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Nigeria

The need to improve transport impact evaluations to better target the Bottom 40%

Julie Babinard's picture
In line with the World Bank’s overarching new goals to decrease extreme poverty to 3 % of the world's population by 2030 and to raise the income of the bottom 40% in every country, what can the transport sector do to provide development opportunities such as access to employment and services to the poorest?

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.