Effectivenessof

Anti-Drunken Driving Campaign: Rajasthan Experiment Design

By Nina Singh, IPS

Inspector General of Police, Rajasthan

Rajasthan:Geographical Location

Background Road Accidents killed more than 9,100

people and injured more than 31,000 in Rajasthan (2010)

Drunken driving one of the major concerns Absence of segregated data about the

reasons of these accidents Enforcement by local police stations Low Priority Work

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MIT Poverty Action Lab Goal: Improve effectiveness of programs by providing

policy makers with clear scientific results that help shape successful polices

Key Approach: Compare randomly chosen reformed (“treatment”) areas with random un-reformed (“control”) areas and examine difference in outcomes

Applies randomized trial approach to a variety of projects in different fields Health Education Governance Reform (such as Police Reforms)

Previous collaboration with Rajasthan Police: “Police Performance and Public Perception” (2005-2008)

Interventions Use of Breath-analyzers at check points Introduction of dedicated police teams

from Reserve Lines for enforcement Use of GPS enabled tracking system for

vehicles used by the dedicated teams from the Reserve Police Line

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Breath Analyzers Device features

Provides rapid evidence of blood-alcohol content

Automatically maintains a record of the date, time, and alcohol level of each breath test

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GPS Monitoring Device features

Provides up-to-the-second information about vehicle location

Maintains a record of vehicle’s travel history

Displays GPS information via an online Google Maps portal accessible to J-PAL researchers, District Police, and Jaipur City Control Room6

Objectives Evaluate the impact of the three

interventions: Breath analyzers on reducing road accidents Dedicated police teams on enforcement Technology aided supervision (GPS) on

execution of interventions Collect objective evidence of success

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Pilot Districts Jaipur Rural contributes

7.9% of total deaths in Rajasthan 8.2% of total accidents in Rajasthan

Bhilwara contributes 3.9% of the total deaths in Rajasthan 4.0% of the total accidents in Rajasthan

Both the districts have long stretches of National Highways

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Methodology: RCTs 40 police stations in the 2 districts were

randomly divided into: “Treatment” stations, each holding 2 check points

per week between 7 pm and 10 pm “Control” stations, doing no special enforcement

How? Computerized random assignment Designed so treatment and control groups are

similar in terms of accident rates, geographic locations, and proximity to national highways

Why? With randomization we expect no systematic

differences between treatment and control groups Thus, control group can serve as an accurate

benchmark for measuring treatment group outcomes 11

Flow Diagram

Fixed/Surprise Check PointsTreatment police stations were further randomly

divided into: Fixed-Check Point stations: Fixed location

and days of checking. Surprise- Check Point stations: Different days

and locations of checking, thereby incorporating the element of surprise.

Why?Gives objective evidence of whether police should

Concentrate enforcement in high-risk areas, or Vary check point locations, to catch offenders off-guard.

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Police Station/Police Line TeamsTwo types of teams constituted in treatment

stations and randomly assigned the duties for conducting the checkings:

Local police station teams Conducted 2 checkings per week in the police station

area Dedicated teams from the district Police

Reserve Lines Conducted 6 checkings per week at 3 different police

station areas Assigned dedicated police jeeps, equipped with GPS

devices

Why?Determine whether the dedicated teams are better

while enforcing checkings compared to the police station teams

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Checking Schedule(30 days of enforcement)

Sources of Data Breath analyzer memory GPS database Police logs kept at checking points Accident data from Police Stations Court records Independent surveys by J-PAL Researchers

and Surveyors Regarding the traffic flow, police checking

pattern and drunk drivers caught at the checking points

Regarding the general traffic patterns in absence of checking points

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Statistical Significance of Pilot Heads Probability that the reported

effect is not due to random chance

Injuries 66%

Deaths 69%

Night Accidents 84%

Highway Accidents 66%

Serious Accidents 34%

Total Accidents 19%

Future Scale Up Approximately 11 districts

Representative sample, based on statistical indicators, accident rates, geography, demographics

Proposed district list: Ajmer, Alwar, Banswara, Bharatpur, Bhilwara, Bikaner, Bundi, Jaipur Rural, Jodhpur, Sikar, Udaipur

Maintain successful practices from pilot Continued use of dedicated Reserve Line teams Both “Fixed” and “Surprise” checking strategies Use of GPS devices for monitoring Lines teams Comprehensive, objective data, including traffic analysis by J-

PAL Improve upon pilot design

More systematic use of breath analyzers Longer intervention, in order to assess sustainability Introduce variation in number of checkings per week Days/Time of the checkings

Scope of improvement: 1 Infrequent use of breath analyzers

14.8% of passing drivers were stopped by police Only 1.2% received breath test

More frequent use would send a stronger message, and perhaps help police catch more drunk drivers.

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5

10

15

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7:30 to 8:00 8:00 to 8:30 8:30 to 9:00 9:00 to 9:30 9:30 to 10:00

%

Percent of passing drivers given breath test

Percent of passing drivers stopped by police

Scope of improvement: 2 Most drunken drivers caught on Tuesdays

and Thursdays: 23.8% more than on Saturdays and Sundays.

Does that mean more drinking on these nights?

Hopefully results from the larger evaluation would help policy planners

to make appropriate policy interventions to improve Road Safety.

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Thank You