Can Central Banks ‘lean against the wind’ and prevent bubbles from bursting?

Central banks in the developed world are still trying to get out of the current crisis and there is an important debate on the medium term risks of unconventional monetary policy (see here ). The other major strand of debate is focused on our ability to prevent the next financial crisis and to avoid these issues in the future. The central area of concern is the financial sector and the ability of central banks to decipher a stable financial sector from an unstable one. Thus far, this issue is dividing economists, both in terms of our collective ability to spot a bubble and the right pre-emptive policies to have in place.

The case against our ability to spot bubbles and act in time

One of the most coherent and persuasive proponents of this side of the debate is Adam Posen, formerly an external member of the UK Monetary Policy Committee and now at the Peterson Institute of International Economics. In a 2011 research paper[1] Posen argued that the case for our ability to do this rested on three empirically testable assumptions:

  1. That we can discern bubbles in real time from the ongoing fluctuations in asset prices before it’s too late
  2. That the monetary policy instruments available affect asset prices in a dependable way
  3. It is worth it on net to pre-empt bubbles, despite the potential loss of output and volatility of doing so

In this paper, Posen mainly addresses the first of these points. His first critique of the optimistic view that policymakers can ‘lean against the wind’ relies on the notion that some booms are different. With colleagues Hellebrandt and Meads, the authors identified historical booms and busts using techniques like sustained above average growth rates and Hodrick-Prescott filters to identify periods of above trend growth. Using one method, only 16 out of 42 real estate booms were followed by a bust, while only 12 equity booms out of 50 experienced a bust in the following two years. This clearly highlights the point that not all bubbles go ‘pop’, implying that pre-emptive monetary policy is unnecessary during the majority of bubbles.

Posen’s second main critique is that predicting bubbles is ‘easier said than done’. Again with colleagues Hellebrandt and Meads, they tried to find evidence for reliable signals of asset price booms. They identified ‘signalling windows’ before asset booms and looked for variables that were above a threshold in this window but remained below the threshold at other times. The authors looked at variables like interest rates, measures of monetary policy and credit growth, among others, but found no consistent indicators of asset booms. Very few of the candidate indicators managed to predict more than 50% of the asset booms.

For Posen, this will make it very difficult for policymakers to try and get ahead of an asset price boom. Due to this pessimistic view of discretionary monetary policy, Posen has advocated the adoption of automatic stabilisers such as cyclically variable taxation on real estate transactions.  Posen concludes by stating that these findings are a concern for those who advocate discretionary monetary and macro prudential measures to fight asset bubbles.

The case for our ability to spot bubbles and act in time

Claudio Borio, Piti Disyatat and Mikael Juselius at the Bank for International Settlements (BIS) have been working on an innovative way of looking at the potential of an economy. Their core message is that financial variables need to be embedded into our view of potential to aid policymaking decisions. Just to recap the importance of an economy’s potential, the view of where an economy is currently at compared to its own potential is a major determinant of central bank decisions on monetary policy. An economy that is well below potential has the room for stimulative policies without the threat of accelerating inflation, whereas an economy already at potential does not.

However, Borio et al have challenged the view that this potential is gauged by traditional factors like a production function, or the productive capacity of the economy’s resources. To Borio, a view on the state of financial business cycle must also be considered. To illustrate this point, an economy may be seemingly stable in terms of inflation, but the financial sector may be out of kilter and therefore vulnerable to overheating.

In a contrast to the views of Posen outlined above, Borio et al incorporated two variables that they found to be good proxies for the financial cycle, that is, credit growth and house prices. They then use statistical techniques to embed these into measures of the potential GDP, resulting in a measure of potential that is not the traditional ‘inflation neutral’ measure, but instead they call it a ‘finance neutral’ measure. Their results suggest that these financial variables add to the statistical precision of the estimates of potential GDP. So, on the surface at least, it looks as if there is something here worth considering.

Addressing another one of Posen’s concerns, Borio et al state that their technique is also more robust than traditional estimates in real time. The charts below show the real time and ex-post estimates of the output gap using the different techniques. When looking at 2006 for example, it seems that the finance-neutral approach was the most accurate real time measure of where the economy was actually at. The other approaches only showed an overheating economy with ex-post revisions.

Real time comparisions

While Borio et al take a good look at what this might mean for fiscal policy, in the sense of a cyclically adjusted government budget balance, it is also highly relevant for monetary policy. While I’m intrigued by Posen’s ideas of automatic stabilisers, I’m equally intrigued by the real-time knowledge of these financial variables.

In the future, if we see that an economy is overheating on the finance-neutral measure, what is the appropriate monetary response? Is it a rise in interest rates or a move on macro-prudential measures, like loan-to-value ratios? Does it depend on the extent that the credit or housing boom is influencing all sectors, or is it confined to a specific part of the economy?

The work of both Posen and Borio is terribly valuable, but we have a long way to go before we are more confident of preventing the next major financial crisis.

[1] Monetary Policy, bubbles, and the knowledge problem. Posen, A. S. Cato Journal, Vol 31, No. 3, (Fall 2011).


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One response to “Can Central Banks ‘lean against the wind’ and prevent bubbles from bursting?

  1. Pingback: Rethinking Macropolicy II: Key insights from a major IMF Conference | globalmacromatters

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