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Brazil

Sao Paulo’s Innovative Proposal to Regulate Shared Mobility by Pricing Vehicle Use

Georges Darido's picture
Taxi drivers in Sao Paulo recently protesting the regularization of TNCs such as Uber.
Photo by: Diego Torres Silvestre / Flickr

How to regulate and manage the emerging services of shared and on-demand mobility? This was a topic of much debate during the most recent Transforming Transportation event, a major global conference of transport professionals organized by the World Bank and the World Resources Institute in Washington DC in January 2016. 

One recent development from Sao Paulo stands out as a worthwhile effort to balance the objectives of promoting innovation by Transportation Network Companies (TNCs, such as Uber, Lyft, EasyTaxi, 99Taxi, and others) and ridesharing services (such as BlablaCar, Caronetas, Tripda and others) with the interests of the city and its residents. 

The Municipal Government of Sao Paulo has published for public comments until January 27, 2016  a draft decree to charge TNCs an upfront fee based on an estimate of vehicle-kilometers, also referred to as “credits”, to be used by its fleet of passenger cars in a two month period, plus a surcharge if credits are exceeded.   The idea is that any registered TNC could bid in an online public auction to purchase credits periodically and with certain limitations to ensure competition.  This approach would create a market for these credits and be aligned with the principle commonly known in the vehicle insurance industry as “pay-as-you-drive”, and would allow the city to receive a fee from TNCs for the commercial use of its public road infrastructure, which can then be used to better manage and maintain it.   The decree would exempt free ridesharing services which the city believes would help reduce the total number of vehicle-kilometers on its congested road network.

Rio: A hot city tackles global warming through mass transit

Daniel Pulido's picture
SuperVia, Rio de Janeiro / 2.0 Brasil

It is the end of another hot day in Rio de Janeiro. I’m tired and sweaty after spending the afternoon checking out the progress on some of the city’s train stations, which are being renovated for the upcoming Olympic Games. But I’m also happy, having witnessed the progress made in improving Rio’s suburban rail system, known as SuperVia, which the World Bank has been supporting for the last 20 years.

Do better roads really improve lives?

Eric Lancelot's picture
Also available in: Español | Français | العربية | Português

How can improved roads change peoples’ lives? How much do people benefit from road projects? Answering these seemingly simple questions is, in fact, much trickier than it appears.

We recently concluded an impact evaluation to measure the socio-economic impacts of World Bank-financed municipal road improvements on poor rural households in the state of Tocantins, Brazil. After 10 years of study, what were the results and lessons learned? And how did we go about conducting the evaluation?

The study followed a methodology traditionally used in impact evaluations in the social sector and was based on a precedent in Vietnam. Throughout the state, one of the least-developed and least-populated in Brazil, most municipal roads are unpaved with inadequate maintenance. The World Bank’s municipal roads project helped construct 700 concrete bridges and 2,100 culverts crossing rivers and streams, providing year-round access to remote populations that once couldn’t access municipal centers during rainy season.

The anticipated result chain of the project was as follows: improvement of physical accessibility would contribute to increase travel demand to markets, schools and health services. This would, in turn, contribute to improved education, better health and increased business opportunities. Finally, it would result in long-term household income growth.

Our study aimed at measuring these impacts through a “difference in differences with matching,” a method that compares a treatment group (population benefiting from the interventions) and a control group (population that does not), while ensuring similar socio-economic characteristics (or comparability) between groups. An “instrumental variables estimator” was then used to confirm the robustness of the results.

The results show positive socio-economic impacts to rural residents, as well as provides for several policy implications: