Pollution, Productivity and Willingness to Pay for Defensive Investments

Last registered on May 04, 2023
View Trial History

Pre-Trial

Trial Information

General Information

Title
Pollution, Productivity and Willingness to Pay for Defensive Investments
RCT ID
AEARCTR-0005364
Initial registration date
February 04, 2020

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
February 07, 2020, 3:43 PM EST

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

Last updated
May 04, 2023, 2:49 PM EDT

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

Locations

Country
Bangladesh
Region
Dhaka

Primary Investigator

Name
Maulik Jagnani
Affiliation
Tufts University
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Teevrat Garg
PI Affiliation
University of California, San Diego
Contact Investigator

Additional Trial Information

Status
On going
Start date
2020-01-15
End date
2024-12-31
Keywords
Environment & Energy
Additional Keywords
JEL code(s)
Q50, Q56, Q58, Q53, O13, O10
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
Air quality has become a pressing concern in many developing countries, particularly in South Asia. The 2019 State of Global Air study found that in South Asia, air quality levels represented a loss of 2-3 years in average life expectancy. In Bangladesh, where we propose our study, it was estimated that 200,000 people died in 2017 due to poor air quality. While the human capital costs of air pollution have been documented extensively, there remain major gaps in our understanding of the effects of air pollution and more importantly the ability and willingness of individuals and firms to avoid these damages. We propose a field experiment with randomized allocation of air purifiers in small-scale textile firms in Bangladesh to estimate the effect of air pollution on worker productivity as well as willingness to pay for defensive investments that help reduce exposure to air pollution.
External Link(s)

Registration Citation

Citation
Garg, Teevrat and Maulik Jagnani. 2023. "Pollution, Productivity and Willingness to Pay for Defensive Investments." AEA RCT Registry. May 04. https://doi.org/10.1257/rct.5364-3.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)


Intervention Start Date
2020-01-15
Intervention End Date
2024-12-31

Primary Outcomes

Primary Outcomes (end points)
productivity indicators and willingness to pay measures
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our research design has two parts: the first part will estimate the effect of pollution on productivity (N = 100 firms); the second part will examine the willingness-to-pay for air pollution purifiers (N = 600 firms).

Part 1: In the first part, we will randomly sample 100 firms and install air quality monitors in each firm. We will install air purifiers in 50 randomly selected firms for a period of 12 months (treatment group). In our analysis, we will compare productivity indicators between the treatment and control group to estimate the impact of air filters on productivity.

Part 2: In the second part, we will randomly sample 600 firms.

Baseline Survey Visit: Surveyors will visit 600 firms and speak to both the factory owner and factory workers about pollution: Surveyors will conduct a baseline survey, which will include a module on pollution and beliefs about outdoor and indoor pollution levels, effect of pollution on productivity, and the protective effects of air purifiers. During the visit, objective indoor and outdoor pollution levels for factories in both the treatment and control group will be collected via air monitors. After the survey, during the same visit, surveyors will conduct the information intervention for the treatment group.

Information Intervention and Pollution Report Cards (Treatment Group Only): Surveyors will walk factory owners and factory workers through pollution report cards describing (objective) outdoor and indoor pollution levels, effect of pollution on productivity (from Part 1), and the protective effects of air pollution purifiers (engineering estimates).

Willingness-to-Pay Experiment: At the end, both factory owners and factory workers will be asked to take part in a real-stakes willingness-to-pay experiment; we will elicit willingness to pay for air purifiers using an incentive-compatible Becker-deGroot-Marschak (BDM) mechanism, which both induces exogenous variation in take-up and yields high resolution data on individual air-purifier demand.

In our analysis, we will simply compare willingness-to-pay estimates across as well as between workers and owners in the treatment and control groups.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
Unit of randomization: garment factories (firms)
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
Intervention #1: 100 firms

Intervention #2: 600 firms
Sample size: planned number of observations
Intervention #1: 2000 workers Intervention #2: 600 firm owners and 600 workers
Sample size (or number of clusters) by treatment arms
Intervention #1: 50 garment factories/firms in the control group, 50 garment factories/firms in the control group

Intervention #2: 300 garment factories/firms in the control group, 300 garment factories/firms in the control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Innovations for Poverty Action - USA
IRB Approval Date
2019-12-19
IRB Approval Number
15026
IRB Name
Institute of Health Economics, University of Dhaka
IRB Approval Date
2023-05-03
IRB Approval Number
N/A
Analysis Plan