Marrying the Macro- and Micro-Prudential Dimensions of Financial Stability

Bank for International Settlements
2001 Social Science Research Network  
Bill White and, in particular, Kostas Tsatsaronis for their helpful comments. We are also grateful to the central banks that provided us with data and comments. Thanks are also due to Philippe Hainaut and Marc Klau for valuable research assistance. The views expressed are those of the authors and do not necessarily reflect those of the BIS. 2 It has a long history, reaching back at least to Fisher (1933), and has recently been subject to extensive theoretical modelling by, amongst others, and .
more » ... For a recent survey, see . 3 In recent times, although from a somewhat different perspective, the role of financial excesses has been stressed by, amongst others, Kindleberger (1996) and and . 10 What is the difference between systematic risk for the system as a whole and systemic risk? One possible way of thinking This approximate "observational equivalence" of different paradigms can provide fertile ground for the formation of persistent misperceptions of risk. It can do so by failing to anchor expectations sufficiently tightly to the actual economic environment. The measurement of systematic, as opposed to idiosyncratic risk, is more likely to involve such misperceptions, not least owing to the dearth of observations available regarding business cycles in comparison with the relative default experience of borrowers and the conceptual difficulties involved, as discussed above. 20 Beliefs can therefore be more vulnerable to the attraction of short-cuts, such as the use of short-term horizons and extrapolative expectations, or to cognitive biases. Two types of well-documented cognitive biases consistent with the misperceptions of risk stressed in this paper are "disaster myopia" and "cognitive dissonance". Disaster myopia refers to the tendency to underestimate the likelihood of high-loss low-probability events. 21 This, in turn, derives from certain cognitive biases, confirmed by psychological controlled experiments, which indicate that individuals tend to put excessive weight on recent events and too little weight on those whose likelihood is regarded as "too" small. 22 Cognitive dissonance refers to the tendency to interpret information in a biased way, so that it reinforces the prevailing belief entertained by the economic agent. 23 22 These are known, respectively, as "availability heuristic" and "threshold heuristic". On the former, see Tversky and Kahneman (1982) ; on the latter, see Simon (1978) and Slovic et al (1977) . Kunreuther et al (1978) contains experimental evidence in favour of these hypotheses. See also . 23 The theory was developed by Festinger (1957) . 24 This is known as the "prisoner's dilemma" or more correctly, in the case of many agents, the "tragedy of the commons". 25 This is almost certainly the case if others do not tighten. It also makes sense if others do tighten, since the action of any individual bank, taken in isolation, would not be such as to lead to a sufficient deterioration in the economic environment to make the bank worse off. The exception might be highly concentrated banking systems. 42 Typically, bond spreads are negatively correlated with the business cycle, with spreads between corporate and government securities tending to narrow in booms and widen in recessions or in periods of financial turmoil. As an illustration, Figure 3 shows the evolution of credit spreads in the United States and Korea. In the United States, spreads generally narrowed in the run-up up to the recession that began in late 1990 and then widened during the recession. 43 Spreads also increased during late 1998, in the aftermath of the Russian debt default and the problems experienced by the hedge fund Long-Term Capital Management. 44 The data for Korea focus on this latter period and show that spreads did not widen before the crisis, but increased by nearly 600 basis points at the same time that the currency was depreciating dramatically. The picture is not fundamentally different if the ratings from credit rating agencies are examined. For instance, Figure 4 shows the recent movement of sovereign credit ratings for Korea and Thailand assigned by the three largest credit rating agencies, Standard & Poor's, Moody's and Fitch IBCA. In both countries, ratings were stable during the period of rapid growth, and were only adjusted after the currencies depreciated dramatically; in Korea's case, repeated downgrades saw the country's rating fall from a AA credit to a junk rating in a matter of months. Then, as currencies strengthened, credit ratings were upgraded. More generally, the evidence suggests that credit rating agencies fail to predict changes in the probability of crises, with downgrades occurring during a crisis, rather than before. 45 Bank provisions are even more strongly procyclical, being highly negatively correlated with the business cycle (Table 1 ). Figure 5 shows that provisions typically do not increase until after economic growth has slowed considerably and often not until the economy is clearly in recession. This pattern is clearest in Australia, Sweden, Norway and Spain. In each of these cases, provisions failed to increase substantially in the late 1980s, when credit and asset prices were growing rapidly and the financial imbalances were developing. In each case, the peak in provisions did not occur until at least one year after the economy had clearly slowed. In Japan, the picture is broadly similar, with the level of provisions increasing substantially only in the second half of the 1990s, long after the problems in the Japanese banking system had been widely recognised. 46 41 For instance, a review of the 1997 Asian crisis stressing these elements can be found in BIS (1997). The role of lending booms, possibly fuelled by financial liberalisation and increasing competition, is stressed, among others, by Gavin and Hausmann (1996), Honohan (1997), Reinhart (1999), Gourinchas et al (1999) and Eichengreen and Arterta (2000). The dearth of data on property prices makes it hard to test formally for their significance, although their role has been widely recognised; see BIS (1997). 42 In addition, recently Lown et al (2000) have provided evidence for the United States on the procyclicality of non-price terms on lending. 43 Gertler and Lown (2000) find that, in addition to moving contemporaneously with economic activity, the spread between low-47 Analysis is also complicated by the fact that government support schemes have influenced capital ratios. Nevertheless, long-run historical time series do not suggest a strong business cycle effect, with the main stylised fact being a steady decline in capital ratios over the 20th century, before a slight increase over the past decade or so. At the same time, there are two important qualifications to the conclusion that capital ratios tend to be acyclical. The first is that, to the extent that provisions underestimate expected losses in expansions, measured capital ratios overstate true capital ratios in expansions. This effect can be significant. For example, if the ratio of provisions to total assets is 1 percentage point below where it should be, then the measured capital ratio is likely to overstate the true capital ratio by at least 10%. If adjustments were made to capital for underprovisioning in economic booms, it is likely that, all else constant, measured capital ratios would fall during expansions and increase during downswings. The second qualification is that there has been a pronounced cycle in aggregate capital ratios over the 1990s in those countries that experienced problems early in the decade. In the years immediately after the crisis, when conditions were still relatively depressed, banks made a concerted effort, not only to rebuild their capital ratios, but also to substantially increase them above previous levels. Then, starting in the middle of the decade, when economic expansions were firmly entrenched, some of the increase in capital ratios was unwound. This pattern is evident in Australia, Sweden and Norway, and to a lesser extent in Finland.
doi:10.2139/ssrn.1165494 fatcat:x5er25so6bakzmjzwuff5kqv7a