Contracting the Road to Development: Early Impacts of a Rural Roads Program
We study here the early impacts of the Peruvian Rural Roads Program (RRP), characterized by a decentralized mechanism that contracts private local firms for the rehabilitation and maintenance of rural roads with local supervision by community leaders setting incentives that favour prevention activities and a sustainable and timely maintenance of rural roads. The analysis is based on a quasi-experimental approach through which control roads are defined prior to the intervention and based on key observable characteristics of the road and the villages they connect. Diff-in-Diff estimates are reported to control for biases associated with time-invariant unobservables. We find that this institutional innovation improved road transitability, which in turn led to significant changes in employment patterns and increased investments in education and health. Income effects are not significant on average, but they appear strong in villages with pre-existent endowments of key productive infrastructure, favouring the notion that road improvements need to be complemented with additional investments to effectively contribute to the reduction of rural poverty. Most of these results, though, are concentrated on interventions in motorized roads, although the inclusion of non-motorized tracks is supported by the empowering of women through their participation in farm activities. Thus, the results of this early evaluation are encouraging in terms of program impacts, as these indicate that the Peruvian RRP has been able to control local capture and corruption threats.
|Date of creation:||2010|
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- Jyotsna Jalan & Martin Ravallion, 2000.
"Estimating the Benefit Incidence of an Antipoverty Program by Propensity Score Matching,"
Econometric Society World Congress 2000 Contributed Papers
0873, Econometric Society.
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- Zhong Zhao, 2004. "Using Matching to Estimate Treatment Effects: Data Requirements, Matching Metrics, and Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 91-107, February.
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