Abstract

The Education Quality Improvement Programme in Tanzania (EQUIP-T) is a large, four-year Department for International Development (DFID) funded programme. It targets some of the most educationally disadvantaged regions in Tanzania to increase the quality of primary education and improve pupil learning outcomes, in particular for girls. EQUIP-T covers seven regions in Tanzania and has five components: 1) enhanced professional capacity and performance of teachers; 2) enhanced school leadership and management skills; 3) strengthened systems that support the district and regional management of education; 4) strengthened community participation and demand for accountability; and 5) strengthened learning and dissemination of results. Together, changes in these five outputs are intended to reduce constraints on pupil learning and thereby contribute to better-quality education (outcome) and ultimately improved pupil learning (impact).

The independent impact evaluation (IE) of EQUIP-T conducted by Oxford Policy Management Ltd (OPM) is a four-year study funded by DFID. It covers five of the seven programme regions (the two regions that will join EQUIP-T in a later phase are not included) and the first four EQUIP-T components (see above). The IE uses a mixed methods approach where qualitative and quantitative methods are integrated. The baseline approach consists of three main parts to allow the IE to: 1) capture the situation prior to the start of EQUIP-T so that changes can be measured during the follow-up data collection rounds; impact attributable to the programme assessed and mechanisms for programme impact explored; 2) develop an expanded programme theory of change to help inform possible programme adjustments; and 3) provide an assessment of the education situation in some of the most educationally disadvantaged regions in Tanzania to the Government and other education stakeholders.

This approach includes:

• Quantitative survey of 100 government primary schools in 17 programme treatment districts and 100 schools in eight control districts in 2014, 2016 and 2018 covering:
• Standard three pupils
• Teachers who teach standards 1-3 Kiswahili and/or mathematics;
• Teachers who teach standards 4-7 mathematics;
• Head teachers; and

• Standard two lesson observations in Kiswahili and mathematics.

• Qualitative fieldwork in nine research sites that overlap with a sub-set of the quantitative survey schools, in 2014, 2016 and 2018, consisting of key informant interviews (KIIs) and focus group discussions (FGDs) with head teachers, teachers, pupils, parents, school committee (SC) members, region, district and ward education officials and EQUIP-T programme staff; and

• A mapping of causal mechanisms, and assessment of the strength of assumptions underpinning the programme theory of change using qualitative and quantitative IE baseline data as well as national and international evidence.

The data and documentation contained in the World Bank Microdata Catalog are those from the EQUIP-T IE quantitative baseline survey conducted in 2014. For information on the qualitative research findings see OPM. 2015b. EQUIP-Tanzania Impact Evaluation. Final Baseline Technical Report, Volume II: Methods and Technical Annexes.

Geographic coverage

The survey is representative of the 17 EQUIP-T programme treatment districts. The survey is NOT representative of the eight control districts. For more details see the section on Representativeness and OPM. 2015. EQUIP-Tanzania Impact Evaluation: Final Baseline Technical Report, Volume I: Results and Discussion and OPM. 2015. EQUIP-Tanzania Impact Evaluation. Final Baseline Technical Report, Volume II: Methods and Technical Annexes.

The 17 treatment districts are:

-Dodoma Region: Bahi DC, Chamwino DC, Kongwa DC, Mpwapwa DC -Kigoma Region: Kakonko DC, Kibondo DC -Shinyanga Region: Kishapu DC, Shinyanga DC -Simiyu Region: Bariadi DC, Bariadi TC, Itilima DC, Maswa DC, Meatu DC -Tabora Region: Igunga DC, Nzega DC, Sikonge DC, Uyui DC

The 8 control districts are:

-Arusha Region: Ngorongoro DC -Mwanza Region: Misungwi DC -Pwani Region: Rufiji DC
-Rukwa Region: Nkasi DC -Ruvuma Region: Tunduru DC -Singida Region: Ikungi DC, Singida DC -Tanga Region: Kilindi DC

Analysis unit

• School
• Teacher
• Pupil
• Lesson (not sampled)

Kind of data

Sample survey data [ssd]

Sampling procedure

Because the EQUIP-T regions and districts were purposively selected (see OPM. 2015. EQUIP-Tanzania Impact Evaluation: Final Baseline Technical Report, Volume I: Results and Discussion.), the IE sampling strategy used propensity score matching (PSM) to: (i) match eligible control districts to the pre-selected and eligible EQUIP-T districts (see below), and (ii) match schools from the control districts to a sample of randomly sampled treatment schools in the treatment districts. The same schools will be surveyed for each round of the IE (panel of schools) and standard 3 pupils will be interviewed at each round of the survey (no pupil panel).

Identifying districts eligible for matching

Eligible control and treatment districts were those not participating in any other education programme or project that may confound the measurement of EQUIP-T impact. To generate the list of eligible control and treatment districts, all districts that are contaminated because of other education programmes or projects or may be affected by programme spill-over were excluded as follows:

-All districts located in Lindi and Mara regions as these are part of the EQUIP-T programme, but the impact evaluation does not cover these two regions; -Districts that will receive partial EQUIP-T programme treatment or will be subject to potential EQUIP-T programme spill-overs; -Districts that are receiving other education programmes/projects that aim to influence the same outcomes as the EQUIP-T programme and would confound measurement of EQUIP-T impact; -Districts that were part of pre-test 1 (two districts); and -Districts that were part of pre-test 2 (one district).

Sampling frame

To be able to select an appropriate sample of pupils and teachers within schools and districts, the sampling frame consisted of information at three levels:

-District level; -School level; and -Within school level.

The sampling frame data at the district and school levels was compiled from the following sources: the 2002 and 2012 Tanzania Population Censuses, Education Management Information System (EMIS) data from the Ministry of Education and Vocational Training (MoEVT) and the Prime Minister's Office for Regional and Local Government (PMO-RALG), and the UWEZO 2011 student learning assessment survey. For within school level sampling, the frames were constructed upon arrival at the selected schools and was used to sample pupils and teachers on the day of the school visit.

Sampling stages

Stage 1: Selection of control districts

Because the treatment districts were known, the first step was to find sufficiently similar control districts that could serve as the counterfactual. PSM was used to match eligible control districts to the pre-selected, eligible treatment districts using the following matching variables: Population density, proportion of male headed households, household size, number of children per household, proportion of households that speak an ethnic language at home, and district level averages for household assets, infrastructure, education spending, parental education, school remoteness, pupil learning levels and pupil drop out.

Stage 2: Selection of treatment schools

In the second stage, schools in the treatment districts were selected using stratified systematic random sampling. The schools were selected using a probability proportional to size approach, where the measure of school size was the standard two enrolment of pupils. This means that schools with more pupils had a higher probability of being selected into the sample. To obtain a representative sample of programme treatment schools, the sample was implicitly stratified along four dimensions:

-Districts; -PSLE scores for Kiswahili; -PSLE scores for mathematics; and -Total number of teachers per school.

Stage 3: Selection of control schools

As in stage one, a non-random PSM approach was used to match eligible control schools to the sample of treatment schools. The matching variables were similar to the ones used as stratification criteria: Standard two enrolment, PSLE scores for Kiswahili and mathematics, and the total number of teachers per school.

The midline and endline surveys will be conducted for the same schools as the baseline survey (a panel of schools). However, the IE will not have a panel of pupils as a pupil only attends standard three once (unless repeating). Thus, the IE will have a repeated cross-section of pupils in a panel of schools.

Stage 4: Selection of pupils and teachers within

Since there was no dedicated Population Based Survey to generate the baseline values, this analysis uses two distinct datasets: (a) Cambodia Socioeconomic Survey (CSES, 2009); (b) Cambodia Demographic and Health Survey (CDHS, 2010). Data was extrapolated and created using the following methodology: (a) Cambodia Socioeconomic Survey (CSES): the Cambodia Socioeconomic Survey (CSES, 2009) was conducted by the National Institute of Statistics (NIS) of the Ministry of Planning (MOP) of Cambodia. The CSES 2009 was a nationally representative survey with a sample of 12,000 households within 720 sampling units (villages), which were divided into 12 monthly samples of 1000 households in 60 villages. The sampling design provided for estimates for urban and rural areas and the Municipality of Phnom Penh. The 2008 Population Census of Cambodia was used as sampling frame (NIS, 2010). The sampling design in the CSES 2009 survey is a threestage design. In stage one, a sample of villages is selected using systematic sampling. In stage two, an Enumeration Area (EA) is selected from each village selected in stage one using Simple Random Sampling (SRS). Finally, in stage three, a sample of households is selected from each EA by systematic sampling. For the generation of the relevant Baseline indicators we used the sample for the four FtF provinces, with a total of 2,453 households (2,096 in rural and 357 in urban areas). The CSES collects a wide range of data related to household living conditions, income generation and expenditures. (b) Demographic and Health Survey (CDHS): The Cambodia Demographic and Health Survey (CDHS, 2010) is a nationally representative sample survey of 18,754 women and 8,239 men age 1549. The 2010 CDHS is the third comprehensive survey conducted in Cambodia as part of the worldwide MEASURE DHS project. The primary purpose of the CDHS is to provide policymakers and planners with up-to-date, reliable data on fertility; family planning; infant, child, and maternal mortality; maternal and child health; nutrition; malaria; knowledge of HIV/AIDS, and women’s status. The sampling frame used for the 2010 CDHS was the complete list of all villages enumerated in the 2008 Cambodia General Population Census provided by the NIS. The survey was based on a stratified sample selected in two stages. In the first stage, 611 EAs were selected with probability proportional to size. The household listings provided the frame from which households were selected in the second stage. To ensure a sample size large enough to calculate reliable estimates for each study domain, it was necessary to restrict the total number of households selected to 24 in each urban EA and 28 in each rural EA. For the purposes of generating the Cambodia Feed the Future Indicators, we use the CDHS 2010 survey sample for the four provinces that make the Zone of Influence, in which 1,814 were respondents of all nonpregnant women in reproductive age (1549 years); 1,796 women in reproductive age with anemia measurement (1549 years); 78 children 05 months; 736 children 059 months; 634 children 659 months with hemoglobin measurement.

Abstract

These data are the baseline data for a randomized experiment conducted in high schools in Ecuador. The intervention is an online education course that covers entrepreneurial soft skills, scientific methods, and interviews with role models. This course is taken by students during class time, under teacher supervision. We work with 14-18-year-old students (about 15,000 students) in 126 schools. We randomly assign schools either to treatment (and receiving the entrepreneurship and science content online), or placebo-control (receiving a placebo treatment of online courses from standard curricula) groups. Within the treatment group, we randomize at the grade-level the type of entrepreneurship curricula, and then randomize the order of entrepreneurship and science courses to measure the short-term effects of each component and to mitigate order effects. In addition, we cross-randomize schools to a role model treatment of interviews with successful scientists and entrepreneurs. In addition, we provide information about career options.

The baseline survey was administrated through an online learning platform in school.

Geographic coverage

Municipality of Quito and Educational Zone 2

Educational Zone 2 has its administrative headquarters in the city of Tena, Napo province. Its covers provinces of Napo, Orellana and Pichincha, 8 districts (15D01, 22D01, 17D10, 17D11, 15D02, 17D12, 22D02, 22D03), its 16 cantons and 68 parishes. It has an area of 39,542.58 km². The educational zone 2 spread from east to the western border of the Ecuador. We cover students of age 14-18 in schools that has sufficient access to the internet and classes of the K10, K11, or K12. We included the municipality of Quito in the study to enrich the coverage of program by having large (capital) city in the sample.

Analysis unit

Student

Kind of data

Sample survey data [ssd]

Sampling procedure

All students in selected schools who were present in classes filled out the baseline questionnaire

Mode of data collection

Internet [int]

Research instrument

The survey consists of a multi-topic questionnaire administered to the students through online learning platform in school during normal educational hours. We collect the following information: 1. Subject specific knowledge tests. Spanish, English, Statistics. 2. Career intentions, preferences, beliefs, expectations, and attitudes. STEM and entrepreneurial intentions, preferences, beliefs, expectations, and attitudes. 3. Psychological characteristics. Personal Initiative, Negotiations, General Cognition (General Self-Efficacy, Youth Self-Efficacy, Perceived Subsidiary Self-Efficacy Scale, Self-Regulatory Focus, Short Grit Scale), Entrepreneurial Cognition (Business Self-Efficacy, Identifying Opportunities, Business Attitudes, Social Entrepreneurship Standards). 4. Other background information. Socioeconomic level, language spoken, risk and time preferences, trust level, parents background, big-five personality traits of student.

This dataset was compiled for the Regional Seabed Monitoring Plan (RSMP) baseline assessment reported in Cooper & Barry (2017). The dataset comprises of 33,198 macrofaunal samples (83% with associated data on sediment particle size composition) covering large parts of the UK continental shelf. Whilst most samples come from existing datasets, also included are 2,500 new samples collected specifically for the purpose of this study. These new samples were collected during 2014-2016 from the main English aggregate dredging regions (Humber, Anglian, Thames, Eastern English Channel and South Coast) and at four individual, isolated extraction sites where the RSMP methodology is also being adopted (e.g. Area 457, North-West dredging region; Area 392, North-West dredging region; Area 376, Bristol Channel dredging region; Goodwin Sands, English Channel).

This dataset contains baseline Early Grade Reading Assessment (EGRA) data conducted under the USAID/Zambia Education Data activity between November – December 2018. Over 15,000 Grade 2 learners were assessed in one of the seven Government of the Republic of Zambia (GRZ) languages of Instruction (LoI) (Chitonga, Cinyanja, Icibemba, Kiikaonde, Lunda, Luvale or Silozi) as well as in English. The EGRA was conducted in five target provinces (Eastern, Muchinga, North-Western, Southern and Western Provinces). The purpose of the 2018 baseline EGRA is to establish a baseline level from which changes in Grade 2 learners’ performance in the core reading skills can be tracked over time. Each assessment contained seven subtasks, which included; (1) listening comprehension in both the LoI and in English; (2) letter sound identification in the LoI; (3) syllable sound identification in the LoI; (4) non-word reading in the LoI; (5) oral reading fluency in the LoI; (6) reading comprehension in the LoI and; (7) English vocabulary. In addition, assessors also administered a Snapshot of School Management and Effectiveness (SSME), which included head teacher, teacher, and learner questionnaires, along with a school inventory, to establish school characteristics and learner demographics in the sampled schools. The 2018 Baseline EGRA used a stratified sampling methodology to randomly select a representative sample of 816 schools from the five target provinces. Of the 816 schools, 630 were Government of the Republic of Zambia (GRZ)-run primary schools and 186 were community-run schools.

Abstract

Mathematica is evaluating the Agriculture Development Project of the MCC Burkina Faso Compact. This evaluation has six components: (1) the evaluation of the integration of ADP activities, (2) the Di perimeter ERR and Di PAP evaluation, (3) Di Lottery RCT, (4) the Sourou O&M evaluation, (5) the IWRM evaluation, (6) and the farmer training evaluation. The Di Lottery evaluation will consist of an impact evaluation in which we will compare outcomes for the treatment group (lottery winners) with outcomes for the control group (eligible candidates who did not obtain a plot of land through the lottery). The remaining evaluations will be performance evaluations that will include document review, interviews, focus groups, and, when possible, pre-post analysis. In the case of pre-post analysis, the data for the baseline is drawn from surveys implemented by previous evaluators. Our data collection will strive to ensure representation of women in our qualitative and quantitative samples, and we will disaggregate the analysis of beneficiary outcomes and perceptions where possible.

Geographic coverage

Sourou Valley. Comoé Basin. Control group for the Di Lottery is also in the entire Boucle du Mouhoun Region.

Analysis unit

Individuals and households. Cows.

Universe

Quantitative: Di perimeter beneficiaries, Di lottery applicants, Farmer training beneficiaries.

Qualitative: Former and current staff from MCA/APD, staff from Regional directorate of Ministry of Agriculture, staff from Ministry of Water resources, staff from other organizations involved as well as community members.

Kind of data

Sample survey data [ssd]

Sampling procedure

BASELINE DATA COLLECTED BY THE PREVIOUS EVALUATORS

Di PAP baseline survey data: The Di PAP baseline survey is a retrospective baseline survey. The survey was administered by BERD to a representative sample of 500 PAPs (out of roughly 1500) in October 2013 as some PAPs began receiving their new plots on the perimeter. A total of 388 PAPs out of the selected 500 PAPs completed the survey. The survey collected information on household demographics, production and land use outside the perimeter, perspectives on compensation, anticipated land use in the perimeter, household assets, access to credit, revenue, and training received. The survey data were received and are thus being delivered by Mathematica in 16 separate files. The files map to specific sections of the baseline survey with each file at the observational unit level of the information collected. Mathematica used these data for the baseline report.

Di Lottery baseline survey data: The Di Lottery baseline survey was administered in late 2013 by CERFODES to all 2,178 Di lottery applicants who met the lottery eligibility criteria (though not necessarily admitted to the lottery). A total of 2,128 applicants completed the survey. The survey collected data on demographic characteristics, socioeconomic status, agricultural experience, and other background characteristics relevant to the criteria for admission to the Di lottery. These survey data are delivered in a single data file in which the unit of observation is the lottery applicant. Mathematica used these data for the baseline report..

Farmer training baseline household survey data: NORC and CERFODES designed and administered the farmer training baseline household survey which was to provide a baseline for the evaluation of a range of ADP activities. The baseline data were collected in two rounds in parallel with the two agricultural seasons in Burkina Faso. The first round of the baseline data was collected immediately after the 2011 dry season, and the second round was collected immediately after the 2011 rainy season. The survey's targeted sample comprised 1,082 matched pairs of farming households with each pair containing one household from the project's treatment area and the other from the comparison area. The lengthy baseline survey is comprised of seven modules focusing on the following content areas: household, agriculture, animal husbandry, forestry, consumption and credit, food security, and health. The data collected via each module was delivered to Mathematica in multiple data files given that the data collected under each module could have been collected at multiple levels (e.g. household, individual, plot, and crop levels). As such, we are delivering each data file as a unique restricted-use file (roughly 50 files per survey round/season) with each file at the observational unit level of the information collected. Mathematica used a subsample of these data for the baseline report.

Barymetric survey data: The barymetric survey was administered by CERFODES to a subsample of farmer training households in two rounds: baseline in mid-2012 and one-year follow-up in mid-2013. In total, 153 households completed the baseline survey of which 146 completed the follow-up survey. In each round, the survey obtained data on cattle herd size, health, weight, milk production, and other related bovine information from each sampled household. The data for each round were received, and are thus delivered, in three separate files mapping to the three distinct sections of the survey: i) cattle herd characteristics at the household level; ii) cattle weight and other bovine characteristics at the cattle level; and iii) milk production at the cattle level. Mathematica did not use these data in the baseline report.

Supplemental household survey data: Implemented by CERFODES in late-2013, the farmer training supplemental household survey primarily collected information on the training and support farmers in the project's treatment area received from AD10. A short additional section of the survey also collected estimates of 2013 household agricultural production. Of the 1,082 farmer training households in the treatment area, 949 completed the survey. The data were received, and are thus delivered, in two separate files which map to the two sections of the survey: the first section covering training and support at the household level, and the second section covering household production at the crop level. Mathematica did not use these data for the baseline report.

FOLLOW-UP/ENDLINE DATA TO BE COLLECTED BY MATHEMATICA

Di perimeter households: We interviewed a sample of households whose land was expropriated to construct the Di Perimeter and who received land in compensation. These are called PAP household, with PAP standing for persons affected by the project. The sample comprises all households who received only rice plots in compensation, households who received rice and polyculture plots and households with only a female PAP head. For households who received only polyculture plots, we draw a sample proportional to size. In addition we draw samples from non-APs from neighboring communities. Women and youth who received small plots of land as parts of women and youth groups are sampled in a two stage sampling process, whereby first groups are chosen, then individuals in these groups. Note that because the sampling for the interim and final evaluation differs from the baseline it is not possible to link interim and baseline samples.

Di Lottery households: We include all Di lottery households for whom baseline information is available in our survey.

Farmer training households: We include all farmer training households who are part of the CERFODES-NORC baseline survey and who participated in farmer training activities (per the AD10 trainee identification survey).

Qualitative Evaluations: We identified our criteria for selecting participants before fielding the study. Certain key informants were selected purposively, based on their role or experience. For example, we interviewed the staff member who was most knowledgeable regarding each aspect of the implementation, while striving to avoid burdening any one agency. For farmer training participants, we used selection criteria to ensure balance and variation based on factors such as geography, demographic characteristics, and so on. For members of PAP households, we will use our criteria to identify participants through contacts and chose them purposively. The composition of the focus groups took a number of elements into consideration, including people's demographics, experiences with the project, geographic characteristics, and plot size. The local data collection firm handled participant selection, in conjunction with Mathematica.

Mode of data collection

In-person interviews. Barymetric measurements for cows.

Research instrument

Individuals and households.

Cleaning operations

Mathematica will work closely with a local data collection partner to train interviewers and monitor the data collection effort. For example, if the data collection firm uses computer-assisted personal interviewing (CAPI) or Survey Solutions, this would enable us to review the data and conduct consistency checks on an ongoing basis.

Upon receipt of the complete datasets, Mathematica will conduct additional cleaning to correct out of range responses, address item nonresponse and inconsistent patterns, and conduct merges between different datasets if necessary.

Mangrove restoration has a strong potential to enhance the services provided by coastal wetlands on a number of Department of the Interior (DOI) managed lands throughout the southeastern United States of America. Services include storm protection, water quality improvement, and biological carbon sequestration. Forest structural attributes including basal area, tree height, and stem density by species are used to calculate above ground biomass and above ground productivity. Percent cover is used to asses the forest canopy health. The data collected for the soils are: bulk density, percent total Nitrogen, percent total Carbon, and selected samples percent total Phosporus. The forest structure plots were placed in three zones; healthy, transition, and dead, along with a reference zone to compare how these plots change over time with the hydrologic restoration. These are pre-restoration measurements.

Abstract

The Ghana Quality for Preschool Impact Evaluation 2015, Baseline survey (QPIE-BL 2015) was approved by the Strategic Impact Evaluation Fund (SIEF) of the World Bank on August 2015 in the Great Accra Region of Ghana. The official project name is called "Testing and scaling-up supply- and demand-side interventions to improve kindergarten educational quality in Ghana”, known as “Quality Preschool for Ghana (QP4G)”.

The project seeks to increase the quality of preschool education during the two years of universal Kindergarten (KG) in Ghana through intervening in the supply-side (i.e., teacher in-service training) and the demand side (i.e., increasing parental awareness for developmentally appropriate quality early education).

The primary goal of the impact evaluation is to test the efficacy of a potentially scalable (8-day) in-service teacher training to improve the quality of KG teacher practices and interactions with children and to improve children’s development, school readiness and learning in both private and public preschools in the Greater Accra Region of Ghana. Additional goals of this evaluation are: to test the added value of combining a scalable (low-cost) parental awareness intervention with teacher in-service training; to compare implementation challenges in public and private schools; and to examine several important sources of potential heterogeneity of impact, primarily impacts in public vs. private schools.

The current submission is for the Baseline Survey, conducted with 5 types of respondents in two phases - Baseline I and Baseline II. Baseline I consisted of interviews with school head teachers and school proprietors (for private schools) and was conducted in June 2015. Baseline II consisted of collecting the following data: (a) direct assessments of children’s school readiness at school entry, (b) surveys of teacher well-being and demographics, (c) video recordings for classroom observations of teachers (not being submitted), and (d) caregiver surveys. This data collection was conducted from Sep-Nov 2015.

Geographic coverage

Urban and Peri-Urban Districts, Greater Accra Region

Analysis unit

Units of analysis include individuals (head teachers, teachers, children, caregivers) and schools.

Universe

The survey universe is 6 poor districts in the Greater Accra Region. We sampled 240 schools, 108 public (Govt.) schools and 132 private schools. The population of interest is KG teachers and students in Kindergarten (KG) 1 and KG 2 classrooms in these schools, as well as the caregivers of sampled students. It also includes school head teachers and owners/proprietors.

Kind of data

Sample survey data [ssd]

Sampling procedure

This impact evaluation applies a cluster-randomized design. Eligible schools were randomly selected to participate in the study. The eligible population was schools with KG 1 and KG 2 classrooms (the two years of universal preprimary education) in six districts in the Greater Accra Region. In these six districts we have sampled 240 schools; 108 public schools and 132 private schools in total.

The unit of randomization for this randomized control trial (RCT) is schools, whereby eligible schools (stratified by public and private sector schools) are randomly assigned to: (1) in-service teacher-training program only; (2) in-service teacher-training program plus parental awareness program; or (3) control (current standard operating) condition.

The sampling frame for this study was based on data in the Education Management Information System (EMIS) from the Ghana Education Service. This data was verified in a 'school listing exercise' conducted in May 2015.

Sample selection was done in multiple stages as shown in Figure 1. The first stage involved purposive selection of six districts within the region based on two criteria: (a) most disadvantaged (using UNICEF's District League Table scores, out of sixteen total districts); and (b) close proximity to Accra Metropolitan for travel for the training of the KG teachers. The six selected municipals were La Nkwantanang-Madina Municipal, Ga Central Municipal, Ledzokuku-Krowor Municipal, Adentan Municipal, Ga South Municipal and Ga East Municipal.

The second stage involved the selection of public and private schools from each of the selected districts in the Accra region. We found 678 public and private schools (schools with kindergarten) in the EMIS database. Of these 361 schools were sampled randomly (stratified by district and school type) for the school listing exercise, done in May 2015. This was made up of 118 public schools and 243 private schools.

The sampling method used for the school listing exercise was based on two approaches depending on the type of school. For the public schools, the full universe of public schools (i.e., 118) were included in the school listing exercise. However, private schools were randomly sampled using probability proportional to the size of the private schools in each district. Specifically, the private schools were sampled in each district proportionate to the total number of district private schools relative to the total number of private schools. In so doing, one school from the Ga South Municipal was removed and added to Ga Central so that all districts have a number of private schools divisible by three. This approach yielded 122 private schools. Additionally, 20 private schools were randomly selected from each of the districts (i.e., based on the remaining list of private schools in each district following from the first selection) to serve as replacement lists. The replacement list was necessary given the potential refusals from the private schools. There were no replacement lists for the public schools since all public schools would automatically qualify for participation.

The third stage involved selecting the final sample for the evaluation using the sampling frame obtained through the listing exercise. A total of 240 schools were randomly selected, distributed by district and sector. Schools were randomized into treatment groups after the first round of baseline data collection was completed.

The survey respondents were sampled using different sampling techniques: a. KG teachers: The research team sampled two KG teachers from each school; one from KG1 and KG2. KG teachers were sampled using purposive sampling method. In schools where there were more than two KG classes, the KG teachers from the "A" stream were selected. For the treatment schools, all KG teachers were invited to participate in the teacher training program. b. KG child-caregiver pair: The research team sampled KG children and their respective caregivers using simple random sampling method. Fifteen KG children-caregivers pair were sampled from each school. For schools with less than 15 KG children (8 from KG1, 7 from KG2 where possible), all KG children were included in the survey. KG children were selected from the same class as the selected KG teacher. The survey team used the class register to randomly select KG children who were present on the day of the school visit. Sampling was not stratified by gender or age. The caregivers of these selected child respondents were invited to participate in the survey.

The research team sought informed consent from the school head teacher, caregivers, as well as child respondents.

Mode of data collection

Face-to-face [f2f]

Research instrument

See attached questionnaires. All instruments have been shared except for IDELA (child assessment) as Save the Children have proprietary rights over this. Please contact the project Task Team Leader Deborah Newitter Mikesell dmikesell@worldbank.org for more information.

Cleaning operations

Data consistency checks (or High Frequency Checks) and back checks (audits) were conducted for all surveys remotely. Corrections were made during and after data collection after errors were reconciled.

All checks and cleaning was done using STATA and IPA possesses all the relevant code.

Response rate

Baseline I Out of the 276 schools that were selected for the Baseline I, 269 schools were surveyed (remember that potential replacement schools were also surveyed during Baseline I). This represents a response rate of 97%. It must, however, be emphasized that there were incomplete surveys in some of the schools, especially for the private schools. Incomplete surveys mean that only one of the surveys (instead of the two) was administered.

Baseline II All the surveys/assessment [with the exception of the Caregiver Survey] reported more than 90% response rate. The response rate for the Caregiver Survey was 60.0%.

In Jordan, GAGE recruited a sample of 4,101 adolescent girls and boys in two separate cohorts (younger adolescents aged 10-12 years and older adolescents age 15-18 years at baseline). GAGE surveyed the adolescents, as well as their adult female caregivers and, for those enrolled in formal schooling, conducted surveys at their schools. This sample includes Syrian refugees living in refugee camps, informal tented settlements (ITS) and host communities, as well as Palestinian refugees living in refugee camps and host communities, vulnerable Jordanian adolescents living in communities hosting refugees, and a small group of adolescents of other nationalities (Egyptian, Iraqi, and others) living in Jordan. The research sample was recruited during 2018 and 2019. Additional information about the sample and the baseline Jordan data are available in the GAGE Jordan Baseline Sample Overview and Data Use Manual (2021) available from UK Data Archive SN 8866.

Gender and Adolescence: Global Evidence: Jordan Baseline School Survey, 2019-2020 contains data collected at baseline from an additional survey conducted in adolescents' communities, which focused on formal primary and secondary schools. Specific schools where Core Respondents attended were identified and linked based on the details collected from the Core Respondent baseline survey. Where schools consented to participate, questionnaires were administered to a key school informant, such as the principal or head teacher, in September 2019 through January 2020.

This dataset contains test results for water and soil quality from Delhi, India. Tests were done in order to determine the baseline prevalence of contamination in piped water and in soil nearby water distribution pipes. Samples were gathered and processed by FARELABS Pvt. Ltd.

Abstract

This study aims to evaluate the impact of a safe-space based life skills training program and a combination of life skills and digital literacy training programs on adolescent girls’ empowerment, education, economic, and reproductive health outcomes. The interventions form two sub-components of the Adolescent Girls’ Initiative for Learning and Empowerment project. The sample covered randomly selected secondary school girls between the ages of 15 and 20 in rural and semi-urban schools that were eligible for the safe space-based life skills and digital skills trainings. The baseline data was collected through face-to-face interviews with 8,223 adolescents, 8,007 caregivers, and 270 school principals across Kaduna, Kano and Katsina States. The field data collection occurred simultaneously across the three States and lasted for 44 days between April and June, 2023. Enumerators collected data with tablets containing programmed questionnaires on SurveyCTO platform.

Geographic coverage

The study sample is comprised of senior secondary 1st year adolescent girls, their caregivers, and school principals from Kaduna (28%), Kano (32%), and Katsina (40%) in Nigeria.

Analysis unit

Individual, schools

Kind of data

Sample survey data [ssd]

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The AGILE Adolescent, Caregiver and School questionnaires are provided for download as supporting documentation for the data.

Metal, hydrocarbon, or nutrient data have not been recorded for the Arctic coastal plain 1002 area of the Arctic National Wildlife Refuge (Arctic Refuge) in areas of prospective oil and corridor development. Pre-development baseline data for contaminants are necessary to enable general characterization of water quality and contaminant residues, as well as to provide site-specific pre-development information in the event of a Congressional decision to open the Arctic coastal plain to oil and gas exploration and development. This study examines 1988-1989 samples of sediments, water, sedge, birds, invertebrates, and fishes from the 1002 area. Volume 1 of the three volumes in this report describes the study area, study sites, methods, and objectives, and provides summary statistics (geometric mean, arithmetic mean, arithmetic standard deviation, maximum, minimum, and median) for those analytes with more than 2/3 of the concentrations greater than the limit of detection. Volume 2contains the raw metal and hydrocarbon contaminant data, and the raw water quality data. Volume 3summarizes quality assurance/quality control (QA/QC) results which include mean relative percent differences (RPD's) from duplicate analyses, mean percent recoveries from spiked analyses, mean recoveries and Z scores from standard reference material analyses, and maximum concentrations from blank analyses. For a comprehensive description of all quality assurance/quality control methods, also see Volume 1. These reports provide a database on a sufficient number of aquatic, terrestrial, and lagoon samples to enable general characterization of water quality and contaminant residues, as well as to provide site specific pre-development information. The reader is strongly encouraged to use the QA/QC data in Volume 3 to assess data quality on an analyte-by-analyte basis for each sample matrix. This information will be used by Refuge management and State and Federal regulators to assess any post development changes that result from any oil and gas exploratory or production activities. The data will also be useful in evaluating special use permits, Clean Water Act Sections 402 and 404 permits, and State wastewater permits, and in recommending appropriate mitigation measures if development occurs on the 1002 area.

Impact Evaluation Framework and Results: Odisha Rural Livelihoods Project This is a baseline panel survey of households from rural Odisha collected to evaluate the impact of the TRIPTI Livelihoods project using a quasi-RDD design. The data were also used, after merging it with information on rainfall patterns, to assess the impact of TRIPTI on mitigating the effects of Hurricane Phailin. Collaboration: World Bank Social Observatory in collaboration with the Government of Odisha. EVALUATION DESIGN This evaluation was designed in 2011 after the project areas were chosen, which meant that a “gold standard” impact evaluation with a Randomized Control Trial method was not feasible. The selection rule for project areas however allowed for the next best available tool of Regression Discontinuity Design (See below). Using this design, the difference in difference approach, which measures the change in outcomes between project or “treatment” and comparable non-project or “control” areas over the evaluation time period can be used to evaluate the impact the project. Selection of TRIPTI Blocks - In each TRIPTI district, 4 blocks were to be chosen for project ""treatment"" using a ""backwardness"" selecton rule - All blocks were given a score that gave weightage to block level development indices (Ghadei Committee Index), SHG coverage, total population and SC/ST Populations - Program blocks then ranked in descending order of scores, and the 4 blocks with highest backwardness score wee chosen for the program Selection of Evaluation Blocks - In each district, the non- program or ""control"" block was chosen to the block that had the closest score to the last of the 4 program blocks - A pair of blocks- one program or “treatment” block, and non- program or “control” blocks) were chosen to be part of the evaluation sample in every district Selection of GPs, Villages and Households - Treatment is universal at the level of the block, which implies that at sub-block units, or Gram Panchayats (GPs) receive TRIPTIs interventions. > 4 GPs randomly chosen in each block > 2 vilages randomly chosen in each GP - All targeted households in a TRIPTI GP are eligible TRIPTI interventions > 15 households randonly chosen in each village > Oversampling of SC/ST housholds to proxy for target housholds EVALUATION DATA The data used in this evaluation come from the first (baseline) of two surveys commissioned by TRIPTI with technical assistance from the World Bank. An independent survey firm implemented both surveys. The baseline survey was completed before the initiation of TRIPTI in the evaluation sample area, between September-November 2011; and the follow up survey was implemented over the same month in 2014. This data therefore covers a 3-year period during which TRIPTI was in operation. The data collected focused on four modules. A general household module collected data on household consumption expenditures (following the same format as India’s National Sample Surveys that are used to measure poverty); and detailed information on the livelihoods portfolio and debt profile of households. A woman’s module was also administered to an adult married woman in each household. This module measured different metrics of women’s empowerment; and included questions on decision-making within the household, and on women’s participation in local public action. Two focus group discussions with the village in general, and women in the villages separately were also implemented in order to understand key elements related to local politics and civic action. In addition, a GPLF survey module- that covered 58 project Gram Panchayats - was implemented during the follow up survey. As part of this evaluation, data was to be collected from a sample of 3000 households selected at random from these 160 villages twice: once before the launch of project interventions in these 80 GPs at baseline (2011), and once at the end of the project. Due to some missing data, the baseline survey included in the end a total of 2875 households and the end line survey included a total of 2,874 households. The working sample is the total set of these households with reliable data. In each round of the survey, each household is linked to village-level data from that round. This evaluation report is an output of the Social Observatory Team of the World Bank and the Orissa Rural Livelihoods Project (TRIPTI), and it was financed by the South Asia Food and Nutrition Security Initiative (SAFANSI). There are two parts to this repot- an executive summary, and a technical paper that is authored by Shareen Joshi (Georgetown University), Nethra Palaniswamy (World Bank), and Vijayendra Rao (World Bank). Discussions with the TRIPTI project team led by the Additional Project Director Babita Mohapatra, and the World Bank task team led by Samik Das were critical to the design of this evaluation. Support from Arvind Padhee and DV Swamy who served as Project Directors of TRIPTI; from...

SIP Ocean program conducted the research cruises for technical development and data collection of baseline condition in deep-sea environments off Minami Torishima. This data set contains 18S rRNA gene based phylogenetic composition of meiofauna community determined from sediment core samples which have been collected in the 2019 cruise of R/V Kaiyo-Maru No.1 (KAIYO ENGINEERING CO., LTD.).

The Advanced Baseline Imager (ABI) operates on board the NOAA Geostationary Operational Environmental Satellite-R (GOES-R) Series weather satellites providing advanced imagery and atmospheric measurements of Earth’s Western Hemisphere. The Advanced Baseline Imager (ABI) instrument samples the radiance of the Earth in sixteen spectral bands using several arrays of detectors in the instrument’s focal plane. Single reflective band ABI Level 1b Radiance Products (channels 1 - 6 with approximate center wavelengths 0.47, 0.64, 0.865, 1.378, 1.61, 2.25 microns, respectively) are digital maps of outgoing radiance values at the top of the atmosphere for visible and near-infrared (IR) bands. Single emissive band ABI L1b Radiance Products (channels 7 - 16 with approximate center wavelengths 3.9, 6.185, 6.95, 7.34, 8.5, 9.61, 10.35, 11.2, 12.3, 13.3 microns, respectively) are digital maps of outgoing radiance values at the top of the atmosphere for IR bands. Detector samples are compressed, packetized and down-linked to the ground station as Level 0 data for conversion to calibrated, geo-located pixels (Level 1b Radiance data). The detector samples are decompressed, radiometrically corrected, navigated and resampled onto an invariant output grid, referred to as the ABI fixed grid. There are three spatial coverage scenes per satellite (GOES East and GOES West): Full Disk is the full hemispheric view; Contiguous U.S. is the lower 48 states; and Mesoscale 1 and 2 are for weather event views.

SIP Ocean program conducted the research cruises for technical development and data collection of baseline condition in deep-sea environments off Minami Torishima. This data set contains physicochemical parameters and microscopic counts of meiofauna determined from sediment core samples which have been collected in the 2019 cruise of R/V Kaiyo-Maru No.1 (KAIYO ENGINEERING CO., LTD.).

Across the world, the number of migrants displaced by civil conflict is on the rise. Recent estimates suggest that nearly 65.6 million people have been forcibly displaced within their own countries or across borders, and that most of them (84 percent) are living in developing countries (UNHCR 2017). Despite the persistence and scale of this displacement, there exists little evidence, or even basic data, addressing the core policy problem: what type of programs should be prioritized to maintain or improve the wellbeing of natives and refugees. The Cox's Bazar Panel Survey (CBPS) endeavours to provide such data through a comprehensive, large-sample survey that tracks both host and refugee households over time in Cox's Bazar, Bangladesh, the site of one of the world's largest refugee camps. The Baseline Survey is intended to be the first round of a multi-year panel survey, and it is hoped that at least three rounds of data will be collected, with one to three years between rounds.

The Baseline Survey has been administrated by Innovations for Poverty Action (IPA), Yale University, The World Bank, and the Gender and Adolescence: Global Evidence (GAGE) (an initiative funded by the Overseas Development Institute, UK Department for International Development) in 5,016 households from six upazilas in Cox's Bazar District: Chakaria, Cox's Bazar Sadar, Ramu, Teknaf, Ukhia, and Pekua; and one upazila in Bandarban District which hosts a significant refugee population. The study aims to capture household and individual level data, and is representative of two core groups of residents in Cox's Bazar:

• Refugees who resided in camps: This includes newly arrived refugees, defined as residents of the 27 internationally-recognized camps who migrated during or after August 2017; and previously arrived refugees who are residing in camps.
  
• The host mauza population: This includes natives, defined as households where the head was born in Bangladesh; and non-natives (which will include Rohingya refugees, as well as other households with heads born outside Bangladesh) who are resident outside camp.
  

The Cox's Bazar Panel Survey: Baseline, 2019 shares a sample with Gender and Adolescence: Global Evidence: Bangladesh-Dhaka Baseline, 2017-2018 (available under SN 8594). All CBPS households with at least one adolescent aged 10-12 or 15-17 were included in the GAGE random sample. This included 1,040 households in camps and 1,288 households in host communities. This study includes merged data files which include both the GAGE and CBPS data from sampled households.

This study addresses the South Coast MPA Baseline Program objectives by describing human use patterns across the study region and establishing initial data points for long-term tracking of conditions and trends in the South Coast. This study is also a part of a three-part study conducted by Point 97 to provide baseline estimates of the quantity, spatial distribution, and economic value of human uses—specifically human use in three specific sectors: coastal recreation, commercial fishing, and commercial passenger fishing vessels in the South Coast region. The South Coast (SC) region coastal recreation survey was launched in May of 2012. In an effort to capture seasonal variations in coastal use, we collected data on the respondent’s most recent coastal trip, and deployed the survey in four survey “waves” over a one-year period. Data collection was completed in March 2013, and the data were then subsequently analyzed and synthesized. In the survey, respondents were asked to recount details of their coastal visitation trips over the previous 12 months and of their last trip, including information about the number of trips taken, participation in recreational activities, the location of activities, and expenditures made. This data package include the raw survey data and a sample PDF map of the spatial data collected.

Abstract

Since 2014, UNHCR has undertaken a comprehensive revision of the framework for monitoring UNHCR Livelihoods and Economic Inclusion programs. Since 2017, mobile data collection (survey) tools have been rolled out globally, including in Malawi. The participating operations conducted a household survey to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline (87 observations) and endline data (78 observations) from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact.

Geographic coverage

Dzaleka

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample size for this dataset is: Baseline data : 87 Endline data : 78 Total : 165

The sampling was conducted by each participating operation based on general sampling guidance provided as the following;

• At least 100 randomly selected beneficiaries for each project
• Representativeness of sub-groups (gender, camp, etc.) should be kept as much as possible
• Baseline and endline beneficiaries should be the same

Sampling deviation

Some operations may deviate from the sampling guidance due to local constraints such as logistical and security obstacles.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The survey questionnaire used to collect the survey consists of five sections: Partner Information, General Information on Beneficiary, Access to Agricultural Production Enabled and Enhanced, Access to Self-Employment/ Business Facilitated, and Access to Wage Employment Facilitated.

Cleaning operations

The dataset presented here has undergone light checking, cleaning, harmonisation of localised information, and restructuring (data may still contain errors) as well as anonymization (includes removal of direct identifiers and sensitive variables, and grouping values of select variables). Empty values can occur for several reasons (e.g. no occurrence of agricultural interventions among the beneficiaries will result in empty variables for the agricultural module).

Response rate

Information not available

Abstract

The Alliance for a Green Revolution (AGRA) is an organization that is at the forefront of agricultural intervention programs in Burkina Faso as well as in other sub-Saharan African countries, including Burkina Faso, Ghana, Mali and Mozambique. Data for the first three countries is available from the ISSER ACEIR Data Hub. AGRA objectives are to increase farmer productivity through access to quality inputs, reduce post-harvest losses through access to post-harvest storage technologies and support farmers through an enabling policy environment. The Institute of Statistical Social and Economic Research (ISSER) conducted a baseline survey of farmer households in five regions in Burkina Faso. Farmer households in Boucle de Mouhoun, Cascades, Centre-Est, Centre-Ouest and Hauts-Bassins were sampled to create baseline data of farming practices, yields, post-harvest loss and other features of the value chain in the cultivation of four major crop, namely maize, rice, sorghum and cowpea. The data seeks to help identify some key challenges to the production of these crops in the five regions and support the development and subsequent evaluation of AGRA interventions over the five-year period.

Geographic coverage

The study collected data from farmer households in five regions of Burkina Faso: Boucle de Mouhoun, Cascades, Centre-Est, Centre-Ouest, and Hauts-Bassins.

Analysis unit

Households and individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

Quantitative and qualitative data collection occurred in both regions from 19 districts. The enumeration areas visited selected as per 2010 Census demarcations, to identify areas where rural households in the regions commonly grew the crops of interest. Based on existing and projected estimates for crop yields and crop losses in AGRA's business plan for Burkina Faso, the survey targeted a statistically acceptable sample size of 3,100 farm households.

A two stage sampling strategy employed to ascertain the needed sample size for the survey. In the first Stage (Primary Sampling), power calculations determined the number of clusters or enumeration areas (EAs,) required for the necessary size of power of at least 80%. It was determined that at least 15 farming households would be randomly selected from each of the 212 EAs to give the total sample of 3,180 households. We selected these clusters based on the distribution of the target crops across the regions and their districts, as provided by the AGRA country business plan. Sample size of 2,784 households, which increased to 3,202 to account for anticipated future attrition and difficulty accessing households or EAs during the initial baseline data collection.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two data collection instruments were employed to collect data for the qualitative baseline study. These are semi-structured interview and discussion guides. A questionnaire was then administered to randomly selected households for the quantitative interviews.