effectiveness of anti-drunken driving campaign: rajasthan experiment design by nina singh, ips...
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Effectivenessof
Anti-Drunken Driving Campaign: Rajasthan Experiment Design
By Nina Singh, IPS
Inspector General of Police, Rajasthan
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
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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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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