Perception biases, car centrism and the distribution of public funding

Last registered on May 30, 2024

View Trial History

Pre-Trial

Trial Information

General Information

Title

Perception biases, car centrism and the distribution of public funding

RCT ID

AEARCTR-0013678

Initial registration date

May 23, 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

May 30, 2024, 3:17 AM EDT

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

Locations

Country

Germany

Region

Primary Investigator

Name

Viola Helmers

Affiliation

RWI - Leibniz Institute for Economic Research

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

On going

Start date

2024-04-24

End date

2024-05-31

Keywords

Environment & Energy, Other

Additional Keywords

Transportation

JEL code(s)

C21, C90, D83, R41, R48

Secondary IDs

Prior work

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

Abstract

This study aims to investigate how Germans perceive the modal split in their cities, whether they can accurately estimate it, specifically the proportion of travel by car, and whether their perception of modal split influences attitudes about public spending on transportation infrastructure. I conduct an information treatment experiment on 4,500 participants within a larger survey on transportation policies and behavior. There are two distinct groups in the survey sample, which receive slightly different experimental designs but with the same overarching hypotheses.

External Link(s)

Registration Citation

Citation

Helmers, Viola. 2024. "Perception biases, car centrism and the distribution of public funding." AEA RCT Registry. May 30. https://doi.org/10.1257/rct.13678-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Participants either receive or do not receive information about modal splits in a) four larger German cities and/or b) in their specific city.

Intervention Start Date

2024-04-24

Intervention End Date

2024-05-31

Primary Outcomes

Primary Outcomes (end points)

We ask participants to distribute hypothetical funds between four transportation modes (car, bike, public transport, walking). The percentages assigned to each of these categories, but especially to the car infrastructure category, are our main outcome.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

We are also interested in how accurately people can estimate the modal split in their city, thus participants' modal split estimates are an important secondary outcome.

Secondary Outcomes (explanation)

Modal split is defined as the percentage of total trips taken in the city that falls onto four mobility categories: car travel (also as passenger, also on motorbikes), biking, taking public transport, and walking.

Experimental Design

By splitting the samples into treatment and control groups, we can investigate how giving additional information and/or making them think more in-depth about modal split in their city or municipality affects participants' preferences about public spending on transport infrastructure.

Experimental Design Details

There are two distinct sub-samples in this study. Both sub-samples receive an information treatment. The sample containing germany-wide participants is split into three groups. The control group does not receive additional information and is also not prompted to estimate their city's modal split. Treatment group 1 is prompted to estimate their city's modal split, but it not provided further information. Treatment group 2 is prompted to give the modal split estimate, and then also receives information on the true modal split in some German cities.
The sample containing participants from three specific cities (Essen, Bochum, Dortmund) is split into two groups. The treatment group here receives exact numbers about their city's specific modal split as an information treatment. The control group does not.
We want to see how receiving different information affects participants' preferences about public spending on transport infrastructure.

Randomization Method

Fully randomized (random assignment into groups).

Randomization Unit

Individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

Sample size: planned number of observations

4,500 participants

Sample size (or number of clusters) by treatment arms

Germany-wide sample: 1000 participants treatment 1, 1000 participants treatment 2, 1000 control
City-specific sample: 750 participants treatment, 750 participants control

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

3.9 percentage points (of funds assigned to car infrastructure) for city-specific sample 3.6 percentage points (of funds assigned to car infrastructure) for Germany-wide sample

Supporting Documents and Materials

IRB