Finance: Research, Policy and Anecdotes

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.  

A more recent example for the power of data has been the field of financial inclusion. In 2005, we had all but anecdotal evidence on the limited access to formal financial services across the globe. Initial data collection efforts on branch/ATM penetration and the number of deposit/loan accounts gave first insights and managed to raise the issue of financial inclusion, ultimately resulting in a permanent collection effort of these data by the IMF (Financial Access Survey). But it was not until the first wave of the Global Findex survey in 2011 that we got detailed data on the share of adult population with access to a formal bank account. Having better data allowing to compare financial inclusion across countries and within countries over time can provide an important reform impetus and allows to establish targets for policy reforms, such as the Universal Financial Access Goal, formulated by the World Bank Group in 2013, that “by 2020, adults, who currently aren't part of the formal financial system, have access to a transaction account to store money, send and receive payments as the basic building block to manage their financial lives.” We have seen many country-specific reform efforts and inclusion targets, based on the now-available detailed data.

However, there is also an important pitfall that I would like to stress, which links to Goodhart’s Law: when an indicator becomes a policy target, it ceases to be a good measure. Providing everyone with an account is one challenge, having people use these accounts for their benefit is another. There are many examples of dormant accounts, which sheds doubt on the usefulness of account ownership as headline indicator. On the upside, this insight has led to a shift in attention from ownership to use of an account and exploring the constraints in the use of financial services.

One critical lesson can be learned in this context from the “success” of the Doing Business data collection exercise. Providing data on critical aspect of the business environment faced by enterprises has given impetus to reforms in these areas across the globe. Ranking countries according to their business environment has fuelled a certain degree of competition, but the pitfalls of such rankings have also become clear. Governments might want to become first in their regional class, but rankings are always relative. Will a government go for low-hanging fruits but less consequential reforms simply to increase their ranking? Should laws and regulations really be changed primarily with indicator definitions and rankings in mind? Goodhart’s law might again be cited here – as doing business indicators and country rankings become policy targets, they might become less relevant for measuring actual constraints in the business environment.

Data are thus critical for moving a policy area up in policymakers’ agenda and that is what we are currently trying to do with the long-term finance scoreboard in Africa. The need for more long-term finance (for infrastructure, firms and housing) is recognised but limited information is available on how much is out there and in what form.  Having a firm quantitative basis can serve as basis not just for rigorous analysis and evidence-based policymaking, but also provide impetus for reforms. The pitfall we should avoid is to focus on one headline indicator or a country ranking, which might simply divert attention from the problems at hand.

27. Feb, 2020