Managing credit bubbles

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Credit markets play an increasingly central role in modern economies. Within the OECD, for instance, domestic credit has risen from 100% of GDP in 1970 to approximately 160% of GDP in 2012 (as measured by the Bank for International Settlements). To be sure, this growth masks large variations across countries and over time, but there is a common feature to all these different country experiences that stands out. Credit has often alternated between ‘booms’ – periods of rapid growth – and ‘busts’ – periods of stagnation or significant decline. Moreover, there is some evidence that these credit booms and busts have become more common in recent years (Mendoza and Terrones 2012, Dell’Ariccia et al. 2012).

These credit booms and busts tend to be accompanied by changes in key economic variables. In particular, it is well documented that credit booms are associated with high asset prices and high growth rates of real GDP, consumption, and investment (Mendoza and Terrones 2012, Dell’Ariccia et al. 2012). In spite of this, credit booms are still viewed with concern by policymakers and academics. The reason is that they eventually end, and their aftermaths are often characterised by financial crises and low economic growth (Schularick and Taylor 2012). This has prompted calls for policies that restrain credit during booms, in the hope that smaller booms will lead to smaller crises.

To evaluate the merit of these calls for policy, one must have a view of the forces driving these credit cycles. Credit may fluctuate for variety of reasons, of course, and different types of fluctuations may call for different policy responses. At a very general level, fluctuations in credit may reflect changes in demand or in supply. And these, in turn, may reflect changes in a variety of factors like preferences, technology, or expectations. Recently, though, macroeconomics has focused on credit fluctuations that are driven by fluctuations in borrowing constraints. This is at the heart of ‘financial accelerator’ models that build on Bernanke and Gertler (1989) and Kiyotaki and Moore (1997), and that have become prevalent in the aftermath of the financial crisis.

The basic narrative in these models is simple – when a borrower obtains credit, she is exchanging goods today for a promise to deliver goods in the future. These promises are only valued by lenders if they have some prospect of being repaid. This depends on the future income of borrowers that can credibly be pledged to lenders, and we can refer to this as the economy’s stock of collateral. If borrowers are constrained, it is this stock of collateral that determines the amount of promises that can be issued. If borrowers are constrained, understanding credit booms and busts requires a theory of collateral fluctuations. In recent work (Martin and Ventura 2014), we construct a macroeconomic model with financial frictions and provide such a theory.

Fundamental vs bubbly collateral

The key innovation of our work is to distinguish between fundamental and bubbly collateral. Fundamental collateral is the part of a borrower’s pledgeable income that corresponds to future output, i.e. it consists of a borrower’s rights to future production. Bubbly collateral is instead the part of a borrower’s pledgeable income that corresponds to bubbles or pyramid schemes, i.e. it consists of a borrower’s rights to future contributions to such schemes. The macroeconomic literature has exclusively focused on fundamental collateral, studying its implications for credit, investment, and growth. This view of collateral is incomplete, though. Whenever fundamental collateral is insufficient (say, because of weak enforcement institutions), we show that there is room for investor optimism to sustain bubbles that expand the economy’s stock of collateral and total credit.

What are the macroeconomic effects of bubbly collateral? By definition, it enables borrowers to obtain credit in excess of their fundamental collateral. Intuitively, current borrowers can obtain ‘excess’ credit today because it is expected that there will be ‘excess’ credit in the future as well, i.e. it is expected to be rolled over. This is the crowding-in effect of bubbles, which ceteris paribus increases investment. But this future ‘excess’ credit will divert some of the resources of future generations away from investment, i.e. resources will be diverted to roll over this credit. This is the crowding-out effect of bubbles, which ceteris paribus reduces investment. The macroeconomic consequences of bubbles depend on the relative strength of these two effects. In particular, we find that the crowding-in effect dominates when bubbly collateral is low, and the crowding-out effect dominates when bubbly collateral is high. This gives rise to an ‘optimal’ bubble that trades off these two effects and provides the amount of bubbly collateral that maximises long-run output and consumption.

A role for policy

An essential feature of bubbly collateral is that its stock is driven by investor sentiment or market expectations. The credit obtained by borrowers today depends on market expectations about the credit that borrowers will obtain tomorrow, which in turn depend on tomorrow’s market expectations about the credit that borrowers will obtain on the day after, and so on. Because of this, markets may sometimes provide too much bubbly collateral and sometimes too little of it, which creates a natural role for stabilisation policies.

We show that a lender of last resort with the authority to tax and subsidise credit can in fact replicate the optimal bubble allocation. To do so, it must adopt a policy of ‘leaning against the wind’ – taxing credit when bubbly collateral is excessive and subsidising it when bubbly collateral is scarce. We show that such a policy raises steady-state levels of output and consumption. It may have ambiguous effects on macroeconomic volatility, though. The reason is that, by managing the economy’s stock of collateral, the policy reduces the responsiveness of credit to ‘investor sentiment’ shocks, but it may enhance the response of credit to standard productivity shocks.

One interesting aspect of the proposed policy is that it requires an actual transfer of resources to or from borrowers. In this regard, it is more of a fiscal than a monetary policy, which is commonly associated with the control of bubbles. However, we show that the policy can also be interpreted as an asset purchase scheme – not unlike the ones adopted by various governments since the onset of the recent financial crisis. When the bubble bursts or deflates in our economy, the stock of bubbly collateral falls and so does the market value of promises that are backed by it. The proposed policy requires the lender of last resort to intervene in such circumstances and purchase these promises at a loss, paying a price that exceeds their market value. By doing so, it raises the economy’s collateral ex post and thus total borrowing ex ante. Moreover, we argue that the same conditions that give rise to bubbly collateral in the first place (i.e. low interest rates) also guarantee that this policy can be financed by issuing debt.

These results provide a coherent and rich view of credit booms and busts, in which both fundamental and bubbly collateral play a key role. They also provide a useful blueprint to guide policy in dealing with credit bubbles. But the theory has limitations. An important one is that the gap between the optimal bubble and the existing one is perfectly observed – the role of policy is simply to bridge this gap. Reality is more complicated because market participants and policymakers may be uncertain as to whether fluctuations are driven by fundamental or bubbly collateral. Introducing this type of uncertainty is an important next step in this research agenda, and there is still much work to be done.


Bernanke, B and M Gertler (1989), “Agency Costs, Net Worth and Business Fluctuations”, The American Economic Review, 79: 14–31.

Dell’Ariccia, G, D Igan, L Laeven, and H Tong, with B Bakker and J Vandenbussche (2012), “Policies for Macrofinancial Stability: How to Deal with Credit Booms”, IMF Staff Discussion Note 12/06.

Kiyotaki, N and J Moore (1997), “Credit Cycles”, Journal of Political Economy, 105: 211–248.

Mendoza, E and M Terrones (2012), “An Anatomy of Credit Booms and their Demise”, NBER Working Paper 18379.

Martin, A and J Ventura (2014), “Managing Credit Bubbles”, CREI working paper.

Schularick, M and A Taylor (2012), “Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870–2008”, The American Economic Review, 102: 1029–1061.