analysis suggests that the following factors also have a significant impact on the enrollment rate:

20 Information on per capita household income for the 1999 survey was obtained from the general NPS database; however, this database does not include the relevant data for the section of households that were over-sampled in order to satisfy the evaluation requirement of the SFD. Thus, in order to maintain the number of observations in the analysis, we used for both sets of data a proxy income variable: for the 1999 sample, we ordered the observations according to per capita household expenditures, created the corresponding deciles and gave the observation a value of 1 to 10 according to the decile they were located in (one being the poorest); for the 2003 ex-post sample, we used a similar decile format on the basis of per capita household income. 21 In general, independent variables that might be correlated with the SFD’s intervention were not included in the analysis. 22 The statistic that measures size and direction of the impact of each independent variable on the dependent variable is Exp (B), which is the “odds ratio” for the probability of a “yes” answer subject to the value

Table 8.e - Results of logistical regression of SFD impact on the gross enrollment rate for children aged 7 to 14 Independent variable Type. Value/1 Exp B Sig R SFD investment completed Cat Yes 1.867 .000 .105 Sex of child = female Cat Yes .235 .000 -.276 Household head = woman Cat Yes 2.440 .000 .093 HH reads/writes bef. Sec. Cat Yes 1.523 .000 .066 Zone = Urban Cat Yes 2.062 .000 .061 Age Cont N/a 1.057 .002 .044 Deciles of income-proxy Cont N/a 1.027 .073 .018 Notes: Cat= categorical, cont. = continuous. Sig = significance of Log LR when the term is removed from the model; bold print means significance level <0.05. Number of cases: 2,844. 1/ This is the value assumed by the categorical variable.



• In urban locations, the probability of being enrolled increases greatly (Exp B = 2.06, Sig <0.000)

• Being a girl implies an enormous reduction in the probability of enrollment, with Exp B =0.24, and Sig <0.000

• The age of the child is still associated with the probability of enrollment (Exp B=1.06 and Sig =0.002.

• Having a woman as the head of the household also increases the probability of school enrollment ( Exp B = 2.44 and Sig <.000)

• If the head of household can read and write, the probability of enrollment of his or her children is higher (Exp B = 1.52= and Sig <.000)

• Increased household income is only very slightly associated with school enrollment24 (Exp B = 1.03 and Sig = 0.073).

We may conclude that SFD investments had a positive measurable impact on the enrollment rate, helping to offset the disadvantages intrinsic in being a girl or living in a rural area – which are also clearly confirmed by the analysis.

Since the sex of the student is such an important determinant of school enrollment, a gender-specific analysis was made, better to identify the effect of the other independent variables, in particular the presence of the SFD support. The results are presented in table 8.f (girls) and 8.g (boys).

For girls, SFD’s intervention has a positive and highly significant impact (Exp B = 2.24 Sig = 0.00). The age of the girl is not a significant factor (exp B = .958 and Sig = 0.82), where late entrance in the school path – albeit improved by program’s efforts – is compensated by early leave, thus showing an indifferent effect of the age factor, contrary to what happens in boys (see enrollment curve for girls in Figure 8a). Living at an urban location and having a female head of household and the literacy level of the head of household remain important contributing factors to the probability of enrollment.

taken by the variable. When Exp B = 1, the independent variable does not tend to reduce or increase the probability of being enrolled. If Exp B > 1, an increase in the value of the independent variable increases that probability, and when Exp < 1, it reduces it. 23 When Sig > 0.1, the impact of the independent variable (as reflected in the Exp B statistic) is not statistically significant 24 Alternative regressions (not shown here) using actual per capita household income (with a reduced number of observations for the 1999 sample) or eliminating the income variable, provide similar results in terms of absolute and relative values of the other coefficients, thus confirming a robust enough model enabling us to use this configuration of the regression equation for the following analyses.

Table 8.f - Results of logistical regression of SFD impact on the gross enrollment rate for girls aged 7 to 14 Independent variable Type. Value/1 Exp B Sig R SFD investment completed Cat Yes 2.243 .000 .145 Household head = woman Cat Yes 2.929 .000 .126 HH reads/writes bef. Sec. Cat Yes 1.496 .001 .065 Zone = Urban Cat Yes 2.258 .000 .078 Age Cont n/a .958 .082 -.024 Deciles of income-proxy Cont n/a 1.015 .469 .000

Notes: Cat= categorical, cont. = continuous. Sig = significance of Log LR when the term is removed from the model; bold print means significance level <0.05. Number of cases: 1,346. 1/ This is the value assumed by the categorical variable.



Among boys (Table 8.g), the Exp B statistic still indicates a positive impact of SDF support, but this observation is slightly less statistically significant (Sig = 0.002). This is consistent with the results obtained in the previous section, where the impact on boys enrollment appears to be smaller.

The age of the child (in this case, the older the boy, the higher the probability of being enrolled), the household income and the sex and literacy level of the head of household are the main contributing factors determining the probability of boys’ primary school enrollment.

8.2.2 The impact of SFD on grade for age in primary education

SFD has also sought to improve educational quality through new classrooms in urban schools, in order to reduce overcrowding, and project components to finance text books and desks. Such investments should lead to higher pass- through rates. The desired outcome of these efforts is an increase in the proportion of children who are up to date with their education (that is, at the right grade for their age). The analysis was undertaken for children aged between the ages of 8 (when at a minimum they should have completed first grade) and 13 (when they

Table 8.g - Results of logistical regression of SFD impact on the gross enrollment rate for boys aged 7 to 14 Independent variable Type. Value/1 Exp B Sig R SFD investment completed Cat Yes 1.560 .002 .069 Household head = woman Cat Yes 1.810 .013 .051 HH reads/writes bef. Sec. Cat Yes 1.500 .009 .056 Zone = Urban Cat Yes 1.586 .144 .009 Age Cont n/a 1.203 .000 .157 Deciles of income-proxy Cont n/a 1.053 .024 .044 Notes: Cat= categorical, cont. = continuous. Sig = significance of Log LR when the term is removed from the model; bold print means significance level <0.05. Number of cases: 1,809. 1/ This is the value assumed by the categorical variable.

Table 8.h - Proportion of children up to date and not up to date with their primary education

Age: 8 9 10 11 12 13 Aver

% of the children in the group

Completed grade level: 1999 Baseline

None.-Pre.-Alph. 48.3 35.5 34.4 27.8 30.0 28.1

Basic 1 Year 11.8 9.8 2.7 3.1 1.0 0.4

Basic 2 Years 24.5 17.6 10.7 9.8 3.8 2.0

Basic 3 Years 8.4 22.3 13.9 9.8 9.3 4.7

Basic 4 Years 5.3 7.8 23.4 19.1 12.1 8.2

Basic 5 Years 1.2 4.7 8.0 15.5 13.4 19.1

Basic 6 Years 2.0 5.6 8.8 17.6 14.8

Basic 7 Years 0.9 3.1 10.9 12.1

Basic 8 Years 0.4 0.3 2.6 1.3 7.0

Basic 9 Years 0.5 0.6 2.3

Secondary-Superior 1.2

% not up to date 48.3 45.3 47.8 50.5 56.2 62.5 51.6

2003 Ex-post

None.-Pre.-Alph. 29.7 21.3 15.7 16.7 26.2 25.5

Basic 1 Year 16.7 9.6 5.7 2.4 2.0

Basic 2 Years 31.2 17.0 10.0 4.8 4.8 2.9

Basic 3 Years 15.9 30.9 21.4 13.1 6.3 4.9

Basic 4 Years 4.3 13.8 25.0 19.0 15.9 7.8

Basic 5 Years 2.2 3.2 16.4 28.6 16.7 11.8

Basic 6 Years 3.2 4.3 13.1 15.1 11.8

Basic 7 Years 1.1 1.4 2.4 9.5 23.5

Basic 8 Years 2.4 7.8


Secondary-Superior 0.8 1.0

% not up to date 29.7 30.9 31.4 36.9 53.20 54.9 39.2

Note: The gray shadow indicates the combinations of age for grade that are below the desired norm; that is, children that are not up to date. Source: NPS 1999 & IES 2003. N = 1,679 (BL) and 684 (EP).



should have completed sixth grade). It was hypothesized that the SFD investment would increase the proportion of children at the right grade for their age.

a) Direct comparison between baseline and ex-post data

The comparison of grade-for-age status of children in the intervention and pipeline comparison group, shown in Table 8.h, suggests that SFD has a positive influence on this variable.

In the baseline group 52% of the children were behind the expected grade level, compared with only 39% in communities that were SFD beneficiaries. This difference is statistically significant, with CIdiff = -6.2 , -18.6%)

The SFD’s effect on grade-for-age is more pronounced in the lower grades (children aged 8-10 years old), that is, the difference between group is larger. This is consistent with the fact that the SFD interventions were relatively recent when the dataset was produced. Older children, who got behind with their education before the SFD investment was made, would not get back up to date when a school opened, they would only cease to fall further behind.

The full effect on the age-for grade status of the opening of a new school or classroom is only felt by the cohorts entering the educational system after the SFD investment is made.

Gender - specific analysis (Tables 8 i and 8j) shows a differential impact on the proportion of children up-to-date in their education between girls (51% vs. 33%, CIdiff = -27.1, -9.1%) and boys (70% vs. 62%, CIdiff= -15.7, 0.5%, NS), that is a 18% impact difference in girls versus 8% in boys. However, the gender gap remains sizeable, with a 19% point difference remaining

Table 8.i - Proportion of girls up to date and not up to date with primary education

Age: 8 9 10 11 12 13 Aver



None.-Pre.-Alph. 56.5 55.8 53.1 45.9 52.1 47.0

Basic 1 Year 11.3 5.3 2.5 2.4 1.4 0.9

Basic 2 Years 24.4 18.6 13.0 5.9 4.3 3.4

Basic 3 Years 6.0 15.0 11.7 5.9 10.7 0.9

Basic 4 Years 1.2 2.7 11.7 21.2 9.3 7.7

Basic 5 Years 0.6 2.7 4.9 9.4 6.4 17.9

Basic 6 Years 2.5 5.9 10.7 9.4

Basic 7 Years 0.6 2.4 4.3 7.7


Basic 9 Years 1.7

Secondary-Superior

% not up to date 56.5 61.1 68.5 60.0 77.9 77.8 67.0

2003 – Ex-post

None.-Pre.-Alph. 40.0 24.4 25.0 27.0 43.9 41.8

Basic 1 Year 16.9 8.9 6.3 2.7

Basic 2 Years 30.8 17.8 4.7 8.1 5.3 3.6

Basic 3 Years 9.2 31.1 20.3 10.8 10.5 3.6

Basic 4 Years 3.1 13.3 25.0 18.9 10.5 5.5

Basic 5 Years 2.2 14.1 18.9 15.8 10.9

Basic 6 Years 2.2 4.7 10.8 8.8 12.7

Basic 7 Years 2.7 1.8 18.2

Basic 8 years 3.5 1.8

Basic 9 Years


% not up to date 40.0 33.3 35.9 48.6 70.2 65.5 48.9

Source: NPS 1999 & IES 2003. N= 785 (BL) and 323 (EP)



between girls and boys in the ex-post group.

b) Multivariate analysis

Once again, multivariate analysis was undertaken to establish whether these differences are attributable to factors other than the SFD investment.

The results of this analysis (Table 8.k) confirm that even after taking account of other factors, the probability of being up to date is significantly higher in communities that received SFD support (Exp B = 1.80, Sig. 0.000). The analysis also confirms that growing older and being a girl child have a strong negative impact (Exp B = 0.85 for older children and 0.33 for girls, Sig = 0.000 for both). Being in an urban location, conversely, has a strong positive impact on the probability of being up to date (Exp B = 1.69, Sig = 0.005), as does having a more educated head of household (Exp B = 1.42, Sig = 0.005) or a female head of household (Exp B = 1.55, Sig. = 0.001). The per capita income proxy variable does have a significant impact.

Table 8.j - Proportion of boys up to date and not up to date

Age: 8 9 10 11 12 13 Aver



None.-Pre.-Alph. 39.4 19.6 17.1 13.8 12.1 12.2

Basic 1 Year 12.3 13.3 2.9 3.7 0.6

Basic 2 Years 24.5 16.8 8.6 12.8 3.5 0.7

Basic 3 Years 11.0 28.0 16.0 12.8 8.1 7.9

Basic 4 Years 9.7 11.9 34.3 17.4 14.5 8.6

Basic 5 Years 1.9 6.3 10.9 20.2 19.1 20.1

Basic 6 Years 3.5 8.6 11.0 23.1 19.4

Basic 7 Years 1.3 1.1 3.7 16.2 15.8

Basic 8 Years 0.7 0.6 4.6 1.7 10.1



% not up to date 39.4 32.9 28.6 43.1 38.7 49.6 38.1

2003 Ex-post

None.-Pre.-Alph. 20.5 18.4 7.9 8.5 11.6 6.4

Basic 1 Year 16.4 10.2 5.3 2.1 4.3

Basic 2 Years 31.5 16.3 14.5 2.1 4.3 2.1

Basic 3 Years 21.9 30.6 22.4 14.9 2.9 6.4

Basic 4 Years 5.5 14.3 25.0 19.1 20.3 10.6

Basic 5 Years 4.1 4.1 18.4 36.2 17.4 12.8

Basic 6 Years 4.1 3.9 14.9 20.3 10.6

Basic 7 Years 2.0 2.6 2.1 15.9 29.8

Basic 8 years 1.4 14.9



% not up to date 20.5 28.6 27.6 27.7 39.1 42.6 30.5

Source: NPS 1999 & IES 2003. N = 894 (BL) and 361 (EP)



Running the regression for boys and girls separately does not yield very different results (tables not shown). One could note that for boys, as for the enrollment rate, the influence of the SFD input is slightly lower than for girls, as is the impact of being from an urban location (that is, rural girls have more problem getting and staying into school than their male counterparts). In the separate analysis, the age of the child is a significant factor for girls, but not for boys.

8.3 Health The Phase 2 Report used information from the 1997 Demographic and Health Survey (DHS) to provide background data for the evaluation of the SFD’s impact, underlining the huge challenges still facing Yemen in primary health, and especially in mother and child health. During the five-year period before the 1997 DHS, only 35% of pregnant women in Yemen received antenatal care (ANC). As in other countries, the proportion of pregnant women attending ANC increased in urban settings (61.5%) and with their education level (rising from 29.7% among illiterate women to 86.7% for women with completed secondary education). For pregnant women who did receive antenatal care, the median number of visits was 1.9. With regard to childhood immunization, the DHS survey shows that only 23.8% of children ages 12-23 months had received all required. The vaccination status of children was positively correlated with the educational status of the mother (rising from 24.0% for children whose mothers had no education to 70.8% if the mother had completed her primary education and with an urban location (56.4% versus 19.6% in rural areas). In this context, SFD investments in rural health posts would normally improve access to health services and this would lead to increased effective use (i.e., use at the level where appropriate care is available close to the community) of health facilities in cases of illness. Development of new primary health facilities would also improve vaccination and antenatal coverage in the communities served by these facilities.

The specific variables to be evaluated were the following:

• % of persons who have suffered a health problem (disease or accident) in the past month and have received medical help

• % of children under two years of age who are up to date with their vaccines • % of pregnant women who attend antenatal care visits

Table 8.k - Logistical regression for factors that influence being up to date in primary education for children aged 8 to 13 Indep.Variable Type Var. Value Exp B Sig R

SFD investment completed Cat Yes 1.799 .000 .102

Sex of h/hold head Cat Fem 1.545 .005 .045

Decile of income proxy Cont n/a 1.006 .718 .000

Zone = urban Cat Urban 1.688 .005 .044

Sex of child Cat Fem .325 .000 -.221

Age of child Cont N/a .846 .000 -.111

HH reads/writes bef. Sec. Cat Yes 1.415 .001 .054 Note: Cat= categorical, cont = continuous. Num. of cases: 2,142.



8.3.1 SFD impact on access to medical attention for health problems

Factors believed to contribute to low levels of utilization of health services in rural areas of Yemen include: the inexistence of facilities in many areas, the difficulty of access to the facilities that do exist, the poor quality of the services on offer and the lack of awareness among the population of the importance of primary health care.

When the SFD constructs a new rural health post or improves an existing one, it is expected that there will be an increase in the utilization of health services, for both preventative and curative care. As a large proportion of preventative procedures are still only carried out when families visit a health center due to an illness of one of their members, the increased consumption of curative care is likely to be correlated with increased consumption of standard preventative procedures and controls.

However, an increase in the use of services of any health post could be due in part to the diversion of some users from other centers (private doctors or other public health centers). This may be a deliberate goal of a strategy to rationalize the use of health services by establishing primary care services closer to the population and to avoid the use of more expensive referral facilities for routine care that should be managed in the health posts. Nevertheless, to the extent that users are diverted from other centers, the benefit from the SFD investment is arguably less than in the case where it stimulates the use of professional services by people who otherwise would have treated themselves.

For this reason, the variable chosen for analysis was the overall probability that a person will receive curative medical attention when facing a health problem (rather than the probability that they will use the particular health post supported by SFD). This assures that SFD is not credited for “crowding out” demand from other centers, but only for increasing the total take-up of primary health care services.

The IES survey recorded the health problems of each household member during the past month, identifying the type of problem and whether it was severe enough to cause the person affected to stop their normal activities. In the sample of households from the ex-post group, 405 problems were identified and in the baseline group, 346 problems were reported. Table 8.l reports the number and type of problems encountered.

Table 8.l - Incidence of health problems in the IES sample

Ex-post Baseline

% of total Number of persons 2,663 2,545

% with a health problem in last month

15.2 13.6

Male 13.3 13.1

Female 17.0 14.1

Urban 8.3 7.0

Rural 16.6 14.5

Number of problems 405 346

Type of problem:

Malaria 117 168

Diarrhea 60 48

E.N.T condition 75 12

Rheumatism 22 14

Skin condition 15 11

Diabetes, blood pressure 9 10

Accident/injury 8 3

Eye condition 7 12

Other conditions 92 68

Source: IES 2003 & NPS 1999.



The proportion of people who have suffered an illness or accident in the month previous to the survey is similar in both groups (15.2% versus 13.6%, p = , CIdiff –1.1 , 4.3%). The proportions were similar in both genders (3-5% differentials, with a slightly higher proportion in women) and were higher among rural than among urban folks in each group (16.6% against 8.3% in the ex-post group).

Table 8.m shows the reported effective access to medical attention for those in the ex-post communities compared with the 1999 NPS data. The proportion of sick individuals who managed to receive health care for their illness rose from 54.9% to 68.4% in the current ex-post group (which was the baseline group in the 1999 survey). The finding is also significant with p = and CIdiff = 3.7, 23.3%. In this case similar increases were recorded for both men and women. This is a clear and positive conclusion regarding the SFD’s impact on access to primary health care. 25

Table 8.n - Evolution of care-seeking practices between 1999 and 2003

Ex-post Baseline M F T M F T

1999 NPS analysis

53.7 58.1 56.0 56.4 53.6 54.9 Ex-post Baseline M F T M F T

2003 IES

70.0 67.2 68.4 73.9 69.6 71.7

As in the case of the data on education access reported above, the observed access rate in the new 2003 baseline dataset is much higher than that observed in the 1999 baseline group and not dissimilar from the ex-post conditions in the communities that received investments between 1999 and 2003 (see Table 9.n). This may reflect a change in the sort of place SFD invests in: it may be moving towards places where it is easier to deal with the sustainability problems that dogged its early efforts in primary health, and such places may have better ex-ante access conditions. There may also be a general trend towards better nation-wide access to health services linked to programs and projects other than the SFD.

25 The absence of any systematic difference between the ex-post and baseline groups within the 1999 NPS dataset (previously reported in the December 2002 study and observable in Table 8n) must therefore be regarded as reflecting sampling errors.

Table 8.m - SFD impact on access to medical attention for a given health problem

2003 E

1999 B li % of total

Did not receive attention 21.6 45.1

Received attention 68.4 54.9

Urban 92.1 77.3

Rural 65.9 53.4

Where they were treated:

Public primary health 39.9 24.7

Main center in city 4.1 5.3

Public Hospital 26.3 30.0

Private provider 16.2 20.0

Traditional healer 3.6 1.6

Other 7.6 18.4

Number of cases analyzed 277 190 Source: IES 2003 & NPS 1999.



We may also be seeing the effect of nation-wide care-seeking promotion campaigns, which would contribute to raise awareness of the availability of health care in the whole territory, independently of the presence of SFD activities. One of the main factors in both groups determining the use of professional services still seems to be the severity of the health problem. Of those who obtained medical care, 80.2% in the ex-post group and 89.5% in the baseline group had been unable to engage in their usual activities due to this problem, compared with 53.4% and 64.1%, respectively, in the group that did not obtain medical care.

Table 8.o. Relationship between care-seeking practices and severity of ailment

Ex-Post 2003 Baseline 1999

Received medical care

Yes No Yes No

Yes 54 61 20 56 Able to work

No 219 70 170 100

Total 273 131 190 156

Multivariate analysis

The multivariate analysis of the incidence of medical attention for health problems included the following independent variables: the existence of a SFD investment, the age and sex of the sick person, seriousness of the problem, income per capita of the household (proxy variable), urban/rural location, and the education of the head of household (Table 8.p).

Contrary to the previously reported findings (which were based on analysis of completed and pipeline projects using the 1999 NPS database), we find that, based on the before-after comparison set now available to us, the presence of SFD investment increases the uptake of professional medical care in a statistically significant manner (Exp B = 1.98, sig=.000).

The main determinant of obtaining medical care is the seriousness of the disease - expressed in terms of inability to engage in usual activities (Exp B = 4.34, Sig=0.000). Being aged 14-50 and living in an urban location are the next most important factors identified; patient’s sex works in the opposite direction (being a woman decreases the probability of seeking care, but not

Table 8.p - Results of the logistical regression of factors that influence access to medical attention Indep. Variable TypeVar. Value Exp B Sig R

SFD invest. completed Cat Yes 1.975 .000 .118

Age I Cat <5 Reference Val.

Age ii (5-13) Cat 5-13 .877 .580 .000

Age iii (14-50) Cat 14-50 1.734 .016 .064

Age iv (> 50) Cat > 50 1.214 .471 .000

HH reads/writes bef. sec. Cont Yes 1.087 .655 .000

Type of sickness Cat Serious 4.341 .000 .243

Sex of h/hold head Cat Fem .818 .580 .000

Sex of patient Cat Fem .839 .306 .000

Geographic zone Cat Urban 3.418 .002 .090

Decile of income proxy Cont n.a. 1.060 .067 .038 Note: Cat= categorical, cont = continuous. Number of cases: 713.



significantly). Household income, sex or education level of the head of household do not seem to play a major role either.

Gender-specific analysis yields similar results with a few differences: the positive impact of SFD investment is slightly greater for women, and young girls aged 5-13 would tend to receive more health care, although the difference is not significant. Of greater importance is the positive role, for medical attention received by women, of having a female head of household, an issue probably linked to cultural and financial factors affecting the decision-making process.

From the beginning, the SFD has encountered difficulties of coordination with the Health Secretariat for the assignation of staff, equipment and supplies to the clinics it has constructed. To counter this, the SFD’s interventions in the health sector were re-focused on organizing communities and mobilizing resources for the operation of a health post, prior to the construction of a physical facility. The above-reported findings suggest that the SFD has advanced with overcoming sustainability problems in the health centres it supports.

8.3.2 SFD impact on vaccination coverage

The analysis of sufficiency of vaccination coverage was conducted twice using slightly different approaches, as during the analysis of the 1999 NPS data. First, the standard World Health Organization (WHO) procedure was applied, analyzing the cohort of children aged 12-23 months at the time of the survey (see Phase 2 report). Then we looked at the timeliness of immunizations by studying the proportion of children up to 2 years of age up-to-date in their immunization schedule.

a) Direct comparison between ex-post and baseline groups

The results of the analysis, presented in Table 8.r, suggest that the SFD investments were associated with an improvement in the

Table 8.q. Factors affecting access to care for men and women

Male Female

Exp B Sig. Exp B Sig SFD invest. Completed 2.074 0.006 1.912 0.006

Age I Reference value

Age II (5-13) 1.143 0.694 .724 0.344

Age III (14-50) 1.813 0.094 1.645 0.107

Age IV (>50) 1.505 0.293 1.041 0.919

HH reads/writes bef. Sec. 1.985 0.021 0.738 0.222

Type of sickness 4.718 0.000 4.268 0.000

Sex of HH head (female) 1.301 0.544 0.646 0.197

Geographic zone (urban) 2.533 0.109 3.911 0.016

Decile of income proxy 1.069 0.165 1.056 0.212

Number of observations 312 401

Table 8.r - Impact of SFD presence on immunization of children under 2years

Ex-Post 2003 Baseline 1999 Indicator % of

children Obser-vations

% of children

Obser-vations

Children 12-23 months with immunization complete 39.1 92 28.3 53

Children under 2 years up-to-date with immunizations 32.7 196 37.1 105



vaccination status of the children in the beneficiary populations (from 28 to 39%), with regards to completeness of immunizations, although the small size of the sample makes this difference not statistically significant (CIdiff = -11.4 – 33.0%). The trend in timeliness of immunization is even downwards, also not significant either, possibly indicating a late tapering of previously more productive immunization efforts.

b) Multivariate analysis

Multivariate analysis suggests that the SFD investment is possibly associated with an improvement in vaccination coverage (Exp B 1.65); but this result is not statistically significant (Sig 0.267). There is no evidence of a positive relationship to the timeliness of immunization (Exp B 0.84, Sig 0.553) (Tables not shown). Living in an urban location remains the most important determinant in both parameters (Exp B 8.27 and 3.51 respectively, with Sig < 0.01), while having a female head of household also increases the likelihood of completing the immunization schedule (Exp B = 2.96 and Sig =0.07).

8.3.3 SFD Impact on the take-up of antenatal care

Primary Health care centers in rural area can deliver another important preventative service: antenatal care for pregnant women. In addition to contributing to a decrease in maternal mortality and morbidity, antenatal visits offer an opportunity to provide to women health education on various aspects of child and family care. In principle, pregnant women should attend the first antenatal visit during the first trimester of their pregnancy and receive at least three controls during this pregnancy. By improving access to professional antenatal care, the SFD should contribute to an increase in the proportion of pregnant women that receive antenatal care, eventually to an increase in the number of visits received and to an improved timeliness of the first visit.

The coverage level for antenatal care is still very low both in Yemen in general (65% of women who gave birth in the previous five years did not receive antenatal care during their pregnancy, as per the Yemen 1997 DHS) and in the survey population (where this figure reached 68.1% in the ex-post group and 71.8% in the baseline group).

The reasons given for not receiving prenatal control were similar in both groups: no difficulty perceived during pregnancy (29.9 and 29.4%), high cost of consultation (26.4 and 22.6%), non availability of service (15.2 and 23.8%), service far away (11.2 and 13.7%). Antenatal care services are available all days only in 82 and 84% of the facilities, and not available at all in 4.5% and 3.2% of these. During their visits, 70% of women from the ex-post attending antenatal clinics received tetanus toxoid immunization, versus 73.2% in the baseline group.

Direct comparison between ex-post and baseline groups

In the IES sample, 45 (11.4%) out of the 396 eligible women in the beneficiary communities and 31 (11.6%) out of the 267 women in the pipeline group were recently pregnant. Their attendance at antenatal care services is reported in Table 8.s. The numbers of observations are rather small and the results are not



statistically significant, but it seems that the presence of SFD investment is not associated with improved antenatal attention for women in rural areas.

8.4 Water projects

Water supply is a major development problem is Yemen. The topography and hydrology of the country make water resources very scarce and it is difficult and expensive to supply piped water to many of the mountain villages.

Urban communities rely normally on public and private networks, often based on wells, facing problems of supply sufficiency and network management (large distribution losses). Rural households use mainly cooperative networks, rainwater harvesting systems (ponds) and wells and springs. The SFD’s water projects are now concentrating entirely on establishing and improving rain water harvesting (collection and storage) systems in rural areas.

The IES 2003 collected data at household level on the type of water system used, the perceptions on quantity and quality of water available to the households before and after interventions, the cost of water, the distance and time needed to fetch water for people without a household connection and the incidence of diarrhea.

Table 8.t shows the distribution of sampled households from water project areas, according to the type of water system they use for their residence before and after intervention (actually without intervention for the baseline group). Although we already mentioned the emphasis of the SFD sub-projects in improving water harvesting systems, we can observe in the ex-post group an increase in the proportion of households getting water from a tap located in their own dwelling, associated with a decrease in the use of cisterns or tanks without pump and/or well or dam water outside of the compound. The SFD intervention increased access to household taps (+35% for drinking water), replacing cisterns without hand pumps (-10%) or with hand pumps (-8%) and wells/dams off the premises (-20%)26.

26 The methodological corrections detailed in Section 9.1 (dropping from the analysis set segments for which we did not have a full before-after comparison pair) made an important difference to the results in this section. In the full dataset, the apparent impact was smaller

Table 8.s - Proportion of pregnant women that attended antenatal care 2003

Ex-post 1999

Baseline

% Obser-vations

%

Obser-vations

All women 24.4 45 12.9 31 Urban 61.5 13 25.0 4 Rural 9.4 32 11.1 27

Table 8.t – Main source of water, before and after SFD interventions, rural areas (ex-post sample)

Drinking water

Water for domestic use

Before After Before After Piped water, household tap 0.0 34.8 0.0 31.1 Piped service, public tap 0.0 2.3 0.0 2.3 Cistern/ tank with hand pump 9.1 1.5 9.1 3.8 Cistern/tank w/o hand pump 22.7 12.1 25.8 18.9 Well on the premises 3.8 3.8 3.0 3.8 Well/dam off the premises 36.4 15.9 37.9 15.9 Tanker 25.0 23.7 24.2 24.2 Number of observations 132 132



Several indicators can be used to assess the impact of water projects on the life of their beneficiaries. The most immediate indicator is the quantity and quality of water available for the family to satisfy its needs (drinking, cooking, hygiene) during a given period. Increases in the amount and improvements in the quality of water consumed lead directly to increased welfare and to better health conditions and the prevention of water-related diseases such as diarrhea. A second indicator is the cost of bringing the water to the dwelling (both in time and money). A water project might significantly reduce this cost, freeing resources for other vital needs. The carrying of water is normally assigned to the women and girls of the household and the need to carry out this task is an important factor reducing girls’ enrollment in school.

45.7% of the 184 households in the ex-post group said that the quantity of water available is much more than before; 37.5% found no significant change, while 10.9% thought that it was less abundant. The quality of available water was deemed better in 33.7% of the households, unchanged in 40.8% and worse in 19.0%.

For those households (101) which indicated that they had to go outside to fetch water, the average consumption was estimated at 15.5 containers of an average size of 16.8 liters, which would yield a total daily amount of 260 liters, that is an average of 35 liters per person per day (using an average of 7.5 persons per household. For those households, there were some gains in the reduction of the average distance needed to fetch water outside of the dwelling (from 1,064 meters on average to 916 meters, a 14% decrease, for the 57 reporting households) and in the corresponding time needed to fetch the water (from 78.3 to 63.4mn, a 19% decrease, for the 98 reporting households). However, those differences are not statistically significant (see Annex D).

While the 2003 survey did not disaggregate those results on a gender basis, data from the 1999 NPS show that women (and children) would be the principal beneficiaries of those gains of time and distance: indeed, household women are responsible for water collection in 74.4% of household that have to fetch water from outside, children have this responsibility in 7.1% of the cases and men (or non household members) in 18.4%. The burden of women and children increases to 92.7 and 95.7% when the water is brought by donkeys or other animals, or by foot, respectively, while men are responsible of 55.5% of the water collection process when it is done by car.

Incidence of diarrhea

The incidence of diarrhea in the month previous to the survey was similar for the baseline and for the ex-post groups, both for the population at large (1.8 versus 2.2%, difference not significant) and for children under 5 (6.2 versus 7.1%, NS).

than that observed here (+23% for household taps, -8, 4 and 1% respectively for cisterns without and with hand pumps, and for wells/dams outside of the house. The elimination from the dataset of households outside of the project’s influence area, led to a bigger estimated impact of the SFD intervention.



Table 8.u - Incidence of diarrhea in the month previous to the survey

Whole population Children under 5

1999 Baseline 2003 Ex-post 1999 Baseline 2003 Ex-post

% n % n % n % n

All 1.8 1,694 2.2 1,400 6.2 274 7.1 239

Male 1.5 841 2.0 702 7.2 139 8.7 115

Female 2.0 853 2.4 698 5.2 135 5.6 124

Urban 1.7 119 2.7 372 11.8 17 9.8 61

Rural 1.8 1,575 2.0 1,028 5.8 257 6.2 178

Multivariate analysis was conducted of the impact of SFD water projects on the probability of children under 5 having had a diarrhea problem in the month previous to the survey. The factors included in the analysis, in addition to SFD project support, were: age and sex of the child, sex and education level of the head of household, geographical zone, per capita household proxy variable, type of water system, type of toilet (none compared to latrine or flush) and main material of the floor (Table 8.v). The analysis found no statistically significant impact of the SFD’s water project’s presence on diarrhea incidence (Exp B = 1.05 and Sig = 0.913).

The sex of the household head and the age of the child are the main factors that determine the probability of having had diarrhea in the previous month, with probability decreasing with age, a finding consistent with the epidemiology of diarrheal diseases. The negative impact assigned to female heads of household may actually be related to the concentration of women holding this responsibility in poorer urban marginal areas. The type of water system or type of toilet does not seem to influence the probability of getting sick. This lack of apparent effects of variables theoretically linked with a higher incidence of diarrhea may be explained by the fact that the link between systems and illness is usually mediated by attitudes and practices related to personal and child hygiene.

8.5 Characteristics of the survey population

The above findings are based, where possible, on rigorous multivariate analysis that allows us to reach inferences about the impact of the SFD’s intervention in spite of the fact that we do not have available a full comparison set of before and after observations for an intervention and a control group.

Table 8.v - Results of the logistical regression of factors that influence the incidence of diarrhea in the previous month Indep. Variable Type

VValue Exp B Sig R

SFD inv. completed Cat Yes 1.047 .913 .000 Sex Cat Fem .620 .205 .000

Age Cont n.a .744 .051 -.086

HH reads/writes bef. Cat Yes .476 .359 -.040

Sex of h/hold head Cat Fem 2.451 .051 .085

Geographic zone Cat Urban 2.286 .129 .035

Water system Cat Inside 1.117 .805 .000

Floor of dwelling Cat Sand .786 .620 .000

Toilet 1 Cat Latrine .717 .470 .000

Toilet 2 Cat Flush .316 .318 .000

Decile of income proxy Cont n.a. 1.018 .808 .000 Note: Note: Cat= categorical, cont = continuous. Number of cases: 485.



A comparison of general household characteristics in the enumeration areas in the 1999 NPS and the 2003 IES confirms that there are some important differences in the socio-economic characteristics of the observed communities, which confirm the importance of using multivariate analysis. Annex G contains more details on this comparison.

• In the 1999 dataset, the proportion of people aged six and above who never enrolled in school was 55%; in the 2003 dataset it is 45%. Similarly, in 1999 the proportion of the population currently enrolled was 29 compared with 33% in the 2003 dataset. The number of illiterate persons (aged 10 years and more) was 53% in the 1999 dataset and 46% in 2003. The gender gap for enrollment (a 41 percentage point difference) is similar in the two datasets.

• Households in the 2003 ex-post sample have a slightly higher number of household goods (electro-domestic items, vehicles) than in the 1999 sample. However, the characteristics of their dwellings are similar.

• The 2003 dataset reports a greater proportion of households with piped water, at 33%, compared with 25% in the 1999 dataset.

• The proportion of households that live near a school (primary or secondary) is greater in the 2003 survey than the 1999 dataset. However, the distance to some other public or community services (pharmacy, hospital, police station, post office) is greater in the 2003 dataset.



9 Conclusions and Recommendations

9.1 Conclusions

9.1.1 SFD outputs and its contribution to the national stock of infrastructure in the social sectors

• As of July 2003, the Social Fund for Development has committed a total of US$213 millions in 3,063 projects, of which 55% have been completed (up from 45% in December 2002), with 44% of the committed funds disbursed. The SFD’s main commitment remains with education projects (54% of the total investment). Along with water, health and rural roads, these four categories represent 79% of all projects.

• Those same categories of projects generate 79% of all direct beneficiaries. The total number of direct beneficiaries is estimated at 3.2 millions, including 48.9% of women. However, detailed examination of survey findings may lead to think that the beneficiary estimates incorporated in the MIS, made during the project planning phase, may be exaggerated. SFD is in the process of rationalizing the definition of beneficiaries to ensure a reliable indicator is used.

• The overall duration of completed projects – from request to completion - is 19.2 months. Rural road projects have a longer median duration (648 days) than health or education projects (562-580 days). The project cycle duration has increased from 282 to 631 days, most of this increase being linked to a lengthening of the first phase (from request to approval), a likely result of the increased number of project requests to process.

• The average project cost per beneficiary varies from US$6 (integrated interventions) to US$221 for training. These costs are generally in line with the parameters anticipated in the program’s design and in the World Bank’s Project Appraisal Document.

• The SFD has built, completed or rehabilitated a total of 5,396 classrooms, which represent 7% of the national stock of infrastructure, as estimated in 2001/2. Moreover, the SFD contributed between 30 and 40% of all new classrooms built in the country. Corresponding figures for completion or rehabilitation of health units and health centers respectively are 5 and 7%. By the end of 2003, the program is expected to have build/repaired 705 km of rural roads, that is, 3.5% of the current national network.

• The overall financial investment of the SFD in the social sectors over the period 1997-2003 represents around 20% of the total national investment in education and 7.5% of the total investment in health, a proportion that has increased year by year.



9.1.2 Targeting outcomes

The targeting analysis shows what proportion of program resources benefits each decile of the population, based on data for the per-capita income of each household and the amount of the SFD’s investment in each community and project.

• A high proportion of SFD resources are benefiting the poorest households in Yemen. 17% of SFD funds go to the poorest decile, 31% to the poorest quintile and 44% to the poorest three deciles. Only 4% of resources are received by households in the top decile. These figures are considerably better than those found in other Social Investment Funds where similar analytical procedures have been applied.

• The distribution index number for the total of the project types analyzed here is above zero, at 0.204, indicating a significant positive impact. It is also noteworthy that the pattern is consistent across sub-project types (with distribution indexes ranging between 0.176 and 0.256. The only exception is micro finance where the distribution index of –0.072 shows a regressive pattern, a normal finding for this sort of project.

• Those findings are more positive than those yielded by previous analysis of the SFD project beneficiary communities covered by the 1999 NPS. This might reflect an improvement in targeting by project officials since 1999, or methodological problems in the analysis of the 1999 dataset related to the link between projects' areas of influence to household data observations.

9.1.3 Consultation, participation, ownership and impact on social capital

• Both the household and the qualitative survey indicate the frequent occurrence of involvement of individual political leaders (shaikh or Parliament member), either to initiate or to support the project, a traditional way for politicians or customary leaders to maintain their status.

• The district and governorate-level offices of the line ministries seem to be only peripherally involved which may indicate the effectiveness of the Fund’s interventions in bypassing common administrative barriers and bottlenecks, and establishing itself as an action-minded organization. On the other hand, it may also reflect a lack of inter-sectorial coordination, which may be prejudicial to the future operations and maintenance of the sub-project.

• Between two-thirds and four fifths of the communities contribute money to the sub-project, the easiest way to participate, provided there is some money available in the community. Direct labor contribution is highest in the road sub-projects. The community contribution estimated by the project survey corresponds to 7% of the completed project costs for education and health projects; 17% for water projects and 11% for roads projects. These figures are above the 5% that constitutes one of the requirements for SFD funding.

• From a household perspective, there is a clear majority of 60% to 89% of interviewees concurring that the project implemented by SFD was the highest priority, with the best ranking going to micro finance projects. For



those who stated other priorities, water projects were the preferred alternative.

• The proportion of respondents who feel themselves not to be a beneficiary is greater in the ex-post than in the baseline group. This is probably due to it being clearer, after a project is finished, who are really the beneficiaries; ex-ante, some people may expect to benefit, and turn out later not to benefit. This could lead to some discontent with the SFD project among the households who do not benefit.

• Not having data on social capital for the ex-ante situation of communities in the ex-post sample, we are only able to compare here the ex-post social capital situation with the ex-ante situation in the new baseline sample, which is not necessarily a good indicator of SFD’s impact on social capital. However, the levels of structural social capital appear to be generally rather low in both datasets.

• The qualitative survey provides an image of poor households so immersed in their daily survival and the repetitive chores linked to getting enough food and water that they rely on leaders who are less poor than them to take care of innovations and project follow-up. Given this cultural setting, it would be utopian to expect the SFD’s projects to transform community dynamics. Nevertheless, in several cases, it is possible to observe the beginning of a change in some of the affected communities, with clear instances of effective participation, cooperation and increase mutual trust.

9.1.4 Service production and sustainability

• The SFD investments in schools were associated with an increase in enrollment, which is particularly strong for girl students, whose teaching conditions were favored by the building of new classrooms, so class sizes for girls remained stable. The number of students increased by 29% generally and 38% for girl-only classes. The average class-size rose by 38% in (but only 8% in girl-only classes). Staffing patterns showing a relatively high proportion of qualified and permanent teachers suggest hat the availability of staff (and funding for their employment) is not a serious limiting constraint, except maybe in the case of female teachers. There is also evidence of a reasonably high level of parental involvement in the schools SFD is supporting.

• In health facilities, the daily, integrated, delivery of services is far from being ensured, implying that people/families with the need for those services may have to come on several occasions to the facility in order to satisfy those needs. The presence of physicians and/or midwives (assigned to 50-60% of the facilities) is associated with a 10-30 percentage point increase in the availability of specific services. The production figures are low, with an estimated utilization rate of 0.28 consultations per person and per year. A major concern is the perceived lack of cooperation with the governorate or district health office, whose usual contribution is to dispatch a medical assistant and send limited amounts of essential drugs, but provides no maintenance budget.



• SFD projects have had a very positive impact on coverage of the water systems. The proportion of households with tap drinking water in their dwelling was reported to increase from 3% to 26%. The SFD intervention also led to a clear increase in per-capita consumption of water and frequency of supply. Financial sustainability of water systems is improving: there is still a shortfall as revenues represent 65% of total costs (up from 34% before the SFD intervention).

• Sewerage projects are generally well received and include the following benefits: improved landscape, improved sanitation, improved safety for children, decreased damage to building walls and foundations, and increase in the prices of the houses located in the drained areas.

• Rural road projects have had a very positive impact on journey times, reducing them on average by 40%. Household level responses also suggest a significant reduction in the cost of travel, as well as some amount of reduction in the cost of basic commodities imported to the villages. The resulting impact is an increase in the number of trips made to next town or market in order to sell local production.

• Micro finance projects have overcome initial governance and accounting problems, at the price at being increasingly perceived as a “regular” business, rather than a service to alleviate poverty. Yet, the survey confirms the positive impact of the schemes on the perceived changes in standards of living, and the number of borrowers, especially women, is increasing in the smaller schemes. However, their capacity for mobilizing savings as a source for loans is limited and the projects still generally report operating losses. Incongruency in the financial statements lead us to suppose that there are still weaknesses in the accounting procedures.

• Special needs groups projects and Institutional Support projects allow the Fund to address real and pressing needs, yet may benefit from a more integrated, less limited approach, such as the combination of access to micro credit schemes for beneficiaries of craft or agricultural training.

• In all type of projects, the existence of initial monetary contributions (household level connection fee, for instance) or the charging of fees for training constitutes a deterrent for the poorest of the poor, even though subsidies from key individuals occur in a number of cases.

9.1.5 Impact on household-level development indicators

The chapter reports the changes from 1999 to 2003 in the household-level indicators attributable to the SFD’s projects completed in this interval:

• There is a very clear and statistically significant increase in gross school enrollment rate for girls where the SFD investments were made, from 42% in 1999 to 58% in 2003. The overall rate rises from 59% to 70%, reconfirming that the SFD is making an important difference to one of the most critical development indicators in Yemen. The multivariate analysis confirms that – ceteris paribus - the SDF investment has been, especially for girls, a significant factor in increasing school enrollment, for which the sex



and level of education of the household head and the urban location also have a significant impact. The SFD interventions are also responsible for decreasing from 52 to 39% the proportion of children aged 8-13 not up-to-date at school, again with a preferential impact on girls (from 67 to 49%). Yet, the gender gap remains sizeable, with a 19% point difference remaining. The multivariate analysis shows results similar to those for gross enrolment.

• With a proportion of people who have suffered an illness or accident in the month previous to the survey similar in both groups, the proportion of sick individuals who managed to receive health care for their illness rose from 55% to 68% due to the SFD intervention in health facilities. Similar increases were recorded for both men and women. This is a clear and positive conclusion regarding the SFD’s impact on access to primary health care. The multivariate analysis indicates that, contrary to the 1999 results, the presence of SFD investment appears to be increasing the uptake of professional medical care in a significant manner, along with the age of the person, the severity of the disease and the urban location.

• Small sample size may be responsible for not observing, either through direct comparisons of rate, or through multivariate analysis, any positive impact of the SFD investment on immunization timeliness and coverage, or for uptake of antenatal care.

• SFD water projects contributed to an increase in the proportion of households getting water from a tap located in their own dwelling (+35% for drinking water), associated with a decrease in the use of cisterns or tanks without pump and/or well or dam water outside of the compound. For those households which have to go outside to fetch water, there were some gains in the reduction of the average distance needed to fetch water and in the corresponding time needed to fetch the water in the order of 14 to 19%. No impact was observed on the incidence of diarrhea.

9.2 Recommendations

The recommendations of this study focus principally on the evaluation methodology and on the future development of the SFD’s M&E system. The implications of the above-reported findings for the future implementation of the program should be derived by the managers and stakeholders themselves, on the basis of the surveys’ results and their own knowledge and experience of the Fund’s objectives and operations.

• Program officers in the field and program management should pay attention to the definition and estimation of beneficiaries in sub-project documents, as specified in the Impact Monitoring and Evaluation Manual. This will allow a more precise estimate of efficiency parameters such as cost per beneficiary.

• The appraisal forms designed for the M&E system should be systematically applied to all new projects, and a sample based ex-post project survey should be carried out bi-annually, together with a beneficiary appraisal of a sub-set of those projects. This will allow the SFD to generate a continual stream of feed back from the M&E system to inform its policy decisions.



• The next full impact evaluation survey should be implemented in 2005 (IES 2005), at which time ex-post data should be collected for the baseline set of data collected in 2003. The program should check, before sampling for this survey (IES 2005), whether all villages in the sampled Enumeration Areas are within the area of influence of the projects which were covered by the 2003 baseline. If they are not, sampling should be done in the relevant villages/ communities only. At the same time, a new baseline dataset should be collected for a sample of projects in the pipeline at that stage.

• There is a need to review/simplify the instruments for evaluation of SFD’s outputs in terms of new/refurbished structures (project surveys).



Annexes

A. List of projects in the 2003 household survey sample

B. List of projects in the qualitative survey with map of project location

C. Calculation worksheet for the targeting outcome (In Excel file)

D. Calculation worksheet for tests of significance (In Excel file)

E. Financial statements from the micro finance projects (In Excel file)

F. List of trainings conducted by the SFD (In Excel File)

G. General and socio-economic characteristics of the population surveyed



Annex A: List of Projects in the 2003 Household Survey Sample

Project # Sector Project Title Governorate Comments

Baseline Survey

21-74-12 Education Construction of Boys School 18 No. class + Supplement + Furniture at Al – Mansurah Aden

21-134-568 Education Consrution of 6 classes + annexes for ASHREA Girl school Al-Baidha

21-74-19 Education Construction of Girls School 6 No. Classes + Supplements + Lodging + Furniture Al-Dhalea

21-104-757 Education construction & furnish 6 classes (male)+6classes (female)-beat alantry-alamariah-alkhabt Al-Mahweet

21-104-780 Education 9 classes with necessary utillity in alzahra school- shebam-shebam-almahweet Al-Mahweet

21-154-242 Education - Constraction &furnishing of 6 Classrooms / arar / al tholth / Sower / Amran . Amran

99-66-299 Education Construct/furnishing alnseer school4 cl. + facilities -gazhet asehe/ alamraen-/ Alsawd. Amran

20-134-98 Education Cnstrution of 6 classes + annexes for Alkwaty Dhamar

21-134-556 Education Consstruction of 2 classes+ annexes Alakdari Dhamar

21-156-8 Education Completing existing 4classes and constructing additional 9 classes at AL-HAMY Hadhramout

99-107-114 Education Constructing and furnishing 6classes school at ATTAWEELAH Hadhramout

99-156-8 Education Maintaining and completing AL-HUSSAIN school-Addalaiaeh Hadhramout

21-154-262 Education Cons./furn. 6 classrooms in AlAbadelahBaniAlzain - Garbi AlKhamisain- KairanAlmharag Hajjah

99-20-101 Education Cons. Of 4 classrooms for boys & 6 classrooms for girls at Algareb-Bani yose – Aflah Hajjah

21-175-19 Education Constructing And furnishing 10 classes with utilities + wall for al-nhdhah school . Hodeidah

21-175-46 Education Reparing and adding 12 new classes with furniture and utilities + wall for al-netaqain sch Hodeidah

21-36-27 Education Construction of four(4)new classrooms with utilities and furniture +wall . Hodeidah

21-36-20 Education Constructing and furnishing (5) new classes with utilities + wall for 27th April school. Hodeidah

20-92-145 Education Const. & furnish. 5 class.(div. In 7)+ facilit. In Omar bin Abd El Aziz Al Soban Al Sabra Ibb

21-147-165 Education constracting new classes for Uqba Ben Nafa' school \Abroh \Sabrah Ibb Ibb

98-26-3531 Education Rap. 3 class.+add & Furnish.5 class.+ facilit.In Azzubair school Al Jalades Hubaish I Ibb

20-74-16 Education Construction of 6 No. Class School For Girls + Supplements + Furniture Lahj

98-106-86 Education Construction of 14 th October School 9 No. Classes at Masha'alla, Yaher, Lahej Lahj

21-104-416 Education construction &furnish 8 classes (male) &6 classes (female)-alakama -alswad-sanhan Sana'a



99-104-16 Education Construct & furnish a 2 classrooms with it's utility-Alswass-khawlan-sanaa Sana'a

21-20-425 Education Mohammed Ismail Boys School Sana'a Capital

21-20-432 Education Othman Bin Affan School - Al-Hasaba Sana'a Capital

21-156-5 Education Constructing and furnishing 4classes school at MALAS Shabwah

21-147-32 Education Construction of 4 classrooms for Oees Alkarne School/ tabeh / mashraa & wahdnan . Taiz

21-147-9 Education Construction of 5 classrooms for Alhagreen wasahoon - Alakrood –TAIZ Taiz

98-26-157 Education ALNASHMA- SCHOOL- TAIZ. Taiz

21-134-309 Health Const. & furinish. a unit of health in Darwa- Mukairas- Al Baidhaa Al-Baidha

21-134-406 Health Constrution and rehabition of health unit Alkorasha Al-Baidha B

21-104-64 Health Construction & Equipping Health Care Unit / Gaweaa / Althare / hofash . Al-Mahweet

20-20-834 Health Constrution and rehabition of Healthcare unit Bani Mater Otma Dhmar Al-Mahweet

20-104-743 Health Construction & Equipping Health care Unit / Al-azake / Alrogem /Almahwet. Al-Mahweet

99-154-2 Health Building and Equiping the health unit in Kasabat Rajeh - Sayran- Sharah – Hajjah Amran

98-26-4439 Health Construction and rehabilitation of health unit care ALSSNAM-Gahrran -dhamar Dhamar

99-107-169 Health complition and furnich Algara health unit Hadhramout

99-107-171 Health Equipping the Health Centre in Al-Raida Al-Sharqiah Hadhramout

99-107-175 Health Construction and furnishing health unit in AlDaleaa Hadhramout

21-20-237 Health Extension and rehabilitation of reproductive health department at Bajil hospital/ Hudeiah Hodeidah

21-20-238 Health Extending and Equipping the reproductive health department at Al-Dhahi hospital Hodeidah

98-66-161 Health Construction and Equiping the health Center /Madgal Al-jedaan –Mareb Maareb

99-66-89 Health Construction the health unit and support the nessary equipment-ALMHARIJ-Alsalfia/Sanaa Sana'a

21-20-408 Health improvement and expansion of health services at Al-Jabeen Hospital/ Mansah/ Jabeen Sana'a

98-26-3002 Health Construction & Equiping Health unit at Barha Al-Awbly / Al- jaafariyah Sana'a

98-26-350 Health Construction and Eqiping a Health unit /Wadi mahd/Aljabeen/Sanna Sana'a

99-104-132 Health Construction and Equiping a health unit /Okab safel / Banee Al harazy /Aljaafria/Sanaa Sana'a

98-26-1716 Health Construction & Equiping the Health unit at bani Masruq / Kusmah Sana'a

20-147-110 Health Construction and Equipping the health center-Al-Arook/Hayfan/Taiz Taiz



98-26-2002 Health construct and equip a health unit consists of 2 rooms-Algarn-Mauiah-Taiz Taiz

98-26-3881 Health Construct and equip a health unit-Talouq-Almisrah-Taiz Taiz

99-20-64 Health Construct and equip a health unit-Alhashamah-Altaiziah-Taiz Taiz

99-92-138 Health Construct and equip ahealth unit-Asrar-Maoiah-Taiz Taiz

99-106-144 Roads ROSUD R. THAMER AL QAHER ROAD PROJECT. Abyan

20-20-1173 Roads Truck Road AlQahra - AlSurfah - Sahm Alardof - Al-Shoaib District - Al-Dhala Al-Dhalea

21-104-634 Roads Al- Mahweet - Al-Madrak / almahweet Al-Mahweet

99-20-380 Roads Alkadan - Alwalajah - Sahari Road / Melhan / Almahweet Al-Mahweet

20-187-3 Roads Protection works for Markiz Alsoud - Bani Talag - Bilad Janab Alamreen Bani Alharith road Amran

21-20-45 Roads Khamis Shejn-Masro'a Road Project (Maghreb Ans-Dhamar) Dhamar

21-20-48 Roads Zaber-Bani Duhaim Road Project (Maghreb Ans - Dhamr) Dhamar

20-20-1009 Roads Athkal escarpment( Rakhiah- Hadramout ) Hadhramout

20-20-1010 Roads Wadi ALGashbah - Madoum road (Kohlan Alshrg -Hajah) Hajjah

21-20-17 Roads Al Henak Road Project (Wadhrah - Hajjah) Hajjah

20-20-880 Roads Gabal al-Dhamer road ( Bajil- Al-Hodeidah ) Hodeidah

99-26-180 Roads Azal - Ageeb Road Project ( Alradhma - Ib ) Ibb

21-104-789 Roads Morad - Altaref - Alakhelah / Rahabah / Ma"reb Maareb

20-20-1008 Roads ALshrorih Road - Asfal Ghamar - Razeh - Sa'adah Sa'adah C

22-126-282 Roads Garbi Alazd road proj. Razeh saada Sa'adah

20-104-71 Roads Sabt Yafan - Mazhar - Thahyan / Maswar / Algabeen / Sanaa Sana'a

20-104-740 Roads Al-Marboa-- Al Salf Road (al qobair- magrabat khodam)/khodam&bani ahmad/ aljabain Sana'a

20-20-555 Roads Bani Yosuf Road Project (Bani Yosuf - Al Mawaset - Taiz) Taiz

21-147-422 Roads Koratha - Al gnaat Road Project ( Al Seelw- Taiz ) Taiz

21-134-603 Water Water project ( net wort and tank )at Goll Salman in Al-Sowadea'a AL-BYDA Al-Baidha

99-106-181 Water Rehabilitation of Water-harvesting reservoir of Aal-Anaam Villages/ Al-shueib -Al-daleh Al-Dhalea

21-104-51 Water Ruin Water Harvesting For Almazab Vellege uzzlat bany AL-Shoishy /bani Saad Al-Mahweet

98-13-21 Water Bani Zaid Small Dam Al-Mahweet C



98-50-109 Water Salf Small dam/ shibam- kawkaban/ AL-Mehweet Al-Mahweet C

21-143-1 Water Water harvesting project forAllomi/ Eial Yahia / Eial Yazid / Amr./ rehabi. (2) cistern Amran

21-143-10 Water water harve pro. For Bait Alhashidi/Wadiaat Hashid / khmir/Amran(one cistern) Amran

21-154-122 Water Cons. of awater project in Auzlat Al-Jodom -Maswar- AmranN Amran

20-20-912 Water Water harvisting for Bakesh & Al-Mogawer Ozlat Osab - Al -safel DHAMAR Dhamar

99-20-520 Water Water Harvisting one cistern at Sofean village at Bane Sweed Doran -Dhammar Dhamar

20-145-37 Water GHIL BAWAZEER rain water harvesting ( Ghil al halka - Gashoosh - Alkobliat- Alraheeba) Hadhramout B

99-26-369 Water Water Harvesting Project in Jabal Aishan - Kholan - Hajjah – hajjah Hajjah B

22-192-1 Water Rehabilitaion of Hand dug wells - Al Monirah & Al Luhayah Hodeidah

21-147-220 Water Rehabilitating channels of Wadi Gobel and Al Aqwoor \Assdah Ibb B

21-106-104 Water Construct a Water Harvesting Dike In Aadan BinAbadel/Al-Muflehi Lahj Govern. Lahj

99-148-8 Water Construct a water- harvesting reservoir in Al-mabareza Al-gaydah /Al-qabayta -Lahj Lahj B

20-126-789 Water Water harvesting pro. For( jaleh)/Shaaban/Razeh/Saadah Sa'adah

20-104-617 Water Rain Water harvesting for tarafat /Alkamis- Arhab. Sana'a

20-104-841 Water Rain Water harvesting (2cisterns)for villeges of Alhdor and darwa/bany yafur/kasamah Sana'a

20-104-846 Water Rain Water harvesting (3 cisterns)in of AL-Hagar and bany flah/AL-Aarosh/khawlan Sana'a

20-104-901 Water Rain Water harvesting For AL Rebat/ AL Aslaf/AL Salafieah Sana'a

20-104-921 Water Rain Water Hrvesting For AL Nawaser Vellege In Arhab/Bany Ali Sana'a

98-66-152 Water Construction of water tank at Al- Jamon / Kosmh Sana'a

98-26-3257 Water Construction of dam -Ngm Al-shaiban –Khawlan Sana'a Capital C

20-67-27 Water Arqa Water - Razoum- Shabwa . Shabwah B

20-92-258 Water Developing Al Mahzaf's pond and Al Mahrom's pond - Saber Taiz

21-147-246 Water Constructing 3 ponds for Gashe' Al Akhfash and Al Mqashebah Athawer Taiz

Ex-post Survey

98-50-67 Education Construction and furnishing of Halima Al Sadia school Al-Baidha A

98-17-17 Education Construction and furnishing of AS SALAMAT school Al-Jawf

97-50-201 Education Construct and Furnish 4 classrooms + Facilities at Alnoor school- Alhejrah- Alro Al-Mahweet A



98-26-196 Education Construction & Furnituring 4 Classes in Al- Hanatbah Scool Amran

98-26-382 Education Construction & Furnisging of 6 Classrooms in Al- Masam. Amran

98-16-50 Education Completion of Yafan school Dhamar B

98-26-2468 Education Construct & furnish 6 classrooms+staff room+ 3 toilts- at Banee Gaber-Dhamar Dhamar

98-26-905 Education Cnstruction&furnish 3 classrooms+staff room+3 toilts -GALAS-DHMAR Dhamar B

97-50-43 Education Building and furnashing 9 classes school for girls in Al- Sweriery Hadhramout

98-26-137 Education Asshoariah School - Aljabr Alaala – Madan Hajjah

98-26-1873 Education Construction& Furnishing of 3 class rooms./ Haiyach / Quaidanaa / Hajjah. Hajjah

98-26-2749 Education building 3 classes at Sharess school Hajjah B

98-26-3961 Education Construction & Furnishing of3 classes in ALqodida/ Middle OF Moustaba/ Moustaba Hajjah

98-26-4821 Education Construction&Furnishing 6 classrooms in Bani Wahan/ Bani Mahddi/Alsharff/ Hajj Hajjah

98-16-37 Education Construction of A l-zerai school Hodeidah

98-16-38 Education Constr. Of Al - Ghailien school Hodeidah A

98-17-9 Education Const. And furnishing of AL MURSHIDDIA school Hodeidah

98-71-6 Education Construct and Furnishing 6 classrooms in Al-Munira Hodeidah A

97-50-419 Education Completion $ add classrooms to Al-Maghareba & Al-Shakhs schools Ibb

98-26-2600 Education building 6 classes at Belqees school-Thari Ibb

98-26-79 Education Construction and furnishing of 3 classrooms in Al Ganad school Al Sayani Ibb Ibb

98-26-513 Education Constructing 6 class rooms for female - Alazibah Lahj B

98-26-518 Education Constructing new school for female - Khadawera Lahj B

98-17-10 Education Const. And furnishing of AL WAHDA school Maareb

98-18-40 Education Al-Zahra School for girls Sa'adah

98-26-734 Education building 4 classes at Kaamla school Sa'adah

98-26-1812 Education Construction & furnishing of 3 classrooms at Raboa Seham Sana'a

98-17-23 Education Construction and furnishing of MAJAB school Shabwah

98-16-44 Education Completion $ Furnishing of Abi Thar School Taiz

98-26-1771 Education Constructing 8 class rooms for Akous school Taiz



98-26-495 Education Rehabilitation & upgrading Annour school – Alahyook Taiz

98-30-26 Education Rehabilitation of Al-Raha School-Bany Himir- Makbana Taiz

97-15-4 Health Rahoob Health Center Project Al-Jawf

98-67-20 Health Restoration and preperation the primary health center in Qeshen Al-Mahrah

98-67-38 Health Restoration and preperation the primary health center in Saihout . Al-Mahrah

97-50-484 Health Construction & Equiping Health Unit - Al-Hegrh Amran

98-15-34 Health BAIT HBA HEALTH UNIT PROJECT Amran

98-26-1912 Health construction and rehabilitation of health care unit/ Jawat Dhari/ Shaharah/ Haja Amran B

98-26-389 Health Construction & Equiping Health Unit - Habah & Bait rdas Amran

98-26-1140 Health construction and rehabilitation of health care unit/ Bani Hatem/Dhawran A'anes/ Dhamar A

98-26-2413 Health construction and rehabilitation of heallth care unit/ Beit Al-Badani/Wasab Al-Sa Dhamar

98-50-26 Health Renovation and rehabilitation of health care center/Kebbah/Wasab Al-Safel/Dhama Dhamar

98-67-30 Health Restoration and preperation the primary health unit in Al- Safal Hadhramout

98-26-4749 Health Construction and rehabilitation of health care unit/ Juma'at Bani Sawi/ Al-Qafr/ Ibb

98-26-83 Health construction and rehabilitation of health care unit/ Al-Qweizan/ Dhi Sufal/ Ibb Ibb

97-15-3 Health AL-HASKI PRIMARY HEALTH CARE UNIT Lahj B

98-15-30 Health Equipping the mother & chidlhood section , out patient section Al- Habilane Lahj

98-15-33 Health Equipping the mother & childhood section out p. atient section at Al- Had . Lahj

97-50-483 Health Gawadeh Health Center Sana'a Capital

98-15-19 Health MANAKHA PRIMARY H. CARE UNIT Sana'a Capital

98-15-37 Health Equipping Bani-Yousef Health Center Sana'a Capital

98-26-3167 Health Hadaran Primary Health Care Unit Sana'a Capital

98-26-1436 Health CONSTRUCT & FURNISH HEALTH UNIT/ Adood/Saber Almawadem/Taiz Taiz

21-20-167 Microfinance Saving and Credit Program- Aden Aden

21-20-360 Microfinance DAR Micro finance program Aden

99-26-41 Microfinance Hadhramout Credit and Savings Scheme Hadhramout

21-20-11 Microfinance credit and saving program- stage 3 Hodeidah



21-20-396 Microfinance Bit Al-fakeeh program for saving and loans Hodeidah

98-3-5 Microfinance Income Generating and Animal Raising- Marawe'ah Hodeidah

98-3-6 Microfinance Micro Credit Program- Hodiedah Hodeidah

21-20-203 Microfinance Beekeeping and Honey Production / Odain / Ibb-PhaseII Ibb

22-20-110 Microfinance Project for establishing Microfinance Programs (Dhamar, Ib and Taiz city) Ibb

98-3-2 Microfinance Beekeeping and Honey Production / Odain / Ibb Ibb

21-20-265 Microfinance Sana,as micro finance program Sana'a Capital

98-26-2199 Roads Protection of the road project Al Aqabah - Khab (Khab Washa'af - Al Jawf) Al-Jawf A

98-26-1426 Roads Al Shatbah-Al Hait Road Project (Dhibin - Amran) Amran

98-26-2335 Roads Mareh-AlMarwan-AlWa'ary(Duran-Dhmar) Dhamar

98-26-2467 Roads Dubbah-Bani Jaber(magreb ans-damar)road Dhamar C

99-20-546 Roads Naqil Bani-Ma'anis road (Wassab AlSafil-Dhamar) Dhamar

99-20-547 Roads Bani Hotam Road - Wosab – Damar Dhamar

98-26-4606 Roads Jabal Haram-Alshahel Road Project (Al Shahel - Hajjah) Hajjah

20-20-448 Roads Beer Alaroos-Al Ja'ashani Road Project Lahj

99-104-40 Roads Al-Watadah - Al-Ashakel (Bedbedah - Mareb) Maareb

21-104-635 Roads Bab Arid-- Almadab -- Algazy Road / almagareb alelya / manakah Sana'a

98-26-4546 Roads Wadi Dajajah-Arwah Upgrading & Maintenance Road Project Sana'a

20-20-624 Roads Naqil Al A'adhabea (Shara'ab Al Salam - Taiz) Taiz

98-26-2806 Roads Jabal Henwab (Demnah-Khadeer-Taiz) Taiz

99-92-169 Roads Al Salaf Road Project (Al Mawaset - Same'a - Taiz) Taiz

98-18-30 Water Al-Kaima Waterand School project Abyan B

20-145-5 Water Saihout & Rakout Water- Al- Mahra Al-Mahrah

20-126-962 Water A tank for harvesting rain water in Waref village-Thola-Amran Amran A

98-13-1 Water Watar Cistern Completion Works Amran B

98-26-1146 Water Constructing a water harvesting reservoir for Alhaziz villages-Wadea'ah- Khamer- Amran

98-26-1171 Water Completion of Water Supply Project in Al Balhusain-Khamer/Sana'a Amran B



98-67-14 Water Expand Al- Shamria Carif Hadhramout

97-13-5 Water Beni Zohier Water Supply Project Ibb

98-13-17 Water Water supply & sanitation Project of Damaran Ibb

98-18-14 Water Al-Ramadi Water Cistern Ibb

98-18-18 Water Water Cistern at Al-Mizhana Ibb B

98-18-41 Water Water Supply Sytem for Jabal Alhibaly-Al-Saddah/Ibb Ibb

98-18-9 Water Shalef water cistern mantainance project Ibb A

98-18-39 Water Al-Mislabah water cistern project Sa'adah A

20-20-711 Water Bait -merran water harvesting project (The completion & rehabilitation of Hamada Sana'a Capital

98-13-4 Water Al-Safiah Water Supply Project Taiz

98-18-8 Water Baher Al-Asfal Water Project Taiz B

98-26-1503 Water Warazan -Al-Raheda Water Supply project-Khadir/Taiz Taiz

98-26-2129 Water Construction of a small dam-wadi gaheb(altaher)-hairam qmaerah-mawiah-Taiz Taiz

A: Project site out of enumeration area; cluster taken out from impact analysis

B: Enumeration areas with several non-beneficiary households; cluster taken out from impact analysis

C: Cluster reclassified to current "Survey Type" after field work



Annex B: List of Projects for the Qualitative Survey

Project Number Project Name District Governorate Education Projects 98-017-0023 Mojib School Nesab Shabwah 98-071-0006 Construct and furnish 6 classrooms in Al Muneerah Al Muneerah Al Hodeidah 98-016-0037 Construction of Al Zerai school Baraa Al Hodeidah 98-018-0040 Al Zahra school for girls Majz Saadah Health Projects 98-015-0030 Equipping the MCH Section and OPD, Al Habilane Radfan Lahj 98-026-1436 Construction and Furnish Health Unit, Adood Saber Al Mawdem Taiz 98-067-0020 Al Gashen Health Center Renovating and Furnishing Gashen Al Mahra 97-050—484 Construction and Equipping Health Center Unit Al Hegrh Thilaa Amran Water Projects 98-026-1503 Warazan Al Raheda Water Supply Project Khadeer Taiz 98-018-0014 Berkat (Cistern) Al Ramady Water Project Al Udain Ibb 98-013-0004 Al Safiah Water Supply Project – Al Shamaayateen Al Shamaayateen Taiz 20-145-0005 Sayhoot Water Project Sayhoot Al Mahra Road Projects 20-020-0448 Beir Al Aros road project Al Moflehi Lahj 98-026-2806 Jabal Henwab Road Project Khader Taiz Micro Finance Projects 98-003-0006 Developing the Income Generating Activities for the city of al Hodeidah Al Hodeidah Al Hodeidah 21-020-0011 Credit and saving program - Hais Hais Al Hodeidah 98-003-0005 Income generating and animal raising Marawe’ah Al Hodeidah 21-020-0360 Dar Saad Microfinance program Dar Saad Aden Environment Projects 98-062-0001 Assad Sewerage Network Project Al Almanah Sana’a City 99-073-0005 Al Memdarah Sewerage Network Shaikh Othman Aden 99-095-0005 Sheéb Salman and Wadi Al Muassel Sewage Network Al Taizia Taiz Special Needs Groups Projects 99-020-002 Incorporating deaf and mute children into basic education Dhamar Dhamar 99-020-0698 Support for the Rehabilitation of Handicapped Association Al Mansurah Al Mansurah 21-020-0115 Supporting Amer & Akbi Charitable Association Al Amanah Sana’a City Training Projects 99-020-0208 Training Course in Agricultural marketing Several Several 21-020-0277 Training Program in marketing for NGOs Al Amanah Sana’a City 22-095-0002 Training Course for Consultants and Contractors Taiz Taiz Institutional Support Projects 21-020-0105 Support Al-Bushra Women Charitable Societies in Al Qabbel Villages Al Amanah Sanaá City 20-020-0627 Supporting the Capacities of Al Amal Women Association in Al Maquirah Village Sanhan Sana’a 99-026-0060 Supporting Al Oulfa Women Charitable Association – Al Qabel Village Bani Al Harith Sana’a



Location of the sites for the qualitative survey (Annex B)

Education Health Water Roads Micro finance Environment

Special needs Groups Training Institutional Support


ESA Consultores International, December 2003

Annex G: General and Socio-Economic Characteristics of the Survey Population

This section summarizes the socio-economic characteristics of the sampled populations in terms of education achievements, employment status, levels of income and poverty, characteristics of dwellings, and access to public and community services. Those data provide a useful background for the understanding of the effects of the SFD interventions and the factors underlying those effects. There also serve to document possible differences between the 1999 baseline and the 2003 ex-post groups, differences that justify the need for using multivariate analysis techniques in the estimation of the program’s impact indicators.

Educational status

In education, the SFD beneficiary communities observed in the 2003 ex-post survey reported higher enrolment, overall, and more students at higher schooling levels, compared with the 1999 sample. The number of persons aged six and more who never enrolled is 55% in the 2003 dataset, compared with 45% in the 1999 dataset; while the proportion enrolled at present is, respectively, 33% and 29%. The 1999 sample reports lower enrollment in higher levels, with 13.2% and 2.3%, respectively in secondary and post-secondary levels compared with 17.4% and 6.2% respectively in the 2003 ex-post sample. The proportion of students enrolled in government managed schools is overwhelming in both cases (98.7% and 99.5%) (see Table G.1).

Table G.1 - School enrolment of sample population Population 6 yrs or more Ex-post

(2003) Baseline (1999)

% who never enrolled in school 45.3 55.0 % currently enrolled 33.1 29.3 Level of enrollment (for those enrolled) Primary/elementary/basic Secondary/vocational training Post-secondary

76.4 17.4

6.2

84.5 13.2

2.3 % enrolled in government institution (for those enrolled)

98.7

99.5

N (population 6 years and above) 11,496 12,862

The final result of the education process is shown in Table G.2. In the baseline dataset, 14.1% of those over ten years old had completed primary education; in the ex-post sample this rises to 18.1%. This difference is statistically significant (p<0.01; CIdiff 95%: 2.6-5.4). The gender differences in educational achievement are striking in both groups (table G.3). Chapter 9 analyses to what extent these differences are attributable to the SFD’s intervention.

Table G.2 - Educational achievements of the sample population Highest educational achievement in persons 10 yrs old and more

2003 Ex-Post

1999 Baseline

Illiterate 46.0 52.9 Know how to read and write 35.8 32.7 Primary/elementary/basic 9.5 9.0 Secondary + 8.6 5.1 N 9,725 10,538



Table G.3 - Gender differences in educational achievements 2003 Ex-post 1999 Baseline Male Female Male Female % illiterate 24.9 66.0 32.8 71.6 % beyond basic education 14.8 3.6 9.8 1.8

Employment status

Thirty three percent of the population over 10 years old in the ex-post group are employed and did perform some work over the week previous to the survey. The corresponding figure in the baseline sample is 44.6%. Among those self-declared employed, the distribution by employment status is shown in Table G.4 below. The difference may be due to the much higher proportion of persons declaring home-based, voluntary work in the baseline group (48% versus 29%). On the other hand, the number of employed or self employed persons increased over time from 30 to 50%, and even in absolute numbers. Once again, gender differences on labor market status are obvious and similar in both datasets (table G.5)

Table G.4 - Employment status of sample population Employment status Ex-post Baseline Employee 32.7 26.5 Self-employed 35.4 23.3 Employer 3.2 2.3 With family, no salary; trainee 28.8 47.7 3,214 4,697

Table G.5 - Gender differences in employment status 2003 Ex-post 1999 Baseline Type of employment

Male Female Male Female Employee 41.8 8.4 40.3 5.2 Self employed 42.2 16.8 32.1 23.3 Employer 4.1 0.8 3.2 2.3 Work within family/no salary 11.5 73.1 24.2 84.1

N 2,331 870 2,843 1,854

In the ex-post group, 84.9% of employed persons are working in the private sector; the government sector represents 14.4%. The precariousness of the employment situation is still important, with only 11% of the population over 10 years old working for a salary (cash salary for 98%), and only 62.2% of the self-declared employed persons having a permanent job.

Another-labor related perspective of the Yemeni population is found in Table G.6, showing the relationship of household members over 10 years of age with the workforce. It should be noted that 22% of the housewives in the ex-post group and 43% in the baseline group are also salaried employees. Similarly, 6% and 16% respectively of the students are also working for a salary.

Table G.6 - Relationship of sample population (over 10 years old) with the workforce Relationship with workforce Ex-post Baseline Working 25.8 30.4 Working housewife 5.5 10.7 Working student 1.6 4.1 Unemployed 2.1 2.9 Housewife 19.8 14.1 Student 24.8 21.4



Does not need to work 1.4 2.1 Disabled 5.2 4.3 Others 13.7 10.1 N 9,704 10,530

However, 46 to 49% of men are categorized as “working” while only 6% of the women in the ex-post group (13% in 1999) are in this situation; on the other hand, the number of “exclusive” housewives has increased from 28 to 39%. 11% of the women are “working housewives”, 21% were in 1999. 34 and 30% of the men are students, against 16 and 13% of the women. These differences in labor market conditions between the two surveyed populations, are not likely to be causally related to the SFD’s intervention.

Table G.7: Relationship of population over 10 years with labor force by sex

2003 Ex-post 1999 Baseline Male Female Male Female

Employed 46.1 6.3 48.5 12.8 Working housewife 0.0 10.7 0.1 21.1 Working student 3.0 0.3 6.7 1.5 Housewife 0.2 38.6 0.0 27.8 Student 33.6 16.4 29.7 13.3 N 4,743 4,932 5,183 5,347

Assets and poverty levels

Data were not available for comparing income or expenditures in the sampled populations. However, the level of well-being can be proxied by asset holdings (vehicles, electro-domestic equipment, etc.). Households in the ex-post group living in dwellings without electricity have on average 3.4 of the listed assets; compared with 2.4 items for such households in the baseline group. For households with an electricity supply, the corresponding numbers are 4.6 and 3.2 respectively.

Characteristics of dwellings

The main physical characteristics of dwellings are very similar in both groups: 90% of the households live in a separate house; the house is actually owned in more than 91% of the cases (88% in the baseline group), a relatively high percentage. Half of them have cut stone as the main wall material, with a majority (60%) having wood and mud roof and one half have a sand floor. The average number of rooms is 3.1/3.0; that of bedrooms 2.3/2.2 .

Table G.8 - Selected characteristics of dwellings Proportion of households Ex-post Baseline Main wall material: cut stone 46.8 43.5 Main roof material: wood + mud 59.6 55.9 Main floor material: cement 36.3 42.3 Own the house 91.4 88.1 Average number of room 3.1 3.0 Average number of bedrooms 2.3 2.2 N 1,789 2,051



The utility situation (Table G.9) shows that households in the ex-post group have a higher proportion of in-house water connections (33% versus 25%), possibly a result of the SFD interventions. Flush toilets are still infrequent; most households have a latrine within the dwelling, but 44% and 48% of the households respectively have toilet facilities outside of their dwelling or do not have facilities at all. Less than half of the households use water and soap to wash hands after using the toilet, but this proportion is higher in the ex post sample. Gas and kerosene still represent the major source of lighting and major cooking fuel. It is interesting to note that the responsibility for fetching water (when it has to be obtained from outside the dwelling) and wood is very much that of women (74-77% and 89% respectively).

Table G.9 – Household access to basic services Utilities Ex-post Baseline Source of water: Network (publ., priv., coop.) Well (public or private)

33.3 26.0

24.9 40.1

For households with water source outside: Average time to fetch water In dry season: In rainy season: Responsibility of women Way of fetching water: by foot

55mn

74.0 64.7

59mn 39mn 77.3 56.7

Human waste disposal: Flush toilet Latrine inside dwelling

5.5

50.4

6.1

46.0 Family uses soap after using the toilet 44.1 32.2 Source of lighting: Electricity Kerosene

37.4 47.5

31.8 52.6

Cooking fuel: Wood Gas

46.3 49.3

45.1 51.6

N 1,867 2,051

Distance to public and community services

An important aspect of community diagnosis is that of access to community services. Access is influenced by the type of residence areas and by the network of communications to these areas. 82.3% of the ex-post households live in villages or sub-villages (hamlets). The main road leading to the village is, in 72.7% of the cases, either a paved road in bad conditions, a mud road or no road at all. This population can thus be characterized as a mostly rural population, with difficult physical access.

Household respondents were asked to point out whether there were public services in the area where they live, how they rated the distance from their home to those services and the time needed to travel there. The results are presented in Table G.10 and Figures G.1 and G.2. The table shows that the probability of living in an area with a school (primary or secondary) or a PHC Center is higher in 2003 than in 1999. However, the walking distance to a number of other public services, such as pharmacy, private clinic, hospital, police station or post office, is greater in the ex-post sample; this could the result of a progressive concentration of such services in more populated areas or could be attributed to sampling errors.



Table G.10 - Presence of public and community services in survey area 2003 Ex-Post 1999 Baseline % present

in living area

Distance in mn

% present in living

area

Distance in mn

Mosque 97.4 11.0 n-a n-a Basic school 90.4 24.8 81.6 28.3 Grocery store 85.9 23.0 n-a n-a Secondary school 59.8 52.6 49.1 53.2 Primary health care center 48.5 68.8 29.4 79.0 Public telephone 34.1 80.7 30.3 75.3 Koranic school 32.5 96.6 23.8 91.0 Pharmacy 31.9 85.5 33.9 68.3 Private clinic 27.1 97.1 27.3 85.1 Public transportation 25.1 100.9 22.5 91.5 Police station 23.6 103.0 24.7 80.0 Hospital 18.0 115.2 20.7 103.1 Mother and Child Health center 17.9 119.0 18.4 109.1 Cooperative association 14.1 123.0 n-a n-a Post Office 14.1 125.5 15.8 110.1 Bank 10.1 136.5 n-a n-a Number of households 1,866 2,051

Figures in Bold and Italics indicate items for which the value in the ex-post group is significantly different from that in the baseline group (Cldiff 95% does not include 0).

Figure G.1 is a graphic representation of the differences in time needed to reach the services between groups, also showing the relative distance between different types of services.

Figure G.1 - Distance (in minutes) from public and community services

Figure G.2, showing the qualitative assessment of distance from services (very near, far, very far) is reported for the ex-post group only; the shape of the graph for the baseline group is similar. The overall picture and differences in access are reflected in this measure too: in the ex-post

0

30

60

90

120

150

180Mosque

Basic school

Grocery store

Secundary school

PHC center

Public Telephone

Koranic school

Pharmacy

Private clinic

Public transportation

Police station

Hospital

Post Office

Bank

Ex-post Baseline



group, 31.2% on average of the public and community services were deemed very near, 22.1% were categorized as far and 46.7 as very far; similar figures for the baseline group are 22.4, 35.0 and 41.7% respectively.

Figure G.2 - Perceived distance to public and community services

��

��

��

��

��

��

��

��

��

0% 20% 40% 60% 80% 100%

MosqueGrocery StoreBasic School

Secondary SchoolPHC Center

Koranic SchoolPublic telephone

PharmacyPublic Transport

Private ClinicPolice Station

HospitalMCH Center

Coop. Assoc.Post Office

Bank

Very Near

�� Far Very far

The mix of public and private sector services can be described as follows in both groups:

- post office, bank, police stations, primary and secondary schools, scientific institutes, hospitals, PHC and MCH centers are mostly – and almost exclusively – public services

- mosques (95%) and koranic schools (80%) are also considered as providing public services

- grocery stores and private clinics by definition belong to the private sector - telephone is provided publicly in two thirds to three quarters of the cases, while

“public” transportation relies for 75% on the private sector.

yemen social fund for development 2003 impact evaluation ... · and recall questions in the project...

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