Schooling, Income, and Health Risk Impact Evaluation Household Survey 2012, Round 4
Malawi, 2012
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MWI_2012_SIHRIE-R4_v02_M
Schooling, Income, and Health Risk Impact Evaluation Household Survey 2012
Round 4
| Name | Country code |
|---|---|
| Malawi | MWI |
Other Household Survey [hh/oth]
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 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 data collection effort includes household surveys, individual quantitative and qualitative interviews, academic assessments, Voluntary Counseling and Testing, earky childhood development assessments, school surveys, market surveys, community surveys, and health facility assessments.
The datasets from the fourth round of the impact evaluation are documented here.
Sample survey data [ssd]
- Households;
- 13-22 year-nold ever-married girls and young women at the baseline;
- Partners of the women recruited at baseline;
- Children of the women recruited at baseline, with those aged 3-4 years old being administered development assessments.
Version
Version 02
2021-02-17
This version includes SIHR4__identifiers_clean.dta, a replacement of SIHR4__identifiers.dta. This new data file includes additional (and better labeled) household ID identifiers that facilitate merging the SIHR Round 4 data with data from the previous rounds.
Scope
The scope of the study includes:
- household characteristics;
- dwelling characteristics;
- durable goods;
- consumption of food over past one week;
- total expenditures over past month;
- safety nets;
- economic shocks;
- deaths;
- family background;
- education and labor;
- health and fertility;
- sexual behaviors;
- marriage;
- AIDS;
- social networks;
- girl level consumption;
- husband level consumption;
- child development assessments.
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.
District
Producers and sponsors
| Name | Affiliation |
|---|---|
| Berk Ozler | World Bank |
| Sarah Baird | George Washington University |
| Craig McIntosh | University of California San Diego |
| Ephraim Chirwa | University of Malawi |
| Name |
|---|
| Global Development Network |
| Bill and Melinda Gates Foundation |
| NBER Africa Project |
| World Bank: Research Support Budget |
| World Bank: KCP Trust Fund |
| World Bank: SIEF Trust Fund |
| World Bank: GAP Trust Fund |
| International Initiative for Impact Evaluation |
Sampling
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.
Sampling weights, which are equal to the inverse of the probability of selection into the study sample were used. In the data, this variable is called "weight". It can be found in the dataset "SIHR4__identifiers".
Survey 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 four parts: one that is administered to the head of the household; another that is administered to a core respondent - a sampled girl from the target population; another part is administered to the core respondent's partner; finally, assessments for early childhood development are administered to children of the core respondents who were aged 3-4 years old at the time of data collection.
The first part of the survey 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 children's health, her dating patterns, sexual behavior, marital expectations, knowledge of HIV/AIDS, as well as her own consumption of girl-specific goods (such as soaps, mobile phone airtime, clothing, braids, sodas and alcoholic drinks, etc.). The partner's survey provides information on the partner's education and labor market participation, health, dating patterns, sexual behavior, and marital expectations. Finally, children of the core respondent who were 3-4 years old at the time of data collection are administered two separate developmental assessments (the Malawi Developmental Assessment Tool and the Strengths and Difficulties Questionnaire).
Much of the information gathered in the fourth round is similar to that collected in the previous rounds, but there is a significant portion of distinct and new information pertinent to Round 4.
Data collection
| Start | End |
|---|---|
| 2012-04 | 2012-08 |
| Name |
|---|
| Wadonda Consult |
Data Access
| Name | Affiliation | URL |
|---|---|---|
| Microdata Library | World Bank | microdata.worldbank.org |
| Is signing of a confidentiality declaration required? |
|---|
| yes |
Public Use Files
The use of the datasets must be acknowledged using a citation which would include:
- the identification of the Primary Investigator
- the full title of the survey and its acronym (when available), and the year(s) of implementation
- the survey reference number
- the source and date of download (for datasets disseminated online).
Example:
Berk Ozler, World Bank; Sarah Baird, George Washington University; Craig McIntosh, University of California San Diego; Ephraim Chirwa, University of Malawi. Malawi Schooling, Income, and Health Risk Impact Evaluation Household Survey (SIHRIE-R4) 2012, Round 4, Ref. MWI_2012_SIHRIE-R4_v02_M. Dataset downloaded from [URL] on [date].
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Contacts
| Name | Affiliation | |
|---|---|---|
| Berk Ozler | DECRG, World Bank | bozler@worldbank.org |
Metadata production
DDI_MWI_2012_SIHRIE-R4_v02_M_WB
| Name | Affiliation | Role |
|---|---|---|
| Development Data Group | World Bank | Documentation of the DDI |
2021-02-19
Metadata version
Version 02
2021-02-19
Identical to version 01 with revisions to SIHR4__identifiers.dta.