Promoting regular labor supply among the urban poor

Last registered on September 09, 2022

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Pre-Trial

Trial Information

General Information

Title

Promoting regular labor supply among the urban poor

RCT ID

AEARCTR-0009402

Initial registration date

May 08, 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

May 09, 2022, 8:25 PM EDT

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

Last updated

September 09, 2022, 5:50 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

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Primary Investigator

Name

Luisa Cefala

Affiliation

UC Berkeley

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Other Primary Investigator(s)

PI Name

Supreet Kaur

PI Affiliation

UC Berkeley

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PI Name

Heather Schofield

PI Affiliation

University of Pennsylvania

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PI Name

Yogita Shamdasani

PI Affiliation

National University of Singapore

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Additional Trial Information

Status

On going

Start date

2022-03-21

End date

2023-12-31

Keywords

Behavior, Labor

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

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

Abstract

Low and irregular labor force participation, high labor turnover and absenteeism are major impediments to productivity in poor countries. We hypothesize that workers have difficulty providing regular labor supply in the formal sector because they might not a preference for doing so. We design an RCT with urban casual laborers in India, where laborers are provided incentives to boost their labor supply to urban labor stands -- their primary source of regular employment. We examine the persistence of effects on labor supply once incentives are removed.

External Link(s)

Registration Citation

Citation

Cefala, Luisa et al. 2022. "Promoting regular labor supply among the urban poor." AEA RCT Registry. September 09. https://doi.org/10.1257/rct.9402-1.1

Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)

In this study, we hypothesize that workers’ preference for, and ability to maintain, long-term employment is malleable. We test this hypothesis by exploiting a habit-formation design, whereby we provide small financial incentives to attend daily to a randomly selected group of informal laborers for a limited period of time (6-8 weeks) and then observe labor market outcomes. The primary hypothesis we will test is that treated participants will attend the stand more often than Control participants not only in Phase 1 (incentives), but also in Phase 2 (follow-up phase, without incentives).

Intervention Start Date

2022-05-09

Intervention End Date

2022-10-31

Primary Outcomes

Primary Outcomes (end points)

Our primary outcome is attendance at the labor stand during phase 2.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

We will measure impacts on employment levels and earnings.

Secondary Outcomes (explanation)

These two outcomes are considered secondary because: 1) they are self-reported leading to additional noise in the data, and 2) they are dependent on labor demand as well, which may vary across contexts. We will also collect supplementary data including: reasons for absences and a brief questionnaire on time use, habits, and identity.

Additional outcomes subject to feasibility. We are piloting to determine whether participants can be asked to wear pedometers for a portion of the study, in the hopes of providing an “objective” measure of the amount of work done. However, we will only analyze this data if we are able to incentivize participants to wear the devices regularly.

Similarly, we are attempting to partner with a construction firm to offer participants the choice of a “regular” job that is salaried and requires consistent attendance. Incentive compatible preferences for this type of work will be elicited and, if possible, a (small) random subset will be offered their choice at the end of the study. Take-up of the offer will be dependent on our being able to secure such a partner firm.
Additional outcomes subject to feasibility. We are piloting to determine whether participants can be asked to wear pedometers for a portion of the study, in the hopes of providing an “objective” measure of the amount of work done. However, we will only analyze this data if we are able to incentivize participants to wear the devices regularly.

Similarly, we are attempting to partner with a construction firm to offer participants the choice of a “regular” job that is salaried and requires consistent attendance. Incentive compatible preferences for this type of work will be elicited and, if possible, a (small) random subset will be offered their choice at the end of the study. Take-up of the offer will be dependent on our being able to secure such a partner firm.

Experimental Design

The RCT will incentivize a subset of workers to increase their attendance at the stand, and then remove the incentives to examine the persistence of labor supply changes among treated participants.

Experimental Design Details

Not available

Randomization Method

The randomization is performed using Stata

Randomization Unit

Participants are randomly assigned at the individual level, stratified on stand, baseline attendance and baseline average daily wage earnings, to either the control arm or the treatment arm. Cut offs to determine the strata are computed using the median number of days of baseline attendance and the median baseline average self-reported daily wage from pilot stands.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

We will enroll approximately 250-350 workers (depending on take-up at the stands) across approximately 15 stands in Chennai.

Sample size: planned number of observations

We will enroll approximately 350-500 workers (depending on take-up at the stands) across approximately 15 stands in Chennai.

Sample size (or number of clusters) by treatment arms

We plan to have half of the sample enrolled in the treatment arm and half in the control arm. Some variation may occur because of the difference size of the strata.

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

Supporting Documents and Materials

IRB