This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2020 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2020. The NCES Education Demographic and Geographic Estimate (EDGE) program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include: City - Large (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more. City - Midsize (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000. City - Small (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000. Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more. Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000. Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000. Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area. Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area. Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area. Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster. Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster. Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.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.

This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2015 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2015. The NCES Education Demographic and Geographic Estimate (EDGE) program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:

Large City (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more.Midsize City (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000.Small City (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000.Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more.Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000.Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000.Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area.Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area.Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area.Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster.Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster.Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.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.

Use this application to identify locale classifications for public, private, and postsecondary schools.What are locales? Locales are general geographic indicators that reflect the type of community where a school is located. NCES creates and uses the indicators for a variety of statistical purposes, and some educational programs use them to identify schools in specific types of areas.The locale data layer used in the Locale Lookup was produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program. The data provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2016 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2016. The NCES Education Demographic and Geographic Estimate (EDGE) program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:Large City (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more.Midsize City (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000.Small City (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000.Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more.Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000.Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000.Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area.Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area.Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area.Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster.Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster.Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.

This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2014 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2014. The NCES EDGE program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:Large City (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more.Midsize City (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000.Small City (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000.Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more.Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000.Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000.Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area.Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area.Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area.Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster.Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster.Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.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.

This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, and rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:City - Large (11): Territory inside an Urban Area with a population of 50,000 or more and inside a Principal City with population of 250,000 or more.City - Midsize (12): Territory inside an Urban Area with a population of 50,000 or more and inside a Principal City with population less than 250,000 and greater than or equal to 100,000.City - Small (13): Territory inside an Urban Area with a population of 50,000 or more and inside a Principal City with population less than 100,000.Suburb – Large (21): Territory outside a Principal City and inside an Urban Area with population of 250,000 or more.Suburb - Midsize (22): Territory outside a Principal City and inside an Urban Area with population less than 250,000 and greater than or equal to 100,000.Suburb - Small (23): Territory outside a Principal City and inside an Urban Area with population less than 100,000. Town - Fringe (31): Territory inside an Urban Area with a population less than 50,000 that is less than or equal to 10 miles from an Urban Area with a population of 50,000 or more.Town - Distant (32): Territory inside an Urban Area with a population less than 50,000 that is more than 10 miles and less than or equal to 35 miles from an Urban Area with a population of 50,000 or more.Town - Remote (33): Territory inside an Urban Area with a population less than 50,000 that is more than 35 miles of an Urban Area with a population of 50,000 or more.Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urban Area of 50,000 or more, as well as rural territory that is less than or equal to 2.5 miles from an Urban Area with a population less than 50,000.Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urban Area with a population of 50,000 or more, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Area with a population less than 50,000.Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urban Area with a population of 50,000 or more and is also more than 10 miles from an Urban Area with a population less than 50,000.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.

Nationally, many school districts are facing a teacher workforce sustainability crisis, and job retention for novice teachers of color represents a key area of focus for educational leaders and policymakers. In this study, we draw on nine years of administrative data from Texas K-12 public schools to better understand how teacher-principal ethnoracial matching is associated with patterns of teacher retention and system-exit. Teacher labor markets are geographically small, so we link data from the National Center for Education Statistics containing geographic locale information to explore how the relationship between ethnoracial matching and novice teacher career outcomes varies across urban, suburban, rural, and town school contexts. We find that matching is associated with an increase in the probability of retention and a decrease in the probability of system-exit, with important variation for novice Black and Latinx teachers working in some non-urban school locales.

Abstract

The survey is the follow-up of the Diagnostic Review on Consumer Protection and Financial Literacy conducted by the World Bank in 2008-2009. The Diagnostic Review in Romania was the fourth in a World Bank-sponsored pilot program to assess consumer protection and financial literacy in developing and middle-income countries.1 The objectives of this Review were three-fold to: (1) refine a set of good practices for assessing consumer protection and financial literacy, including financial literacy; (2) conduct a review of the existing rules and practices in Romania compared to the good practices; and (3) provide recommendations on ways to improve consumer protection and financial literacy in Romania. The Diagnostic Review was prepared at the request of the National Authority for Consumers' Protection (ANPC), whose request was endorsed by the Ministry of Economy and Finance. Support was provided by the National Bank of Romania (BNR), which supervises banks and non-bank credit institutions. Further assistance was given by the supervisory commissions for securities (CNVM), insurance (CSA) and private pensions (CSSPP).

The Diagnostic Review found that the basic foundations needed for consumer protection and financial literacy are in place in Romania but they benefit from further strengthening support. The Review proposes improvements in six areas: consumer awareness, information and disclosure for consumers, professional competence, dispute resolution, financial education and financial literacy surveys.

Consequently, in 2010 the World Bank commissioned a nation-wide survey of the levels of financial literacy. A consultant (sociologist Manuela Sofia Stanculescu) developed the survey methodology (sampling methodology and questionnaire) in line with the Financial Literacy Survey in Russia (the World Bank, 2008) and the baseline survey Financial Capability in the UK (Financial Services Authority, 2005).2 The final form of the questionnaire was agreed with representatives of the National Bank of Romania (BNR), the Romanian Banking Institute (IBR), the National Authority for Consumers' Protection (ANPC), and the Financial Companies Association in Romania (ALB). The Institute for World Economy (Romanian Academy) collected the data in May 2010.

The main objective of this work is the establishment (and later the evaluation) of a well targeted national program of financial education.

Geographic coverage

National

Analysis unit

Household, individual

Universe

Non-institutionalized persons aged 18 or older

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the survey is probabilistic, two-stage, stratified, representative at national level with an error of +/- 3% at a 95% confidence level.

The sample is based on two stratification criteria: (i) historical region (8 regions) and (ii) type of locality (7 types depending on the city size, in urban areas, and on the synthetic index of community development,4 in the rural ones).

The sample volume is 2048,5 out of which 148 cases represent a boost of persons aged 16, 17 or those had their 18th birthday after November 2009.6 Respondents were randomly selected from electoral registers corresponding to 185 voting sections (randomly selected), located in 141 localities (77 communes, 63 towns/cities and the capital Bucharest).

The sample includes a slight over-representation of men, rural respondents, and elderly particularly due to the boost of young but also to the fact that people left abroad concentrate among the 25-44 age category. Nevertheless, the sample fairly reproduces the structure (by gender, age categories and area of residence) of the country population 16+ years according to the data for 2009 provided by the National Institute for Statistics. Socio-demographic structure of the sample is presented in table 3 of the survey report.

Demographic data and data regarding the use of financial services were collected for all members of respondents? households. In the respondents? households live 5406 persons overall. This extended sample has also a slight over-representation of rural respondents and an under-representation of children (0-14 years) and persons 25-24 years (most probably young people who left abroad with children).

MORE INFORMATION ON THE SAMPLING METHODOLOGY

Sample volume: 2,200 non-institutionalized persons aged 18 or older. In addition, the sample will be boosted with 180 persons aged 16-18 years old. Overall, at least 2,000 valid questionnaires should be completed during fieldwork.

Type of the sample: Probabilistic, two-stage, stratified, representative at national level, with an error of +/- 2.8% at a 95% confidence level.

Stratification criteria: The sampling scheme is based on two stratification criteria

(a) Historical region (8 regions) (b) Type of locality, with 7 theoretical strata

i. Urban areas - 4 strata 1. very small towns under 30 thou inhabitants 2. small towns 30,001-100 thou inhabitants 3. medium cities 100,001-199 thou inhabitants 4. large cities 200 thou inhabitants or more

ii. Rural areas - 3 strata determined based on the synthetic index of community development 37 1. poor communes (the 30% communes with the lowest level of development within the country) 2. medium developed communes 3. developed communes (the 30% communes with the highest level of development within the country).

Sampling stages: The sampling scheme includes two stages.

Sampling units: There are two sampling units corresponding to the two sampling stages. In the first sampling stage, voting sections are selected and in the second stage, non-institutionalized persons aged 18 years or more.

Selection: Random selection in all sampling stages.

Sampling scheme: In the first stage the sample is distributed proportionally with the volume of population for each of the 56(= 8 x 7) theoretical strata different from zero.

The corresponding number of voting sections for each strata is determined taking into account on the one hand, the volume of each strata sub-sample (= sample size x share of total population in that strata) and, on the other hand, a minimum level of 10 questionnaires for each sampling point. The voting sections which will represent sampling points are then randomly selected based on the exhaustive national list of voting sections (the latest available from the Permanent Electoral Authority).

The sample has 188 sampling points (voting sections) of which 104 are in urban areas, and 84 are in rural localities, including the capital city.

For each sampling point is computed the number of corresponding questionnaires by dividing the strata sub-sample by the number of sampling points of that strata. In the second sampling stage, the electoral registers corresponding to the voting sections (selected as sampling points) are used as sampling frame. Non-institutionalized persons aged 18 or more are randomly selected from the electoral registers based on the mechanical step method.

In those localities where the electoral registers are not available (or the municipality do not grant access), the random route method will be used. All these cases will be specified and explained in the fieldwork report, except for Bucharest, where the random route method will be used for all voting sections, as the rate of replacement from electoral registers is high in all national representative surveys.

The electoral registers include only persons 18 years or more. Accordingly, the sample will include a boost of persons aged 16, 17 or persons that had their 18th birthday after November 2009.39 For each voting section, one person aged 16-18 years will be added. They will be selected based on the random route method.

Mode of data collection

Face-to-face [f2f]

Response rate

The overall response rate of the survey is 95.2%. More detailed information is provided in "Table 2 Response rates and quality of the sampling frame by sampling method (%) " of the survey report.

Abstract

Malawi Conditional Cash Transfer Program (CCT) is a randomized cash transfer intervention targeting young women in Zomba region. The program provides incentives to current schoolgirls and recent dropouts to stay in or return to school. The incentives include average payment of US$10 a month conditional on satisfactory school attendance and direct payment of secondary school fees.

The CCT program started at the beginning of the Malawian school year in January 2008 and continued until November 2009. The impact evaluation study was designed to evaluate the impact of the program on various demographic and health outcomes of its target population, such as nutritional health, sexual behavior, fertility, and subsequent HIV risk.

Baseline data collection was administered from September 2007 to January 2008. The research targeted girls and young women, between the ages of 13 and 22, who were never married. Overall, 3,810 girls and young women were surveyed in the first round. The follow-up survey was carried out from October 2008 to February 2009. The third round was conducted between March and September 2010, after Malawi Conditional Cash Transfer Program was completed. The fourth round started in April 2012 and will continue until September 2012.

Datasets from the baseline round are documented here.

Enumeration Areas (EAs) in the study district of Zomba were selected from the universe of EAs produced by the National Statistics Office of Malawi from the 1998 Census. 176 enumeration areas were randomly sampled out of a total of 550 EAs using three strata: urban areas, rural areas near Zomba Town, and rural areas far from Zomba Town.

Baseline schoolgirls in treatment enumeration areas were randomly assigned to receive either conditional or unconditional transfers, or no transfers at all. A multi-topic questionnaire was administered to the heads of households, where the selected sample respondents resided, as well as to girls and young women.

Geographic coverage

Zomba district.

Zomba district in the Southern region was chosen as the site for this study for several reasons. First, it has a large enough population within a small enough geographic area rendering field work logistics easier and keeping transport costs lower. Zomba is a highly populated district, but distances from the district capital (Zomba Town) are relatively small. Second, characteristic of Southern Malawi, Zomba has a high rate of school dropouts and low educational attainment. Third, unlike many other districts, Zomba has the advantage of having a true urban center as well as rural areas. As the study sample was stratified to get representative samples from urban areas (Zomba town), rural areas near Zomba town, and distant rural areas in the district, we can analyze the heterogeneity of the impacts by urban/rural areas. Finally, while Southern Malawi, which includes Zomba, is poorer, has lower levels of education, and higher rates of HIV than Central and Northern Malawi, these differences are relative considering that Malawi is one of the poorest countries in the world with one of the highest rates of HIV prevalence.

Analysis unit

• Households;
• Girls and young women.

Universe

The survey covers never married girls and young women between the ages of 13 and 22 in Zomba district.

Kind of data

Sample survey data [ssd]

Sampling procedure

First, 176 enumeration areas (EA) were randomly sampled out of a total of 550 EAs using three strata in the study district of Zomba. Each of these 176 EAs were then randomly assigned treatment or control status. The three strata are urban, rural areas near Zomba Town, and rural areas far from Zomba Town. Rural areas were defined as being near if they were within a 16-kilometer radius of Zomba Town. Researchers did not sample any EAs in TA Mbiza due to safety concerns (112 EAs).

Enumeration areas (EAs) in Zomba were selected from the universe of EAs produced by the National Statistics Office of Malawi from the 1998 Census. The sample of EAs was stratified by distance to the nearest township or trading centre. Of the 550 EAs in Zomba, 50 are in Zomba town and an additional 30 are classified as urban (township or trading center), while the remaining 470 are rural (population areas, or PAs). The stratified random sample of 176 EAs consisted of 29 EAs in Zomba town, eight trading centers in Zomba rural, 111 population areas within 16 kilometers of Zomba town, and 28 EAs more than 16 kilometers from Zomba town.

After selecting sample EAs, all households were listed in the 176 sample EAs using a short two-stage listing procedure. The first form, Form A, asked each household the following question: "Are there any never-married girls in this household who are between the ages of 13 and 22?" This form allowed the field teams to quickly identify households with members fitting into the sampling frame, thus significantly reducing the costs of listing. If the answer received on Form A was a "yes", then Form B was filled to list members of the household to collect data on age, marital status, current schooling status, etc.

From this researchers could categorize the target population into two main groups: those who were out of school at baseline (baseline dropouts) and those who were in school at baseline (baseline schoolgirls). These two groups comprise the basis of our sampling frame. In each EA, enumerators sampled all eligible dropouts and 75%-100% of all eligible school girls, where the percentage depended on the age of the baseline schoolgirl. This sampling procedure led to a total sample size of 3,810 (in the first round, and 3,805 in follow-up rounds) with an average of 5.1 dropouts and 16.7 schoolgirls per EA.

Mode of data collection

Face-to-face [f2f]

Research instrument

The annual household survey consists of a multi-topic questionnaire administered to the households in which the selected sample respondents reside. The survey consists of two parts: one that is administered to the head of the household and another that is administered to the core respondent - the sampled girl from the target population. The former collects information on the household roster, dwelling characteristics, household assets and durables, shocks and consumption. The core respondent survey provides information about her family background, her education and labor market participation, her health, her dating patterns, sexual behavior, marital expectations, knowledge of HIV/AIDS, her social networks, as well as her own consumption of girl-specific goods (such as soaps, mobile phone airtime, clothing, braids, sodas and alcoholic drinks, etc.).

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE NATIONAL INSTITUTE OF STATISTICS - TUNISIA (INS)

The National Survey on Household Budget, Consumption, and Standard of Living, 2005 is a quinquennial survey. It is the eighth survey of its kind that was carried out by the National Institute of Statistics (INS) in Tunisia. The seven previous surveys were conducted in 1968, 1975, 1980, 1985, 1990, 1995 and 2000, concurrently with the preparatory work for the Tunisian development plans. The 2005 survey was conducted as part of the preparation work for the Tenth Development Plan (2007-2011). Its expected findings would allow assessing the progress made in the improvements of the living level & conditions of the population.

The survey aims at providing detailed information on the procurement of goods and services for consumption (food consumption as well as household access to community services of health and education). And its data was collected from direct observation of household consumption to allow for having the necessary elements to assess the situation & changes in the living standards & conditions of the households.

Thus, the 2005 survey tackles three major areas of study: 1 - Household expenditure and acquisitions during the survey period 2 - Food consumption and nutritional status of households. 3 - Household access to community services of health and education.

The objectives of the survey are: a- Identifying levels of expenditure on the household level: The survey aims to assess the levels of household expenditure .The total expenditure of the household, is not only an indicator of income, but it is also a quantitative assessment of the standard of living index.

b- Income distribution: Due to the absence of data on income distribution, the mass distribution of expenditure between the different categories of the population constitutes a first outline for the income distribution in the country.

c- Investigating the structure of expenditure: Detailed information collected on expenditures per product used to establish the structures of the household expenditure as well as the budget coefficients according to different levels of classifications of goods in the nomenclature of goods and services. These factors coefficients are particularly useful for revision and development of the weights of the Consumer Prices Index (CPI). It should also be noted that the change in expenditure structure is an indicator of the evolution of living standards.

d- Analysis of household demand: Household behavior in terms of product demand is synthesized by the coefficients of income elasticity which, according to the model of consumption retained and under the assumptions of the growth of income and population, allows predicting future household demand.

e- Resources-use balance in the national accounts: The results related to the consumption by product are necessary elements for the development of balanced resource-use of products in the frame of national accounts.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

Covering a sample of all urban, small and medium towns and rural areas.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE NATIONAL INSTITUTE OF STATISTICS - TUNISIA (INS)

Sampling method

The National Survey on Household Budget, Consumption and Standard of Living, 2005 has focused initially on a sample of 13,392 households representing 0.61% of total households in the country (61 surveyed household for every 10,000 household) . This sample is distributed across 1116 districts covering all the country governorates, cities, urban and rural areas. The sample was also equally divided on the months of the survey year to take the seasonal changes in household expenditure into account.

These households were drawn using a two stages stratified random sampling in each governorate. The sampling frame follows that of the general Census of Population and Housing in 2004.

Stratification criteria: The sampling frame is stratified by two geographical criteria: namely the governorate and the living area. The latter is stratified as follows: large municipalities, medium and small towns, major cities and the rest of the non-municipal areas. These stratification criteria (governorate, habitat and size of municipalities) represent the differentiation variable of lifestyles households. Strata used are as follows:

Stratum of large cities (stratum 1): the municipalities of the city of Tunis and its suburbs, the city of Bizerte and its suburbs, the city of Sousse and its suburbs, the city of Kairouan and its suburbs, the city Sfax and its suburbs, and the general Gabes. Thus, this stratum is formed of large urban centers corresponding to municipalities with more than 100.000 inhabitants and neighboring municipalities.

Stratum of other cities (stratum 2): This is all small and medium sized cities other than those classified in the stratum of large cities.

Stratum of the main cities (stratum 3): These are non-municipal urban areas classified as major cities during the general census of population and housing 2004 (with a population of more than 70 households).a city is considered a main city if the number of its inhabitants exceeds 400 during the census of 2004.

Stratum dispersed outside communes (stratum 4): These are areas of land located outside the main towns and cities. Households in these areas live in houses scattered or grouped in small towns.

This strata classification is closely related to the levels of household income and lifestyle.

Survey type:

The sampling frame is divided on the level of each governorate according to strata previously defined. It was set, at the level of each stratum, to make a two-stage random sampling for the selection of the household survey sample. This drawing process allows to breakdown the sample into clusters of 12 households relatively little distant from each other, thereby facilitating the conduct of the survey at the time of the information collection in the field

In the first stage: a sample of primary units is drawn in proportion to their size in number of households as they were identified. Taking into consideration that the primary units correspond to the districts that have been defined in the census of the population and these geographic areas contain on average 70 households.

In the second stage: in each sampled district, 12 households are selected according to the following method: The households in each sampled district are classified primarily according to the number of employed persons in the household. Within each category of classified households, households are also classified according to the number of persons in each household. A systematic sampling is then performed to select 12 sampled households per primary unit (sampled district). For each sampled district, another 12 households are drawn according to the same previously illustrated criteria. These households serve as a substitutive sample so that in case the interviewer failed to get in contact with the originally selected household (due to long absence- change of place of residence) , after coordinating with the supervisor, this household can be replaced by one from the substitutive sample. For this purpose, two lists of the names of head of households were developed (original list, substitutive list) that the survey is supposed to cover.

Distribution of districts and households sampled by governorates

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE NATIONAL INSTITUTE OF STATISTICS - TUNISIA (INS)

The National Survey on Household Budget, Consumption, and Standard of Living is a quinquennial survey. The 2010 survey is the ninth of its kind that was carried out by the National Institute of Statistics (INS) in Tunisia. The eight previous surveys were conducted in 1968, 1975, 1980, 1985, 1990, 1995, 2000 and 2005, concurrently with the preparatory work for the Tunisian development plans.

The survey aims at providing detailed information on the procurement of goods and services for consumption. Its data was collected from direct observation of household consumption to allow for having the necessary elements to assess the situation & changes in the living standards & conditions of the households.

The National Survey on Household Budget, Consumption, and Standard of Living consists of three fundamental parts; the budget survey, the nutrition survey and the access to community services survey. Thus, it tackles three areas of study: 1- Households expenses and acquisitions during the survey period. 2 - Food consumption and nutritional status of households. 3 - Household access to health and education community services.

The main objectives of the "budget survey" are: a- Estimate the levels of expenditure on the household level: The total expenditure of the household is not only an indicator on household income, but it is also a quantitative assessment of the standard of living index. b- Evaluate the income distribution: Due to the absence of data on income distribution, the mass distribution of expenditure between the different categories of the population constitutes a first sketch for the income distribution in the country. c- Assess the structure of expenditure: Detailed information collected on expenditures per product are used to establish the structures of the household expenditure, as well as the budget coefficients according to different levels of classifications of goods and services. These coefficients are particularly useful in the revision and development of the Consumer Prices Index (CPI) weights. d- Predict the demand of households: The household behavior, assessed in terms of product demand, is synthesized by the coefficients of income elasticity, which, according to the model of consumption retained and under the assumptions of the growth of income and population, allows predicting future household demand. e- Analyze the importance of consumer subsidies: analysis of the consumption of subsidized goods by expenditure deciles allows identifying the impact of direct consumer subsidies. It also allows evaluating the effectiveness of public policies grants.

The main objectives of "the nutrition survey" are: a- Provide estimates of food consumption by product for different groups of households according to their demographic and socio-economic characteristics. b- Estimate food consumption of each product by collecting data on the quantities consumed of each product by source, whether purchased or own produced. c- Identify the nutritional status of the population according to its demographic, geographic and socio-economic level. The comparison between the standards needs of nutrients to those acquired by the household enables assessing of the nutritional status and thus deficits in different nutrients such as calories, protein, vitamins, calcium, ... can also be captured. d- Estimate the calorie intake and energy needs of the Tunisian population: This estimate is indispensible in the calculation of the food component of the poverty line and, in consequence, the threshold of global poverty.

The main objective of "the access to community services survey" is to provide an overview on the state of morbidity of the Tunisian population, from one hand, and on the households' access to various health and education public services on other hand.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

Covering a sample of all urban, small and medium towns and rural areas.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling method

The National Survey on Household Budget, Consumption and Standard of Living, 2010 has focused initially on a sample of 13,392 households drawn using a two stages stratified random sampling in each governorate. The sampling frame follows that of the General Census of Population and Housing in 2004 which was updated during the implementation of the National Population and Employment Survey in 2009.

Stratification criteria: The sampling frame is stratified by two geographical criteria: namely the governorate and the living area. The latter is stratified as follows: large cities, medium and small cities, and non-communal areas.

These stratification criteria (governorate, living area and size of city) represent variables that differentiate between surveyed households' lifestyles. Thus, the 3 strata types used are as follows:

Stratum of large cities (stratum 1): This stratum is formed of large urban centers corresponding to municipalities with more than 100.000 inhabitants and neighboring municipalities.

Stratum of medium and small cities (stratum 2): This stratum includes all medium and small sized cities other than those classified in the stratum of large cities.

Stratum of non-communal areas (stratum 3): It includes agglomerations in rural areas that are classified as major agglomerations in the General Census of Population and Housing 2004 and the National Population and Employment Survey in 2009. In addition to other areas that are located outside the territory of main municipalities and cities. 

Households in these areas reside in scattered dwellings or are grouped in small agglomerations.

Survey type

The sampling frame is divided on the level of each governorate according to strata previously defined. On the stratum level, a two-stage random sampling is planned for the selection of the survey sample of households. This process allows to breakdown the sample into clusters of 12 households relatively little distant from each other, thereby facilitating the conduct of the survey at the time of the information collection in the field.

In the first stage, a sample of 1,116 primary units is drawn in proportion to the number of households identified in the 2009National Population and Employment Survey. Taking into consideration that the primary units correspond to the districts that have been defined in the General Census of Population and Housing in 2004, which are geographic areas comprising on average 70 households.

In the second stage, from each primary unit (or cluster), twelve households are drawn through a simple random sampling technique. A substitutive sample of 12 additional households is further drawn from each primary unit. Those additional households constituting a substitutive list are used to cover for unidentified households at the time of the survey, given the mobility of households and the period between the date on which the sample is drawn and the date on which the survey is conducted.

Sample size

The size of the sample drawn in the first stage is 1,116 primary sampling units (PSU) corresponding to 13,392 households. The samples in the second stage are 12 households per primary unit. To optimize the use of logistic and material resources available, a sample of at least 36 PSU was selected from the less populated governorates, 3 PSU per month (the survey is conducted over a 12 months period). This represents the monthly work of the survey team (3 interviews and 1 supervisor to whom a car is assigned). Moreover, as the number of households varies from one governorate to another, it was agreed to adopt different rate of sampling from one governorate to another.

The following table shows the regional distribution of the sample and the corresponding sampling rates.

Regional Distribution of the Survey Sample

Abstract

The Schooling Income and Health Risk (SIHR) project is a randomized evaluation of a conditional and unconditional cash transfer intervention targeting young women in Malawi that provided incentives (in the form of school fees and cash transfers) to current schoolgirls and recent dropouts to stay in or return to school. The program, known as the Zomba Cash Transfer Program (ZCTP), took place in Zomba, Malawi during 2008 and 2009. The incentives include average payment of US$10 a month conditional on satisfactory school attendance and direct payment of secondary school fees.

The SIHR project was specifically designed to answer a number of important questions about cash transfer programs for which there is little prior evidence. First, almost all information about the impacts of these programs come from Latin America, where income levels are much higher and institutional capacity is vastly superior compared with many poor countries in Sub-Saharan Africa. Second, the evidence base to effectively choose program design parameters (such as conditionality, transfer size, and the specific identity of the program beneficiary within households) is limited. Third, evidence on final outcomes, such as learning, labor market outcomes, and HIV risk is lacking. Finally, long term evaluations of cash transfer programs are rare - mainly because the control groups in these evaluations are treated after a short period of time.

The baseline data collection was administered from September 2007 to January 2008. The research targeted girls and young women, between the ages of 13 and 22, who were never married. Overall, 3,810 girls and young women were surveyed in the first round. Enumeration Areas (EAs) in the study district of Zomba were selected from the universe of EAs produced by the National Statistics Office of Malawi from the 1998 Census. 176 enumeration areas were randomly sampled out of a total of 550 EAs using three strata: urban areas, rural areas near Zomba Town, and rural areas far from Zomba Town. The follow-up survey (Round 2) was carried out from October 2008 to February 2009. The third round was conducted between March and September 2010, after Malawi Conditional Cash Transfer Program was completed. The fourth round took place in 2012-2013. The fifth round is planned for 2017.

The data collection effort includes household surveys, individual quantitative and qualitative interviews, academic assessments, Voluntary Counseling and Testing, school surveys, market surveys, community surveys, and health facility assessments.

The datasets from the second round of the impact evaluation are documented here.

Geographic coverage

Zomba district.

Zomba district in the Southern region was chosen as the site for this study for several reasons. First, it has a large enough population within a small enough geographic area rendering field work logistics easier and keeping transport costs lower. Zomba is a highly populated district, but distances from the district capital (Zomba Town) are relatively small. Second, characteristic of Southern Malawi, Zomba has a high rate of school dropouts and low educational attainment. Third, unlike many other districts, Zomba has the advantage of having a true urban center as well as rural areas. As the study sample was stratified to get representative samples from urban areas (Zomba town), rural areas near Zomba town, and distant rural areas in the district, researchers can analyze the heterogeneity of the impacts by urban/rural areas. Finally, while Southern Malawi, which includes Zomba, is poorer, has lower levels of education, and higher rates of HIV than Central and Northern Malawi, these differences are relative considering that Malawi is one of the poorest countries in the world with one of the highest rates of HIV prevalence.

Analysis unit

• Households;
• 13-22 year-old never-married females at baseline

Kind of data

Sample survey data [ssd]

Sampling procedure

First, 176 enumeration areas (EA) were randomly sampled out of a total of 550 EAs using three strata in the study district of Zomba. Each of these 176 EAs were then randomly assigned treatment or control status. The three strata are urban, rural areas near Zomba Town, and rural areas far from Zomba Town. Rural areas were defined as being near if they were within a 16-kilometer radius of Zomba Town. Researchers did not sample any EAs in TA Mbiza due to safety concerns (112 EAs).

Enumeration areas (EAs) in Zomba were selected from the universe of EAs produced by the National Statistics Office of Malawi from the 1998 Census. The sample of EAs was stratified by distance to the nearest township or trading centre. Of the 550 EAs in Zomba, 50 are in Zomba town and an additional 30 are classified as urban (township or trading center), while the remaining 470 are rural (population areas, or PAs). The stratified random sample of 176 EAs consisted of 29 EAs in Zomba town, eight trading centers in Zomba rural, 111 population areas within 16 kilometers of Zomba town, and 28 EAs more than 16 kilometers from Zomba town.

After selecting sample EAs, all households were listed in the 176 sample EAs using a short two-stage listing procedure. The first form, Form A, asked each household the following question: “Are there any never-married girls in this household who are between the ages of 13 and 22?” This form allowed the field teams to quickly identify households with members fitting into the sampling frame, thus significantly reducing the costs of listing. If the answer received on Form A was a “yes”, then Form B was filled to list members of the household to collect data on age, marital status, current schooling status, etc.

From this researchers could categorize the target population into two main groups: those who were out of school at baseline (baseline dropouts) and those who were in school at baseline (baseline schoolgirls). These two groups comprise the basis of our sampling frame. In each EA, enumerators sampled all eligible dropouts and approximately two-thirds of all eligible school girls, where the sampling percentage depended on the age and location of the baseline schoolgirl. This sampling procedure led to a total sample size of 3,796 with an average of 5.1 dropouts and 16.7 schoolgirls per EA.

Mode of data collection

Face-to-face [f2f]

Research instrument

The annual household survey consists of a multi-topic questionnaire administered to the households in which the selected sample respondents reside. The survey consists of two parts: one that is administered to the head of the household and another that is administered to a core respondent - a sampled girl from the target population. The former collects information on the household roster, dwelling characteristics, household assets and durables, shocks, deaths and consumption. The core respondent survey provides information about her family background, her education and labor market participation, her health, her dating patterns, sexual behavior, marital expectations, knowledge of HIV/AIDS, her social networks, as well as her own consumption of girl-specific goods (such as soaps, mobile phone airtime, clothing, braids, sodas and alcoholic drinks, etc.).

Response rate

At the first follow-up in Round 2, 94% of baseline schoolgirls and 90% of baseline dropouts were interviewed. There was no differential attrition between treatment groups.

This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2019 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2019. The NCES Education Demographic and Geographic Estimate (EDGE) program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:City - Large (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more. City - Midsize (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000. City - Small (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000. Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more. Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000. Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000. Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area. Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area. Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area. Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster. Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster. Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.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.

This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, but they rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The 2016 NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line 2016. The NCES Education Demographic and Geographic Estimate (EDGE) program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to annually update the locale boundaries. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:Large City (11): Territory inside an Urbanized Area and inside a Principal City with population of 250,000 or more.Midsize City (12): Territory inside an Urbanized Area and inside a Principal City with population less than 250,000 and greater than or equal to 100,000.Small City (13): Territory inside an Urbanized Area and inside a Principal City with population less than 100,000.Suburb – Large (21): Territory outside a Principal City and inside an Urbanized Area with population of 250,000 or more.Suburb - Midsize (22): Territory outside a Principal City and inside an Urbanized Area with population less than 250,000 and greater than or equal to 100,000.Suburb - Small (23): Territory outside a Principal City and inside an Urbanized Area with population less than 100,000.Town - Fringe (31): Territory inside an Urban Cluster that is less than or equal to 10 miles from an Urbanized Area.Town - Distant (32): Territory inside an Urban Cluster that is more than 10 miles and less than or equal to 35 miles from an Urbanized Area.Town - Remote (33): Territory inside an Urban Cluster that is more than 35 miles of an Urbanized Area.Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urbanized Area, as well as rural territory that is less than or equal to 2.5 miles from an Urban Cluster.Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urbanized Area, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Cluster.Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urbanized Area and is also more than 10 miles from an Urban Cluster.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 Schooling Income and Health Risk (SIHR) project is a randomized evaluation of a conditional and unconditional cash transfer intervention targeting young women in Malawi that provided incentives (in the form of school fees and cash transfers) to current schoolgirls and recent dropouts to stay in or return to school. The program, known as the Zomba Cash Transfer Program (ZCTP), took place in Zomba, Malawi during 2008 and 2009. The incentives include average payment of US$10 a month conditional on satisfactory school attendance and direct payment of secondary school fees.

The SIHR project was specifically designed to answer a number of important questions about cash transfer programs for which there is little prior evidence. First, almost all information about the impacts of these programs come from Latin America, where income levels are much higher and institutional capacity is vastly superior compared with many poor countries in Sub-Saharan Africa. Second, the evidence base to effectively choose program design parameters (such as conditionality, transfer size, and the specific identity of the program beneficiary within households) is limited. Third, evidence on final outcomes, such as learning, labor market outcomes, and HIV risk is lacking. Finally, long term evaluations of cash transfer programs are rare - mainly because the control groups in these evaluations are treated after a short period of time.

The baseline data collection was administered from September 2007 to January 2008. The research targeted girls and young women, between the ages of 13 and 22, who were never married. Overall, 3,810 girls and young women were surveyed in the first round. Enumeration Areas (EAs) in the study district of Zomba were selected from the universe of EAs produced by the National Statistics Office of Malawi from the 1998 Census. 176 enumeration areas were randomly sampled out of a total of 550 EAs using three strata: urban areas, rural areas near Zomba Town, and rural areas far from Zomba Town. The follow-up survey (Round 2) was carried out from October 2008 to February 2009. The third round was conducted between March and September 2010, after Malawi Conditional Cash Transfer Program was completed. The fourth round took place in 2012-2013. The fifth round is planned for 2017.

The data collection effort includes household surveys, individual quantitative and qualitative interviews, academic assessments, Voluntary Counseling and Testing, school surveys, market surveys, community surveys, and health facility assessments.

The datasets from the third round of the impact evaluation are documented here.

Geographic coverage

Zomba district.

Zomba district in the Southern region was chosen as the site for this study for several reasons. First, it has a large enough population within a small enough geographic area rendering field work logistics easier and keeping transport costs lower. Zomba is a highly populated district, but distances from the district capital (Zomba Town) are relatively small. Second, characteristic of Southern Malawi, Zomba has a high rate of school dropouts and low educational attainment. Third, unlike many other districts, Zomba has the advantage of having a true urban center as well as rural areas. As the study sample was stratified to get representative samples from urban areas (Zomba town), rural areas near Zomba town, and distant rural areas in the district, researchers can analyze the heterogeneity of the impacts by urban/rural areas. Finally, while Southern Malawi, which includes Zomba, is poorer, has lower levels of education, and higher rates of HIV than Central and Northern Malawi, these differences are relative considering that Malawi is one of the poorest countries in the world with one of the highest rates of HIV prevalence.

Analysis unit

• households;
• 13-22 year-old never-married girls and young women at the baseline.

Kind of data

Sample survey data [ssd]

Sampling procedure

First, 176 enumeration areas (EA) were randomly sampled out of a total of 550 EAs using three strata in the study district of Zomba. Each of these 176 EAs were then randomly assigned treatment or control status. The three strata are urban, rural areas near Zomba Town, and rural areas far from Zomba Town. Rural areas were defined as being near if they were within a 16-kilometer radius of Zomba Town. Researchers did not sample any EAs in TA Mbiza due to safety concerns (112 EAs).

Enumeration areas (EAs) in Zomba were selected from the universe of EAs produced by the National Statistics Office of Malawi from the 1998 Census. The sample of EAs was stratified by distance to the nearest township or trading centre. Of the 550 EAs in Zomba, 50 are in Zomba town and an additional 30 are classified as urban (township or trading center), while the remaining 470 are rural (population areas, or PAs). The stratified random sample of 176 EAs consisted of 29 EAs in Zomba town, eight trading centers in Zomba rural, 111 population areas within 16 kilometers of Zomba town, and 28 EAs more than 16 kilometers from Zomba town.

After selecting sample EAs, all households were listed in the 176 sample EAs using a short two-stage listing procedure. The first form, Form A, asked each household the following question: “Are there any never-married girls in this household who are between the ages of 13 and 22?” This form allowed the field teams to quickly identify households with members fitting into the sampling frame, thus significantly reducing the costs of listing. If the answer received on Form A was a “yes”, then Form B was filled to list members of the household to collect data on age, marital status, current schooling status, etc.

From this researchers could categorize the target population into two main groups: those who were out of school at baseline (baseline dropouts) and those who were in school at baseline (baseline schoolgirls). These two groups comprise the basis of our sampling frame. In each EA, enumerators sampled all eligible dropouts and approximately two-thirds of all eligible school girls, where the sampling percentage depended on the age and location of the baseline schoolgirl. This sampling procedure led to a total sample size of 3,796 with an average of 5.1 dropouts and 16.7 schoolgirls per EA.

Mode of data collection

Face-to-face [f2f]

Research instrument

The household survey consists of a multi-topic questionnaire administered to the households in which the selected sample respondents reside.

The survey consists of two parts: one that is administered to the head of the household and another that is administered to a core respondent - a sampled girl from the target population. The former collects information on the household roster, dwelling characteristics, household assets and durables, shocks, deaths and consumption. The core respondent survey provides information about her family background, her education and labor market participation, her health, her dating patterns, sexual behavior, marital expectations, knowledge of HIV/AIDS, her social networks, as well as her own consumption of girl-specific goods (such as soaps, mobile phone airtime, clothing, braids, sodas and alcoholic drinks, etc.).

Much of the information gathered in the third round is similar to the first and second rounds of data collection, but there is a significant portion of distinct and new information pertinent to Round 3.