Smart Congestion Pricing: Testing Travel Incentives to Reduce Congestion in Bangalore

Last registered on March 09, 2017
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Pre-Trial

Trial Information

General Information

Title
Smart Congestion Pricing: Testing Travel Incentives to Reduce Congestion in Bangalore
RCT ID
AEARCTR-0002083
Initial registration date
March 09, 2017

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
March 09, 2017, 3:33 PM EST

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

Locations

Country
India
Region
Bangalore

Primary Investigator

Name
Gabriel Kreindler
Affiliation
Massachusetts Institute of Technology
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2017-02-06
End date
2017-12-31
Keywords
Environment & Energy
Additional Keywords
urba, transportation, traffic
JEL code(s)
Secondary IDs
Abstract
Cities in developing countries increasingly face severe and apparently intractable traffic congestion. Congestion charges that discourage driving at peak hours and in congested areas are theoretically appealing. However, we know very little about how they work in practice. This experiment tests the impact of time-based (peak-hour) and area-based congestion charges on travel behavior, for a sample of car and motorcycle drivers in Bangalore. GPS enabled smartphones are used to collect travel behavior data, to communicate with respondents, and to implement the congestion charges.
External Link(s)

Registration Citation

Citation
Kreindler, Gabriel. 2017. "Smart Congestion Pricing: Testing Travel Incentives to Reduce Congestion in Bangalore." AEA RCT Registry. March 09. https://doi.org/10.1257/rct.2083-1.0
Former Citation
Kreindler, Gabriel. 2017. "Smart Congestion Pricing: Testing Travel Incentives to Reduce Congestion in Bangalore." AEA RCT Registry. March 09. https://www.socialscienceregistry.org/trials/2083/history/14827
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2017-03-13
Intervention End Date
2017-09-08

Primary Outcomes

Primary Outcomes (end points)
We study urban travel behavior using private modes of transportation. The main outcomes are trip departure time and trip duration. We will also look at the extensive margin of travel, as well as route choice.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Commuters who regularly drive a car or a motorcycle are recruited in Bangalore, and invited to install a smartphone app that collects travel information using GPS. After a period of baseline data collection, they are randomized into the intervention. The main treatment participants receive time-based congestion charge type incentives (deducted from an initial grant); there is also an information group who receives similar information about traffic congestion patterns and regular updates about their travel behavior, but no incentives. There is also a control group that receives neither. A second type of treatment is an area congestion charge, and this is cross-randomized with the main treatment.
Experimental Design Details
Commuters who regularly drive a car or a motorcycle are recruited in gas stations Bangalore, and invited to install a smartphone app that collects travel information using GPS. After a period of two weeks of baseline data collection, they are randomized into the intervention, which lasts 4-5 weeks. The main treatment participants receive time-based congestion charge type incentives (deducted from an initial grant) for a period of three weeks; there is also an information group who receives similar information about traffic congestion patterns and regular updates about their travel behavior, but no incentives. There is also a control group that receives neither. A second type of treatment is an area congestion charge, and this is cross-randomized with the main treatment. The congestion charge arm of the main treatment contains low and high incentives sub-treatments, as well as low and high initial grant sub-treatments. The area congestion charge contains: low and high incentives, short and long induced detour, and early and late implementation sub-treatments.
Randomization Method
Randomization done in office by a computer.
Randomization Unit
Individual study participant.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
600 commuters
Sample size: planned number of observations
600 commuters
Sample size (or number of clusters) by treatment arms
Peak-Hour Congestion Charge: 240
Information: 180
Control: 180
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Institute for Finanacial Management Research (IFMR)
IRB Approval Date
2016-02-20
IRB Approval Number
IRB00007107; FWA00014616; IORG0005894
IRB Name
Massachusetts Institute of Technology (MIT) Committee on the Use of Humans as Experimental Subjects (COUHES)
IRB Approval Date
2016-12-07
IRB Approval Number
1511312369A002
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