In this series of posts, I have made the case for borrower-based macroprudential policies, discussed their distributional effects, and compared them with monetary policy. One overarching theme has been that the costs of these tools are immediate and distributional, while the benefits, although most likely distributional as well, are much more difficult to quantify.

Quantifying these benefits requires serious empirical work, detailed household- or loan-level data, and, often, a negative shock such as a recession. The key issue is that these data are typically held by central banks. The arrangements differ across institutions, but access by outsiders is usually highly restricted. The same institution that designs and implements these policies is therefore, in many cases, also the one best placed to evaluate them.

It is not difficult to see why that can be a problem. There is evidence that research done within central banks tends to report stronger effects of quantitative easing (compared to non-central-bank researchers). There have been some papers disputing this claim, and the authors have responded. There have also been more direct allegations of institutional interference elsewhere: The World Bank allegedly tried to suppress a paper documenting elite capture of foreign aid.

And these are only the instances we know about. We cannot know how often preliminary findings have been discouraged, delayed, or abandoned because they went against an institution’s official position. Nor does an institution need to stop an existing piece of research. Sometimes central banks announce their research priorities and, once a policy is in place, its evaluation simply never appears among them. There can be a lot of “soft management” to steer research away from certain topics.

So we have, on the one hand, an institution with considerable power that uses policies whose costs are unequal and whose benefits are difficult to quantify. On the other hand, the data necessary for this evaluation are controlled by the same institution and remain largely inaccessible to outside academics. The conclusion is, unfortunately, clear: we should not have to rely exclusively on in-house analysis. Not because the analysis is necessarily wrong, but because institutional incentives may affect which questions are asked and how the evidence is interpreted, while outsiders often have no way to replicate, challenge, or extend it.

So what should central banks do? For one, they should open up their data. Obviously, they cannot make all of it public. But they should provide secure ways for external researchers to use the data and analyse these policies. This should not require co-authors from the central bank, nor should the central bank exercise substantive oversight over the research question, the methods, or the conclusions. Its oversight should be limited to protecting confidentiality, ensuring data security, and preventing identifiable information from being made public. Some central banks already provide this type of setup, for instance the Deutsche Bundesbank, but these arrangements remain uneven and often apply to a small proportion of the data that they collect. The empirical work of assessing the policies—and not just borrower-based macroprudential tools—could largely be carried out by researchers themselves, without central banks having to commission (and pay for) it.

This would have other desirable consequences. To date, if one wanted to conduct research using loan-level data, one often needed a contact within the central bank (the publicly available US mortgage data collected under the Home Mortgage Disclosure Act being a notable exception). I have several papers using confidential central-bank data, and this has always been my experience. This is understandable, given the confidentiality of the data, but it also means that researchers without those contacts are at a disadvantage when trying to do research in banking and financial markets. Providing access to external researchers in the way suggested above would help level the playing field.

But the key reason would be to promote transparency: using the academic community to learn more about how these policies work and to provide independent evidence on their costs and benefits. Central banks may be best placed to collect the relevant data, but they should not be the only institutions able to analyse them.

This is, of course, far from the only problem central banks are facing at the moment. Political pressures to curtail their independence and the questions about their legitimacy are genuine issues that need to be tackled. But somehow I do not think that becoming more closed will help. Nor do I think that the way forward is for central banks to assess the impact of their actions less carefully, or to make it harder for others to do so. If central banks want to preserve the powers and independence they have been granted, they need to make a stronger case for them. Making the relevant data available, and allowing outsiders to examine whether their policies are working, is part of that case.