Enriching Impact Assessment: Long-term Geospatial Evaluations in PeruADP Inception Report

The Geospatial Impact Evaluation (GIE) team will conduct a geospatial impact evaluation into components of the Alternative Development Program (ADP) using the Expanding the Reach of Impact Evaluation (ERIE) methodology within the Monitoring, Evaluation, Research, and Learning Innovations Program (MERLIN) USAID mechanism. ERIE facilitates retrospective, long-term impact evaluations of completed USAID interventions to assess if short-term impacts were sustained or if long-term outcomes emerged. This approach leverages existing program data and employs innovative data collection strategies to identify appropriate counterfactuals and generate lessons for planning and conducting long-term impact evaluations.

While many development interventions are assumed to have long-term impacts, evidence is often lacking due to a focus on short-term outcomes, rigid program cycles, unreliable funding for monitoring and evaluation, and shifting programmatic priorities. This lack of evidence hinders informed decision-making, particularly in sectors with theories of change extending beyond typical project cycles. Addressing this requires measuring policy or program results over extended periods and large geographic scales, which is currently rare. Such evaluations are well-suited to environmental and natural resources interventions where landscape change is typically measured at decadal or semi-decadal scales and across broad landscapes.

Two recent developments make long‐term evaluations in development programs more feasible now than in the past:

1. First, the uptick in impact evaluations has built a portfolio of rigorously studied programs we can revisit for long‐term follow‐up.
2. Second, a rapid improvement in the granularity, coverage, and nature of geospatial data — from both aid activities and outcomes — has created new opportunities for rigorous, quasi‐experimental evaluations, including retrospective analyses. For example, advances in geocoded data and big data analytical capabilities allow us to construct measures of broad economic activities across a landscape. Geocoding, GIS, and satellite imagery allow us to define what activities took place, where, when, and by whom. When merged with traditional socio-economic evaluation data, these new kinds of program and outcome data create potent opportunities for assessing long-term impacts that currently lack evidence