چگونه نسبتهای احتیاطی کل، مشکلاتی سیستم بانکداری را به خوبی شناسایی می کند؟
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|18308||2010||15 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Financial Stability, Volume 6, Issue 3, September 2010, Pages 130–144
Aggregate prudential ratios have become a mainstay of financial stability analysis. But how reliable are these indicators when it comes to distinguishing between strong and weak banking systems? We address this issue by analyzing the performance of aggregate prudential ratios in systemic banking crises, drawing upon a large cross-country dataset. We caution against sole reliance on these indicators, and advocate supplementing them with other tools and techniques. Nonetheless, our findings offer evidence that some of the ratios can help identify systemic banking problems.
Reflecting the high costs of banking crises,2 banking sector stability has received increased attention in policy discussions in the past two decades. The debate acquired a new level of urgency when banking systems around the world experienced major disruptions in 2007–2009. An important question in those discussions is how to measure strengths and weaknesses of banking systems, so that problems at the systemic level can be properly identified and addressed. The monitoring and analysis of systemic stability often employs aggregate prudential ratios, such as the banking system capital adequacy ratio (CAR), nonperforming loans (NPLs) to total loans, and return on assets in the banking system. Surveys of financial stability reports published by central banks find that virtually all such reports use aggregate prudential ratios in their financial stability assessment (Čihák, 2006 and Oosterloo et al., 2007).3 The use of such ratios, though less ubiquitous, is also common in academic articles on financial stability, including those in the Journal of Financial Stability. 4 For example, Sorge and Virolainen (2006) approximate banking sector soundness in Finland by the (aggregate) ratio of loan-loss provisions to total loans, and estimate the relationship between this variable and a set of macroeconomic and other explanatory variables. Reflecting on the perceived importance of aggregate prudential ratios, substantial efforts have been devoted on national and international levels to define and compile so-called financial soundness indicators (FSIs). These FSIs are a subset of aggregate prudential ratios aiming to measure soundness of banks and their corporate and household counterparts (Sundararajan et al., 2002).5 But what do the aggregate prudential indicators actually indicate? In particular, are these FSIs able to identify instabilities of banking systems? In this paper, we attempt to answer these questions. Drawing upon a set of aggregate prudential ratios for 100 developed and developing economies, we present the first econometric analysis of the applicability of these ratios for the identification of banking problems. We employ parametric and nonparametric techniques to establish the extent to which a set of aggregate prudential ratios is able to explain the emergence of a banking crisis. Our paper is the first that systematically uses aggregate prudential ratios to examine whether they are beneficial for the identification of banking crises. Also, unlike most of the existing early warning system literature, the models presented here include indicators that capture information about the soundness of the nonfinancial sector. To preview our results, we find that certain indicators, such as banks’ return on equity and corporate leverage, are useful for the detection of banking system vulnerabilities. We also find that the contemporaneous capital adequacy ratio and the contemporaneous ratio of nonperforming loans to total loans provide warning signals for systemic banking problems. The paper is structured as follows. Section 2 surveys the literature on models of banking crises. Section 3 describes the dataset, and performs an initial analysis. Section 4 presents the methodological approach and the estimation results. Section 5 concludes.
نتیجه گیری انگلیسی
Aggregate prudential ratios are often used to describe developments in banking system soundness. In this paper, we analyze the information content of those indicators, and specifically, whether they help in identifying banking crises in a broad set of countries. In doing so, we contribute to the literature aiming to explain the occurrence of banking crises. Our findings underscore that aggregate prudential indicators need be interpreted with care. Such indicators may disguise problems in individual banks or groups of banks. Also, these ratios are usually based on regulatory data, which are backward looking, and may not capture sensitivity to future shocks. Moreover, some of the data may be subject to smoothing. Bank resolutions may take place before allowing the problems to be reflected in the data, and some banks may even engage in “creative accounting” in difficult times. Nonetheless, our analysis does yield some interesting results. In particular, it suggests that a number of the aggregate prudential ratios (especially those that aim to capture asset quality) behave in an intuitive way in crisis countries, and that some of the ratios can be useful for identifying weak banking systems. In particular, bank return on equity and (non-bank) corporate leverage are good indicators for the build-up of systemic banking problems. We also find some evidence that the contemporaneous ratio of NPLs to total loans and the contemporaneous capital adequacy ratio are useful for the identification of banking turmoil. Moreover, our results corroborate the hypothesis that banking problems tend to occur in less developed economies vulnerable to sudden capital outflows. This result is in line with the work by Davis and Stone (2004). In sum, the available data are supportive of the hypothesis that aggregate prudential ratios provide signals for the build-up of imbalances in banking systems. Aggregate prudential ratios offer some benefit to the macroprudential analyst. However, close attention needs to be paid to the construction of these ratios to ensure that all the relevant exposures are included (and not excluded, as in the above-mentioned case of the “shadow banking system”). Even then, the ratios need to be used jointly with other tools, both quantitative (e.g., stress tests or market-based indicators) and qualitative (e.g., assessment of the supervisory, regulatory, and institutional framework for the financial sector). Market-based and other quantitative indicators can provide information on the probability of a crisis, and stress tests can help quantify the impact of such a crisis. The qualitative information can be used to assess the ability of financial institutions and supervisors to mitigate the impacts of a crisis.