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Heckle and Chide: Empowering matatu passengers to enforce better driving behavior in Kenya. James Habyarimana Georgetown University and William Jack Georgetown University. Motivation.
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Heckle and Chide:Empowering matatu passengers to enforce better driving behavior in Kenya James Habyarimana Georgetown University and William Jack Georgetown University
Motivation • “Accidents happen!” he says, with a cheerful shrug. "Maniacs? Maybe we are a little bit - butyou've got to drive fast to get the money!” • A matatu driver in Kenya • “Taxi drivers put money first and passengers' and pedestrians' lives second” • Patrick Ayumu, Ghana
Objectives of the project • Evaluate a randomized intervention aimed at reducing matatu accidents by • empowering passengers to…. • .…enforce better driving behavior • Using evocative messages placed inside the matatu
WHY road safety? • Major cause of injury and death • Rising share in global deaths • Economically costly – 2% of national income in Kenya • Vulnerable population: working age (15-44) accounts for 75% of RT fatalities (Odero (2003))
WHY matatus ? • They account for a large share of inter-city passenger transport • Vulnerable population in road traffic injuries • They are involved in 20% of recorded crashes • But larger share of injuries/fatalities • They are well suited to our intervention
WHY so many crashes? • Road conditions • Vehicle conditions • Behavior of other road users • Behavior of matatu drivers Focus of study
WHO can affect driver behaviour? Government (incl. police) Owners / Operators Matatu drivers Focus of study Passengers
HOW do we empower passengers? • Tell them to speak up! • “Heckle and Chide” • Insert stickers with messages inside matatus
Sticker Placement Plan Side door Vibaya Leg Front of matatu Driver’s seat Ajali Sit Foot
HOW do we evaluate impact of the intervention? • RCT • compare randomly selected matatus with stickers to a control group of matatus without stickers • Outcome measures • Crash rates • Associated injuries/fatalities • Survey results of passenger and driver behavior
Motivating the intervention • Are accident rates efficient? • Collective action problems inside matatus • If not, what is the role of regulation? • Enforcement problems in public regulation • Stickers could either: • increase perceived benefit of action – if people underestimate the effects of accidents; or • reduce the cost of taking action • stickers legitimize heckling • Focal point for passenger action
Timeline January 2000 May 2008 March2008 August 2007 Pilot recruitment • Weekly Raffles • Accident Data Collection • Follow up surveys • Trip observations Recruitment
Data • Sample of 2,276 matatus from 21 SACCOs* • 6 SACCOs account for about 50% of the sample • account for 166-312 vehicles • 40% of sample had been assigned during pilot phase • Random assignment from SACCO lists to treatment status: p=0.625 • 60% new matatus • assignment based on last digit of plate number • Odd Treatment • Even Control * Savings and Credit Cooperatives
Consent and Compliance • Informed consent obtained from drivers • Consent from owners very difficult • Better compliance in pilot sample
Outcome data: accidents • Main outcome of interest is accidents • Accident occurrence • Severity - # injured, killed per accident • Collected data from two sources • Insurance companies • All vehicles are required to have minimal coverage • In theory all accidents should be observable – submission of claims endogenous • Our own data collection efforts
Other outcome data • Survey data from drivers and passengers to assess behavior of both • Safety of drivers • Heckling and chiding by passengers • Direct observation of driver behavior • Send anonymous passengers on matatu trips?
Empirical Specification • Difference-in-differences strategy to estimate • Parallel trends assumption • Main concern is that treatment status is potentially endogenous • Estimate intent-to-treat parameter • Use assignment to treatment as instrument • IV estimates
Average treatment effect Standard errors in parentheses, + significant at 10%; * significant at 5%; ** significant at 1%
Intent-to-Treat Estimator Standard errors in parentheses, + significant at 10%; * significant at 5%; ** significant at 1%
Average Treatment Effects: LPM P-values in parentheses, + significant at 10%; * significant at 5%; ** significant at 1%
Next Steps • Examine data on possible mechanisms • Collect more detailed claims data from insurance companies • Includes data on injuries • Types of events being affected by intervention • Direct observation