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Air Pollution SMS Messaging in Mexico City

Last registered on February 12, 2019
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Pre-Trial

Trial Information

General Information

Title
Air Pollution SMS Messaging in Mexico City
RCT ID
AEARCTR-0003879
Initial registration date
February 11, 2019

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 12, 2019, 4:59 PM EST

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

Locations

Country
Mexico
Region

Primary Investigator

Name
Bridget Hoffmann
Affiliation
Inter-American Development Bank
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2019-04-01
End date
2020-04-01
Keywords
Environment & Energy, Health
Additional Keywords
air pollution information, willingness to pay, avoidance behavior
JEL code(s)
Q53; Q51; D83; D12; O12; C93
Secondary IDs
Abstract
Many cities and countries invest in air pollution monitoring systems. The value of these systems depends crucially on how the information that they collect is used by the public. For example, Mexico City has a robust monitoring network of over 30 stations with hourly pollutant readings that are available online and through an app. However, the public is not regularly using this information to engage in protective "avoidance" behaviors to reduce their exposure to air pollution and mitigate its related health risks.

We develop a messaging service that provides location and pollutant specific (ozone and particulate matter) alerts through SMS message early in the day. We use an incentive compatible mechanism to elicit willingness to pay for the SMS alert service and we randomly assign households to receive or not receive the SMS alert service. Participants are also randomly assigned to two cross-cutting treatments: (1) monthly SMS reminders of air pollution trends and avoidance behaviors, and (2) provision of a free N95 certified mask. We will estimate the causal effect of the alert service and reminder information on avoidance behavior. Because the N95 mask is effective in reducing exposure to particulate matter but not ozone, receiving a free mask lowers the cost of avoidance for days with high particulate matter relative to days with high ozone. We will use this variation to investigate the causal effect of the cost of avoidance behavior on engaging in avoidance behavior.
External Link(s)

Registration Citation

Citation
Hoffmann, Bridget. 2019. "Air Pollution SMS Messaging in Mexico City." AEA RCT Registry. February 12. https://doi.org/10.1257/rct.3879-1.0
Former Citation
Hoffmann, Bridget. 2019. "Air Pollution SMS Messaging in Mexico City." AEA RCT Registry. February 12. https://www.socialscienceregistry.org/trials/3879/history/41436
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Air quality alerts: SMS messaging service that sends location and pollutant specific air quality alerts to participants

Reminders: monthly SMS message with reminders of air quality trends and air pollution avoidance behaviors

Masks: free provision of a certified N95 mask
Intervention Start Date
2019-04-01
Intervention End Date
2020-04-01

Primary Outcomes

Primary Outcomes (end points)
Willingness to pay, air pollution information, avoidance behaviors
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Beliefs about air pollution trends and levels
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The sample consists of households in randomly selected blocks in Mexico City. Households are randomized into the pure control group or one of the 7 treatment arms described below.

Pure control: no intervention
Arm 1: free provision of mask
Arm 2: air quality alerts
Arm 3: reminders
Arm 4: air quality alerts + reminders
Arm 5: air quality alerts + mask
Arm 6: reminders + mask
Arm 7: air quality alerts + reminders + mask

Within each of the pure control and treatment arms, the participants will be split between a regular compensation group and a high compensation group.
Experimental Design Details
Randomization Method
Randomization done in office by computer
Randomization Unit
Household
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1,440 households
Sample size: planned number of observations
1,440 households
Sample size (or number of clusters) by treatment arms
Pure control and all arms: 1/8 of the sample. Within each cell of the treatment matrix, 70% of the participants will receive the regular compensation level and 30% of participants will receive the high compensation level.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Southern California
IRB Approval Date
2017-04-14
IRB Approval Number
IRB17-0091
IRB Name
Harvard University
IRB Approval Date
2017-04-14
IRB Approval Number
IRB17-0091
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials