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    Home / Central Data Catalog / LSMS / SLV_2022_SELM_V01_M
lsms

Methodological Innovations for Measuring Informality – A Survey Experiment on Labor Measurement 2022

El Salvador, 2022
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Reference ID
SLV_2022_SELM_v01_M
Producer(s)
Amparo Palacios-Lopez, Ivette Contreras
Collection(s)
Living Standards Measurement Study (LSMS)
Metadata
Documentation in PDF DDI/XML JSON
Created on
Sep 16, 2026
Last modified
Sep 16, 2026
Page views
290
Downloads
7
  • Study Description
  • Data Description
  • Documentation
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  • Identification
  • Version
  • Scope
  • Coverage
  • Producers and sponsors
  • Sampling
  • Data collection
  • Data processing
  • Data Access
  • Disclaimer and copyrights
  • Contacts
  • Metadata production
  • Identification

    Survey ID number

    SLV_2022_SELM_v01_M

    Title

    Methodological Innovations for Measuring Informality – A Survey Experiment on Labor Measurement 2022

    Abbreviation or Acronym

    SELM 2022

    Country/Economy
    Name Country code
    El Salvador SLV
    Study type

    Living Standards Measurement Study [hh/lsms]

    Abstract
    This dataset contains individual- and household-level data collected across 1,008 households and 2,480 individuals in rural and peri-urban areas of the departments of San Salvador and Usulután, El Salvador. Collected via CAPI using the World Bank's Survey Solutions platform, the data were gathered as part of a randomized experiment with three arms designed to test different survey design approaches for measuring informal work among women and youth. The dataset covers a broad set of modules including demographics, education, technology access, labor force participation, time use (24-hour recall), social norms, risk aversion, household assets, and a discrete choice experiment on job preferences. Its distinguishing feature is the experimental variation in how labor questions were administered making it uniquely suited for methodological research on informal labor measurement in low- and middle-income country contexts.
    Kind of Data

    Sample survey data [ssd]

    Unit of Analysis
    • Households
    • Individuals

    Version

    Version Description

    Version 01: Edited, anonymized dataset for public distribution

    Scope

    Notes

    The survey covers the following topics:

    • Household roster
    • Education
    • Technology
    • List of activities
    • Labor
    • Skills and readiness to work
    • Aspirations
    • Time use
    • Social norms
    • Attitudes
    • Discrete choice experiment
    • Risk aversion
    • Housing
    • Non-farm enterprise
    • Food security
    • Agriculture
    • Household assets
    • Other income in the last 12 months

    Coverage

    Geographic Coverage

    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.

    Producers and sponsors

    Primary investigators
    Name Affiliation
    Amparo Palacios-Lopez World Bank Group
    Ivette Contreras World Bank Group
    Funding Agency/Sponsor
    Name Abbreviation
    International Fund for Agricultural Development IFAD
    World Bank Group WB

    Sampling

    Sampling Procedure

    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.

    Response Rate

    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%).

    Data collection

    Dates of Data Collection
    Start End
    2022-08-15 2022-10-31
    Mode of data collection
    • Computer Assisted Personal Interview [capi]

    Data processing

    Data Editing

    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.

    Data Access

    Access conditions

    Before being granted access to the dataset, all users have to formally agree:

    • To make no copies of any files or portions of files to which s/he is granted access except those authorized by the data depositor.
    • Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files.
    • To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the data depositor.
    Citation requirements

    Use of the dataset must be acknowledged using a citation which would include:

    • The identification of the primary investigators
    • The title of the survey (including country, acronym, and year of implementation)
    • The survey reference number
    • The source and date of download

    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].

    Disclaimer and copyrights

    Disclaimer

    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

    Contacts
    Name Affiliation Email
    LSMS Data Manager World Bank Group lsms@worldbank.org

    Metadata production

    DDI Document ID

    DDI_SLV_2022_SELM_v01_M

    Producers
    Name Abbreviation Affiliation Role
    Development Data Group DECDG World Bank Group Documentation of the survey

    Metadata version

    DDI Document version

    Version 01 (September 2026)

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