In the last two years we (Mesopartner) have been exploring how complexity science affects development practice. Well, we were quite shocked to realize how much of development is based on preference and bias, and how little is actually based on proper scientific research. Frequently practitioners takes little bits and pieces of different theoretical bases to create a construct of an approach that is suitable to them because it meets their own hypotheses of how the world works. It is important also to not confuse evidence based monitoring and evaluation with scientific evidence.
The famous economic thinker, Gregory Mankiw, has published an article in the New York Times where he goes into this topic with his usual easy to understand arguments. The title of his article is “when the scientist is also a philosopher”. He argues that a danger of economics (I would argue of all economic development) is that we are not aware of our bias, and we do not depend on proper scientific methods. He recommends that we offer our advice with a healthy dose of humility, as we are often not aware of how complex the economy is and how our advice will affect other systems, or whether our advice will work at all.
Gregory Mankiw was a great inspiration for me during my PhD research and I am grateful to have stumbled across this article. He is currently an economics professor at Harvard.
Dear Shawn, I agree with you to be aware about our biases. Mankiw mentions the first principle to consider in this respect: “Do no harm.” Nonetheless I would also argue that there is always a pressure, especially in politics, to act. I am referring back to another article from you and to our last work together in Namibia (your article on moving from generic to specific and then to systemic http://shawncunningham.wordpress.com/2014/02/01/moving-from-generic-to-specific-and-then-onto-systemic/ I think we cannot stop or run away from not acting because of the “do no harm” argument. Rather we need to better be able to work and act in the complex environment. Often long analysis will not help us to find better answers. Often not acting also will not provide us with deeper insight. Trial and error will be part of it. But how is it possible in such long-term decisions (like minimum wage increases) to practice save to fail experiments? How is it possible to try something out in the system when the consequences are difficult to foresee and where a save to fail experiment will not provide us with many insights overall because the outcome might only provide a learning in the pilot project itself? Just some questions which came up while reading Mankiws and your blog post.
Best, Frank