Appendix I. Economic Hypotheses about Post-Financial-Crisis Recoveries
Economic theory suggests that post-financial-crisis recoveries can often be weak, long, and creditless. Credit-fueled booms that often precede financial crises are usually large, persistent, and driven by exuberant expectations. The bigger the boom, the larger the correction when the bubble busts, hence the longer the recovery. Moreover, the smaller the precautionary equity cushions of the groups most affected, the larger the shifts in asset prices, their balance sheets, and the perceived real natural interest rate. These shifts are needed to reconcile post-crisis savings and investment decisions. Both the corrective powers of the economy as well as the quality and timeliness of policy actions to facilitate the adjustment can influence the length of the recovery. The initial recovery is more likely to be creditless, if the debt is high, the correction large, and cushions small, hence adversely affecting both the willingness and ability to borrow and lend. This box lists economic theories supporting these assertions.
Exuberant expectations followed by shattered confidence are at the core of most boom-bust theories. Expectations are the best proxy to deal with incomplete and imperfect information in the real world. Learning through trial and error, however, causes a fog of risk and uncertainty (Knight, 1921), but also exuberance that can generate self-fulfilling erroneous expectations. Such expectations can fuel bubbles and cause Manias, Panics, and Crashes (Kindleberger, 1978). This phenomenon has also been described by Minsky’s Financial Instability Hypothesis (Randall, 2016), while Guttentag and Herring’s (1984) Disaster Myopia demonstrates that large cycles can be caused by rare but important triggers. Myopic behavior is often seen as irrational after the fact (e.g., Yao and Zhang, 2011), but may actually be rational under certain constraints, including non-linear time preferences, e.g., Strotz (1955), Laibson (1997), and Bordalo, Gennaiola, and Shleifer (2016).
Most of these theories identify three distinct phases: boom, bust, and recovery (Figure). During the boom, heterogeneous rational agents see that their more aggressive competitors prevail, supported by overshooting of asset prices due to inelastic supply, new technology, new regulations, etc. More and more investors join the rally, convinced that This Time is Different (Reinhart and Rogoff, 2009). The bubble bursts when a trigger event exposes the unrealistic prospects, typically based on expectations of future price increases rather than on the net present value of realistic returns from the functions that the asset performs. During the recovery, expectations are recalibrated and balance sheets are adjusted, which sometimes cause asset price deflation and excessive pessimism. Credit policies may be introduced to support the recovery (IMF, 2013). Ultimately, a “new normal” emerges. Agents that rely on own resources may increase their consumption and investments, when they think that prices have bottomed. For the indebted, the deleveraging gradually comes to an end, allowing for renewed optimism that strengthens the recovery. Lending then resurfaces. As the perceived risks fade, crisis-prevention safeguards, put in place in reaction to the collapse, may be deemed an obstacle for the recovery. If reduced, or even eliminated without otherwise addressing the potential risks, the starting conditions for the next cycle are created.
Severe boom-bust cycles are typically amplified by excessive debt provided by an unhinged financial sector. Irving Fisher (1933, page 341) noted that “…over-confidence seldom does any great harm except when, as, and if, it beguiles its victims into debt.”1 While financial intermediaries can facilitate growth, they can also amplify a bubble, being convinced that they can diversify and cover their risk by collateral. As the asset prices and collateral values increase, they lend even more, creating a financial accelerator (Kiyotaki and Moore, 1997; Bernanke, Gertler and Gilchrist, 1999). Furthermore, financial innovation may temporarily result in neglected risks (Gennaioli et al., 2012). Distorted short-term incentives of bank managers and shareholders can further boost unsustainable lending. Large banks feel that they are “too big to fail” and take excessive individual and systemic risks (Laeven et al. 2014). During the recovery phase, credit institutions may, as a whole, instead become: (i) less willing to lend, due to excessive pessimism, as the more aggressive ones have suffered large losses; or, (ii) less able to lend, since the losses have absorbed their regulatory capital, made funding prohibitively expensive for weaker banks, and made them focus on recovering non-performing loans. Finally, until there is clarity about new “financial-crisis-prevention regulation,” many banks may put lending to new projects and clients on hold.
The size of equity cushions and the efficiency of debt-recovery processes may affect the length of the recovery and whether it will be creditless initially. Adequate cushions can reduce the risks for fire sales as well as the motivation to rebuild precautionary savings following a collapse. Households may target a precautionary savings buffer stock (Carroll et al., 1992), which depends on liquidity constraints (Deaton, 1991). For instance, the targeted savings—combined with a large decline in real estate prices, the most important asset for most households (Mian and Sufi, 2014)—will usually have been diluted during a collapse. This can, in addition to poorer employment prospects, cause a further contraction in demand by the less wealthy households.2 Companies give priority to survival; thus, they reduce debt and rebuild equity, even when the expected net present value of new investments is positive. If a critical mass perceive that they have insufficient buffers, growth and lending may be further suppressed and cause a more severe balance sheet recession (Koo, 2003, 2011). Country-specific factors affect the magnitude and distribution of buffers.3 The larger the cushions for those affected and the easier to rebuild them, the faster the recovery and renewed demand for credit.
Many have tried to model severe debt-fueled boom and busts á la Fisher (debt-deflation), Minsky (financial sector instability), and Koo (balance sheet recession). Eggertsson and Krugman (2012) offer an interesting reconciliation of these approaches capturing private sector debt-overhang. Their New Keynesian-style model allows for some agents to become over-indebted. After a shock requiring deleveraging hits, aggregate demand tanks. Monetary policy can alleviate modest shocks, but in case of severe recessions, the zero-lower bound is quickly reached. Even with central banks promising future inflation, the resulting negative real interest rates may still not be able to clear the markets. Instead, an expansionary fiscal stance may be needed to temporarily alleviate sluggish demand, while the balance sheet re-adjustment takes place. The fiscal impact is usually bigger during a recession and will not be fully crowded out. The impact, however, will depend on: (i) how well the over-indebted agents are being relieved; and (ii) how the measure is financed, i.e. how those taxed today or in the future adjust their demand today. The model also derives that productivity-enhancing structural policies can worsen debt dynamics by further subduing aggregate demand in case of a liquidity trap. This may, however, stem from the fact that the model does not fully capture that structural policies making the economy more efficient can potentially boost the perceived real-risk-adjusted return—i.e., increase the marginal propensity to invest and consume—and thus advance the recovery.