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Impact Evaluation of Rural Feeder Roads Rehabilitation in Rwanda

This study evaluates the impact of rural feeder road rehabilitation on market efficiency, consumer welfare, asset pricing, and regional development in Rwanda. The data ecosystem created enables precise measurement through an event study design. Preliminary results show potential for income growth in remote villages post-road rehabilitation.

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Impact Evaluation of Rural Feeder Roads Rehabilitation in Rwanda

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  1. Rwanda Rural Feeder Roads Impact Evaluation:Creating a Data EcosystemMaria Jones18 July 2017

  2. national scope = unique IE opportunity

  3. rehabilitation of rural feeder roads

  4. research questions improved roads market efficiency faster development What is the impact of feeder road rehabilitation on … … market prices of village imports and exports? (trade economics) … HH adaptations to price changes in terms of goods produced and purchased? (consumer welfare functions) … market valuation of improved road access as measured by aggregate land value changes? (asset pricing approach) … Regional development as measured by total population? (welfare measure from urban economics)

  5. design • Event study (at the segment level) • Exact timing of rehabilitation of any particular segment as good as random • idiosyncrasies of donor calendars, construction delays, permitting, and weather • Track exact start and end of construction for each segment • Key explanatory variable is road roughness before and after upgrading • Identification relies on high-frequency market information in catchment area of each road segment • sample restricted to segments located close to an existing market

  6. Data

  7. household sample • Sample frame: all villages within 1km of road segment • 2 sampled villages per segment • Class 1: close to a market (for identification) • Class 2: very remote, i.e. those whose transport costs are expected to change most with the road rehabilitation • 15 HHs randomly selected in each village

  8. HH surveys necessary but not sufficient • IE design • Event study design requires higher frequency data than practical through HH surveys • Scope of research questions • interest in precisely measuring market-wide price changes, which will be difficult for any one household to report • Sample size / budget practicalities • Difficult to know ex-ante which households will benefit most; catchment areas are large and little pre-existing data • impact for any one HH in segment catchment likely small

  9. feeder roads: data ecosystem

  10. what makes this work? • Collaboration with project team started long before road construction (2012) • Coordinated monitoring data collection plan across donors so data can be easily merged • Rwandan government collects a lot of administrative data, relatively organized • Advantage of one national ID number, used for all government interactions

  11. Early Results

  12. market integration • At baseline, market integration is poor • Most market vendors report being professional traders (not producers), but the majority sell at only one market • Product availability and price varies within small geographic areas

  13. trader occupation

  14. trader movement across markets

  15. product availability Source: 2017 Price market survey

  16. product price variance Source: 2017 Price market survey

  17. preliminary HH impacts • First follow-up survey conducted one year after baseline • Few segments actually completed; analysis focuses on initial short-term impacts • Follow-up surveys to be conducted every 1-2 years over the project lifetime

  18. preliminary results on HH income • Suggestive evidence that investing in feeder roads allows relatively remote HHs to catch up to relatively more connected HHs • Being located in a remote village decreases HH income by $73 • Mean HH income is $316, so 23.1% decrease • But feeder road rehabilitation increases HH income by $74 (23.4% increase) • Results in a full catch-up to more connected villages • Effect driven by income from HH farm & related activities

  19. Thank you!

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