Duncan Watts - Social Science, Small worlds and Big Data

In combining theory and experiments, we should have two objectives in mind. The first objective is to confront the theory with some data to see whether the theory is at all consistent with the behavior exhibited in the laboratory. Clearly, there is much that can be learned about the theory from the data, quite apart from any notion of "testing" the theory. We hope to learn whether the theory is useful in interpreting the data, of course, but we also expect to find out what extensions of the theory are required to make it compatible with the data. The second objective is to confront the data with the theory. A theoretical framework is needed for two reasons. First, the data set generated by experiments can be extremely rich and the behavior predicted by the theory is sometimes complex and subtle. Any attempt to explain rich datasets in purely "behavioral" terms would require a large number ad hoc assumptions, which would render the "explanation" rather uninformative. The second reason is that, without a theoretical framework, it is quite impossible to draw general conclusions that go beyond the particular setting of the experiment. Conversations in Economics is a series of interviews with Cambridge-INET Institute visitors. These distinguished economists explore some of today's most challenging economic questions and introduce viewers to their exciting research. http://www.inet.econ.cam.ac.uk/video-series/