I am just returning from a technical workshop in Nairobi, where central banks staff from across Africa assembled to discuss the second data collection round for the long-term finance scoreboard
that we launched last year. While many of the discussions were technical, there were also more fundamental conversations on the role of data in the policymaking and, ultimately, development process. In my presentation, I pointed to the important opportunities
that better data can afford research and ultimately policy making, but also certain pitfalls. The empirical finance and growth literature (as started by Ross Levine and Bob King 30 years ago) relied initially on broad cross-country data from the International
Financial Statistics, but quickly moved to industry and firm-level data to explore not only the question of causality, but also the channels and mechanisms through which finance affects growth. But it is important to note that measures of financial development
(such as Private Credit to GDP) are not policy variables.