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Tuomas A. Peltonen

7 April 2005
WORKING PAPER SERIES - No. 467
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This paper examines the link between socio-economic development and fiscal policy. We introduce an indicator for socio-economic development (SEDI) and investigate its relationship with different fiscal variables, using data for the cohesion countries, namely Greece, Portugal, Spain and Ireland for 1980-1999. We find that an improvement in the net lending position of the government, as well as a fall in the level of public debt, would be beneficial for socio-economic development in the medium term. Furthermore, fiscal consolidation is found to be more relevant for promoting socio-economic development in the cohesion countries than in the other EU-15 Member States. Our results provide support for incentives to curb spending, such as the fiscal criteria of the Maastricht Treaty or the Stability and Growth Pact.
JEL Code
H6 : Public Economics→National Budget, Deficit, and Debt
H5 : Public Economics→National Government Expenditures and Related Policies
I0 : Health, Education, and Welfare→General
13 January 2006
WORKING PAPER SERIES - No. 571
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This paper analyzes the predictability of emerging market currency crises by comparing the often used probit model to a new method, namely a multi-layer perceptron artificial neural network (ANN) model. According to the results, both models were able to signal currency crises reasonably well in-sample, but the forecasting power of these models out-ofsample was found to be rather poor. Only in the case of Russian (1998) crisis were both models able to signal the crisis well in advance. The results reinforced the view that developing a stable model that can predict or even explain currency crises is a challenging task.
JEL Code
F31 : International Economics→International Finance→Foreign Exchange
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
C25 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Discrete Regression and Qualitative Choice Models, Discrete Regressors, Proportions
C23 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Panel Data Models, Spatio-temporal Models
C45 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Neural Networks and Related Topics
30 November 2007
WORKING PAPER SERIES - No. 829
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We model provincial inflation in China during the reform period. In particular, we are interested in the ability of the hybrid New Keynesian Phillips Curve (NKPC) to capture the inflation process at the provincial level. The study highlights differences in inflation formation and shows that the NKPC provides a reasonable description of the inflation process only for the coastal provinces. A probit analysis suggests that the forwardlooking inflation component and the output gap are important inflation drivers in provinces that have advanced most in marketisation of the economy and have most likely experienced excess demand pressures. These results have implications for the relative effectiveness of monetary policy across the Chinese provinces.
JEL Code
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
31 January 2008
WORKING PAPER SERIES - No. 857
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The study quantifies stock market and housing market wealth effects on households' non-durable consumption using Italian household panel data (SHIW) of 1989-2002. We found all households react similarly to aggregate housing and stock market gains. We also found statistically and economically significant housing wealth effects with a marginal propensity to consume out of idiosyncratic housing wealth gains to be over 8 percent. The results from idiosyncratic equity wealth e¤ects were lower, at around 0.4 percent. We also found that older households react more to changes in housing wealth.
JEL Code
D12 : Microeconomics→Household Behavior and Family Economics→Consumer Economics: Empirical Analysis
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
31 July 2008
WORKING PAPER SERIES - No. 918
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The paper analyses the impact of import penetration on firms' profitability in 15 manufacturing industries in 10 euro area countries during 1995-2004, focusing on the role of emerging market economies. Our results indicate that import competition from emerging market economies has had an overall negative impact on companies' profitability in the euro area manufacturing sector, especially for imports coming from China and Russia. However, similar negative effects are also estimated for imports from the United States. In contrast, imports from Latin America are estimated to be positively correlated with profitability. Finally, we find asymmetric effects on profitability across euro area countries and sectors.
JEL Code
L11 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Production, Pricing, and Market Structure, Size Distribution of Firms
L13 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Oligopoly and Other Imperfect Markets
F12 : International Economics→Trade→Models of Trade with Imperfect Competition and Scale Economies, Fragmentation
C23 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Panel Data Models, Spatio-temporal Models
16 October 2008
WORKING PAPER SERIES - No. 951
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This paper estimates export and import price equations for 41 countries -including 28 emerging market economies. Further, it relates the estimated elasticities to structural factors and tests for statistical breaks in the relation between trade prices and exchange rates. Results indicate that (i) the elasticity of trade prices in emerging markets is sizeable, but not significantly higher than in advanced economies; (ii) such elasticity is primarily influenced by macroeconomic factors such as the exchange rate regime and the inflationary environment, although microeconomic factors such as product differentiation also play a role; (iii) export and import price elasticities tend to be strongly correlated across countries; (iv) pass-through to import prices has declined in some advanced economies, noticeably the United States; this is consistent with a rise in pricing-to-market in several EMEs and especially with a change in the geographical composition of U.S. imports.
JEL Code
F10 : International Economics→Trade→General
F30 : International Economics→International Finance→General
F41 : International Economics→Macroeconomic Aspects of International Trade and Finance→Open Economy Macroeconomics
14 January 2009
WORKING PAPER SERIES - No. 993
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Due to the emergence of global production networks, trade statistics have became less accurate in describing the dependence of emerging Asia on external demand. This paper analyses, using an update of the Asian International Input-Output (AIO) table, the interdependence of emerging Asian countries, the United States, the EU15, and Japan via trade and production linkages. According to the results, we do not find evidence of the decoupling of emerging Asia from the rest of the world. On the contrary, we find evidence on increasing trade integration, both globally and regionally. Nonetheless, our analysis indicates that emerging Asia’s dependence on exports is only about one-third of its GDP, i.e. well below the 50% exposure suggested by trade data. This finding can be explained by the high import content of exports in these economies, which is a result of the increasing segmentation of production across the region.
JEL Code
F14 : International Economics→Trade→Empirical Studies of Trade
C67 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Input?Output Models
E23 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Production
28 January 2009
WORKING PAPER SERIES - No. 1000
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We build a panel of 14 emerging economies to estimate the magnitude of housing, stock market, and money wealth effects on consumption. Using modern panel data econometric techniques and quarterly data for the period 1990:1-2008:2, we show that: (i) wealth effects are statistically significant and relatively large in magnitude; (ii) housing wealth effects tend to be smaller for Asian emerging markets while stock market wealth effects are, in general, smaller for Latin American countries; (iii) housing wealth effects have increased for Asian coutries in recent years; and (iv) consumption reacts stronger to negative than to positive shocks in housing and financial wealth.
JEL Code
E21 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Consumption, Saving, Wealth
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
D12 : Microeconomics→Household Behavior and Family Economics→Consumer Economics: Empirical Analysis
24 April 2009
WORKING PAPER SERIES - No. 1046
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Abstract
We reappraise the relationship between productivity and equilibrium real exchange rates using a panel estimation framework that incorporates a large number of countries and importantly, a dataset that allows explicit consideration of the role of non-traded, as well as traded, sector productivity shocks in exchange rate determination. We find evidence of significant correlation between real exchange rates and productivity differentials in both sectors. But our finding of a significant role for the non-traded sector in exchange rate determination, and of a relatively larger correlation between exchange rates and productivity shocks of a given size emanating from this sector, represent clear contradictions of the widely cited Balassa-Samuelson hypothesis. Our findings remain valid in the face of a number of robustness tests, including the exchange rate regime and numéraire currency.
JEL Code
F31 : International Economics→International Finance→Foreign Exchange
O47 : Economic Development, Technological Change, and Growth→Economic Growth and Aggregate Productivity→Measurement of Economic Growth, Aggregate Productivity, Cross-Country Output Convergence
C23 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Panel Data Models, Spatio-temporal Models
20 July 2009
WORKING PAPER SERIES - No. 1073
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Abstract
A core stylized fact of the empirical exchange rate literature is that half-life deviations of equilibrium real exchange rates from levels implied by Purchasing Power Parity (PPP) are very persistent. Empirical efforts to explain this persistence typically proceed along two distinct paths, resorting either to the presence of real shocks such as productivity differentials that drive equilibrium exchange rates away from levels implied by PPP, or the presence of non-linearities in the adjustment process around PPP. By contrast, we combine these two explanations in the context of an innovative panel estimation methodology. We conclude that both explanations are relevant to the behavior of exchange rates and that resulting half-lives are much shorter than estimated using linear PPP and more consistent with the observed volatility of nominal and real exchange rates.
JEL Code
F31 : International Economics→International Finance→Foreign Exchange
C23 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Panel Data Models, Spatio-temporal Models
L6 : Industrial Organization→Industry Studies: Manufacturing
L7 : Industrial Organization→Industry Studies: Primary Products and Construction
L8 : Industrial Organization→Industry Studies: Services
L9 : Industrial Organization→Industry Studies: Transportation and Utilities
20 May 2010
WORKING PAPER SERIES - No. 1190
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This paper empirically models China’s stock prices using conventional fundamentals: corporate earnings, risk-free interest rate, and a proxy for equity risk premium. It uses the estimated longrun stock price misalignments to date booms and busts, and analyses equity market reforms and excess liquidity as potential drivers of these stock price misalignments. Our results show that China’s equity prices can be reasonable well modelled using fundamentals, but that various booms and busts can be identified. Policy actions, either taking the form of deposit rate changes, equity market reforms or excess liquidity, seem to have significantly contributed to these misalignments.
JEL Code
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
24 March 2011
WORKING PAPER SERIES - No. 1311
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This paper develops a framework for assessing systemic risks and for predicting (out-of-sample) systemic events, i.e. periods of extreme financial instability with potential real costs. We test the ability of a wide range of
JEL Code
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
F01 : International Economics→General→Global Outlook
F37 : International Economics→International Finance→International Finance Forecasting and Simulation: Models and Applications
G01 : Financial Economics→General→Financial Crises
Network
Macroprudential Research Network
21 September 2011
WORKING PAPER SERIES - No. 1382
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The paper uses the Self-Organizing Map for mapping the state of financial stability and visualizing the sources of systemic risks as well as for predicting systemic financial crises. The Self-Organizing Financial Stability Map (SOFSM) enables a two-dimensional representation of a multidimensional financial stability space that allows disentangling the individual sources impacting on systemic risks. The SOFSM can be used to monitor macro-financial vulnerabilities by locating a country in the financial stability cycle: being it either in the pre-crisis, crisis, post-crisis or tranquil state. In addition, the SOFSM performs better than or equally well as a logit model in classifying in-sample data and predicting out-of-sample the global financial crisis that started in 2007. Model robustness is tested by varying the thresholds of the models, the policymaker's preferences, and the forecasting horizons.
JEL Code
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
F01 : International Economics→General→Global Outlook
F37 : International Economics→International Finance→International Finance Forecasting and Simulation: Models and Applications
G01 : Financial Economics→General→Financial Crises
Network
Macroprudential Research Network
29 August 2013
WORKING PAPER SERIES - No. 1583
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This paper analyses the network structure of the credit default swap (CDS) market, using a unique sample of counterparties’ bilateral notional exposures to CDS on 642 sovereign and financial reference entities. We study the network structure, similarly to the literature on interbank and payment systems, by computing a variety of network metrics at the aggregated level and for several subnetworks. At a reference entity level, we analyse the determinants of some key network properties for large reference entities. Our main results, obtained on a sub-sample of 191 reference entities, are the following. First, the CDS network shows topological similarities with the interbank network, as we document a “small world” structure and a scale-free degree distribution for the CDS market. Second, there is considerable heterogeneity in the network structures across reference entities. In particular, the outstanding debt volume and its structure (maturity, collateralization), the riskiness, the type (sovereign/financial) and the location (European/non-European) of reference entities significantly influence the size, the activity and the concentration of the CDS exposure network. For instance, the network on a high-volatility reference entity is typically more active, larger in size and less concentrated.
JEL Code
G15 : Financial Economics→General Financial Markets→International Financial Markets
17 September 2013
OCCASIONAL PAPER SERIES - No. 4
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Abstract
Over the past few years the CDS market’s role has evolved from mostly providing default protection towards credit risk trading. The first-ever credit event in a developed country’s sovereign CDS has further highlighted the importance of the CDS market from a macro-prudential perspective. Developments in the European sovereign CDS market are a part of the major structural shift in euro sovereign debt: in the market’s view, there has been a significant shift from sovereign debt as a (default-free) risk-free benchmark (i.e. bearing interest rate risk only) to sovereign debt as a credit risk asset. Therefore, a significant repricing of the entire asset category has taken place, with major implications ranging from asset allocation to risk management. This implies that some policy issues are not necessarily and exclusively related to the CDS market, but are part of broader developments in the EU financial system. This Occasional Paper aims to provide a comprehensive analysis of the CDS market from a macroprudential perspective. In order to so, a wide range of analytical approaches is applied: Structural analysis of the EU CDS market: description of the market structure, key segments, concentration and evolution over time. Network analysis of bilateral CDS exposures: description of the structure and resilience of the network at an aggregate level as well as of sub-samples. In particular, analysis is conducted on: (i) the aggregated CDS network; (ii) various sub-networks, such as the sovereign CDS network; and (iii) networks for particular CDS reference entities. In order to carry out this analysis, we applied the established literature on interbank and payment systems networks to the CDS exposures network. “Super-spreader” analysis: identification of key “too interconnected to fail” market participants, their activities in the CDS market and their risk-bearing capacity. Scenario analysis of sovereign credit risk: the impact of sovereign credit events on the EU banking system and their potential spillovers. Domino effects in the CDS market: estimation of default chain scenarios for major participants in the CDS market; again, following the literature on interbank networks, we analysed the network impact of the collapse of a major market participant. Comparison of market- and exposure-based assessments of contagion: systemic risk rankings based on market price estimates (e.g. CoVaR) are compared with the rankings obtained using confidential DTCC exposure data in order to understand to what extent market participants are aware of who is a systemically relevant trader in the CDS market and whether these measures of systemic risk are consistent.
JEL Code
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
G33 : Financial Economics→Corporate Finance and Governance→Bankruptcy, Liquidation
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
15 October 2013
WORKING PAPER SERIES - No. 1597
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The paper develops an early-warning model for predicting vulnerabilities leading to distress in European banks using both bank and country-level data. As outright bank failures have been rare in Europe, the paper introduces a novel dataset that complements bankruptcies and defaults with state interventions and mergers in distress. The signals of the early warning model are calibrated not only according to the policy-maker's preferences between type I and II errors, but also to take into account the potential systemic relevance of each individual financial institution. The key findings of the paper are that complementing bank specific vulnerabilities with indicators for macro-financial imbalances and banking sector vulnerabilities improves model performance and yields useful out-of-sample predictions of bank distress during the current financial crisis.
JEL Code
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
F01 : International Economics→General→Global Outlook
F37 : International Economics→International Finance→International Finance Forecasting and Simulation: Models and Applications
G01 : Financial Economics→General→Financial Crises
Network
Macroprudential Research Network
16 October 2013
WORKING PAPER SERIES - No. 1599
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Abstract
This paper presents a stress test model for the CDS market, with a focus on the interplay between banks' bond and CDS holdings. The model enables the analysis of credit risk transfer mechanisms, includes features of market and liquidity risk, and allows for contagious propagation of counterparty failures. As an illustration, we calibrate the model using sovereign bond and CDS data for 65 major European banks. The model simulation shows that, in case of a sovereign credit event, banks' losses due to direct and correlated bond exposures are significantly higher than losses due to CDS exposures. The main risk for CDS sellers is found to be sudden increases in collateral requirements on multiple correlated CDS exposures. Close-out netting considerably reduces the extent to which contagion may occur.
JEL Code
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
H63 : Public Economics→National Budget, Deficit, and Debt→Debt, Debt Management, Sovereign Debt
G15 : Financial Economics→General Financial Markets→International Financial Markets
Network
Macroprudential Research Network
5 November 2013
WORKING PAPER SERIES - No. 1604
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This paper assesses the usefulness of private credit variables and other macrofinancial and banking sector indicators for the setting of Basel III / CRD IV countercyclical capital buffers (CCBs) in a multivariate early warning model framework, using data for 23 EU Members States from 1982 Q2 to 2012 Q3. We find that in addition to credit variables, other domestic and global financial factors such as equity and house prices as well as banking sector variables help to predict vulnerable states of the economy in EU Member States. We therefore suggest that policy makers take a broad approach in their analytical models supporting CCB policy measures.
JEL Code
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
Network
Macroprudential Research Network
27 November 2013
FINANCIAL STABILITY REVIEW - ARTICLE
Financial Stability Review Issue 2, 2013
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Abstract
The systemic dimension of the financial crisis has underscored the need for an expanded set of policies to contain systemic risk throughout the financial cycle. Counter-cyclical capital buffers (CCBs) form an integral part of the expanded European macro-prudential toolkit in this respect, with a “time series” focus in that they increase the resilience of the banking sector to shocks arising from financial and economic stress over the cycle and thereby provide a means to attenuate pro-cyclicality inherent in the financial system. To guide the setting of CCBs, the Basel Committee on Banking Supervision (BCBS) has proposed a focus on, inter alia, the deviation of the domestic credit-to-GDP ratio fromits backward-looking trend (also known as the domestic credit-to-GDP gap), given its track record of signalling financial stress well in advance. The Capital Requirements Directive (CRD) IV specifies that other variables should also be taken into consideration in addition to the credit gap. This special feature assesses the usefulness of private sector credit and other macro-financial and banking sector indicators in guiding the setting of CCBs in a multivariate early warning model framework. The analysis shows that in addition to credit variables, other domestic and global financial factors such as equity and house prices, as well as aggregate banking sector balance sheet indicators, help to predict historical periods of financial vulnerabilities in EU Member States. Consequently, policy-makers deciding on CCB measures could benefit from considering a wide range of indicators.
JEL Code
G00 : Financial Economics→General→General
27 November 2014
FINANCIAL STABILITY REVIEW - ARTICLE
Financial Stability Review Issue 2, 2014
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Abstract
This special feature discusses ways of measuring financial cycles for macro-prudential policymaking. It presents some estimates and empirical characteristics of financial cycles. Existing studies on financial cycle measurement remain quite nascent in comparison with the voluminous literature on business cycles. In this context, two approaches – turning point and spectral analysis – are used to capture financial and business cycles at the country level. The results of the empirical analysis suggest that financial cycles tend to be more volatile than business cycles in the euro area, albeit with strong cross-country heterogeneity. Both aspects underscore the relevance of robust financial cycle estimates for macro-prudential policy design in euro area countries.
JEL Code
G00 : Financial Economics→General→General
13 July 2015
WORKING PAPER SERIES - No. 1828
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Abstract
Building on the literature on systemic risk and financial contagion, the paper introduces estimated network linkages into an early-warning model to predict bank distress among European banks. We use multivariate extreme value theory to estimate equity-based tail-dependence networks, whose links proxy for the markets' view of bank interconnectedness in case of elevated financial stress. The paper finds that early warning models including estimated tail dependencies consistently outperform bank-specific benchmark models with- out networks. The results are robust to variation in model specification and also hold in relation to simpler benchmarks of contagion. Generally, this paper gives direct support for measures of interconnectedness in early-warning models, and moves toward a unified representation of cyclical and cross-sectional dimensions of systemic risk.
JEL Code
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G33 : Financial Economics→Corporate Finance and Governance→Bankruptcy, Liquidation
C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling
D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
14 September 2015
WORKING PAPER SERIES - No. 1846
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Abstract
We introduce a methodology to characterise financial cycles combining a novel multivariate spectral approach to identifying common cycle frequencies across a set of indicators, and a time varying aggregation emphasising systemic developments. The methodology is applied to 13 European Union countries as well a synthetic euro area aggregate, based on a quarterly dataset spanning 1970-2013. Results suggest that credit and asset prices share cyclical similarities, which, captured by a synthetic financial cycle, outperform the credit-to-GDP gap in predicting systemic banking crises on a horizon of up to three years. Financial cycles tend to be long, particularly in upswing phases and with important dispersion across country cases. Concordance of financial and business cycles is observed only 2/3 of the time. While a similar degree of concordance for financial cycles is apparent across countries, heterogeneity is high
JEL Code
E30 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→General
E40 : Macroeconomics and Monetary Economics→Money and Interest Rates→General
C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling
16 November 2015
WORKING PAPER SERIES - No. 1866
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Abstract
This paper uses domestic and cross-border linkages to measure the interconnectedness of the banking sector, and relates it to banking crises in Europe. Beyond cross-border financial linkages of the banking sector, we also account for financial linkages to the other main financial and non-financial sectors within the economy. We enrich conventional early-warning models using macro-financial vulnerabilities, by including measures of banking sector centrality as potential determinants of banking crises. Our results show that a more central position of the banking sector in these so-called macro-networks significantly increases the probability of a banking crisis. By analyzing the different types of risk exposures, our evidence shows that credit as well as market risks are important sources of vulnerabilities. Finally, the results show that early-warning models augmented with interconnectedness measures outperform traditional models in terms of out-of-sample predictions of recent banking crises in Europe.
JEL Code
F36 : International Economics→International Finance→Financial Aspects of Economic Integration
G20 : Financial Economics→Financial Institutions and Services→General
15 December 2015
WORKING PAPER SERIES - No. 1873
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Abstract
This paper introduces a new methodology to date systemic financial stress events in a transparent, objective and reproducible way. The financial cycle is captured by a monthly country-specific financial stress index. Based on a Markov Switching model, high financial stress regimes are identified and a simple algorithm is used to select those episodes of financial stress that are associated with a substantial negative impact on the real economy. By applying this framework to 27 EU countries, the paper is a first attempt to provide a chronology of systemic financial stress episodes in addition to the expert-detected events available so far.
JEL Code
C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling
G01 : Financial Economics→General→Financial Crises
G15 : Financial Economics→General Financial Markets→International Financial Markets
26 January 2016
OCCASIONAL PAPER SERIES - No. 9
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Abstract
An epidemiologist calculating the risk of a localised epidemic becoming a global pandemic would investigate every possible channel of contagion from the infected region to the rest of the world. Focusing on, say, the incidence of close human contact would underestimate the pandemic risk if the disease could also spread through the air. Likewise, calculating the quantity of financial system risk requires practitioners to understand all of the channels through which small and local shocks can become big and global. Much of the empirical finance literature has focused only on “direct” contagion arising from firms’ contractual obligations. Direct contagion occurs if one firm’s default on its contractual obligations triggers distress (such as illiquidity or insolvency) at a counterparty firm. But contractual obligations are not the only means by which financial distress can spread, just as close human contact is not the only way that many infectious diseases are transmitted. Focusing only on direct contagion underestimates the risk of financial crisis given that other important channels exist. This paper represents an attempt to move systemic risk analysis closer to the holism of epidemiology. In doing so, we begin by identifying the fundamental channels of indirect contagion, which manifest even in the absence of direct contractual links. The first is the market price channel, in which scarce funding liquidity and low market liquidity reinforce each other, generating a vicious spiral. The second is information spillovers, in which bad news can adversely affect a broad range of financial firms and markets. Indirect contagion spreads market failure through these two channels. In the case of illiquidity spirals, firms do not internalise the negative externality of holding low levels of funding liquidity or of fire-selling assets into a thin market. Lack of information and information asymmetries can cause markets to unravel, even following a relatively small piece of bad news. In both cases, market players act in ways that are privately optimal but socially harmful. The spreading of market failure by indirect contagion motivates policy intervention. Substantial progress has been made in legislating for policies that will improve systemic resilience to indirect contagion. But more tools might be needed to achieve a fully effective and efficient macroprudential policy framework. This paper aims to frame a high-level policy discussion on three policy tools that could be effective and efficient in ensuring systemic resilience to indirect contagion – namely macroprudential liquidity regulation; restrictions on margins and haircuts; and information disclosure.
JEL Code
G15 : Financial Economics→General Financial Markets→International Financial Markets
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
12 July 2016
WORKING PAPER SERIES - No. 1935
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Abstract
We develop an integrated Early Warning Global Vector Autoregressive (EW-GVAR) model to quantify the costs and benefits of capital-based macroprudential policy measures. Our findings illustrate that capital-based measures are transmitted both via their impact on the banking system's resilience and via indirect macro-financial feedback effects. The feedback effects relate to dampened credit and asset price growth and, depending on how banks move to higher capital ratios, can account for up to a half of the overall effectiveness of capital- based measures. Moreover, we document significant cross-country spillover effects, especially for measures implemented in larger countries. Overall, our model helps to understand how and through which channels changes in capitalization affect bank lending and the wider economy and can inform policy makers on the optimal calibration and timing of capital-based macroprudential instruments.
JEL Code
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
12 July 2016
WORKING PAPER SERIES - No. 17
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Abstract
We develop an integrated Early Warning Global Vector Autoregressive (EW-GVAR) model to quantify the costs and benefits of capital-based macroprudential policy measures. Our findings illustrate that capital-based measures are transmitted both via their impact on the banking system’s resilience and via indirect macro-financial feedback effects. The feedback effects relate to dampened credit and asset price growth and, depending on how banks move to higher capital ratios, can account for up to a half of the overall effectiveness of capitalbased measures. Moreover, we document significant cross-country spillover effects, especially for measures implemented in larger countries. Overall, our model helps to understand how and through which channels changes in capitalization affect bank lending and the wider economy and can inform policy makers on the optimal calibration and timing of capital-based macroprudential instruments.
JEL Code
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
14 November 2016
WORKING PAPER SERIES - No. 29
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Abstract
We estimate a multivariate early-warning model to assess the usefulness of private credit and other macro-financial variables in predicting banking sector vulnerabilities. Using data for 23 European countries, we find that global variables and in particular global credit growth are strong predictors of domestic vulnerabilities. Moreover, domestic credit variables also have high predictive power, but should be complemented by other macro-financial indicators like house price growth and banking sector capitalization that play a salient role in predicting vulnerabilities. Our findings can inform decisions on the activation of macroprudential policy measures and suggest that policy makers should take a broad approach in the analytical models that support risk identification and calibration of tools.
JEL Code
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
22 December 2016
WORKING PAPER SERIES - No. 33
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Abstract
We develop a framework to analyse the Credit Default Swaps (CDS) market as a network of risk transfers among counterparties. From a theoretical perspective, we introduce the notion of flow-of-risk and provide sufficient conditions for a bow-tie network architecture to endogenously emerge as a result of intermediation. This architecture shows three distinct sets of counterparties: i) Ultimate Risk Sellers (URS), ii) Dealers (indirectly connected to each other), iii) Ultimate Risk Buyers (URB). We show that the probability of widespread distress due to counterparty risk is higher in a bow-tie architecture than in more fragmented network structures. Empirically, we analyse a unique global dataset of bilateral CDS exposures on major sovereign and financial reference entities in 2011 −2014. We find the presence of a bow-tie network architecture consistently across both reference entities and time, and thatt the flow-of-risk originates from a large number of URSs (e.g. hedge funds) and ends up in a few leading URBs, most of which are non-banks (in particular asset managers). Finally, the analysis of the CDS portfolio composition of the URBs shows a high level of concentration: in particular, the top URBs often show large exposures to potentially correlated reference entities.
JEL Code
G10 : Financial Economics→General Financial Markets→General
G15 : Financial Economics→General Financial Markets→International Financial Markets
15 March 2017
WORKING PAPER SERIES - No. 40
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Abstract
This paper provides a unique snapshot of the exposures of EU banks to shadow banking entities within the global financial system. Drawing on a rich and novel dataset, the paper documents the cross-sector and cross-border linkages and considers which are the most relevant for systemic risk monitoring. From a macroprudential perspective, the identification of potential feedback and contagion channels arising from the linkages of banks and shadow banking entities is particularly challenging when shadow banking entities are domiciled in different jurisdictions. The analysis shows that many of the EU banks’ exposures are towards non-EU entities, particularly US-domiciled shadow banking entities. At the individual level, banks’ exposures are diversified although this diversification leads to high overlap across different types of shadow banking entities.
JEL Code
F65 : International Economics→Economic Impacts of Globalization→Finance
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
29 March 2017
WORKING PAPER SERIES - No. 2041
Details
Abstract
We develop a framework to analyse the Credit Default Swaps (CDS) market as a network of risk transfers among counterparties. From a theoretical perspective, we introduce the notion of flow-of-risk and provide sufficient conditions for a bow-tie network architecture to endogenously emerge as a result of intermediation. This architecture shows three distinct sets of counterparties: i) Ultimate Risk Sellers (URS), ii) Dealers (indirectly connected to each other), iii) Ultimate Risk Buyers (URB). We show that the probability of widespread distress due to counterparty risk is higher in a bow-tie architecture than in more fragmented network structures. Empirically, we analyse a unique global dataset of bilateral CDS exposures on major sovereign and financial reference entities in 2011 - 2014. We find the presence of a bow-tie network architecture consistently across both reference entities and time, and that the flow-of-risk originates from a large number of URSs (e.g. hedge funds) and ends up in a few leading URBs, most of which are non-banks (in particular asset managers). Finally, the analysis of the CDS portfolio composition of the URBs shows a high level of concentration: in particular, the top URBs often show large exposures to potentially correlated reference entities.
JEL Code
G10 : Financial Economics→General Financial Markets→General
G15 : Financial Economics→General Financial Markets→International Financial Markets
2 May 2017
WORKING PAPER SERIES - No. 43
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Abstract
Failing to account for joint dynamics of credit and asset prices can be hazardous for countercyclical macroprudential policy. We show that composite financial cycles, emphasising expansions and contractions common to credit and asset prices, powerfully predict systemic banking crises. Further, the joint consideration yields a more robust view on financial cycle characteristics, reconciling an empirical puzzle concerning cycle properties when using two popular alternative methodologies: frequency decompositions and standard turning point analysis. Using a novel spectral approach, we establish the following facts for G-7 countries (1970Q1-2013Q4): Relative to business cycles, financial cycles differ in amplitude and persistence – albeit with heterogeneity across countries. Average financial cycle length is around 15 years, compared with 9 years (6.7 excluding Japan) for business cycles. Still, country-level business and financial cycles relate occasionally. Across countries, financial cycle synchronisation is strong for most countries; but not for all. In contrast, business cycles relate homogeneously.
JEL Code
C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G01 : Financial Economics→General→Financial Crises
31 July 2017
OCCASIONAL PAPER SERIES - No. 194
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Abstract
This paper presents a new database for financial crises in European countries, which serves as an important step towards establishing a common ground for macroprudential oversight and policymaking in the EU. The database focuses on providing precise chronological definitions of crisis periods to support the calibration of models in macroprudential analysis. An important contribution of this work is the identification of financial crises by combining a quantitative approach based on a financial stress index with expert judgement from national and European authorities. Key innovations of this database are (i) the inclusion of qualitative information about events and policy responses, (ii) the introduction of a broad set of non-exclusive categories to classify events, and (iii) a distinction between event and post-event adjustment periods. The paper explains the two-step approach for identifying crises and other key choices in the construction of the dataset. Moreover, stylised facts about the systemic crises in the dataset are presented together with estimations of output losses and fiscal costs associated with these crises. A preliminary assessment of the performance of standard early warning indicators based on the new crises dataset confirms findings in the literature that multivariate models can improve compared to univariate signalling models.
JEL Code
G01 : Financial Economics→General→Financial Crises
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
E60 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→General
H12 : Public Economics→Structure and Scope of Government→Crisis Management
Annexes
31 July 2017
OCCASIONAL PAPER SERIES - No. 13
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Abstract
This paper presents a new database for financial crises in European countries, which serves as an important step towards establishing a common ground for macroprudential oversight and policymaking in the EU. The database focuses on providing precise chronological definitions of crisis periods to support the calibration of models in macroprudential analysis. An important contribution of this work is the identification of financial crises by combining a quantitative approach based on a financial stress index with expert judgement from national and European authorities. Key innovations of this database are (i) the inclusion of qualitative information about events and policy responses, (ii) the introduction of a broad set of non-exclusive categories to classify events, and (iii) a distinction between event and post-event adjustment periods. The paper explains the two-step approach for identifying crises and other key choices in the construction of the dataset. Moreover, stylised facts about the systemic crises in the dataset are presented together with estimations of output losses and fiscal costs associated with these crises. A preliminary assessment of the performance of standard early warning indicators based on the new crises dataset confirms findings in the literature that multivariate models can improve compared to univariate signalling models.
JEL Code
G01 : Financial Economics→General→Financial Crises
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
E60 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→General
H12 : Public Economics→Structure and Scope of Government→Crisis Management
Related
31 July 2017
FINANCIAL CRISES DATABASE
15 December 2017
WORKING PAPER SERIES - No. 62
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Abstract
This paper analyses whether the post-crisis regulatory reforms developed by globalstandard-setting bodies have created appropriate incentives for different types of market participants to centrally clear Over-The-Counter (OTC) derivative contracts. Beyond documenting the observed facts, we analyse four main drivers for the decision to clear: 1) the liquidity and riskiness of the reference entity; 2) the credit risk of the counterparty; 3) the clearing member’s portfolio net exposure with the Central Counterparty Clearing House (CCP) and 4) post trade transparency. We use confidential European trade repository data on single-name Sovereign Credit Derivative Swap (CDS) transactions, and show that for all the transactions reported in 2016 on Italian, German and French Sovereign CDS 48% were centrally cleared, 42% were not cleared despite being eligible for central clearing, while 9% of the contracts were not clearable because they did not satisfy certain CCP clearing criteria. However, there is a large difference between CCP clearing members that clear about 53% of their transactions and non-clearing members, even those that are subject to counterparty risk capital requirements, that almost never clear their trades. Moreover, we find that diverse factors explain clearing members’ decision to clear different CDS contracts: for Italian CDS, counterparty credit risk exposures matter most for the decision to clear, while for French and German CDS, margin costs are the most important factor for the decision. Moreover, clearing members use clearing to reduce their exposures to the CCP and largely clear contracts when at least one of the traders has a high counterparty credit risk.
JEL Code
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
11 October 2018
WORKING PAPER SERIES - No. 2182
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Abstract
This paper proposes a framework for deriving early-warning models with optimal out-of-sample forecasting properties and applies it to predicting distress in European banks. The main contributions of the paper are threefold. First, the paper introduces a conceptual framework to guide the process of building early-warning models, which highlights and structures the numerous complex choices that the modeler needs to make. Second, the paper proposes a flexible modeling solution to the conceptual framework that supports model selection in real-time. Specifically, our proposed solution is to combine the loss function approach to evaluate early-warning models with regularized logistic regression and cross-validation to find a model specification with optimal real-time out-of-sample forecasting properties. Third, the paper illustrates how the modeling framework can be used in analysis supporting both microand macro-prudential policy by applying it to a large dataset of EU banks and showing some examples of early-warning model visualizations.
JEL Code
G01 : Financial Economics→General→Financial Crises
G17 : Financial Economics→General Financial Markets→Financial Forecasting and Simulation
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G33 : Financial Economics→Corporate Finance and Governance→Bankruptcy, Liquidation
C52 : Mathematical and Quantitative Methods→Econometric Modeling→Model Evaluation, Validation, and Selection
C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling