Clean Air in the Classroom: Environmental Inputs and Human Capital Formation

Last registered on January 09, 2024

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Pre-Trial

Trial Information

General Information

Title

Clean Air in the Classroom: Environmental Inputs and Human Capital Formation

RCT ID

AEARCTR-0012772

Initial registration date

January 08, 2024

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

January 09, 2024, 1:16 PM EST

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

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Primary Investigator

Name

Samreen Malik

Affiliation

New York University (AD)

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Other Primary Investigator(s)

PI Name

Torsten Figueiredo Walter

PI Affiliation

New York University (AD)

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PI Name

Talha Naeem

PI Affiliation

University of British Columbia

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PI Name

Nitin Kumar Bharti

PI Affiliation

New York University (AD)

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PI Name

David Blakeslee

PI Affiliation

New York University (AD)

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Additional Trial Information

Status

On going

Start date

2023-08-01

End date

2024-08-31

Keywords

Education, Environment & Energy, Health

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

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

Abstract

Poor air quality has become endemic in many parts of the world due to its negative impact on health and cognitive abilities, with several developing countries shutting down their education and economic activities for weeks when air quality is bad. Early exposure to bad air quality is linked with serious health impacts that could limit one's potential (Prunicki et al., 2021), making young children particularly vulnerable. While improving outdoor air quality is costly and requires collective action from numerous stakeholders, improving indoor air pollution (IAP) may not only aid in mitigating some of the negative impacts of exposure to bad air quality but also serve as a relatively cheap and feasible policy alternative to shutting down education and economic activities. Our understanding of the efficacy of improving IAP is limited. To that end, we are currently running a randomized field experiment in a private school network in and around Lahore -- one of the most polluted cities in Pakistan -- through which we provide randomly selected schools in the network with air purifiers and monitors to investigate whether improved IAP impacts young children's health, cognitive, and non-cognitive outcomes and how those effects change with cumulative exposure.

External Link(s)

Registration Citation

Citation

Bharti, Nitin Kumar et al. 2024. "Clean Air in the Classroom: Environmental Inputs and Human Capital Formation." AEA RCT Registry. January 09. https://doi.org/10.1257/rct.12772-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

We assigned schools to air purifier treatment, i.e., the schools randomly assigned to the treatment status receive an air purifier. We also place air monitors in treatment and control schools to track air quality.

Intervention Start Date

2023-11-09

Intervention End Date

2024-03-31

Primary Outcomes

Primary Outcomes (end points)

1. Air Quality
2. Test Scores

Primary Outcomes (explanation)

1. Air Quality: We use air monitoring devices to quantify the variations in air quality resulting from our intervention. These monitoring instruments directly capture and record data concerning the concentration of particulate matter present in the air.

Secondary Outcomes

Secondary Outcomes (end points)

1. Disaggregated measures of test scores capturing different aspects of learning and performance
2. Cognitive endurance
3. Non-cognitive outcomes: moral judgement, absenteeism, classroom behavior
4. Adaptation
5. Physical and mental health, including chronic and short-term health problems, sleeping pattern, and happiness.

Secondary Outcomes (explanation)

Experimental Design

We adopted a stratified randomization design, assigning 132 schools to treatment and control within each stratum. The strata are based on a combination of three variables: location (whether the school is located inside or outside the ring road), school size (whether the school is a single or multi-section school) and batch (total of four batches) in which we received the up-to-date data on the school from our first visit. Within each batch (except the last batch), we divide the schools into four types: inside ring road and single section, inside ring road and multi-section, outside ring road and single section, inside ring road and multi-section. In the last batch, since there were only eight schools (all outside the ring road and only one multi-section), we formed it into one stratum. In total, there are 13 strata.

We assigned 60 schools to the treatment group and 72 to the control group. Within multi-section schools, we randomly select a section where equipment is installed. The treatment schools (or the randomly selected section if the school is multi-section) are provided with an air purifier and an air quality monitor. In control schools, we randomly selected 44 schools (out of 72) to receive air quality monitors due to the limited stock of air monitors.

Experimental Design Details

Not available

Randomization Method

Stratified randomization is done in the office by a computer.

Randomization Unit

Section/School

Was the treatment clustered?

Yes