Association for Public Policy Analysis & Management

There is a growing consensus in international development about poverty as a multidimensional phenomenon, however, there is no consensus on a single definition of multidimensional poverty. Poverty is context specific and affected by a complex interaction of multiple factors. In addition, the use of multidimensional results implies a practical difficulty in program evaluation: the changes in the results could be driven by one dimension, multiple dimensions or the interaction between them. This paper proposes a methodological framework to evaluate international development programs, integrating multidimensional outcomes with complexity theory. This framework is based on a mixed-methods exploratory sequential design, which uses causal loop diagrams to involve the perspective of local communities in the development of quantitative research strategies. First, qualitative methods are used as the main input for the construction of a program's theory of change. This implies the participation of local actors to define a Multidimensional Poverty Index (MPI) and a causal systems theory on the program's implementation. Second, quantitative methods are used to test this theory. This implies the use of econometric tools for causal inference to test the program effect over the MPI. Finally, the qualitative inputs are used to identify the causal mechanisms explaining the quantitative results and, therefore, to evaluate the external validity of the program. Instead of providing a black and white description of the program's average treatment effect, the objective of this methodology is to analyze the transformation process initiated by a program and to generate knowledge about its implementation in a complex system.