Slow Down! Pilots to Decrease Speeding and Incidence of Fatal Traffic Accidents in Nicaragua

Last registered on January 09, 2020

View Trial History

Pre-Trial

Trial Information

General Information

Title

Slow Down! Pilots to Decrease Speeding and Incidence of Fatal Traffic Accidents in Nicaragua

RCT ID

AEARCTR-0005233

Initial registration date

January 06, 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

January 09, 2020, 3:46 PM EST

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

Locations

Country

Nicaragua

Region

Latin America

Primary Investigator

Name

Arndt Reichert

Affiliation

Leibniz University Hannover/ The World Bank

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

In development

Start date

2020-03-31

End date

2022-01-31

Keywords

Crime, Violence, & Conflict, Health, Other

Additional Keywords

road safety

JEL code(s)

Secondary IDs

Abstract

This experiment will generate evidence on the use of various (behaviorally informed) engineering measures for decreasing drivers’ speeds on road spots at which accident rates are much higher than the average. In a randomized control trial, we will compare three different strategies of road markings that drivers are exposed to when approaching a risky road spot.

External Link(s)

Registration Citation

Citation

Reichert, Arndt. 2020. "Slow Down! Pilots to Decrease Speeding and Incidence of Fatal Traffic Accidents in Nicaragua." AEA RCT Registry. January 09. https://doi.org/10.1257/rct.5233-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2020-06-01

Intervention End Date

2021-05-31

Primary Outcomes

Primary Outcomes (end points)

Driver speed: Speed driven as measured by radar guns at pre-determined road sections; we will look at speeding variance as well as top speeds, taking into account speeds at different times of the day
• Traffic accidents: Accidents recorded by the Nicaraguan Police, assigned by Police to road sections in situ; we differentiate by type of individual involved in the accident (driver, other road user, pedestrian)
• Accident-related hospital admittances: hospital admittances recorded by the Nicaraguan Ministry of Health, assigned to road sections by the Police and Ministry of Health; we differentiate by type of individual involved in the accident (driver, other road user, pedestrian)
• Accident-related fatalities: fatalities attributed to traffic accidents, assigned by Police to road sections in situ; we differentiate by type of individual involved in the accident (driver, other road user, pedestrian)

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

In a randomized control trial, we will compare three different strategies of road markings that drivers are exposed to when approaching a risky road spot. These markings in parts use physical adjustment as well as optical illusion techniques and vary by the degree of predictability (or surprise factor) for the drivers with expected trade-offs in terms of the duration and strength of the impact on speeding. For instance, markings to narrow the lane width around the risky spots is likely to have a marginal but steady effect on speeding because these changes are quite common and hence have less of a surprise effect. On the contrary, optical illusion techniques that make it look like physical traffic calming barriers on the road may cause minor damages to the vehicle if not slowing down, is likely to have strong and immediate impacts in the short term, but the impact are expected to fade quickly given that drivers update their priors about the risks of vehicle damage as a result of speeding.

Experimental Design Details

Randomization Method

randomization done in office by a computer

Randomization Unit

risky spot

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

100

Sample size: planned number of observations

100

Sample size (or number of clusters) by treatment arms

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

Due to high frequency of the data, we will be able to detect an effect size of roughly 0.25 of a standard deviation, or approximately a reduction of 0.925 accidents per month.

Supporting Documents and Materials

IRB