Measuring Women’s and Youths’ Informal Work in Non-Urban Settings: Evidence from El Salvador

Last registered on August 16, 2022

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Pre-Trial

Trial Information

General Information

Title

Measuring Women’s and Youths’ Informal Work in Non-Urban Settings: Evidence from El Salvador

RCT ID

AEARCTR-0009541

Initial registration date

August 01, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

August 16, 2022, 3:35 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country

El Salvador

Region

Latin America

Primary Investigator

Name

Lelys Dinarte

Affiliation

The World Bank

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Other Primary Investigator(s)

PI Name

Amparo Palacios-Lopez

PI Affiliation

The World Bank

Contact Investigator

PI Name

Valentina Costa

PI Affiliation

The World Bank

Contact Investigator

PI Name

Ivette Contreras

PI Affiliation

The World Bank

Contact Investigator

Additional Trial Information

Status

In development

Start date

2022-07-16

End date

2022-12-31

Keywords

Agriculture, Gender, Labor, Welfare

Additional Keywords

Informal work, willingness to pay, data collection improvement, El Salvador

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Measuring informal work is crucial for policy making, especially in development countries where informal work represents a high share of employment. Moreover, existing evidence shows that reporting engagement in work-related activities may differ across population groups. For the case of El Salvador, official data shows that women that answer by themselves register a lower participation rate than when data is reported by another household member. This behavior could be endogenous, since women are more likely to be at home so they perceive that they are not working, but it can also be that they are more likely to underreport.

The objective of this project is threefold. First, it aims to advance our understanding of how to obtain improved measures of labor, especially of those activities that tend to be underestimated in households’ surveys, such as informal and sporadic activities. More specifically, this project will provide experimental evidence on how to improve data collection on informal work, focusing on women and youth in non-urban (rural and peri-urban) areas. Second, it will also explore if the type of respondent (self or proxy) affects how labor participation is measured. Finally, this project aims to provide evidence on women’s and youths’ preferences on formal work attributes.

To achieve the first two goals, the plan is to design and implement a survey experiment to measure and compare the impact of different methods of collecting information on informal work and of the type of informant. The evidence on women's and youths' preferences for formal work attributes will be obtained from a discrete choice experiment inspired in Datta (2019).

External Link(s)

Registration Citation

Citation

Contreras, Ivette et al. 2022. "Measuring Women’s and Youths’ Informal Work in Non-Urban Settings: Evidence from El Salvador." AEA RCT Registry. August 16. https://doi.org/10.1257/rct.9541-1.0

Sponsors & Partners

Partner

Name

FUSADES

Type

ngo

URL

https://fusades.org/

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Experimental Details

Interventions

Intervention(s)

This project aims to advance our understanding of how to obtain improved measures of labor, especially of those activities that are usually miscounted in household surveys such as causal and sporadic activities.

There are two interventions in this trial:
• Members of the households assigned to treatment group 1 will be exposed to an additional survey module (Activities Module) before collecting their labor information. The Activities Module includes a list of the most common labor activities that people in their region do. The list is curated to use to provide examples of different income-generating activities that can be considered as work for statistical purposes.
• Members of the households assigned to treatment group 2 should provide their labor information by themselves (as opposed to using a proxy respondent as is common in household surveys).

Moreover, all households will respond to a discrete choice experiment that aims to measure respondents' willingness to pay on different attributes related to formal employment.

Intervention Start Date

2022-08-08

Intervention End Date

2022-10-15

Primary Outcomes

Primary Outcomes (end points)

Labor force participation

Primary Outcomes (explanation)

The labor force participation will be estimated using ILO guidelines.

Secondary Outcomes

Secondary Outcomes (end points)

Willingness to pay for formal employment attributes.

Secondary Outcomes (explanation)

Experimental Design

Group status: Control group
Type of labor module: Standard (LSMS labor module following 19th, ICLS)
Type of respondent: Main household respondent or if another household member (15-64 years old) is present, he/she provides his/her own information.

Group status: Treatment group 1
Type of labor module: New labor module that includes a new list of work activities
Type of respondent: Main household informant or if another household member (15-64 years old) is present, he/she provides his/her own information

Group status: Treatment group 2
Type of labor module: Standard (LSMS labor module following 19th, ICLS)
Type of respondent: Only self-respondents, selected household members (15-64 years old) must provide their own information

Experimental Design Details

Randomization Method

Computer randomization for selection into experiment arms: C, T1, or T2.

Randomization Unit

Unit of randomization will be the household.

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

1008 households

Sample size: planned number of observations

3,024 individuals

Sample size (or number of clusters) by treatment arms

336 households C, 336 households T1, 336 households T2

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

For the statistical power and sample size estimations, we assume that, for the T1 and T2 comparison, we will have information on 672 households (a total of 336 households in T1 and T2). Further conservative assumptions are the following: an intra-household correlation (ICC) of 0.12, a type I error rate of 0.05, and statistical power of 0.9. Considering this, the minimum detectable effect (MDE) for the labor participation outcome will be 8.8 percentage points.

Supporting Documents and Materials

IRB