Estimating the direct and indirect benefits of transport projects remains difficult. Only a handful of rigorous impact evaluations have been done as the methodologies are technically and financially demanding. There are also differences between the impact of rural and urban projects that need to be carefully anticipated and evaluated.
Can we simplify the methodologies?
Despite the Bank’s rich experience with transport development projects, it remains quite difficult to fully capture the direct and indirect effects of improved transport connectivity and mobility on poverty outcomes. There are many statistical problems that come with impact evaluation. Chief among them, surveys must be carefully designed to avoid some of the pitfalls that usually hinder the evaluation of transport projects (sample bias, timeline, direct vs. indirect effects, issues with control group selection, etc.).
Impact evaluation typically requires comparing groups that have similar characteristics but one is located in the area of a project (treatment group), therefore it is likely to be affected by the project implementation, while the other group is not (control group). Ideally, both groups must be randomly selected and sufficiently large to minimize sample bias. In the majority of road transport projects, the reality is that it is difficult to identify control groups to properly evaluate the direct and indirect impact of road transport improvements. Also, road projects take a long time to be implemented and it is difficult to monitor the effects for the duration of a project on both control and treatment groups. Statistical and econometric tools can be used to compensate for methodological shortcomings but they still require the use of significant resources and knowhow to be done in a systematic and successful manner.
Estos “bonos de proyectos” están principalmente dirigidos a inversionistas institucionales —incluidos fondos de pensiones— y han generado un gran interés entre banqueros de inversión, firmas de abogados e inversionistas. Todo este bombo plantea una serie de preguntas: ¿Están los "bonos de proyectos" realmente a la altura de las expectativas? ¿Pueden los Gobiernos depender de los ahorros pensionales para financiar proyectos (¡un nuevo significado para la sigla APP!)? ¿Qué necesitamos hacer para convertir a los fondos de pensiones en una fuente de financiamiento significativa y así terminar con el déficit de inversión en el sector de infraestructura?
These “Project Bonds” mostly target institutional investors - including pension funds, and have generated a great deal of interest among investment bankers, lawyers and investors. All this hype raises a number of questions: Are these “Project Bonds” really living up to expectations? Can governments really rely on Pensioners Paying for Projects (a newfound meaning for PPPs!)? What do we need to do to turn these instruments into a significant source of financing and close the infrastructure investment gap?
While we have not been significantly involved with such services thus far, a recently appointed mobility secretary in a big Latin American city has asked us for support on developing an approach to the shared taxi industry, as part of a "Smart Mobility" strategy for the city. In that context, we wanted to start a conversation on optimal strategies for cities to be able to welcome and foster such innovations, while still capitalizing on the opportunity to create value for its citizens.
Construction of the Quito Metro
We know that technology is not a panacea, that gadgetry and software are not always the right solutions for our transport problems. But how do we know – really know -- when technology is truly the wrong way to go – when, say, using an old-fashioned compass is genuinely better than a GPS?
Thanks to blogger Sebastiao Ferreira, writing for MIT’s CoLab Radio, I have learned about an intriguing phenomenon in Lima, where entrepreneur data collectors, named dateros, stand with clipboards along frequented informal microbus routes, collecting data on headways, passenger counts, and vehicle occupancy levels. The microbus drivers pay dateros about 10-cents per instant update, and they use the information to adjust their driving speed. For example, if there is a full bus only a minute ahead of the driver’s vehicle, the driver will slow down, hoping to collect more passengers further down the route. In informal transit systems, where drivers’ incomes are directly tied to passenger counts, paying dateros is a good investment (Photo from MIT CoLab Radio).
If you think about it, use of dateros could be more efficient than traditional schedule or GPS-based dispatch, because the headways are dynamically and continuously updated to optimize the number of passengers transported at any given time of day. According to Jeff Warren (a DIY cartography pioneer), the dateros have been praised as the “natural database, an ‘informal bank’ of transportation optimization data.”
Does this little-known practice call into question our traditional prescription for high-tech solutions to bus dispatch?