Saturday, June 30, 2012

A framework for dealing with domestic systemically important banks - consultative document

A framework for dealing with domestic systemically important banks - consultative document

June 2012

The consultative document sets out a framework of principles covering the assessment methodology and the higher loss absorbency requirement for domestic systemically important banks (D-SIBs). The D-SIB framework takes a complementary perspective of the global systemically important bank (G-SIB) framework published by the Basel Committee in November 2011. It focuses on the impact that the distress or failure of banks will have on the domestic economy. While not all D-SIBs are significant from a global perspective, the failure of such a bank could have an important impact on its domestic financial system and economy compared to non-systemic institutions. In order to accommodate the structural characteristics of individual jurisdictions, the assessment and application of policy tools should allow for an appropriate degree of national discretion. That is why the D-SIB framework is proposed to be a principles-based approach, which contrasts with the prescriptive approach in the G-SIB framework.

The proposed D-SIB framework requires banks, which have been identified as D-SIBs by their national authorities, to comply with the principles beginning in January 2016. This is consistent with the phase-in arrangements for the G-SIB framework and means that national authorities will establish a D-SIB framework by 2016. The Basel Committee will introduce a strong peer review process for the implementation of the principles. This will help ensure that appropriate and effective frameworks for D-SIBs are in place across different jurisdictions.

The Basel Committee welcomes comments on this consultative document. Comments should be submitted by Wednesday, 1 August 2012 by e-mail to: baselcommittee@bis.org. Alternatively, comments may be sent by post to the Secretariat of the Basel Committee on Banking Supervision, Bank for International Settlements, CH-4002 Basel, Switzerland. All comments may be published on the website of the Bank for International Settlements unless a comment contributor specifically requests confidential treatment.

Friday, June 29, 2012

Basel Committee - The internal audit function in banks - final document

Basel Committee - The internal audit function in banks - final document

June 28, 2012

The Basel Committee on Banking Supervision today issued its final document The internal audit function in banks .
 
This supervisory guidance is built around 20 principles that seek to promote a strong internal audit function within banks. Drawing on lessons learned from the financial crisis, the principles revise and update the Committee's supervisory guidance issued in 2001, also taking account of developments in supervisory practices and in banking organisations. For that purpose, the guidance addresses supervisory expectations for the internal audit function and the supervisory assessment of that function. It also encourages bank internal auditors to comply with national and international professional standards on internal auditing. Finally, it promotes due consideration of prudential issues by internal auditors. An annex to the consultative document details responsibilities of a bank's audit committee.

Mr Stefan Ingves, Chairman of the Basel Committee on Banking Supervision and Governor of Sveriges Riksbank, Sweden's central bank, noted that "an internal audit function, independent from management and composed of competent auditors, is a key component of a bank's sound governance framework. The Committee's document lays out expectations that should help banks and their supervisors strengthen professional practices in this area."

An earlier version of today's guidance was issued for consultation in December 2011. The Committee wishes to thank those who provided feedback and comments.

Tuesday, June 26, 2012

Rising Tensions Over China's Monopoly on Rare Earths?

Rising Tensions Over China's Monopoly on Rare Earths?, by June Nakano
East-West Center Asia Pacific Bulletin, no. 163
Washington, DC, May 2, 2012
http://www.eastwestcenter.org/publications/rising-tensions-over-china%E2%80%99s-monopoly-rare-earths

Jane Nakano, Fellow with the Energy and National Security Program at the Center for Strategic and International Studies, explains that "the current rare earth contention should serve as a reminder of the fundamental importance of supply diversification, and the enduring value that research and development plays in meeting many of the energy and resource related challenges society faces today."

Excerpts:

The recent Chinese industry consolidation may not be a welcome development as it will most likely increase the price of many rare earth materials. However, it is probably too short-sighted to view this move as a simple measure to side-step international complaints about China’s restrictive export policies on rare earth materials. In reality, the consolidation likely has multiple objectives, such as to demonstrate to the Chinese public an effort to both curb pollution and eradicate illegal mining, to ensure an adequate level of supply to domestic consumers, and to encourage higher value exports—if the consolidation leads to an in-flow of foreign rare earth processors to China. It would be neither easy nor particularly meaningful to determine which factor is most dominant.

Wednesday, June 20, 2012

Too Much Finance?

Too Much Finance? By Jean-Louis Arcand, Enrico Berkes, and Ugo Panizza
IMF Working Paper No. 12/161
June, 2012
http://www.imfbookstore.org/ProdDetails.asp?ID=WPIEA2012161

Summary: This paper examines whether there is a threshold above which financial development no longer has a positive effect on economic growth. We use different empirical approaches to show that there can indeed be "too much" finance. In particular, our results suggest that finance starts having a negative effect on output growth when credit to the private sector reaches 100% of GDP. We show that our results are consistent with the "vanishing effect" of financial development and that they are not driven by output volatility, banking crises, low institutional quality, or by differences in bank regulation and supervision.

Excerpts:

Introduction

In this paper we use different datasets and empirical approaches to show that there can indeed be “too much” finance. In particular, our results show that the marginal effect of financial depth on output growth becomes negative when credit to the private sector reaches 80-100% of GDP. This result is surprisingly consistent across different types of estimators (simple cross-sectional and panel regressions as well as semi-parametric estimators) and data (country-level and industry-level). The threshold at which we find that financial depth starts having a negative effect on growth is similar to the threshold at which Easterly, Islam, and Stiglitz (2000) find that financial depth starts having a positive effect on volatility. This finding is consistent with the literature on the relationship between volatility and growth (Ramey and Ramey, 1995) and that on the persistence of negative output shocks (Cerra and Saxena, 2008). However, we show that our finding of a non-monotone relationship between financial depth and economic growth is robust to controlling for macroeconomic volatility, banking crises, and institutional quality.

Our results differ from those of Rioja and Valev (2004) who find that, even in their “high region,” finance has a positive, albeit small, effect on economic growth. This difference is probably due to the fact that they set their threshold for the "high region" at a level of financial depth which is much lower than the level for which we start finding that finance has a negative effect on growth.

Our results are instead consistent with the vanishing effect of financial depth found by Rousseau and Wachtel (2011). If the true relationship between financial depth and economic growth is non-monotone, models that do not allow for non-monotonicity will lead to a downward bias in the estimated relationship between financial depth and economic growth.

Monday, June 18, 2012

Monitoring Systemic Risk Based on Dynamic Thresholds

Monitoring Systemic Risk Based on Dynamic Thresholds. By Kasper Lund-Jensen
IMF Working Paper No. 12/159
June 2012
http://www.imfbookstore.org/ProdDetails.asp?ID=WPIEA2012159

Summary: Successful implementation of macroprudential policy is contingent on the ability to identify and estimate systemic risk in real time. In this paper, systemic risk is defined as the conditional probability of a systemic banking crisis and this conditional probability is modeled in a fixed effect binary response model framework. The model structure is dynamic and is designed for monitoring as the systemic risk forecasts only depend on data that are available in real time. Several risk factors are identified and it is hereby shown that the level of systemic risk contains a predictable component which varies through time. Furthermore, it is shown how the systemic risk forecasts map into crisis signals and how policy thresholds are derived in this framework. Finally, in an out-of-sample exercise, it is shown that the systemic risk estimates provided reliable early warning signals ahead of the recent financial crisis for several economies.

Excerpts:

Introduction

The financial crisis in 2007–09, and the following global economic recession, has highlighted the importance of a macroprudential policy framework which seeks to limit systemic financial risk.  While there is still no consensus on how to implement macroprudential policy it is clear that successful implementation is contingent on establishing robust methods for monitoring systemic risk.3 This current paper makes a step towards achieving this goal. Systemic risk assessment in real time is a challenging task due to the intrinsically unpredictable nature of systemic financial risk. However, this study shows, in a fixed effect binary response model framework, that systemic risk does contain a component which varies in a predictable way through time and that modeling this component can potentially improve policy decisions.

In this paper, systemic risk is defined as the conditional probability of a systemic banking crisis and I am interested in modeling and forecasting this (potentially) time varying probability. If different systemic banking crises differ completely in terms of underlying causes, triggers, and economic impact the conditional crisis probability will be unpredictable. However, as illustrated in section IV, systemic banking crises appear to share many commonalities. For example, banking crises are often preceded by prolonged periods of high credit growth and tend to occur when the banking sector is highly leveraged.

Systemic risk can be characterized by both cross-sectional and time-related dimensions (e.g.  Hartmann, de Bandt, and Alcalde, 2009). The cross-sectional dimension concerns how risks are correlated across financial institutions at a given point in time due to direct and indirect linkages across institutions and prevailing default conditions. The time series dimension concerns the evolution of systemic risk over time due to changes in the macroeconomic environment. This includes changes in the default cycle, changes in financial market conditions, and the potential build-up of financial imbalances such as asset and credit market bubbles. The focus in this paper is on the time dimension of systemic risk although the empirical analysis includes a variable that proxies for the strength of interconnectedness between financial institutions.

This paper makes the following contributions to the literature on systemic risk assessment: Firstly, it employs a dynamic binary response model, based on a large panel of 68 advanced and emerging economies, to identify leading indicators of systemic risk. While Demirgüç-Kunt and Detragiache (1998a) study the determinants of banking crises the purpose of this paper is to evaluate whether systemic risk can be monitored in real time. Consequently, it employs a purely dynamic model structure such that the systemic risk forecasts are based solely on information available in real time. Furthermore, the estimation strategy employed in this paper is consistent under more general conditions than a random effect estimator used in other studies (e.g.  Demirgüç-Kunt and Detragiache (1998a) and Wong, Wong and Leung (2010)). Secondly, this paper shows how to derive risk factor thresholds in the binary response model framework. The threshold of a single risk factor is dynamic in the sense that it depends on the value of the other risk factors and it is argued that this approach has some advantages relative to static thresholds based on the signal extraction approach.4 Finally, I perform a pseudo out-of-sample analysis for the period 2001–2010 in order to assess whether the risk factors provided early-warning signals ahead of the recent financial crisis.

Based on the empirical analysis, I reach the following main conclusions:

1. Systemic risk, as defined here, does appear to be predictable in real time. In particular, the following risk factors are identified: banking sector leverage, equity price growth, the credit-to-GDP gap, real effective exchange rate appreciation, changes in the banks’ lending premium and the degree of banks interconnectedness as measured by the ratio of non-core to core bank liabilities. There is also some evidence which suggests that house price growth increases systemic risk but the effect is not statistically significant at conventional significance levels.

2. There exists a significant contagion effect between economies. When an economy with a large financial sector is experiencing a systemic banking crisis, the systemic risk forecasts in other economies increases significantly.

3. Rapid credit growth in a country is often associated with a higher level of systemic risk.  However, as highlighted in a recent IMF report (2011), a boom in credit can also reflect a healthy market response to expected future productivity gains as a result of new technology, new resources or institutional improvements. Indeed, many episodes of credit booms were not followed by a systemic banking crisis or any other material instability. It is critical that a policymaker is able to distinguish between these two scenarios when implementing economic policy. I find empirical evidence which suggests that credit growth increases systemic risk considerably more when accompanied by high equity price growth. Therefore, I argue that the evolution in equity prices can be useful for identifying a healthy credit expansion.

4. In a crisis signaling exercise, I find that the binary response model approach outperforms the popular signal extracting approach in terms of type I and type II errors.

5. Based on a model specification with credit-to-GDP growth, banking sector leverage and equity price growth I carefully evaluate the optimal credit-to-GDP growth threshold.  Contrary to the signal extraction approach the optimal threshold is not static but depends on the value of the other risk factors. For example, the threshold is around 10 percent if equity prices have decreased by 10 percent and banking sector leverage is around 130 percent but only around 0 percent if equity prices have grown by 20 percent and banking sector leverage is 160 percent. In comparison, the signal extraction method leads to a (static) credit-to-GDP growth threshold of 4.9 percent based on the same data sample.

6. In the out-of-sample analysis, I find that the systemic risk factors generally provided informative signals in many countries. Based on an in-sample calibration, around 50– 80 percent of the crises were correctly identified in real time without constructing too many false signals. In particular, a monitoring model based on credit-to-GDP growth and banking sector leverage signaled early warning signals ahead of the U.S. subprime crisis in 2007.

Wednesday, June 13, 2012

Obama Family Portrait


Fiscal Transparency, Fiscal Performance and Credit Ratings

Fiscal Transparency, Fiscal Performance and Credit Ratings. By Arbatli, Elif; Escolano, Julio
IMF Working Paper No. 12/156
June 2012
http://www.imf.org/external/pubs/cat/longres.aspx?sk=25996.0


Summary: This paper investigates the effect of fiscal transparency on market assessments of sovereign risk, as measured by credit ratings. It measures this effect through a direct channel (uncertainty reduction) and an indirect channel (better fiscal policies and outcomes), and it differentiates between advanced and developing economies. Fiscal transparency is measured by an index based on the IMF’s Reports on the Observance of Standards and Codes (ROSCs). We find that fiscal transparency has a positive and significant effect on ratings, but it works through different channels in advanced and developing economies. In advanced economies the indirect effect of transparency through better fiscal outcomes is more significant whereas for developing economies the direct uncertainty-reducing effect is more relevant. Our results suggest that a one standard deviation improvement in fiscal transparency index is associated with a significant increase in credit ratings: by 0.7 and 1 notches in advanced and developing economies respectively.

Tuesday, June 12, 2012

Bringing Africa Back to Life: The Legacy of George W. Bush

Bringing Africa Back to Life: The Legacy of George W. Bush. By Jim Landers
Dallas Morning News
June 08, 2012


LUSAKA, Zambia — On a beautiful Saturday morning, Delfi Nyankombe stood among her bracelets and necklaces at a churchyard bazaar and pondered a question: What do you think of George W. Bush?
“George Bush is a great man,” she answered. “He tried to help poor countries like Zambia when we were really hurting from AIDS. He empowered us, especially women, when the number of people dying was frightening. Now we are able to live.”

Nyankombe, 38, is a mother of three girls. She also admires the former president because of his current campaign to corral cervical cancer. Few are screened for the disease, and it now kills more Zambian women than any other cancer.

“By the time a woman knows, she may need radiation or chemotherapy that can have awful side effects, like fistula,” she said. “This is a big problem in Zambia, and he’s still helping us.”

The debate over a president’s legacy lasts many years longer than his term of office. At home, there’s still no consensus about the 2001-09 record of George W. Bush, with its wars and economic turmoil.
In Africa, he’s a hero.

“No American president has done more for Africa,” said Festus Mogae, who served as president of Botswana from 1998 to 2008. “It’s not only me saying that. All of my colleagues agree.”
AIDS was an inferno burning through sub-Saharan Africa. The American people, led by Bush, checked that fire and saved millions of lives.

People with immune systems badly weakened by HIV were given anti-retroviral drugs that stopped the progression of the disease. Mothers and newborns were given drugs that stopped the transmission of the virus from one generation to the next. Clinics were built. Doctors and nurses and lay workers were trained. A wrenching cultural conversation about sexual practices broadened, fueled by American money promoting abstinence, fidelity and the use of condoms.

“We kept this country from falling off the edge of a cliff,” said Mark Storella, the U.S. ambassador to Zambia. “We’ve saved hundreds of thousands of lives. We’ve assisted over a million orphans. We’ve created a partnership with Zambia that gives us the possibility of walking the path to an AIDS-free generation. This is an enormous achievement.”

Bush remains active in African health. Last September, he launched a new program — dubbed Pink Ribbon Red Ribbon — to tackle cervical and breast cancer among African women. The program has 14 co-sponsors, including the Obama administration.


Read the rest here: http://www.bushcenter.com/blog/2012/06/11/icymi-bringing-africa-back-to-life-the-legacy-of-george-w-bush

Systemic Risk and Asymmetric Responses in the Financial Industry

Systemic Risk and Asymmetric Responses in the Financial Industry. By López-Espinosa, Germán; Moreno, Antonio; Rubia, Antonio; and Valderrama, Laura
IMF Working Paper No. 12/152
June, 2012
http://www.imf.org/external/pubs/cat/longres.aspx?sk=25991.0

Summary: To date, an operational measure of systemic risk capturing non-linear tail comovement between system-wide and individual bank returns has not yet been developed. This paper proposes an extension of the so-called CoVaR measure that captures the asymmetric response of the banking system to positive and negative shocks to the market-valued balance sheets of individual banks. For the median of our sample of U.S. banks, the relative impact on the system of a fall in individual market value is sevenfold that of an increase. Moreover, the downward bias in systemic risk from ignoring this asymmetric pattern increases with bank size. The conditional tail comovement between the banking system and a top decile bank which is losing market value is 5.4 larger than the unconditional tail comovement versus only 2.2 for banks in the bottom decile. The asymmetric model also produces much better estimates and fitting, and thus improves the capacity to monitor systemic risk. Our results suggest that ignoring asymmetries in tail interdependence may lead to a severe underestimation of systemic risk in a downward market.

Excerpts:

In this paper, we discuss the suitability of the general modeling strategy implemented in Adrian and Brunnermeier (2011) and propose a direct extension which accounts for nonlinear tail comovements between individual bank returns and financial system returns. Like most VaR models, the CoVaR approach builds on semi-parametric assumptions that characterize the dynamics of the time series of returns. Among others, the procedure requires the specification of the functional form that relates the conditional quantile of the whole financial system to the returns of the individual firm. The model proposed by Adrian and Brunnermeier (2011) assumes that system returns depend linearly on individual returns, so changes in the latter would feed proportionally into the former. This assumption is simple, convenient, and to a large extent facilitates the estimation of the parameters involved and the generation of downside-risk comovement estimates. On the other hand, this structure imposes certain limitations, as it neglects nonlinear patterns in the propagation of volatility shocks and of perturbations to the risk factors affecting banks' exposures. Both patterns feature distinctively in downside-risk dynamics.

There are strong economic arguments that suggest that the financial system may respond nonlinearly to shocks initiated in a single institution. A sizeable, positive shock in an individual bank is unlikely to generate the same characteristic response (i.e., comovement with the system) in absolute terms than a massive negative shock of the same magnitude, particularly if dealing with large-scale financial institutions.2 The disruption to the banking system caused by the failure of a financial institution may occur through direct exposures to the failing institution, through the contraction of financial services provided by the weakening institution (clearing, settlement, custodial or collateral management services), or from a shock to investor confidence that spreads out to sound institutions under adverse selection imperfections (Nier, 2011). Indeed, an extreme idiosyncratic shock in the banking industry, will not only reduce the market value of the stocks a¤ected, but may also spread uncertainty in the system rushing depositors and lending counterparties to withdraw their holdings from performing institutions and across unrelated asset classes, precipitating widespread insolvency. Historical experience suggests that a confidence loss in the soundness of the banking sector takes time to dissipate and may generate devastating e¤ects on the real economy. Bernanke (1983) comes to the conclusion that bank runs were largely responsible of the systemic collapse of the financial industry and the subsequent contagion to the real sectors during the Great Depression. Another channel of contagion in a downward market is through the fire-sales of assets initiated by the stricken institution to restore its capital adequacy, causing valuation losses in firms holding equivalent securities. This mechanism, induced by the generalized collateral lending practices that are prevalent in the wholesale interbank market, can exacerbate price volatility in a crisis situation, as discussed by Brunnermeier and Pedersen (2009).  The increased complexity and connectedness of financial institutions can generate "Black Swan" effects, morphing small perturbations in one part of the financial system into large negative shocks on seemingly unrelated parts of the system. These arguments suggest that the financial system is more sensitive to downside losses than upside gains. In such a case, the linear assumption involved in Adrian and Brunnermeier (2011) would neglect a key aspect of downside risk modeling and lead to underestimate the extent of systemic risk contribution of an individual bank.

We propose a simple extension of this procedure that encompasses the linear functional form as a special case and which, more generally, allows us to capture asymmetric patterns in systemic spillovers. We shall refer to this specification as asymmetric CoVaR in the sequel. This approach retains the tractability of the linear model, which ensures that parameters can readily be identified by appropriate techniques, and produces CoVaR estimates which are expected to be more accurate. Furthermore, given the resultant estimates, the existence of nonlinear patterns that motivate the asymmetric model can be addressed formally through a standard Wald test statistic. In this paper, we analyze the suitability of the asymmetric CoVaR in a comprehensive sample of U.S. banks over the period 1990-2010. We find strong statistical evidence suggesting the existence of asymmetric patterns in the marginal contribution of these banks to the systemic risk. Neglecting these nonlinearities gives rise to estimates that systematically underestimate the marginal contribution to systemic risk. Remarkably, the magnitude of the bias is tied to the size of the firm, so that the bigger the company, the greater the underestimation bias. This result is consistent with the too-big-to-fail hypothesis which stresses the need to maintain continuity of the vital economic functions of a large financial institution whose disorderly failure would cause significant disruption to the wider financial system.3 Ignoring the existence of asymmetries would thus lead to conservative estimates of risk contributions, more so in large firms which are more likely to be systemic. Accounting for asymmetries in a simple extension of the model would remove that bias.

 Concluding Remarks

In this paper, we have discussed the suitability of the CoVaR procedure recently proposed by Adrian and Brunnermeier (2011). This valuable approach helps understand the drivers of systemic risk in the banking industry. Implementing this procedure in practice requires specifying the unobservable functional form that relates the dynamics of the conditional tail of system's returns to the returns of an individual bank. Adrian and Brunnermeier (2011) build on a model that assumes a simple linear representation, such that returns are proportional.

We show that this approach may provide a reasonable approximation for small-sized banks.  However, in more general terms, and particularly for large-scale banks, the linear assumption leads to a severe underestimation of the conditional comovement in a downward market and, hence, their systemic importance may be perceived to be lower than their actual contribution to systemic risk. Yet, how to measure and buttress e¤ectively the resilience of the financial system to losses crystallizing in a stress scenario is the main concern of policy makers, regulatory authorities, and financial markets alike. Witness the rally on U.S. equities and dollar on March 14, 2012 after the regulator announced favorable bank stress test results for the largest nineteen U.S. bank holding companies.

The reason is that the symmetric model implicitly assumes that positive and negative individual returns are equally strong to capture downside risk comovement. Our empirical results however, provide robust evidence that negative shocks to individual returns generate a much larger impact on the financial system than positive disturbances. For a median-sized bank, the relative impact ratio is sevenfold. We contend that this non-linear pattern should be acknowledged in the econometric modeling of systemic risk to avoid a serious misappraisal of risk. Moreover, our analysis suggests that the symmetric specification introduces systematic biases in risk assessment as a function of bank size. Specifically, the distortion caused by a linear model misspecification is more pronounced for larger banks, which are also more systemic on average. Our results show that tail interdependence between the financial system and a bottom-size decile bank which is contracting its balance sheet is 2.2 times larger than its average comovement. More strikingly, this ratio reaches 5.4 for the top-size decile bank. This result is in line with the too-big-to-fail hypothesis and lends support to recent recommendations put forth by the Financial Stability Board to require higher loss absorbency capacity on large banks. Likewise, it is consistent with the resolution plan required by the Dodd-Frank Act for bank holding companies and non-bank financial institutions with $50 billion or more in total assets. Submitting periodically a plan for rapid and orderly resolution in the event of financial distress or failure will enable the FDIC to evaluate potential loss severity and minimize the disruption that a failure may have in the rest of the system, thus performing its resolution functions more e¢ ciently. This measure will also help alleviate moral hazard concerns associated with systemic institutions and strengthen the stability of the overall financial system.

To capture the asymmetric pattern on tail comovement, we propose a simple yet e¤ective extension of the original CoVaR model. This extension preserves the tractability of the original model and its suitability can formally be tested formally through a simple Wald-type test, given the estimates of the model. We show that this simple extension is robust to more general specifications capturing non-linear patterns in returns, though at the expense of losing tractability.

The refinement of the CoVaR statistical measure presented in the paper aims at quantifying asymmetric spillover e¤ects when strains in banks' balance sheets are elevated, and thus contributes a step towards strengthening systemic risk monitoring in stress scenarios.  Furthermore, its focus on tail comovement originated from negative perturbations in the growth rate of market-valued banks' balance sheets, may yield insights into the impact on the financial system from large-scale deleveraging by banks seeking to rebuild their capital cushions. This particular concern has been recently rekindled by the continued spikes in volatility in euro area financial markets. It has been estimated that, following pressures on the European banking system as banks cope with sovereign stress, European banks may shrink their combined balance sheet significantly with the potential of unleashing shockwaves to emerging economies hurting their financial stability (IMF, 2012). The estimation of the impact on the real economy from aggregate weakness of the financial sector, and the design of optimal macroprudential policies to arrest systemic risk when tail interdependencies feed non-linearly into the financial system, are left for future research.

Friday, June 8, 2012

Policy Analysis and Forecasting in the World Economy: A Panel Unobserved Components Approach

Policy Analysis and Forecasting in the World Economy: A Panel Unobserved Components Approach. By Francis Vitek
IMF Working Paper No. 12/149
http://www.imf.org/external/pubs/cat/longres.aspx?sk=25974.0

Summary: This paper develops a structural macroeconometric model of the world economy, disaggregated into thirty five national economies. This panel unobserved components model features a monetary transmission mechanism, a fiscal transmission mechanism, and extensive macrofinancial linkages, both within and across economies. A variety of monetary policy analysis, fiscal policy analysis, spillover analysis, and forecasting applications of the estimated model are demonstrated, based on a Bayesian framework for conditioning on judgment.

Thursday, June 7, 2012

Policies for Macrofinancial Stability: How to Deal with the Credit Booms

Policies for Macrofinancial Stability: How to Deal with the Credit Booms. By Dell'Ariccia, Giovanni; Igan, Deniz; Laeven, Luc; Tong, Hui; Bakker, Bas B.; Vandenbussche, Jérôme
IMF Staff Discussion Notes No. 12/06
June 07, 2012
http://www.imf.org/external/pubs/cat/longres.aspx?sk=25935.0

Excerpts

Executive summary

Credit booms buttress investment and consumption and can contribute to long-term financial deepening. But they often end up in costly balance sheet dislocations, and, more often than acceptable, in devastating financial crises whose cost can exceed the benefits associated with the boom. These risks have long been recognized. But, until the global financial crisis in 2008, policy paid limited attention to the problem. The crisis—preceded by booms in many of the hardest-hit countries—has led to a more activist stance. Yet, there is little consensus about how and when policy should intervene. This note explores past credit booms with the objective of assessing the effectiveness of macroeconomic and macroprudential policies in reducing the risk of a crisis or, at least, limiting its consequences.

It should be recognized at the onset that a more interventionist policy will inevitably imply some trade-offs. No policy tool is a panacea for the ills stemming from credit booms, and any form of intervention will entail costs and distortions, the relevance of which will depend on the characteristics and institutions of individual countries. With these caveats in mind, the analysis in this note brings the following insights.

First, credit booms are often triggered by financial reform, capital inflow surges associated with capital account liberalizations, and periods of strong economic growth. They tend to be more frequent in fixed exchange rate regimes, when banking supervision is weak, and when macroeconomic policies are loose.

Second, not all booms are bad. About a third of boom cases end up in financial crises. Others do not lead to busts but are followed by extended periods of below-trend economic growth.  Yet many result in permanent financial deepening and benefit long-term economic growth.  Third, it is difficult to tell “bad” from “good” booms in real time. But there are useful telltales. Bad booms tend to be larger and last longer (roughly half of the booms lasting longer than six years end up in a crisis).

Fourth, monetary policy is in principle the natural lever to contain a credit boom. In practice, however, capital flows (and related concerns about exchange rate volatility) and currency substitution limit its effectiveness in small open economies. In addition, since booms can occur in low-inflation environments, a conflict may emerge with its primary objective.

Fifth, given its time lags, fiscal policy is ill-equipped to timely stop a boom. But consolidation during the boom years can help create fiscal room to support the financial sector or stimulate the economy if and when a bust arrives.

Finally, macroprudential tools have at times proven effective in containing booms, and more often in limiting the consequences of busts, thanks to the buffers they helped to build. Their more targeted nature limits their costs, although their associated distortions, should these tools be abused, can be severe. Moreover, circumvention has often been a major issue, underscoring the importance of careful design, coordination with other policies (including across borders), and close supervision to ensure the efficacy of these tools. 


Conclusions

Prolonged credit booms are a harbinger of financial crises and have real costs. Our analysis shows that, while only a minority of booms end up in crises, those that do can have longlasting and devastating real effects if left unaddressed. Yet it appears to be difficult to identify bad booms as they emerge, and the cost of intervening too early and running the risk of stopping a good boom therefore has to be weighed against the desire to prevent financial crises.

While the analysis offers some insights into the origins and dynamics of credit booms, from a policy perspective a number of questions remain unaddressed. In part this reflects the limited experience to date with macroprudential policies and the simultaneous use of multiple policy tools, making it hard to disentangle specific policy measures’ effectiveness.

First, while monetary policy tightening seems the natural response to rapid credit growth, we find only weak empirical evidence that it contains booms and their fallout on the economy.  This may be partly the result of a statistical bias. But there are several “legitimate” factors that limit the use and effectiveness of monetary policy in dealing with credit booms, especially in small open economies. In contrast, there is more consistent evidence that macroprudential policy is up to this task, although it is more exposed to circumvention.

All of the above raise important questions about the optimal policy response to credit booms.  Our view is that when credit booms coincide with periods of general overheating in the economy, monetary policy should act first and foremost. If the boom lasts and is likely to end up badly or if it occurs in the absence of overheating, then macroprudential policy should come into play. Preferably, this should be in combination and coordination with macroeconomic policy, especially when macroeconomic policy is already being used to address overheating of the economy.

Second, questions remain about the optimal mix and modality of macroprudential policies, also in light of political economy considerations and the type of supervisory arrangements in the country. Political economy considerations call for a more rules-based approach to setting macroprudential policy to avoid pressure from interest groups to relax regulation during a crisis. But such considerations have to be weighed against the practical problems and unintended effects of a rules-based approach, such as the calibration of rules with rather demanding data requirements and the risk of circumvention in the presence of active earnings management. The design of a macroprudential framework should also consider the capacity and ability of supervisors to enforce such rules so that unintended and potentially dangerous side effects can be avoided.

Third, the optimal macroprudential policy response to credit booms, as well as the optimal policy mix, will likely have to depend on the type of credit boom. Because of data limitations, our analysis has focused on aggregate credit. While it seems natural that policy response should adapt to and be targeted to the type of credit, additional analysis is needed to assess the effectiveness of policies to curtail booms that differ in the type of credit.

Fourth, policy coordination, across different authorities and across borders, may increase the effectiveness of monetary tightening and macroprudential policies. Cooperation and a continuous flow of information among national supervisors, especially regarding the activities of institutions that are active across borders, are crucial. Equally important is the coordination of regulations and actions among supervisors of different types of financial institutions. Whether and how national policymakers take into account the effects of their actions on the financial and macroeconomic stability of other countries is a vital issue, calling for further regional and global cooperation in the setup of macroprudential policy frameworks and the conduct of macroeconomic policies.

IMF Staff Notes: Externalities and Macro-Prudential Policy

Externalities and Macro-Prudential Policy. By De Nicoló, Gianni; Favara, Giovanni; Ratnovski, Lev
IMF Staff Discussion Notes No. 12/05
June 07, 2012
http://www.imf.org/external/pubs/cat/longres.aspx?sk=25936.0

Excerpts

Executive Summary

The recent financial crisis has led to a reexamination of policies for macroeconomic and financial stability. Part of the current debate involves the adoption of a macroprudential approach to financial regulation, with an aim toward mitigating boom-bust patterns and systemic risks in financial markets.

The fundamental rationale behind macroprudential policies, however, is not always clearly articulated. The contribution of this paper is to lay out the key sources of market failures that can justify macroprudential regulation. It explains how externalities associated with the activity of financial intermediaries can lead to systemic risk, and thus require specific policies to mitigate such risk.

The paper classifies externalities that can lead to systemic risk as:

1. Externalities related to strategic complementarities, that arise from the strategic interaction of banks (and other financial institutions) and cause the build-up of vulnerabilities during the expansionary phase of a financial cycle;
2. Externalities related to fire sales, that arise from a generalized sell-off of financial assets causing a decline in asset prices and a deterioration of the balance sheets of intermediaries, especially during the contractionary phase of a financial cycle; and
3. Externalities related to interconnectedness, caused by the propagation of shocks from systemic institutions or through financial networks.

The correction of these externalities can be seen as intermediate targets for macroprudential policy, since policies that control externalities mitigate market failures that create systemic risk.

This paper discusses how the main proposed macroprudential policy tools—capital requirements, liquidity requirements, restrictions on activities, and taxes—address the identified externalities. It is argued that each externality can be corrected by different tools that can complement each other. Capital surcharges, however, are likely to play an important role in the design of macroprudential regulation.

This paper’s analysis of macroprudential policy complements the more traditional one that builds on the distinction between time-series and cross-sectional dimensions of systemic risk.


Conclusions

This paper has argued that the first step in the economic analysis of macroprudential policy is the identification of market failures that contribute to systemic risk. Externalities are an important source of such market failures, and macroprudential policy should be thought of as an attempt to correct these externalities.

Building on the discussion in the academic literature, the paper has identified externalities that lead to systemic risk: externalities due to strategic complementarities, which contribute to the accumulation of vulnerabilities during the expansionary phase of a financial cycle; and externalities due to fire sales and interconnectedness, which tend to exacerbate negative shocks especially during a contractionary phase.

The correction of these externalities can be seen as an intermediate targets for macroprudential policy, since policies that control externalities mitigate market failures that create systemic risk. This paper has studied how the identified externalities can be corrected by the main macroprudential policy proposals: capital requirements, liquidity requirements, restrictions on bank activities, and taxation. The main finding is that even though some of these policies can complement each other in correcting the same externality, capital requirements are likely to play an important role in the design of any macroprudential framework.

It has also been argued that although externalities can be proxied through a variety of risk measurements, the accumulation of evidence on the effectiveness of alternative policy tools remains the most pressing concern for the design of macroprudential policy.