Abstract

The 2016/17 Uganda National Household Survey (UNHS) is the sixth in a series of national household surveys that Uganda Bureau of Statistics (UBOS) has undertaken. The survey collected information on socio-economic characteristics at both household and community levels. The main objective of the survey was to collect high quality data on demographic and socio-economic characteristics of households for monitoring Uganda’s development performance of key indicators in the various sectors. The 2016/17 UNHS comprises four (4) modules. Those are the Socio-Economic, Labour Force, Community, and Market price modules. The main findings are based on the four modules and include trends of several indicators on Education, Health, Household Expenditure and Poverty, Food security, Income and loans, Information and Communication Technology, Vulnerable Groups, Community Characteristics and Non-crop household enterprises, presented at national, rural-urban, regional and sub-regional levels. The survey collected much more information besides what has been included in the main findings. Therefore, UBOS calls upon all stakeholders to utilize the wealth of data collected and availed over the years to undertake in-depth empirical analysis so as to better inform future policy debate.

Geographic coverage

National coverage

Analysis unit

The UNHS 2016/17 had the following units of analysis: individuals, housheholds, and communities.

Universe

The survey covered all de jure household members (usual residents), all currently employed and unemployed persons aged 5 years and above, resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2016/17 UNHS sample was designed to allow for generation of separate estimates at the national level, for urban and rural areas and for the 15 sub-regions of Uganda. At the time of the survey there were only 112 districts. This number later increased to 122 districts. A two-stage stratified sampling design was used. At the first stage, Enumeration Areas (EAs) were grouped by districts of similar socio-economic characteristics and by rural-urban location. The EAs were then drawn using Probability Proportional to Size (PPS). At the second stage, households which are the ultimate sampling units were drawn using Systematic Random Sampling. A total of 1,750 EAs were selected from the 2014 National Population and Housing Census (NPHC) list of EAs which constituted the Sampling Frame. The EAs were then grouped into 15 sub-regions, taking into consideration the standard errors required for estimation of poverty indicators at sub-regions and the rural-urban domains. In addition to the sub-regions, the other sub-groups that were considered during the analysis of the 2016/17 UNHS include the Peace and Recovery Development Plan (PRDP) districts and Hard-to-reach areas such as the mountainous areas. The survey targeted to interview 10 households per EA, implying a total sample of 17,540 households. Prior to the main survey data collection, all the sampled EAs were updated by listing all the households within their boundaries.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The UNHS 2016/17 adminstered four questionnaires including: Socio-Economic, Labour Force, Market Prices, and Community. All questionnaires and modules are provided as external resources in this documentation.

Response rate

Out of the total 17,320 households selected for the 2016/17 UNHS sample, 15,672 households were successfully interviewed, giving a response rate of 91 percent. The response rate was higher in rural areas (93%) compared to urban areas (88%).

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling errors usually result from mistakes made during data collection and capture and those include misunderstanding of the questions, either by the respondent or by the interviewer and by capture of wrong entries. Such errors were controlled through rigorous training of the data collectors and through field spot-checks undertaken by the supervisors at the different levels. On the other hand, sampling errors (SE) are evaluated statistically. The 2016/17 UNHS sample is one of the many possible samples that could have been selected from the same population using the same sampling design. Sampling errors are a measure of the variability between all possible samples that would yield different results from the selected sample. Sampling errors are usually measured in terms of the standard error for a particular statistic such as the mean, percentages, etc. The Tables in Appendix III present standard errors and Coefficients of Variations (CVs) for selected indicators at national, rural-urban and sub-regional levels.

The 2017-2018 School Neighborhood Poverty Estimates are based on school locations from the 2017-2018 Common Core of Data (CCD) school file and income data from families with children ages 5 to 17 in the U.S. Census Bureau’s 2014-2018 American Community Survey (ACS) 5-year collection. The ACS is a continuous household survey that collects social, demographic, economic, and housing information from the population in the United States each month. The Census Bureau calculates the income-to-poverty ratio (IPR) based on money income reported for families relative to the poverty thresholds, which are determined based on the family size and structure. Noncash benefits (such as food stamps and housing subsidies) are excluded, as are capital gains and losses. The IPR is the percentage of family income that is above or below the federal poverty level. The IPR indicator ranges from 0 to a top-coded value of 999. A family with income at the poverty threshold has an IPR value of 100. The estimates in this file reflect the IPR for the neighborhoods around schools which may be different from the neighborhood conditions of students enrolled in schools.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

The National Longitudinal Study of Adolescent to Adult Health (Add Health) Parent Study Public Use collection includes data gathered as part of the Add Health longitudinal survey of adolescents. The original Add Health survey is a longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-1995 school year. In Wave 1 of the Add Health Study (1994-1995), a parent of each Add Health Sample Member (AHSM) was interviewed. The Add Health Parent Study gathered social, behavioral, and health survey data in 2015-2017 from the parents of Add Health Sample members who were originally interviewed at Wave 1 (1994-1995). Wave 1 Parents were asked about their adolescent children, their relationships with them, and their own health. The Add Health Parent Study interview is a comprehensive survey of Add Health parents' family relations, education, religious beliefs, physical and mental health, social support, and community involvement experiences. In addition, survey data contains cognitive assessments, a medications log linked to a medications database lookup table, and household financial information collection. The survey also includes permission for administrative data linkages and includes data from a Family Health History Leave-Behind questionnaire. Interviews were conducted with parents' spouse/partner when available. Research domains targeted in the survey and research questions that may be addressed using the Add Health Parent Study data include: Health Behaviors and Risks Many health conditions and behaviors run in families; for example, cardiovascular disease, obesity and substance abuse. How are health risks and behaviors transmitted across generations or clustered within families? How can we use information on the parents' health and health behavior to better understand the determinants of their (adult) children's health trajectories? Cognitive Functioning and Non-Cognitive Personality Traits What role does the intergenerational transmission of personality and locus of control play in generating intergenerational persistence in education, family status, income and health? How do the personality traits of parents and children, and how they interact, influence the extent and quality of intergenerational relationships and the prevalence of assistance across generations? Decision-Making, Expectations, and Risk Preferences Do intergenerational correlations in risk preferences represent intergenerational transmission of preferences? If so, are the transmission mechanisms a factor in biological and environmental vulnerabilities? Does the extent of genetic liability vary in response to both family-specific and generation-specific environmental pressures? Family Support, Relationship Quality and Ties of Obligation How does family complexity affect intergenerational obligations and the strength of relationship ties? As parents near retirement: What roles do they play in their children's lives and their children in their lives? What assistance are they providing to their adult children and grandchildren? What do they receive in return? And how do these ties vary with divorce, remarriage and familial estrangement? Economic Status and Capacities What are the economic capacities of the parents' generation as they reach their retirement years? How have fared through the wealth and employment shocks of the Great Recession? Are parents able to provide for their own financial need? And, do they have the time and financial resources to help support their children and grandchildren and are they prepared to do so?

Abstract

The Integrated Household Survey is one of the primary instruments implemented by the Government of Malawi through the National Statistical Office (NSO) roughly every 5 years to monitor and evaluate the changing conditions of Malawian households. The IHS data have, among other insights, provided benchmark poverty and vulnerability indicators to foster evidence-based policy formulation and monitor the progress of meeting the Millennium Development Goals (MDGs), the goals listed as part of the Malawi Growth and Development Strategy (MGDS) and now the Sustainable Development Goals (SDGs).

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Children under 5 years
• Consumption expenditure commodities/items
• Communities
• Agricultural household/ Holder/ Crop

Universe

Members of the following households are not eligible for inclusion in the survey: • All people who live outside the selected EAs, whether in urban or rural areas. • All residents of dwellings other than private dwellings, such as prisons, hospitals and army barracks. • Members of the Malawian armed forces who reside within a military base. (If such individuals reside in private dwellings off the base, however, they should be included among the households eligible for random selection for the survey.) • Non-Malawian diplomats, diplomatic staff, and members of their households. (However, note that non-Malawian residents who are not diplomats or diplomatic staff and are resident in private dwellings are eligible for inclusion in the survey. The survey is not restricted to Malawian citizens alone.) • Non-Malawian tourists and others on vacation in Malawi.

Kind of data

Sample survey data [ssd]

Sampling procedure

The IHS4 sampling frame is based on the listing information and cartography from the 2008 Malawi Population and Housing Census (PHC); includes the three major regions of Malawi, namely North, Center and South; and is stratified into rural and urban strata. The urban strata include the four major urban areas: Lilongwe City, Blantyre City, Mzuzu City, and the Municipality of Zomba. All other areas are considered as rural areas, and each of the 27 districts were considered as a separate sub-stratum as part of the main rural stratum. This is the first round of the survey to include the island district of Likoma in the sampling frame. The sampling frame further excludes the population living in institutions, such as hospitals, prisons and military barracks. Hence, the IHS4 strata are composed of 32 districts in Malawi.

A stratified two-stage sample design was used for the IHS4.

Note: Detailed sample design information is presented in the "Fourth Integrated Household Survey 2016-2017, Basic Information Document" document.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

HOUSEHOLD QUESTIONNAIRE The Household Questionnaire is a multi-topic survey instrument and is near-identical to the content and organization of the IHS3. It encompasses economic activities, demographics, welfare and other sectoral information of households. It covers a wide range of topics, dealing with the dynamics of poverty (consumption, cash and non-cash income, savings, assets, food security, health and education, vulnerability and social protection). Although the IHS4 household questionnaire covers a wide variety of topics in detail it intentionally excludes in-depth information on topics covered in other surveys that are part of the NSO’s statistical plan (such as maternal and child health issues covered at length in the Malawi Demographic and Health Survey).

AGRICULTURE QUESTIONNAIRE All IHS4 households that are identified as being involved in agricultural or livestock activities were administered the agriculture questionnaire, which is primarily modelled after the IHS3 counterpart. The modules are expanding on the agricultural content of the IHS3, IHS2, AISS, and other regional agricultural surveys, while remaining consistent with the NACAL topical coverage and methodology. The development of the agriculture questionnaire was done with input from the aforementioned stakeholders who provided input on the household questionnaire as well as outside researchers involved in research and policy discussions pertaining to the Malawian agriculture. The agriculture questionnaire allows, among other things, for extensive agricultural productivity analysis through the diligent estimation of land areas, both owned and cultivated, labor and non-labor input use and expenditures, and production figures for main crops, and livestock. Although one of the major foci of the agriculture data collection effort was to produce smallholder production estimates for major crops, it is also possible to disaggregate the data by gender and main geographical regions. The IHS4 cross-sectional households supply information on the last completed rainy season (2014/2015 or 2015/2016) and the last completed dry season (2015 or 2016) depending on the timing of their interview.

FISHERIES QUESTIONNAIRE The design of the IHS4 fishery questionnaire is identical to the questionnaire designed for IHS3. The IHS3 fisheries questionnaire was informed by the design and piloting of a fishery questionnaire by the World Fish Center (WFC), which was supported by the LSMS-ISA project for the purpose of assembling a fishery questionnaire that could be integrated into multi-topic household-surveys. The WFC piloted the draft instrument in November 2009 in the Lower Shire region, and the NSO team considered the revised draft in designing the IHS4 fishery questionnaire.

COMMUNITY QUESTIONNAIRE The content of the IHS4 Community Questionnaire follows the content of the IHS3 & IHPS Community Questionnaires. A “community” is defined as the village or urban location surrounding the enumeration area selected for inclusion in the sample and which most residents recognize as being their community. The IHS4 community questionnaire was administered to each community associated with the 780 cross-sectional EAs. Identical to the IHS3 approach, to a group of several knowledgeable residents such as the village headman, the headmaster of the local school, the agricultural field assistant, religious leaders, local merchants, health workers and long-term knowledgeable residents. The instrument gathers information on a range of community characteristics, including religious and ethnic background, physical infrastructure, access to public services, economic activities, communal resource management, organization and governance, investment projects, and local retail price information for essential goods and services.

Cleaning operations

DATA ENTRY PLATFORM To ensure data quality and timely availability of data, the IHS4 was implemented using the World Bank’s Survey Solutions CAPI software. To carry out IHS4, 1 laptop computer and a wireless internet router were assigned to each team supervisor, and each enumerator had an 8–inch GPS-enabled Samsung Galaxy Tab S2 tablet computer. The use of Survey Solutions allowed for the real-time availability of data as the completed data was completed, approved by the Supervisor and synced to the Headquarters server as frequently as possible. While administering the first module of the questionnaire the enumerator(s) also used their tablets to record the GPS coordinates of the dwelling units. In Survey Solutions, Headquarters can then see the location of the dwellings plotted on a map of Malawi to better enable supervision from afar – checking both the number of interviews performed and the fact that the sample households lie within EA boundaries. Geo-referenced household locations from that tablet complemented the GPS measurements taken by the Garmin eTrex 30 handheld devices and these were linked with publically available geospatial databases to enable the inclusion of a number of geospatial variables - extensive measures of distance (i.e. distance to the nearest market), climatology, soil and terrain, and other environmental factors - in the analysis.

DATA MANAGEMENT The IHS4 Survey Solutions CAPI based data entry application was designed to stream-line the data collection process from the field. IHS4 Interviews were collected in “sample” mode (assignments generated from headquarters) as opposed to “census” mode (new interviews created by interviewers from a template) for the NSO to have more control over the sample.

The range and consistency checks built into the application was informed by the LSMS-ISA experience in IHS3 and IHPS. Prior programming of the data entry application allowed for a wide variety of range and consistency checks to be conducted and reported and potential issues investigated and corrected before closing the assigned enumeration area. Headquarters (NSO management) assigned work to supervisors based on their regions of coverage. Supervisors then made assignments to the enumerators linked to their Supervisor account. The work assignments and syncing of completed interviews took place through a Wi-Fi connection to the IHS4 server. Because the data was available in real time it was monitored closely throughout the entire data collection period and upon receipt of the data at headquarters, data was exported to STATA for other consistency checks, data cleaning, and analysis.

DATA CLEANING The data cleaning process was done in several stages over the course of field work and through preliminary analysis. The first stage of data cleaning was conducted in the field by the field based field teams utilizing errors generated with the Survey Solutions application. For questions that

The 2016-2017 School Neighborhood Poverty Estimates are based on school locations from the 2016-2017 Common Core of Data (CCD) school file and income data from families with children ages 5 to 18 in the U.S. Census Bureau’s 2013-2017 American Community Survey (ACS) 5-year collection. The ACS is a continuous household survey that collects social, demographic, economic, and housing information from the population in the United States each month. The Census Bureau calculates the income-to-poverty ratio (IPR) based on money income reported for families relative to the poverty thresholds, which are determined based on the family size and structure. Noncash benefits (such as food stamps and housing subsidies) are excluded, as are capital gains and losses. The IPR is the percentage of family income that is above or below the federal poverty level. The IPR indicator ranges from 0 to a top-coded value of 999. A family with income at the poverty threshold has an IPR value of 100. The estimates in this file reflect the IPR for the neighborhoods around schools which may be different from the neighborhood conditions of students enrolled in schools.

The American Community Survey Education Tabulation (ACS-ED) is a custom tabulation of the ACS produced for the National Center of Education Statistics (NCES) by the U.S. Census Bureau. The ACS-ED provides a rich collection of social, economic, demographic, and housing characteristics for school systems, school-age children, and the parents of school-age children. In addition to focusing on school-age children, the ACS-ED provides enrollment iterations for children enrolled in public school. The data profiles include percentages (along with associated margins of error) that allow for comparison of school district-level conditions across the U.S. For more information about the NCES ACS-ED collection, visit the NCES Education Demographic and Geographic Estimates (EDGE) program at: https://nces.ed.gov/programs/edge/Demographic/ACSAnnotation values are negative value representations of estimates and have values when non-integer information needs to be represented. See the table below for a list of common Estimate/Margin of Error (E/M) values and their corresponding Annotation (EA/MA) values.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.-9An '-9' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.-8An '-8' means that the estimate is not applicable or not available.-6A '-6' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.-5A '-5' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate.-3A '-3' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.-2A '-2' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.

The Survey of Public Participation in the Arts (SPPA) 2017 collection is comprised of responses from two sets of surveys, the Current Population Survey (CPS) and the SPPA supplement to the CPS administered in July 2017. This supplement asked questions about public participation in the arts within the United States, and was sponsored by the National Endowment for the Arts. The CPS, administered monthly by the U.S. Census Bureau, collects labor force data about the civilian, noninstitutionalized population aged 15 years or older living in the United States. The CPS provides current estimates of the economic status and activities of this population which includes estimates of total employment (both farm and nonfarm), nonfarm self-employed persons, domestics, unpaid helpers in nonfarm family enterprises, wage and salaried employees, and estimates of total unemployment. The basic CPS items in this data provide labor force activity for the week prior to the survey. In addition, the CPS provides respondents' demographic characteristics such as age, sex, race, marital status, educational attainment, family relationships, occupation, and industry. In addition to the basic CPS questions, interviewers asked supplementary questions on public participation in the arts of two randomly selected household members aged 18 or older from about one-half of the sampled CPS households. The supplement contained questions about the respondent's participation in various artistic activities over the last year. If the selected respondent had a spouse or partner, then the respondent answered questions on behalf of their spouse/partner and the spouse/partner responses are proxies. The 2017 SPPA included two core components: a questionnaire used in previous years to ask about arts attendance and literary reading, and a newer survey about arts attendance, venues visited, and motivations for attending art events. In addition, the SPPA supplement included five modules designed to capture other types of arts participation as well as participation in other leisure activities. Questions included items on the frequency of participation, types of artistic activities, training and exposure, musical and artistic preferences, school-age socialization, and computer and device usage related to the arts. The five modules were separated by topic: Module A: Consuming Art via Electronic Media Module B: Performing Art Module C: Creating Visual Art and Writing Module D: Other Leisure Activities Module E: Arts Education, and Arts Access and Opportunity Respondents were randomly assigned to either of the core questionnaires and were then randomly assigned to two of the five additional modules so that each module was administered to a portion of the sampled cases.

Abstract

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Geographic coverage

The General Household Survey has national coverage.

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa, and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons, and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Face-to-face [f2f]

Research instrument

Data was collected with a household questionnaire and a questionnaire administered to a household member to elicit information on household members.

Data appraisal

Please note that DataFirst provides versioning at dataset and file level. Revised files have new version numbers. Files that are not revised retain their original version numbers. Changes to any of the data files will result in the dataset having a new version number. Thus version numbers of files within a dataset may not match

Abstract

The 2019/20 Uganda National Household Survey (UNHS) is the seventh in a series of national household surveys that Uganda Bureau of Statistics (UBOS) has undertaken. The survey collected information on socio-economic characteristics at both household and community levels. The main objective of the survey was to collect high quality data on demographic and socio-economic characteristics of households for monitoring Uganda's development performance of key indicators in the various sectors. The 2019/20 UNHS comprises four (4) modules. Those are the Socio-Economic, Labour Force, Community, and Market price modules. The main findings are based on the four modules and include trends of several indicators on Education, Health, Household Expenditure and Poverty, Food security, Income and loans, Information and Communication Technology, Vulnerable Groups, Community Characteristics and Non-crop household enterprises, presented at national, rural-urban, regional and sub-regional levels. The survey collected much more information besides what has been included in the main findings. Therefore, UBOS calls upon all stakeholders to utilize the wealth of data collected and availed over the years to undertake in-depth empirical analysis so as to better inform future policy debate.

Geographic coverage

National Coverage

Analysis unit

The UNHS 2016/17 had the following units of analysis: individuals, housheholds, and communities.

Universe

The survey covered all de jure household members (usual residents), all currently employed and unemployed persons aged 5 years and above, resident in the household.

Sampling procedure

Sampling Design The Uganda National Household Survey 2019/20 (UNHS VI1 will be seventh survey of its kind in Uganda following the one implemented in 2019/2017. The survey calls for a nationally representative sample of 14480 households from 1448 sample clusters. It is designed to collect high quality and timely data on demographic, social and economic characteristics of the household population to monitor international and national development frameworks. The survey is designed to produce representative estimates for the poverty indicators for the country as a whole, for the urban and rural areas separately, for each of the 15 geo-regions. The definition of the geo-regions and the study domains are given in section 2. In addition to the geo-regions, the survey indicators will be produced for the following areas: The Island, The Greater Kampala areas, PRDP.

Sampling Frame The sampling frame used for UNHS VII is the frame for the Uganda Population and Housing Census which conducted on August 2014 (UPHC 2014). The sampling frame is a complete list of census Enumeration Areas (EA) created for the census covering the whole country, consisting of 78,692EAs (excluding Refugees, forests and forest reserves and institutional population). Currently in Uganda there are 128 districts, each districts is sub-divided into Sub County, and each sub country into parish, and each parish into villages and then Enumeration areas. The frame file contains the administrative belongings for each EA and its number of households at the time of the census operation. Each EA has also a designated residence type, urban or rural. According to 2014 Population and Housing Census, an EA was either a village or part of the village. EAs with less than 50 households were linked to others EAs by GIS section so that the primary sampling units are not very small. The allocation of clusters (EA) per sub-region will be relatively equal across domains. The allocation per domain will be well balanced and small changes in the allocation will not affect the precision of estimates. The 2200 selected households should result in about 2000 households successfully interviewed. The sample will be selected independently from each stratum using probability proportional to size. The country currently has 134districts and 12 Cities, these are grouped into the following 15 sub-regions:

1. Kampala: Kampala
2. Buganda South: Butambala, Gomba, Mpigi, Bukomansimbi, Kalangala, Kalungu, Lwengo, Lyantonde, Masaka, Rakai, Sembabule, Wakiso, Kyotera, Masaka City
3. Buganda North: Buikwe, Buvuma, Kayunga, Kiboga, Kyankwanzi, Luwero, Mityana, Mubende, Mukono, Nakaseke, Nakasongola, Kassanda
4. Busoga: Bugiri, Namutumba, Buyende, Iganga, Jinja, Kaliro, Kamuli, Luuka, Mayuge, Namayingo, Bugweri, Jinja City
5. Bukedi: Budaka, Butaleja, Kibuku, Pallisa, Toororo, Busia, Butebo
6. Egon: Bulambuli, Kapchorwa, Kween, Bududa, Manafwa, Mbale, Sironko, Bukwo, Namisindwa, Mbale City
7. Teso: Amuria, Bukedea, Katakwi, Kumi, Ngora, Soroti, Kaberamaido, Serere, Kapelebyong
8. Lango: Alebtong, Amolatar, Dokolo, Lira, Otuke, Apac, Kole, Oyam, Kwania, Lira City
9. Acholi: Agago, Amuru, Gulu, , Lamwo, Pader,Kitgum ,Nwoya, Gulu City
10. Karamoja: Abim, Amudat, Kaabong, Kotido, Moroto, Nakapiripirit, Napak, Nabilatuk
11. West Nile: Adjumani, Arua, Koboko, Maracha, Moyo, Nebbi, Yumbe, Zombo, Pakwach, Obongi, Terego, Arua City
12. Tooro: Bundibugyo, Kabarole, Kasese, NTooroko, Kyenjojo, Kamwenge, Kyegegwa, Bunyangabu, Fort portal City
13. Bunyoro: Buliisa, Hoima, , Kibaale, Kiryandongo, Masindi, Kikuube, Hoima City, KItagwenda
14. Ankole: Buhweju, Bushenyi, Ibanda, Isingiro, Kiruhura, Mbarara, Mitooma, Ntungamo, Rubirizi, Sheema, Mbarara City, Rwampara, Kazo
15. Kigezi: Kabale, Kisoro, Kanungu, Rukungiri, Rukiga

Mode of data collection

Data collection The survey collected data on food, drinks and beverage consumption using a seven-day recall period on the four major food sources22. Information was collected both in terms of expenditures and quantities, except for food consumed away from home only having the expenditure recorded. To ensure the accuracy of the information provided by respondents, data on food quantities was collected in local units of measurement. Conversion factors were then used to transform local units of measurement into standard metric units of quantity derived from the market survey conducted during the survey. Macronutrients and micronutrient values were mainly derived from the recent "Food Composition Table for Central and Eastern Uganda" (Harvest-Plus 2012)23.

Abstract

The Integrated Living Conditions Survey (ILCS), conducted annually by the RA NSS (Republic of Armenia National Statistical Service), formed the basis for most of the empirical analyses in the report. The ILCS is a universally recognized best-practice statistical survey for collecting data to inform about the living standards of households. ILCS comprises comprehensive and valuable data on the welfare of households and separate individuals which affords the NSS an opportunity to provide the public with up to date information on the population’s income, expenditures, the level of poverty and the other changes in living standards on an annual basis.

In 2003-2004 the National Statistical Service of the Republic of Armenia took important steps to improve the Armenia Integrated Leaving Conditions Survey (ILCS) and bring the poverty measurement methodology it applied up to date.

With technical assistance from the World Bank provided through a series of consultations and hands-on-training, the following changes were made:

• the sample frame for the Integrated Leaving Conditions Survey was updated using the 2001 Population Census data;
• the sample size was expanded, so as to make the ILSC representative at the regional (marz) level;
• the ILSC questionnaire was revised to account for economic and social changes since 1998-1999 and an extensive labor module was added to the survey;
• staff involved in ILCS implementation was better trained.

Geographic coverage

Urban and rural communities

Analysis unit

• Households;
• Individuals.

Kind of data

Sample survey data [ssd]

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The Questionnaire is filled in by the interviewer in the course of at least five visits to households per month. During face-to-face interviews with the household head or another knowledgeable adult member, the interviewer collects information on the composition and housing conditions of the household, the employment status, educational level and health condition of the members, availability and use of land, livestock, and agricultural machinery, monetary and commodity flows between households, and other information.

Certain changes were made into the 2014 questionnaire. Particularly, the sections “List of Household Members”, "Migration", “Housing and Dwelling Conditions”, "Employment", “Social Assistance” were revised.

Thus, the 2015 survey questionnaire had the following sections: (1) “List of Household Members”, (2) “Migration”, (3) “Housing and Dwelling Conditions”, (4) “Employment”, (5) “Education”, (6) “Agriculture”, (7) “Food Production”, (8) “Monetary and Commodity Flows between Households”, (9) “Health (General) and Healthcare”, (10) “Debts”, (11) “Subjective Assessment of Living Conditions”, (12) “Provision of Services”, (13) “Social Assistance”, (14) “Households as Employers for Service Personnel”, and (15) “Household Monthly Consumption of Energy Resources”.

The Diary is completed directly by the household during one month. Every day the household would record all its expenditures on food, non-food products and services, also giving a detailed description of such purchases; e.g. for food products the name, quantity, cost, and place of purchase of the product is recorded. Besides, the household records its consumption of food products received and used from its own land and livestock, as well as from other sources (e.g. gifts, humanitarian aid). Non-food products and services purchased or received for free are also recorded in the diary. Then, the household records its income received during the month. At the end of the month, information on rarely used food products, durable goods and ceremonies is recorded, as well. The records in the diary are verified by the interviewer in the course of 5 mandatory visits to the household during the survey month.

The Survey Diary has the following sections: (1) food purchased during the day, (2) food consumed at home during the day, (3) expenditures on food consumed away from home, (4) non-food products purchased and services obtained, (5) non-food products and services received free of charge, (6) household income and monetary inflows, (7) food products, which are usually consumed in small quantities during the day, (8) list of real estate, durable goods, and ceremonies. The interviewer’s manual provides detailed instructions for completing the questionnaire and the diary.

The Questionnaire, the Diary and the Interviewer's Manual are revised and adjusted, as appropriate, prior to the launch of the survey. Starting from 2012, data are codified under the “Classification of Individual Consumption by Purpose” (COICOP) classifier.

Abstract

The Integrated Household Survey is one of the primary instruments implemented by the Government of Malawi through the National Statistical Office (NSO) roughly every 3-5 years to monitor and evaluate the changing conditions of Malawian households. The IHS data have, among other insights, provided benchmark poverty and vulnerability indicators to foster evidence-based policy formulation and monitor the progress of meeting the Millennium Development Goals (MDGs), the goals listed as part of the Malawi Growth and Development Strategy (MGDS) and now the Sustainable Development Goals (SDGs).

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Consumption expenditure commodities/items
• Communities
• Agricultural household/ Holder/ Crop
• Market

Universe

Members of the following households are not eligible for inclusion in the survey: • All people who live outside the selected EAs, whether in urban or rural areas. • All residents of dwellings other than private dwellings, such as prisons, hospitals and army barracks. • Members of the Malawian armed forces who reside within a military base. (If such individuals reside in private dwellings off the base, however, they should be included among the households eligible for random selection for the survey.) • Non-Malawian diplomats, diplomatic staff, and members of their households. (However, note that non-Malawian residents who are not diplomats or diplomatic staff and are resident in private dwellings are eligible for inclusion in the survey. The survey is not restricted to Malawian citizens alone.) • Non-Malawian tourists and others on vacation in Malawi.

Kind of data

Sample survey data [ssd]

Sampling procedure

The IHS5 sampling frame is based on the listing information and cartography from the 2018 Malawi Population and Housing Census (PHC); includes the three major regions of Malawi, namely North, Center and South; and is stratified into rural and urban strata. The urban strata include the four major urban areas: Lilongwe City, Blantyre City, Mzuzu City, and the Municipality of Zomba. All other areas are considered as rural areas, and each of the 27 districts were considered as a separate sub-stratum as part of the main rural stratum. The sampling frame further excludes the population living in institutions, such as hospitals, prisons and military barracks. Hence, the IHS5 strata are composed of 32 districts in Malawi.

A stratified two-stage sample design was used for the IHS5.

Note: Detailed sample design information is presented in the "Fifth Integrated Household Survey 2019-2020, Basic Information Document" document.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

HOUSEHOLD QUESTIONNAIRE The Household Questionnaire is a multi-topic survey instrument and is near-identical to the content and organization of the IHS3 and IHS4 questionnaires. It encompasses economic activities, demographics, welfare and other sectoral information of households. It covers a wide range of topics, dealing with the dynamics of poverty (consumption, cash and non-cash income, savings, assets, food security, health and education, vulnerability and social protection). Although the IHS5 household questionnaire covers a wide variety of topics in detail it intentionally excludes in-depth information on topics covered in other surveys that are part of the NSO’s statistical plan (such as maternal and child health issues covered at length in the Malawi Demographic and Health Survey).

AGRICULTURE QUESTIONNAIRE All IHS5 households that are identified as being involved in agricultural or livestock activities were administered the agriculture questionnaire, which is primarily modelled after the IHS3 counterpart. The modules are expanding on the agricultural content of the IHS4, IHS3, IHS2, AISS, and other regional agricultural surveys, while remaining consistent with the NACAL topical coverage and methodology. The development of the agriculture questionnaire was done with input from the aforementioned stakeholders who provided input on the household questionnaire as well as outside researchers involved in research and policy discussions pertaining to the Malawian agriculture. The agriculture questionnaire allows, among other things, for extensive agricultural productivity analysis through the diligent estimation of land areas, both owned and cultivated, labor and non-labor input use and expenditures, and production figures for main crops, and livestock. Although one of the major foci of the agriculture data collection effort was to produce smallholder production estimates for major crops, it is also possible to disaggregate the data by gender and main geographical regions. The IHS5 cross-sectional households supply information on the last completed rainy season (2017/2018 or 2018/2019) and the last completed dry season (2018 or 2019) depending on the timing of their interview.

FISHERIES QUESTIONNAIRE The design of the IHS5 fishery questionnaire is identical to the questionnaire designed for IHS3. The IHS3 fisheries questionnaire was informed by the design and piloting of a fishery questionnaire by the World Fish Center (WFC), which was supported by the LSMS-ISA project for the purpose of assembling a fishery questionnaire that could be integrated into multi-topic household-surveys. The WFC piloted the draft instrument in November 2009 in the Lower Shire region, and the NSO team considered the revised draft in designing the IHS5 fishery questionnaire.

COMMUNITY QUESTIONNAIRE The content of the IHS5 Community Questionnaire follows the content of the IHS3 & IHS4 Community Questionnaires. A “community” is defined as the village or urban location surrounding the enumeration area selected for inclusion in the sample and which most residents recognize as being their community. The IHS5 community questionnaire was administered to each community associated with the cross-sectional EAs interviewed. Identical to the IHS3 and IHS4 approach, to a group of several knowledgeable residents such as the village headman, the headmaster of the local school, the agricultural field assistant, religious leaders, local merchants, health workers and long-term knowledgeable residents. The instrument gathers information on a range of community characteristics, including religious and ethnic background, physical infrastructure, access to public services, economic activities, communal resource management, organization and governance, investment projects, and local retail price information for essential goods and services.

MARKET QUESTIONNAIRE The Market Survey consisted of one questionnaire which is composed of four modules. Module A: Market Identification, Module B: Seasonal Main Crops, Module C: Permanents Crops, and Module D: Food Consumption.

Cleaning operations

DATA ENTRY PLATFORM To ensure data quality and timely availability of data, the IHS5 was implemented using the World Bank’s Survey Solutions CAPI software. To carry out IHS5, 1 laptop computer and a wireless internet router were assigned to each team supervisor, and each enumerator had an 8–inch GPS-enabled Lenovo tablet computer. The use of Survey Solutions allowed for the real-time availability of data as the completed data was completed, approved by the Supervisor and synced to the Headquarters server as frequently as possible. While administering the first module of the questionnaire the enumerator(s) also used their tablets to record the GPS coordinates of the dwelling units. In Survey Solutions, Headquarters can then see the location of the dwellings plotted on a map of Malawi to better enable supervision from afar – checking both the number of interviews performed and the fact that the sample households lie within EA boundaries. Geo-referenced household locations from that tablet complemented the GPS measurements taken by the Garmin eTrex 30 handheld devices and these were linked with publically available geospatial databases to enable the inclusion of a number of geospatial variables - extensive measures of distance (i.e. distance to the nearest market), climatology, soil and terrain, and other environmental factors - in the analysis.

The range and consistency checks built into the application was informed by the LSMS-ISA experience in previous IHS waves. Prior programming of the data entry application allowed for a wide variety of range and consistency checks to be conducted and reported and potential issues investigated and corrected before closing the assigned enumeration area. Headquarters (NSO management) assigned work to supervisors based on their regions of coverage. Supervisors then made assignments to the enumerators linked to their Supervisor account. The work assignments and syncing of completed interviews took place through a Wi-Fi connection to the IHS5 server. Because the data was available in real time it was monitored closely throughout the entire data collection period and upon receipt of the data at headquarters, data was exported to STATA for other consistency checks, data cleaning, and analysis.

DATA MANAGEMENT The IHS5 Survey Solutions CAPI based data entry application was designed to stream-line the data collection process from the field. IHS5 Interviews were collected in “sample” mode (assignments generated from headquarters) as opposed to “census” mode (new interviews created by interviewers from a template) for the NSO to have more control over the sample.

The range and consistency checks built into the application was informed by the LSMS-ISA experience in previous IHS waves. Prior programming of the data

Abstract

This study aimed to (a) investigate the impacts of offering an additional year of pre-primary education in Bangladesh on child development outcomes (cognitive and social-emotional) and (b) examine the benefits relative to the costs of the program. The study also examined the mechanisms through which the Early Year Pre-School Program affected the outcomes of interest (e.g., children's school readiness) and the operational and community conditions for program implementation. This study provides evidence for the government of Bangladesh on how and how much the additional year of preschool benefits children, and at what cost. In addition to informing future policy in Bangladesh, this information may be useful for other countries considering similar programming. This survey provides endline findings for the evaluation and incorporates information from the baseline (2017) and midline (2018) surveys.

Geographic coverage

District of Meherpur

Analysis unit

Individuals, schools, and communities

Kind of data

Sample survey data [ssd]

Sampling procedure

We conducted a randomized controlled trial (RCT) of the EYPP to determine its impacts on children's learning and development. In 2016, we randomly assigned 100 schools in the Meherpur district of Bangladesh to either a treatment group receiving the EYPP (n = 50) or a no-program control group (n = 50). In October 2017, we conducted a census of the area around all 100 schools to identify children who lived within a 15-minute walk of the school and were in the target age range-that is, children expected to enroll in a typical government pre-primary in 2019 and enter Grade 1 in 2020. In the 50 treatment school catchment areas, children selected for the study were invited to participate in the EYPP at their local school during the 2018 school year and then would go on to government pre-primary as usual in 2019. In the 50 control school catchment areas, children selected for the study would be eligible to enroll in the government pre-primary as usual in 2019 but did not have the EYPP available to them the year before.

Sampling of Children: The target sample for our study included all children in the census areas born from January 1, 2013 - December 31, 2013 (because on-time enrollment in government pre-primary school for these children would be in January 2019). In most cases (exact figure unknown but in a substantial majority), children's dates of birth were verified with the Extended Program of Immunization (EPI) card or a birth certificate. If these documents were unavailable (even after parents were encouraged to search), enumerators recorded what the parent reported as the child's date of birth. We identified a total of 1,986 children born in 2013. We did not exclude any age-eligible children based on any other criteria (for example, children with disabilities were included in our sample pool).

AIR agreed with the World Bank that we would sample an average of 20 children in each of the 100 study communities. Many communities had fewer than 20 eligible children. Because EYPP centers will typically enroll up to 25 children, for both treatment and control communities with 25 or fewer children, we included all eligible children in the study (with parental consent). In the 20 communities (14 treatment and 6 control) with over 25 children in the target age range, we drew a random subsample of 25 for inclusion in this sample.

For this longitudinal study, we collected baseline, midline, and endline data. The midline and endline samples included schools, children, and families enrolled in the study at baseline; we did not add any new participants after baseline. Of the 1,856 enrolled children and families, 1,801 (97%) participated at all three timepoints.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

We administered the family questionnaire at baseline, midline, and endline. Its purpose was to gather information on the characteristics of the study children and their home environments and, at midline and endline, to determine whether and how the intervention affected the home learning environment. Nearly all items on this questionnaire were already used widely in Bangladesh as part of national household surveys. To administer this tool, enumerators read questions and response options aloud to respondents (parents or guardians of the study children). For some questions about family background, we asked the question only at baseline because the answers were unlikely to change across time and were unrelated to the intervention.

At each timepoint, we measured children's school readiness with the IDELA, which has been used widely in Bangladesh. A trained enumerator administered the assessment to children one on one. At endline, we also added subtasks from the Early Grade Reading Assessment (EGRA) and the Early Grade Mathematics Assessment (EGMA) as used in Bangladesh. Because the EGRA and EGMA were designed for children in Grade 1 and higher, we did not expect the study children to perform well, but wanted to ensure that we were prepared should we have ceiling issues with children's performance on the IDELA.

The endline parent questionnaire can be found under the 'Documentation' tab. To obtain a free copy of the IDELA questionnaire please go to https://idela-network.org/the-idela-tool/ and register.

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: - Office editing and coding - During data entry - Structure checking and completeness - Secondary editing - Structural checking of STATA data files

Response rate

97% (n = 1801 children)

The American Community Survey Education Tabulation (ACS-ED) is a custom tabulation of the ACS produced for the National Center of Education Statistics (NCES) by the U.S. Census Bureau. The ACS-ED provides a rich collection of social, economic, demographic, and housing characteristics for school systems, school-age children, and the parents of school-age children. In addition to focusing on school-age children, the ACS-ED provides enrollment iterations for children enrolled in public school. The data profiles include percentages (along with associated margins of error) that allow for comparison of school district-level conditions across the U.S. For more information about the NCES ACS-ED collection, visit the NCES Education Demographic and Geographic Estimates (EDGE) program at: https://nces.ed.gov/programs/edge/Demographic/ACSAnnotation values are negative value representations of estimates and have values when non-integer information needs to be represented. See the table below for a list of common Estimate/Margin of Error (E/M) values and their corresponding Annotation (EA/MA) values.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.-9An '-9' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.-8An '-8' means that the estimate is not applicable or not available.-6A '-6' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.-5A '-5' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate.-3A '-3' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.-2A '-2' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.

Abstract

To understand the socio-economic impact of COVID-19 and associated government measures over the long term, the fourth round of the COVID-19 National Panel Phone Survey 2020 was collected by the National Institute of Statistics of Djibouti (INSD) between March 11 and April 25, 2021. Various channels of impact are explored such as job loss, availability and price changes of basic food items, ability to access healthcare and education, food insecurity. The survey also includes a section on gender issues, including time-use and decision making, as well as a section on attitudes towards COVID-19 Vaccine. Within households, a respondent was chosen at random between the household heads and spouses, allowing comparison between female and male respondents in the sample. Further, the education questions are asked for a randomly chosen boy or girl within the households that have children.

Geographic coverage

Urban areas only. The survey is representative of the bottom 80 percent of the consumption distribution of the national households (thus the top 20 percent are excluded). It is representative by poverty status and by three domains of Balbala, rest of Djibouti city and urban areas outside Djibouti city.

Analysis unit

• Household
• Individual

Universe

The survey covers national households that reported telephone numbers, are included in the social registry data collected by the Ministry of Social Affairs and Solidarity (MASS) and have been interviewed after 2017.

Kind of data

Sample survey data [ssd]

Sampling procedure

As a recently conducted representative household survey with telephone numbers was not available, data from the national social registry collected by the Ministry of Social Affairs (MASS) was used as the sampling frame of the national sample. The social registry is an official database of households in Djibouti that may benefit from public transfers and be particular targets of poverty alleviation efforts. The sample consists of households drawn randomly from the social registry data restricted to urban households having at least one phone number and interviewed after July 1, 2017. The sample design is a one-stage probability sample selected from the sampling frame and stratified along two dimensions: the survey domain (three categories) and the poverty status (binary). This yields six independent strata. Within each stratum, households are selected with the same ex-ante probability but this differs across strata. The fourth wave sample consists of 1,561 respondents, 1,122 of which are panel households interviewed in wave 3, and 439 replacement households. The response rate of the whole sample stands at 71.8 percent. Unlike the third wave, in the fourth wave, households who were not reachable in wave 3 but were part of the first two waves, were considered as part of the sampling frame

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire of the fourth round is adapted from the questionnaire of the third round and in accordance with the template questionnaire prepared by the Poverty and Equity GP to measure the impact of COVID-19 on household welfare. It was designed in French and dispensed in local languages (Afar, Arabic, Somali, French or other). The questionnaire includes the following sections: - Household Roster - Employment - Household's Income Sources - Access to Basic Goods - Access to Healthcare and Education - Food Insecurity - Vaccine Attitudes - Gender

Cleaning operations

The CsPro CATI data entry application helped to enforce skip and range patterns during data collection. Standard consistency checks (like age differences between parents and children and unicity of household heads) were carried out at the time of the data collection. Because the entry application was strictly system-controlled, complete cases including missing items were avoided. The various checks resulted in a limited need for secondary data editing, which eventually entailed two main steps from the WB team. First, duplicated names of household members, who were otherwise distinct, were corrected by adding a suffix “bis” to the names. Second, after analysis of text responses mentioned in the residual “other” categories, a few items codes were adjusted (not exceeding 10 in any category).

Response rate

The response rate of the whole sample stands at 71.8 percent, with variations across location. In Balbala region, the rate was 75.1 percent, in the rest of Djibouti City, 71.6 percent, in other urban areas, it was 68.8 percent.

The 2014 Head Start Family and Child Experiences Survey, or FACES 2014, is the sixth in a series of national studies of Head Start, with earlier studies conducted in 1997, 2000, 2003, 2006, and 2009. This release includes nationally representative samples of Head Start programs and centers, classrooms, children and their families through spring of 2017. Data from surveys of Head Start program and center directors, classroom teachers, and parents provided descriptive information about program policies and practices, classroom activities, and the background and experiences of Head Start staff and families. Classroom observations were used to assess the quality of Head Start classrooms. Children in the study participated in a direct assessment that provided a picture of their school readiness skills at different time points. FACES 2014 used a new study design that differs from earlier rounds of FACES in several important ways: (1) it included larger program and classroom samples, (2) all data were collected in a single program year, (3) the baseline sample of children included both children enrolled in their first and second year of Head Start, and (4) several special studies were conducted along with the main (Core) study to collect more detailed information about a given topic, to study new populations of Head Start programs and participants, and to evaluate measures for possible use in future rounds of FACES. For example, the Family Engagement Plus study collected information from parents and staff (teachers and family services staff) on family engagement efforts and service provision in Head Start programs. The Office of Head Start, the Administration for Children and Families, other federal agencies, local programs, and the public have depended on FACES for valid and reliable national information on (1) the skills and abilities of Head Start children, (2) how Head Start children's skills and abilities compare with preschool children nationally, (3) Head Start children's readiness for and subsequent performance in kindergarten, and (4) the characteristics of the children's home and classroom environments. The FACES study was designed to enable researchers to answer a wide range of research questions that are crucial for aiding program managers and policymakers. Some of the questions that are central to FACES include: What are the demographic characteristics of the population of children and families served by Head Start? How has the population served by Head Start changed? What are the experiences of families and children in the Head Start program? How have they changed? What are the cognitive and social skills of Head Start children at the beginning and end of the program year? Has Head Start program performance improved over time? What are the qualifications of Head Start teachers in terms of education, experience, and credentials? Are average teacher education levels rising in Head Start? What is the observed quality of Head Start classrooms as early learning environments, including the level and range of teaching and interactions, provisions for learning, emotional and instructional support, and classroom organization? How has quality changed over time? What program- and classroom-level factors are related to observed classroom quality? How is observed quality related to children's outcomes and developmental gains? The User Guide provides detailed information about the FACES 2014 study design, execution, and data to inform and assist researchers who may be interested in using the data for future analyses. The following items are provided in the User Guide as appendices. Appendix A - Elements Of The FACES Design And Key Measures Used (And Child Outcomes Captured): FACES 1997 - FACES 2014 Appendix B - Copyright Permissions Appendix C - Instrument Content Matrices Appendix D - Instruments Appendix E - Spring 2015 Center/Program Codebook Appendix F - Spring 2015 Classroom/Teacher Codebook Appendix G - 2014-2015 Child Codebook Appendix H - Spring 2015 Family Engagement Family Service Staff Interview Codebook Appendix I - Spring 2015 Family Engagement Parent Interview Codebook Appendix J - Spring 2017 Center/Program Codebook Appendix K - Spring 2017 Classroom/Teacher Codebook Appendix L - Descriptions of Constructed/Derived Variables Appendix M - Synthetic Estimation for Child Growth Across Two Years

Add Health Parent Study (2015-2017) gathered social, behavioral, and health survey data in 2015-2017 on a probability sample of the "https://addhealth.cpc.unc.edu/" Target="_blank">Add Health parents who were originally interviewed in 1995. Data for 2,013 Wave I parents, ranging in age from 50-80 years and representing 2,244 Add Health sample members, are available. Add Health Parent Study Wave I Parents were the biological, adoptive, or stepparent of an Add Health child; not deceased or incarcerated at the time of Parents (2015-2017) sampling; and had at least one Add Health child who is also not deceased at the time of Parents (2015-2017) sampling. The Add Health Parent Study interview also gathered survey data on the current cohabiting Spouse or Partner of Wave I Parents who completed the interview. Nine hundred eighty-eight (988) current Spouse/Partner interviews are available. These data can be linked with Wave I parent data, and corresponding Add Health respondents at Waves I - V.

The Add Health Parent Study (2015-2017) interview is a comprehensive survey of Add Health parents' family relations, education, religious beliefs, physical and mental health, social support, and community involvement experiences. In particular, the study was designed to improve the understanding of the role that families play through socioeconomic channels in the health and well-being of the older, parent generation and that of their offspring. This unique data set supports the analyses of intergenerational transmissions of (dis)advantage that have not been possible to date. Add Health Parent Study data permits the examination of both short-term and long-term linkages and interactions between parents and their adult children.

For more information, please visit the Add Health Parent Study official website "https://addhealth.cpc.unc.edu/about/#studies-satellite" Target="_blank">here.

This file is the Household and Family Roster data collected 2015-2017 from Add Health Wave I Parent. This file is also organized on the ID of the Add Health child, so rosters are duplicated when an interviewed Wave I Parent has multiple Add Health children. Users who want to analyze roster data on the parent level (one roster per parent) can eliminate duplicate rosters by using a variable provided for that purpose (see details of file contents). The name of the file is "prprnt2" on official Add Health "https://www.cpc.unc.edu/projects/addhealth/documentation/restricteduse/datasets#parent_study_files" Target="_blank">data documentation.

Add Health Parent Study (2015-2017) gathered social, behavioral, and health survey data in 2015-2017 on a probability sample of the "https://addhealth.cpc.unc.edu/" Target="_blank">Add Health parents who were originally interviewed in 1995. Data for 2,013 Wave I parents, ranging in age from 50-80 years and representing 2,244 Add Health sample members, are available. Add Health Parent Study Wave I Parents were the biological, adoptive, or stepparent of an Add Health child; not deceased or incarcerated at the time of Parents (2015-2017) sampling; and had at least one Add Health child who is also not deceased at the time of Parents (2015-2017) sampling. The Add Health Parent Study interview also gathered survey data on the current cohabiting Spouse or Partner of Wave I Parents who completed the interview. Nine hundred eighty-eight (988) current Spouse/Partner interviews are available. These data can be linked with Wave I parent data, and corresponding Add Health respondents at Waves I - V.

The Add Health Parent Study (2015-2017) interview is a comprehensive survey of Add Health parents' family relations, education, religious beliefs, physical and mental health, social support, and community involvement experiences. In particular, the study was designed to improve the understanding of the role that families play through socioeconomic channels in the health and well-being of the older, parent generation and that of their offspring. This unique data set supports the analyses of intergenerational transmissions of (dis)advantage that have not been possible to date. Add Health Parent Study data permits the examination of both short-term and long-term linkages and interactions between parents and their adult children.

For more information, please visit the Add Health Parent Study official website "https://addhealth.cpc.unc.edu/about/#studies-satellite" Target="_blank">here.

The file contains data from Wave I Parent's family health history leave-behind forms. The name of the file is "fhhp2" on official Add Health "https://www.cpc.unc.edu/projects/addhealth/documentation/restricteduse/datasets#parent_study_files" Target="_blank">data documentation.

The 2020-2021 School Neighborhood Poverty Estimates are based on school locations from the 2020-2021 Common Core of Data (CCD) school file and income data from families with children ages 5 to 17 in the U.S. Census Bureau’s 2017-2021 American Community Survey (ACS) 5-year collection. The ACS is a continuous household survey that collects social, demographic, economic, and housing information from the population in the United States each month. The Census Bureau calculates the income-to-poverty ratio (IPR) based on money income reported for families relative to the poverty thresholds, which are determined based on the family size and structure. Noncash benefits (such as food stamps and housing subsidies) are excluded, as are capital gains and losses. The IPR is the percentage of family income that is above or below the federal poverty level. The IPR indicator ranges from 0 to a top-coded value of 999. A family with income at the poverty threshold has an IPR value of 100. The estimates in this file reflect the IPR for the neighborhoods around schools which may be different from the neighborhood conditions of students enrolled in schools.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

Abstract

The Nigeria Multiple Indicator Cluster Survey (MICS) 2016-17 was conducted by the National Bureau of Statistics (NBS) in collaboration with United Nations Children's Fund (UNICEF). It is part of the global MICS exercise aimed primarily to collect data on main indicators related to survival, development and protection of children, women and men. In Nigeria, the current survey is the fifth round, having previously conducted the survey in 1995, 1999, 2007 and 2011. The survey serves as a reliable information source and a sound basis for informed decision-making for planners, policy-makers and programme implementers.

More specifically, Nigeria MICS 2016-17 collected data on indicators related to child mortality; child and maternal nutrition; child health, reproductive health; water and sanitation; child development; literacy and education; child protection; knowledge of HIV and AIDS; access to mass media and use of information and communication technology among others. The survey provides estimated disaggregation of Nigeria by states, geo political zones, sex, age, residence (urban and rural), mother's education and wealth quintiles. For this round of Nigeria MICS, water quality testing was also included for the first time and has generated valuable data on the quality of drinking water consumed at the household level. This was done by subjecting water used in the household for cooking and drinking to microbiological parameters test. (related to E.coli and coliform).

The current round of MICS has been expanded in content and scope to include questionnaires for individual men and water quality test. New modules were also introduced such as tobacco and alcohol use, life satisfaction, access to mass media and use of information and communication technology. Another innovation introduced in the MICS 2016-17 also included the pilot testing of further analysis and disaggregation of state data up to senatorial district levels (as can be seen in Lagos and Kano states) with the aim of providing data that can be used for better planning and programming at the grassroots. The climax of the new innovations was the successful combination and implementation of two National surveys (The Multiple Indicator Cluster Survey and the National Immunization Coverage Survey - MICS/NICS) jointly executed together.

Nigeria MICS data will aid in monitoring progress towards post Millennium Development Goals (MDGs) as well as various international agreements such as A World Fit for Children (WFFC). The survey's findings also provide a baseline for Sustainable Development Goals (SDGs) for Nigeria. I am confident that the findings from Nigeria MICS 2016-17 will be instrumental in formulating sectoral plans and shaping policies toward the post-MDG agenda. I look forward to see the results and the dataset being used widely and effectively by the public, most especially the policy-makers, planners, researchers, development partners and Non Governmental Organizations (NGOs) to formulate and monitor programmes and strategies.

The primary objectives of Multiple Indicator Cluster Survey (MICS) Nigeria 2016-17 are:

• To provide up-to-date information for assessing the situation of children and women in Nigeria;

• To generate data for the critical assessment of the progress made in various programme areas, and to identify areas that require more attention;

• To contribute to the generation of baseline data for the SDG;

• To furnish data needed for monitoring progress toward goals established in the post Millennium Declaration and other internationally agreed goals, as a basis for future action;

• To provide disaggregated data to identify disparities among various groups to enable evidence based actions aimed at social inclusion of the most vulnerable;

Geographic coverage

National converage

Analysis unit

Household Women Men Children under 5

Universe

the survey covered - all household - all Women (15-49 years) - men (15-49 years) - children under five

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the Nigeria MICS 2016-17 was designed to provide estimates for a large number of indicators on the situation of children and women at the national, rural/urban, states as well as the 6 geo-political zones of Nigeria. The states within each zone were identified as the main sampling Strata while the Enumeration Areas (EAs) within each state were identified as the Primary Sampling Units (PSUs). The EAs for the survey were selected from the National Integrated Survey of Households round 2 (NISH2) master sample, based on a list of EAs prepared for the 2006 Population Census. Two stage sampling was conducted with the first stage being the selection of EAs within the strata while the second stage was the selection of households within each EAs.

Within each state, 60 EAs were selected systematically from the NISH2 master sample, apart from Lagos and Kano states where 120 EAs (respectively) were sampled. The larger sample size for Lagos and Kano states was based on requests by the respective State governments to have sufficient sample to enable disaggregation of indicators at senatorial district level. After a household listing was carried out within the selected EAs, a systematic sample of sixteen (16) households was drawn in each sample EA. The sample was stratified by state and is not self-weighting. For reporting of results, sample weights were applied. Out of 2340 EAs selected for coverage, 2,239 were listed and covered during the fieldwork period. A total of 101 EAs could not be enumerated because they were inaccessible due to insecurity especially in Borno, Yobe and Adamawa states. A more detailed description of the sample design can be found in Appendix A,

The sample size for the Nigeria NICS was calculated as 44,960 households.

The Nigeria MICS 2016-17 was implemented jointly with the National Immunisation Coverage Survey (NICS) which was designed to provide estimates of vaccine coverage for the country. However, the sample size for MICS 2016-17 was not sufficient to estimate state level vaccination coverage for children aged 12 to 23 months in twenty states, namely: Abia, Akwa ibom, Anambra, Bayelsa, Benue, Cross River, Delta, Edo, Ekiti, Enugu, Imo, Kogi, Kwara, Ogun, Ondo, Osun, Oyo, Plateau, Rivers and FCT (Abuja). Consequently, supplemental sampling was conducted to meet the requirements for vaccine coverage estimation, in these twenty states.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four sets of questionnaires were used in the MICS 2016-17: 1. Household questionnaire - used to collect basic demographic information on all the household members (usual residents) and household characteristics; 2. Individual women questionnaire - administered in each household to all women age 15-49 years; 3. Individual men questionnaire - administered to all men age 15-49 years in every other(one in every two) households; 4. Under-5 children questionnaire - administered to mothers or caretakers of all children under 5 years of age2 living in sampled households.

The questionnaires are based on the MICS5 questionnaire model (English version), customised and pre-tested in Cross River, Enugu, Gombe, Lagos, Kaduna, Kano, Nasarawa and Oyo states in April, 2016. Based on the results of the pre-test, modifications were made to the wording of the questionnaires. A copy of the Nigeria MICS questionnaires is provided in Appendix F.

In addition to the administration of questionnaires, salt iodization and water quality tests were conducted. Weight and height of children age under 5 years were also measured.. Details of the tests and measurements are provided in the respective sections of the report.

Cleaning operations

Data were analysed using the Statistical Package for Social Scientists (SPSS) software, Version 21. Model syntax and tabulation plans developed by UNICEF MICS team were customized and used for this purpose.

Response rate

Out of 37,440 households sampled, 35,747 households were visited, 34,289 were found to be occupied and 33,901 were successfully interviewed, representing a household response rate of 98.9 percent.

In the interviewed households, 36,176 women (age 15-49 years) were identified. Of these, 34,376 were successfully interviewed, yielding a response rate of 95.0 percent within the interviewed households.

The survey also sampled men (age 15-49), but required only a subsample. All men (age 15-49) were identified in 17,868 households selected for the men questionnaire; 16,514 men (age 15-49 years) were listed in the household questionnaires. Questionnaires were completed for 15,183 eligible men, which corresponds to a response rate of 91.9 percent within eligible interviewed households.

There were 28,578 children under age five listed in the household questionnaires. Questionnaires were completed for 28,085 of these children, which corresponds to a response rate of 98.3 percent within interviewed households.

Overall response rates of 93.9, 90.9 and 97.2 are calculated for the individual interviews of women, men, and under-5s, respectively

Sampling error estimates

The sample of respondents selected in the Multiple Indicator Cluster Survey (MICS) 2016 is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between the estimates from all possible

Abstract

The recent global economic slowdown, caused by the COVID-19 pandemic, created an urgent need for timely data to monitor the socioeconomic impacts of the pandemic. Tanzania is among other countries in the world which are affected by the recent global economic slowdown, caused by the COVID-19 pandemic. Therefore, there is an urgent need for timely data to monitor and mitigate the socio-economic impacts of the crisis in the country. Responding to this need, the National Bureau of Statistics (NBS) and the Office of the Chief Government Statistician (OCGS), Zanzibar in collaboration with the World Bank and Research on Poverty Alleviation (REPOA) implemented a rapid household telephone survey called the Tanzania High-Frequency Welfare Monitoring Survey (HFWMS).

Thus, the main objective of the survey is to obtain timely data that is critical for evidence-based decision making aimed at mitigating the socio-economic impact of the downturn caused by COVID-19 pandemic by filling critical gaps of information that can be used by the government and stakeholders to help design policies to mitigate the negative impacts on its population.

Geographic coverage

National

Analysis unit

Households Individuals

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

Phase one of the Tanzania High Frequency Welfare Monitoring Panel Survey (THFWMPS I) draws its sample from various previous face-to-face surveys, including the Mainland Household Budget Survey (HBS) 2017/18, the Zanzibar HBS 2019/20, and the National Panel Survey (NPS) 2014. The inclusion of telephone numbers from most participants of these surveys provides the foundation for the survey sample.

The target for monthly sample completion is approximately 3,000 households. The NPS serves as the primary sample frame, supplemented by the Mainland and Zanzibar HBS. For THFWMPS Phase II, the sample frame comprises respondents from Phase I who did not explicitly refuse to participate (2,200 households), alongside additional households from the 2021 Booster sample of NPS Wave 5 (NPS 5) households with available phone numbers.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Each survey round consists of one questionnaire - a Household Questionnaire administered to all households in the sample.

Baseline The questionnaire gathers information on demographics; employment; education; access to basic services; food security; TASAF; and mental health. The contents of questionnaire are outlined below:

• Cover: Household identifiers and enumerator identifiers.
• Interview Information: Details of call attempts, result and respondent of call attempt, interview consent, date and time of call back, phone numbers called, the information of the person that the listed phone number belongs to.
• Basic Information: Roster of members of the household, relationship to the household head, gender, age, relationship to head, reason for joining the household if new, and reason for leaving the household if left.
• Employment: Status and information of income-generating activities (wage work, family business and farming), reason for stopped working, reason for not able to perform activities as usual, and reason for reduced revenue from family business.
• Education: School attendance, type of school attended, learning activities of children at home, return to school, contact with children’s teachers during school closure.
• Access to Basic Services:Household’s access to staple food (maize grain, cassava, rice, and maize flour), medical treatment, and reasons for not being able to access the services.
• Food Security: Household’s food security status during the last 30 days.
• TASAF: Households access to the TASAF money, use of the money received, challenges encountered in accessing the funds.
• Mental Health: Information on 8 items pertaining to measuring mental health.
• Recontact: Data on how the household can be recontacted in the future.
• Interview Results: Result of interview including observation notes by enumerator regarding the interview, respondent and language of interview.

Round 2 The questionnaire gathers information on demographics; employment; non-farm enterprise; tourism; education; access to health services; and TASAF. The contents of questionnaire are outlined below:

• Cover: Household identifiers and enumerator identifiers.
• Interview Information: Details of call attempts, result and respondent of call attempt, interview consent, date and time of call back, phone numbers called, the information of the person that the listed phone number belongs to.
• Basic Information: Roster of members of the household, relationship to the household head, gender, age, relationship to head, reason for joining the household if new, and reason for leaving the household if left.
• Employment: Status and information of income-generating activities (wage work, family business and farming), reason for stopped working, and reason for not able to perform activities as usual.
• Non-farm Enterprise: Status and information of non-farm income-generating activities, reason for stopped operating, reason for not able to perform activities as usual, and reason for reduced revenue from family business.
• Tourism: Employment of household members in tourism sector, and who benefits from tourism.
• Education (selected members aged 4-18 years): School attendance, reason for not attending, grade attending, type of school, absence and reason for being absent.
• Access to Health Services: Women’s access to pre-natal/post-natal care, household’s access to preventative care and medical treatment, and reasons for not being able to access the services.
• TASAF: Households access to the TASAF money, use of the money received, challenges encountered in accessing the funds.
• Recontact: Data on how the household can be recontacted in the future.
• Interview Results: Result of interview including observation notes by enumerator regarding the interview, respondent and language of interview

Round 3 The questionnaire gathers information on demographics; employment (respondent and other household members); non-farm enterprise; credit; women savings; and shocks and coping. The contents of questionnaire are outlined below:

• Cover: Household identifiers and enumerator identifiers.
• Interview Information: Details of call attempts, result and respondent of call attempt, interview consent, date and time of call back, phone numbers called, the information of the person that the listed phone number belongs to.
• Basic Information: Roster of members of the household, relationship to the household head, gender, age, relationship to head, reason for joining the household if new, and reason for leaving the household if left.
• Employment (respondent): Status and information of income-generating activities (wage work, family business and farming), reason for stopped working, and reason for not able to perform activities as usual.
• Employment (other members): Status in employment (current and 2020), consistency of work in 2020, why currently not working, job search, change in jobs, actual job.
• Non-farm Enterprise: Status and information of non-farm income-generating activities, reason for stopped operating, reason for not able to perform activities as usual, and reason for reduced revenue from family business.
• Credit: Household’s debts status since the beginning of the coronavirus crisis; use of loan, ability to repay loan when their scheduled payment is due.
• Women Savings: Women having bank accounts to financial institutions and changes in their savings since the start of the pandemic.
• Shocks and Coping: Shocks that affected household since the baseline interview and their coping strategies.
• Recontact: Data on how the household can be recontacted in the future.
• Interview Results: Result of interview including observation notes by enumerator regarding the interview, respondent and language of interview.

Round 4 The questionnaire gathers information on demographics; employment; non-farm enterprise; digital technology; and income changes. The contents of questionnaire are outlined below:

• Cover: Household identifiers and enumerator identifiers.
• Interview Information: Details of call attempts, result and respondent of call attempt, interview consent, date and time of call back, phone numbers called, the information of the person that the listed phone number belongs to.
• Basic Information: Roster of members of the household, relationship to the household head, gender, age, relationship to head, reason for joining the household if new, and reason for leaving the household if left.
• Employment (respondent): Status and information of income-generating activities (wage work, family business and farming), reason for stopped working, and reason for not able to perform activities as usual.
• Non-farm Enterprise: Status and information of non-farm income-generating activities, reason for stopped operating, reason for not able to perform activities as usual, and reason for reduced revenue from family business.
• Income changes: Household’s sources of livelihood.
• Digital Technology: Household ownership of phones, computers and digital devices, access to internet and challenges in accessing internet
• Recontact: Data on how the household can be recontacted in the future.
• Interview Results: Result of interview including observation notes by enumerator regarding the interview, respondent and language of interview.

Round 5 The questionnaire gathers information on demographics;