“If there is one common theme to the vast range of crises we consider in this book, it is that excessive debt accumulation, whether it be by government, banks, corporations or consumers, often poses greater systemic risks than it seems [to do] during a boom.”- Carmen Reinhart and Kenneth Rogoff, 2009
Annex I. List of Selected Financial Institutions
Annex II. List of Intervened Financial Institutions
Annex III. Definition of Indicators
Annex IV. Indicators in the Panel Specification
Annex V. Methodology for Panel Cointegration
Annex VI. Methodology for Long-Run Causal Effect
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Thanks are due to Laura Kodres and Brenda Gonzalez-Hermosillo for their advice and to Peter Pedroni, who helped to improve the econometric work. I am also grateful to the participants of “Regulatory Responses to the Financial Crisis” in July 2010 for their constructive comments, and to Yoon Sook Kim and Ryan Scuzzarella, who provided data support. All remaining errors are my own.
The 45 FIs have been selected on the basis of their systemic importance in terms of size, business scope, and possible regional/global impact, though proving this is beyond the reach of this paper. Intervened institutions are assumed to be those that have gone bankrupt, have received government capital injections or loans, have had assets purchased by government, have received official loans to facilitate a merger or acquisition. Central bank temporary liquidity injections are not considered to be a type of intervention. Intervened institutions and periods of intervention are detailed in Annex I.
CAMELS refers to capital adequacy, asset quality, management quality, earnings, liquidity, and sensitivity to market risk.
The negative coefficients could be explained by interactions between companies or by a change in the behavior of banks. In times of recession, banks may be less willing to lend and quicker to close companies down.
The insurance companies were excluded from the analysis given their different business lines. The rationale for choosing these FIs is based on their systemic importance while keeping a balanced sample that is representative of the various regions around the world. Data constraints also played a role, as the sample chosen was limited to FIs for which balance sheet and market-based data were available.
The reasons that capital adequacy ratios are not always useful indicators of distress may reflect (i) difficulties in determining the actual riskiness of assets; (ii) deficiencies in mark-to-market accounting practices; and (iii) locating assets and contingent claims (e.g., derivatives) in off-balance sheet vehicles where they can receive lower risk-weights.
The higher risks associated with the higher retained earnings to equity ratio indicate that it is unlikely that the use of retained earnings to build up capital, as being encouraged by European regulators, will prevent subsequent interventions (The Wall Street Journal, Sep 28, 2009).
Here we check indicators on leverage rather than the formal leverage ratio—total assets to capital ratio and debt to capital ratio. The reason is that (i) capital includes too many items and does not distinguish among type of capital, although the capital in general acquires the regulatory minima; (ii) the formal leverage ratio may prove overly-optimistic since the use of leverage migrates to entities’ balance sheets, requiring less capital but with higher risk; and (iii) the retained earning phenomenon is a signal that too much money is being made by the firms due to excessive risk-taking.
Short-term debt and current portfolio long-term debt refer to that portion of debt payable within one year.
The ratio of ROE has to be interpreted with caution, since a high ratio may indicate both high profitability as well as low capitalization, and a low ratio can mean low profitability as well as high capitalization (IMF, 2000). This caveat further encourages the use of ROA as a better measure of earnings.
The difference between the two EDFs is that there is a higher relative variance of the one-year EDF compared to the five-year EDF.
Theoretically speaking, the link between inflation and EDF is mainly twofold, through factor prices and the prices that companies charge for their goods and services. On the one hand, higher factor prices lead to increased production costs of borrowers and tend to impair credit quality, thus leading to higher EDF. On the other hand, higher product prices can boost earnings and thereby improve creditworthiness, thus resulting in lower EDF. In this case, the empirical evidence shows that the effect of higher product prices outweighs that of higher factor prices, at least in the short run.
Here again, the formal leverage ratio—total assets to capital ratio—is insignificant, further indicating it is less useful than some other leverage ratios.
The negative association between ROA and EDF in the panel regressions is not in conflict with the fact that the ICBs have a higher ROA. This is because the ROA for the intervened institutions have declined quickly since late 2007, as indicated by Figure 7. This reflects the rising EDFs and is consistent with the panel analysis. The higher ROA value across 1998–2008 in Table 1 and Figure 7 overwhelm the decline in ROAs since the outbreak of the subprime crisis. In addition, this negative association shows the advantage of panel regressions, which incorporate the combined effects of various indicators during the long time span, and provide a more robust measure of their impact on EDFs.
The general insignificance of GDP growth, though significant for intervened FIs, is not in line with the research of Bunn and Redwood (2003) using UK companies. This could be due to the fact that we use more countries in the sample, and the variation in GDP growth across countries could be large enough to produce an insignificant coefficient.
As a robustness check, we also put those useful indicators identified in Section III into the panel regressions. The results show that book value per share (stock performance) is significant, while deposits-to-assets ratio (liquidity), and mortgage loans-to-total loans ratio (business scope) are generally insignificant.
However, FSIs are still helpful in assessing individual and systemic vulnerabilities when reliable market data may not be available—particularly in less-developed financial markets—as they can provide both an indication of rising vulnerabilities and as a check when other information reveals weaknesses. For countries with more sophisticated sources of information, FSIs could be usefully reevaluated, perhaps refocusing them on leverage ratios and ROA as a proxy for risk-taking. Of course, FSIs should be complemented by other measures and systemic stress tests, and be broadened to better capture off-balance-sheet exposures and liquidity mismatches.
In theory, debt is a disciplining device because default allows creditors the option to force the firm into liquidation and thus exert pressure on the management to avoid borrowing too much. However, the tremendous gain from leverage could impose strong incentives for the management’s borrowing to achieve excessive returns. The moral hazard associated with Too-Big-To-Fail would strengthen the incentives.
Given the fact that the deleveraging process could trigger downward spirals in asset prices, regulators must consider leverage constraints when designing policies for capital regulation, and in fact, Basel III has done so.
Higher capital ratios, on their own, do not necessarily stop banks from financing frothy asset purchases, and becoming vulnerable when a crisis occurs.
The coefficient, λ2, on the lagged equilibrium cointegrating relationship in the dynamic error correction equation for ΔLEVERAGEt and ΔEDFt is zero if, and only if, innovations to log leverage have no long-run effect on the log of EDF. The null hypothesis is that there is no long-run effect of leverage on the EDFs in any institution of the panel.