When economists take research questions to the data, some type of prior views on the results is both inevitable and necessary. In fact, the data do not uniquely speak with one voice about what drives the data. It is then useful to approach the data with some views, called in Bayesian technical jargon, “prior beliefs”. The researcher combines such views with the data in order to form “posterior beliefs”. These can then be used as a basis to answer the economic question of interest. A preliminary condition for this to happen, though, is that there exist economic tools of analysis that can flexibly combine data with beliefs, and can do so in a technically non-demanding way.
Before the work of the Fellowship, the tools available for economic analysis were relative restricted. On the one hand, one needs tools that allow for the technical analysis not to be computationally demanding. In fact, if the methodology used to combine data and beliefs requires a very long time to run on the computer or if it requires knowledge beyond what taught in graduate programmes, then the ability to address economic questions is considerably impaired. On the other hand, though, the researcher requires the flexibility to form his or her own beliefs about the phenomenon studied in the analysis. Before the work of this Fellowship, the literature frequently constrained the flexibility allowed for in the formation of prior beliefs for the benefit of making the analysis computationally more tractable. In other words, only special cases of prior beliefs could be handled, since any other one would make the analysis too technical and too costly to run. Unfortunately, this was the case irrespectively of whether the special prior beliefs allowed for were too restrictive and at odds with the views of the researcher.
The key objective of the Fellowship is to offer one step forward to overcome the above challenge. The analysis now offers a new methodological framework in which the researcher can now entertain a wider class of prior beliefs. Importantly, doing so now does not come at a computational cost. This enriches the tools of analysis available to the research community at large. The analysis was carried out in the interest of academic and policy making researchers, who apply economic tools to a variety of economic questions. Research questions that can be addressed with the new methodology cover different types of Applied Economics, ranging from the study of monetary policy to the effects of fiscal stimulus, and to other sources of shocks that hit the economy.
