In order to make informed policy recommendations, development research faces two broad challenges: first, to identify and estimate the effects of interventions where they have occurred, and second to build and test theories about the effects that a related intervention would be hypothesized to exert in a different context. I review three recent strands of research that seek to integrate qualitative methods into policy-oriented development research and find that qualitative methods, when incorporated into mainstream development research, are often used to improve measurement validity and to develop hypotheses and theories that address the first challenge. However, qualitative approaches to causal inference are rarely used, and as a result qualitative methods can rarely be used for testing theories, particularly with regard to the second challenge. After suggesting an a priori argument for why qualitative causal inference could benefit policy-oriented research, I demonstrate how this approach gives rise to significantly different policy implications than would otherwise emerge in a specific context: rural land institutions in India.

Last modified

• 01/03/2019

Creator

• Andre Nickow

DOI

• https://doi.org/10.21985/N26F30

Alternate Identifier

• 15-001

Keyword

• policy-oriented
• casual inferences
• buffett
• development research

Date created

• 2015

Resource type

• Research Paper

Rights statement

• In Copyright