Agricultural development projects usually combine multiple inputs and activities in order to raise farmers production, productivity and income. Such interventions are complex and often evolve during implementation, which often lasts for several years. Moreover, this type of project is part of a complex environment where economic, social and environmental conditions are constantly changing. In addition, the potential beneficiaries themselves face diverse initial conditions in terms of access to production factors, knowledge and strategies. This presentation intends to show that a rigorous and information-rich qualitative analysis within a treatment/control setting constitutes a valuable alternative to a purely quantitative approach to impact evaluation for this type of project. Furthermore, we argue that a systemic approach can usefully improve the internal validity of an impact evaluation based on qualitative analysis, when combined with the purposeful sampling of households from comparable communities in order to construct a comparison group.
This presentation will explain the systemic impact evaluation method step by step and the multi-level analysis it implies.
We developed and tested the systemic impact evaluation method on an agricultural project in Guinea, called Guinean Oil Palms and Rubber Company (SOGUIPAH) project.
The central issue of the "Social Assistance System Modernization" Project in Ukraine is the introduction of Single Window Technology (SWT) for citizens applying for several assistance programs, known as the "one-stop shop". The systemic approach is used in order to investigate the effects of main activities performed by the government for the SWT implementation. Keeping in mind complexity and inertia of social processes involving intricate interrelations between social assistance system components, we carefully design the structural model describing the mechanism of effects transmission. We explore the short-term effects on three logical blocks of performance indicators, such as changes in capacity/efficiency, qualitative characteristics of the system and the behavior of the households/ population. For the purpose of analysis the data from several comprehensive datasets are collected in order to assess re-engineering efforts from the point of view of different participants.