Evaluating the Impacts of the Dar es Salaam BRT System Team Ronald Lwakatare, John Shauri, Ami Srivastava (DART) Gharad Bryan, Clare Balboni, Adam Cole (London School of Economics) Melanie Morten, Chris Becker (Stanford University) Yonas Mchomvu, Bilal Siddiqi, Cecilia Escalante (World Bank) Rachel Steinacher, Jessica Mahoney, Nicolas Lusingu (Innovations for Poverty Action)

Dar es Salaam Bus Rapid Transit System Phase 1 of (6 phase) Dar es Salaam BRT Opened May 2016 21km of bus ways, 5 terminals, 2 depots, 27 bus stations Connects high-income CBD with middle/low-income residential areas First operational BRT in East Africa

We would like to know: does the Dar BRT… Reduce travel times? Create jobs and boost income? Encourage firm productivity, trade and growth? Improve property values? Make roads safer? Increase the health, wealth and happiness of Dar residents – especially the poorest?

Evaluation approach aims to… …estimate the impacts of BRT Phase 1 Understand how the BRT has affected the lives and welfare of residents As well as the impacts on urban neighborhoods, development and growth … and understand the mechanisms through which impacts happen e.g. through greater mobility? Relocation of people/firms? …while laying the groundwork to evaluate future phases Phases 2, 3 planned in the near future, 4-6 later on Don’t want to reinvent the wheel for future evaluations! …and providing information relevant to for other contexts! Should inform BRTs planned in other African cities, elsewhere in the world

Combination of methods used to achieve this Spatial “triple-differences” approach Compare places (i) near and far from Phase 1 with places (ii) near and far from planned Phase 2, (iii) before and after Phase 1. Mechanism experiments (randomized controlled trials) Temporary fare subsidies to encourage (some) commuters to use BRT – compare to control group to understand impacts of using the BRT “Spatially conditional” cash transfers to encourage (some) residents to stay where they are, or relocate – to understand BRT’s impacts on relocation and urban development Structural modeling to estimate general equilibrium impacts Mechanism experiments will produce key elasticities for model Allow findings to be applied to other contexts

What we have been up to so far Jan 2016: Baseline surveys Travel time survey Household survey May 2016: BRT Phase 1 Opens Mar 2017: Tracking baseline sample Household tracking survey Mobile survey enrolment May 2017 (onwards): Mobile survey SMS- and call-based Semi-monthly to panel of respondents

Spatial triple differences approach We are trying to understand if the BRT caused changes in outcomes of interest Want to make sure that changes were not caused by other things If BRT went to neighborhoods that were richer, we would see more jobs, higher income – but not caused by BRT! If rich people moved away from BRT areas, we would see less income – but not caused by BRT either! Need a comparison (“control”) group Find locations and individuals that look just like those affected by BRT Compare “treatment” and “control” groups – just like a medical experiment!

Spatial triple differences approach Compare places (i) near and far from Phase 1 with places (ii) near and far from planned Phase 2, (iii) before and after Phase 1. Difference 1: Compare A* to B* = ∆ Difference 2: Compare ∆ to difference between A’ and B’ Difference 3: Compare these differences before and after Phase 1

Baseline data collection (Jan 2016) Dense geographical sampling strategy ensures coverage inside and outside catchment areas of Phase 1 Surveyed 1749 households from sampled neighborhoods Data can be used as baseline for impact evaluation of future phases

Examples of baseline data (Jan 2016)

Baseline sample tracking and mobile surveys Very early results from first tracking attempt Baseline sample: 1749 households, 2 respondents/HH Through phone/tracking, so far reached and enrolled 1315 individual respondents in monthly mobile surveys Of these, 902 one of the baseline survey respondents Asked 3 simple questions Going forward, hope to get (almost) full sample… Full follow-up survey of baseline respondents Sep 2017 We expect results to change

Who is riding the BRT? Of 902 tracked baseline respondents, 32% rode the BRT last week Socioeconomic status: Basic Needs Poverty Line: 24% below vs 34% above Unemployed: 32% Informal sector workers: 31% Age 18-60 32.5% vs 61+ 25% Female 30% vs Male: 33% Private vehicle users 44%, vs Daladala 35%, Walk: 31%

Changes in hours worked Scale Red/orange: hours worked went up Blue/green: hours worked went down No conclusive relationship (yet) between BRT Phase 1 and hours worked But suggests focusing on time-use If people save time from commuting, what do they use the time for?

What we plan to do next! Follow-up survey of baseline sample Estimate short-term (18 month) impacts Experiments to understand mechanisms of change – to develop this week Experiment 1: Fare subsidies Objectives: (i) to measure direct effects of riding the BRT and (ii) to understand access issues Experiment 2: “Spatially Conditional” Cash Transfers Objective: to understand relocation and urban development due to BRT

Experiment 2: “Spatially Conditional” Cash Transfers

What we plan to do – for the next 3 years! July-Aug 2017 – Qualitative study of urban housing market To inform the feasibility and design of housing RCT Sep 2017 – Follow-up survey 1 Reinterview all baseline respondents Oct-Dec 2017 – Analysis First set of spatial triple-diff results Presented and disseminated Jan-Feb 2018 – Housing RCT launch Sample enrolment and baseline survey Disbursement of first set of cash transfers Oct 2018 – Follow-up survey 2 Will provide 2-year impacts Nov-Dec 2018 – Fare RCT launch Sample enrolment and baseline survey Disbursement of 6-month smartcards Jan 2019 – Housing RCT endline Feb–Jun 2019 – Analysis Second set of spatial triple-diff results Results from housing RCT Presented and disseminated July 2019 – Fare RCT endline Aug 2019-Jun 2020 – Analysis Results from fare RCT Results from structural modeling exercise Final results presented and disseminated