Knowledge that Transforms

This paper measures the systemic risk of a banking sector as a hypothetical distress insurance premium, identifies various sources of financial instability, and allocates systemic risk to individual financial institutions. The systemic risk measure, defined as the insurance cost to protect against distressed losses in a banking system, is a summary indicator of market perceived risk that reflects expected default risk of individual banks, risk premia as well as correlated defaults. An application of our methodology to a portfolio of twenty-two major banks in Asia and the Pacific illustrates the dynamics of the spillover effects of the global financial crisis to the region. The increase in the perceived systemic risk, particularly after the failure of Lehman Brothers, was mainly driven by the heightened risk aversion and the squeezed liquidity. Further analysis, which is based on our proposed approach to quantifying the marginal contribution of individual banks to the systemic risk, suggests that “too-big-to-fail” is a valid concern from a macro-prudential perspective of bank regulation.

An endogenous switching regression model is employed for this study, categorizing the banks into regimes of high and low degrees of diversification, with our results indicating that net interest margins can be less sensitive to fluctuations in bank risk factors for functionally diversified banks as compared to more specialized banks. In turn, this implies that by diversifying their income sources, these banks can reduce the shocks to net interest margins arising from idiosyncratic risk. Our results show that prior findings can hold when the banks are located in a regime with a low degree of diversification.

In the wake of the subprime crisis of 2007 which uncovered shortfalls in capital levels of most financial institutions, the Basel Committee planned to strengthen current regulations contained in Basel II. While maintaining the Internal Model Approach based on Value-at-Risk, a stressed VaR calculated over highly strung periods is to be added to present directives to constitute Minimum Capital Requirements. Consequently, the adoption of the appropriate VaR specification remains a subject of paramount importance as it determines the financial condition of the firm. In this article I explore the performance of several models to compute MCR in the context of Emerging and Frontier stock markets within the present and proposed capital structures. Considering the evidence gathered, two major contributions arise: (a) heavy-tailed distributions – particularly Extreme Value (EV) ones-, reveal as the most accurate technique to model market risks, hence preventing huge capital deficits under current measures; (b) the application of such methods could allow slight modifications to present mandate and simultaneously avoid sVaR or at least reduce its scope, thus mitigating the impact regarding the enhancement of capital base. Therefore, I suggest that the inclusion of EV in planned supervisory accords should reduce development costs and foster healthier financial structures.

We analyze whether banking supervision responsibilities should be concentrated in the hands of a single supervisor. We find that splitting supervisory powers among different supervisors is a superior arrangement in terms of social welfare to concentrating them in a single supervisor when the capture of supervisors by bankers is a concern. This result has implications for the design of banking supervisory architecture and informs current reform efforts in this field.

In many countries, Mutual Loan-Guarantee Societies (MGSs) are assuming ever-increasing importance for small business lending. In this paper we provide a theory to rationalize the raison d’être of MGSs. The basic intuition is that the motivation for MGSs lies in the inefficiencies created by adverse selection, when borrowers do not have enough wealth to satisfy collateral requirements and induce self-selecting contracts. In this setting, we view MGSs as a wealth-pooling mechanism that allows otherwise inefficiently rationed borrowers to obtain credit.

I describe household behavior in boom and bust economic cycles with a particular focus on the recent financial crisis. The behaviors are motivated by cognitive limitations and psychological bias. In boom times, households’ extrapolation bias and groupthink lead to chasing and extending asset bubbles (like tech stocks and real estate). Increasing use of debt spurs the economy and eventually overburdens households. In bust times, the biases and fear lead to selling previously popular assets at low prices. Households generally respond to bust times by spending less, repaying debt and saving more, which drags on an already slow economy. In addition, households influence businesses and governments into actions during the cycle. In the recent boom, predatory lenders preyed on cognitive limitations and biases of subprime borrowers to sell them high cost mortgages that they would not be able to repay. Another contributing factor is that during boom times, household attention is not focused on financial regulation. This is when business influences the political process and laws are enacted to loosen market regulation. These changes may extend the boom period into bubble territory. During bust times, public outcry influences politicians to tighten business regulation, likely inhibiting the economic rebound. Thus, household behavior plays an important role in economic boom/bust cycles.

This paper investigates macro stress testing of system-wide credit risk with special focus on the tails of the credit risk distributions conditional on adverse macroeconomic scenarios. These tails determine the ex-post solvency probabilities derived from the scenarios. This paper estimates the macro-credit risk link by the traditional Wilson, 1997a, Wilson, 1997b model as well as by an alternative proposed quantile regression (QR) method (Koenker and Xiao, 2002), in which the relative importance of the macro variables can vary along the credit risk distribution, conceptually incorporating uncertainty in default correlations. Stress-testing exercises on the Brazilian household sector at the one-quarter horizon indicate that unemployment rate distress produces the most harmful effect, whereas distressed inflation and distressed interest rate show higher impacts at longer periods. Determining which of the two stress-testing approaches perceives the scenarios more severely depends on the type of comparison employed. The QR approach is revealed more conservative based on a suggested comparison of vertical distances between the tails of the conditional and unconditional credit risk cumulative distributions.

By examining the impact of capital regulation on bank risk-taking using a local estimation technique, this paper attempts to quantify for the first time the heterogeneous response of banks towards this type of regulation in banking sectors of western-type economies. Subsequently, using this information, we examine the sources of heterogeneity. The findings suggest that the impact of capital regulation on bank risk is very heterogeneous across banks and the sources of this heterogeneity can be traced into both bank and industry characteristics, as well as into macroeconomic conditions. An important implication of the findings is that common capital regulatory umbrellas are not sufficient to promote financial stability, especially if they are not accompanied by supervisory effectiveness. On the basis of our findings, we contend that more focus should be placed on the actions needed to restrain excessive risk-taking of banks.

This paper investigates the dynamics between key regulatory and supervisory policies and various aspects of commercial bank efficiency and performance for a sample of 22 EU countries over 2000–2008. In the first stage of the analysis we measure efficiency by employing the Data Envelopment Analysis (DEA) technique. In addition, we employ two distinct accounting ratios to capture the costs of intermediation (net interest margin) and cost effectiveness (cost-to-income ratio). Our regression framework includes truncated regressions and generalized linear models. Moreover, we carry out a sensitivity analysis for robustness using a fractional logit estimator. Our results show that strengthening capital restrictions and official supervisory powers can improve the efficient operations of banks. Evidence also indicates that interventionist supervisory and regulatory policies such as private sector monitoring and restricting bank activities can result in higher bank inefficiency levels. Finally, the evidence produced suggests that the beneficial effects of capital restrictions and official supervisory powers (interventionist supervisory and regulatory policies) on bank efficiency are more pronounced in countries with higher quality institutions.