Proposal: Evaluating Development Project Outcomes

Research Question:

Broadly: Can Social Network Analysis be a useful tool in evaluating development programs?

Specific to Current Proposal: What are some key predictors of household cook-stove purchases? Who are socially influential actors within a household and outside of it? Can recommendations be made to increase probabilities of purchase based on network analysis?

Background:

The field of international development is increasingly moving towards data-driven methodologies. Systematic evaluations, carried out before, during, and after implementing a program, can be useful not only in determining whether an extant project has been successful, but also by providing transferrable lessons that may reduce redundancies in future endeavors. Data driven methodologies, if combined with knowledge sharing among development organizations and governments, could lead to better overall outcomes. I believe that social network analysis has been an underutilized tool in evaluating development projects, and could become particularly useful for projects with strong socio-cultural components.

Objective:

I am hoping to use pre-existing data-sets from a completed development project which contains strong social network effects on outcomes.

I have chosen a multi-part study on the dissemination of healthy cook-stoves in rural Bangladesh. This study, by Mushfiq Mobarak et al., evaluates how price and influential social actors affect villagers’ purchase decisions. Mobarak and his team primarily use econometric tools to carry out evaluations. I hope to use the study’s survey and attribute data sets to evaluate the project using social network analysis tools and determine whether new decision patterns and insights arise.

Data and Methodology:

Caveat: This study mentioned above is associated with MIT’s Abul Latif Jameel Poverty Action Lab (JPAL). My ability to carry out a SNA analysis is dependent on whether JPAL is willing to share its data-sets.

 Data-sets for some of JPAL’s projects are available for free here: http://thedata.harvard.edu/dvn/dv/jpal

The Cook Stove Study was carried out between 2006—2009 and focused on a sample of 4000 households in 42 villages. Villages were randomly selected into 8 different control groups receiving different offer prices, community leader opinions, and combinations thereof. Data was also collected at the household level: cohabitant family members, relatives, smart household member, and “close” household member.  Data was collected in two stages: In the first stage, households were asked questions relating to their willingness to purchase a stove given relevant a price point and social network constraints; in the second-stage, follow-up surveys were carried out to see whether households had behaved according to their initial statements.

Attribute data will consist of the various relationship indicators and relevant community leader identifiers. A two-mode data set will be created and used to map relationship patterns and to determine individuals with strong eigenvectors both on a village-scale and within individual households. Ego-networks of village opinion leaders will be examined to determine the strength (or lack thereof) of their recommendations. One mode data sets will also be created to compare a household’s intentions to buy with final outcomes.

Ultimately, the hope is that potentially predictive patterns of behavior/influence emerge. Are women more likely than men (or vice versa) to purchase an environmentally friendly cook-stove? Are opinion leaders, in fact, influential in affecting a household purchase decision?

Final Thoughts:

Ultimately, this study could demonstrate an alternative method to traditional econometric analysis in evaluating development projects. I look forward to any comments or critiques of my project proposal.

Sources:

Miller, Grant, and A. Mushfiq Mobarak. "Learning About New Technologies Through Opinion Leaders and Social Networks: Experimental Evidence on Non-Traditional Stoves in Rural Bangladesh." Working Paper, January 2013. http://www.povertyactionlab.org/publication/learning-about-new-technologies-through-opinion-leaders-and-social-networks-experimental