SLV_2022_SELM_v01_M
Methodological Innovations for Measuring Informality – A Survey Experiment on Labor Measurement 2022
SELM 2022
| Name | Country code |
|---|---|
| El Salvador | SLV |
Living Standards Measurement Study [hh/lsms]
Sample survey data [ssd]
Version 01: Edited, anonymized dataset for public distribution
The survey covers the following topics:
The study was focused on the provinces of Usulutan and San Salvador in El Salvador. Including 1,008 households in 48 enumeration areas classified as rural or peri-urban.
| Name | Affiliation |
|---|---|
| Amparo Palacios-Lopez | World Bank Group |
| Ivette Contreras | World Bank Group |
| Name | Abbreviation |
|---|---|
| International Fund for Agricultural Development | IFAD |
| World Bank Group | WB |
To ensure that the experimental design targets settings where underreporting is most salient, the sample is restricted to enumeration areas (EAs) classified as rural or peri urban. The 2007 Salvadoran Population Census (the latest available at the time of the experiment) classifies EAs into three categories: (i) urban areas, defined as segments containing the municipality mayor’s office and more than 500 continuously grouped dwellings; (ii) peri urban areas, comprising segments surrounding the urban core; and (iii) rural areas, defined as all remaining segments after excluding those classified as urban and peri urban.
Using the 2007 Salvadoran Population Census, we identified 276 rural and peri-urban EAs with at least 30 households, 114 from Region 1 and 162 from Region 2. We then randomly selected 48 EAs and conducted a full household listing in each. From these lists, we randomly selected 21 households per EA, yielding a total of 1,008 households. Each household was required to have at least two working-age members. Within each selected household, all working-age members (ages 15-64) were eligible for interview. In households with up to four working-age members (96.7% of the sample) we interviewed all of them. In the remaining 3.3% of households, four members were randomly selected, with the draw stratified by sex (male or female) and age group (youths aged 15-24 and adults aged 25-64), reflecting our primary hypotheses about differential impacts along these dimensions. This resulted in a final individual sample of 2,480 respondents.
Across all three arms, 21.9% of households were replaced during fieldwork. Refusal to participate accounts for most replacements (17.2% of all households), followed by ineligible households (2.3%), households that could not be located (1.2%), and interviews started but discontinued by the main respondent (0.5%).
| Start | End |
|---|---|
| 2022-08-15 | 2022-10-31 |
As an additional aid to ensuring good quality data, extensive monitoring was performed throughout the fieldwork for each round of the survey. Two monitoring exercises were implemented during data collection. First, Survey Solutions’ audio recording functionality was activated for 25 percent of the sample. These interview recordings were audited by 3 trained monitors, though not all recorded interviewers were able to be reviewed due to personnel constraints. On a daily basis, the monitors will listen to these recordings and fill in a structured questionnaire with their observations on interviewer performance. The feedbacks from these audio audits are then filtered to the respective interviewers.
The second quality check implemented were multiple visits to contacted households. Multiple visits were conducted by trained interviewers who are not part of the main data collection interviewers. Each day, up to 36 households that were contacted by the interviewing team are called by these call back interviewers. These interviewers conduct a short interview with the household to confirm that the interviewer did indeed conduct the interview, that certain key elements were clearly stated to the respondent, that the interviewer conducted themselves in a professional manner, and other details on the interview process. Further, the team asked several time-invariant questions of the respondent to further confirm the interview was fully conducted and the interviewer captured the information correctly. Feedback from this quality checks were routed to the respective interviewers to improve on identified areas. Further, the interviewers also visited households that were not successfully contacted by the main interviewer. In some cases, the interviewer was able to reach the household. In such cases, the case was sent back to the interviewer to conduct the interview.
Before being granted access to the dataset, all users have to formally agree:
Use of the dataset must be acknowledged using a citation which would include:
Example:
Amparo Palacios-Lopez (World Bank Group), Ivette Contreras (World Bank Group). El Salvador - Methodological Innovations for Measuring Informality – A Survey Experiment on Labor Measurement in El Salvador 2022. Ref: SLV_2022_SELM_v01_M. Downloaded from [uri] on [date].
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.
| Name | Affiliation | |
|---|---|---|
| LSMS Data Manager | World Bank Group | lsms@worldbank.org |
DDI_SLV_2022_SELM_v01_M
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank Group | Documentation of the survey |
Version 01 (September 2026)
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