Wildfire Risk and Self-Protective Investment

Last registered on April 26, 2023

View Trial History

Pre-Trial

Trial Information

General Information

Title

Wildfire Risk and Self-Protective Investment

RCT ID

AEARCTR-0011188

Initial registration date

April 17, 2023

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

April 18, 2023, 5:16 PM EDT

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

Last updated

April 26, 2023, 2:34 PM EDT

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

Locations

Country

United States of America

Region

Oregon

Primary Investigator

Name

Judson Boomhower

Affiliation

University of California San Diego

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Patrick Baylis

PI Affiliation

University of British Columbia

Contact Investigator

PI Name

Bob Horton

PI Affiliation

Western Fire Chiefs Association

Contact Investigator

Additional Trial Information

Status

In development

Start date

2023-04-22

End date

2023-12-23

Keywords

Environment & Energy

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

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

Abstract

Like other weather-related disasters, the occurrence of severe wildfires is growing throughout North America. This escalating risk can be mitigated through efforts by property owners to manage vegetation and other flammable material near homes. Despite the cost-effectiveness of these investments, take-up is low. There are several economic and psychological theories for why beneficial self-protective investments in wildfire readiness could have low take-up despite their likely cost-effectiveness: these could include lack of information, complexity and psychological frictions, credit/cash constraints, and spatial externalities across neighboring properties. We propose to conduct a pilot study to identify interventions to address these barriers. We will randomize households in areas with high wildfire risk to receive (1) information about existing resources to support defensible space (e.g., a home assessment from the local fire department) and (2) information about existing resources and a financial incentive. We will also have a pure control group that will not receive any outreach.

External Link(s)

Registration Citation

Citation

Baylis, Patrick, Judson Boomhower and Bob Horton. 2023. "Wildfire Risk and Self-Protective Investment." AEA RCT Registry. April 26. https://doi.org/10.1257/rct.11188-2.0

Sponsors & Partners

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Experimental Details

Interventions

Intervention(s)

We will randomize households in areas with high wildfire risk to receive (1) information about existing resources to support defensible space (e.g., a home assessment from the local fire department) and (2) information about existing resources and a financial incentive. We will also have a pure control group that will not receive any outreach.

Intervention Start Date

2023-04-22

Intervention End Date

2023-06-30

Primary Outcomes

Primary Outcomes (end points)

Improvement in wildfire safety of the property as measured by a State of Oregon wildfire safety checklist and by imagery-based remote assessment technologies.

Primary Outcomes (explanation)

Imagery-based remote assessment is based on a third-party wildfire risk assessment product; our outcome of interest is improvement in this third-party wildfire risk assessment at endline relative to baseline.

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

Experimental Design Details

Randomization Method

Randomization of homes by researchers using a computer.

Randomization Unit

Street level. Each cluster is a set of at most 10 homes located on the same street. If a street contains more than 10 homes, we divide it up, clustering homes together in sets of 10 by their address number. In other words, if William Street has houses numbered from 1, 2, …, 18, we would create two clusters: the first group would have the homes from 1-10 William Street, while the second cluster would have homes from 11-18 William Street.

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

There are 648 total clusters. Each cluster contains between 1 and 10 homes on the same street, as described above.

Sample size: planned number of observations

There are 4,662 homes in the sample.

Sample size (or number of clusters) by treatment arms

540 clusters control, 27 clusters $250 incentive, 27 clusters $500 incentive, 27 clusters information treatment, 27 clusters "moral suasion" treatment.

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

Supporting Documents and Materials

IRB