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Lev Ratnovski

16 July 2010
WORKING PAPER SERIES - No. 1223
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Abstract
Banks increasingly use short-term wholesale funds to supplement traditional retail deposits. Existing literature mainly points to the "bright side" of wholesale funding: sophisticated financiers can monitor banks, disciplining bad but refinancing good ones. This paper models a "dark side" of wholesale funding. In an environment with a costless but noisy public signal on bank project quality, short-term wholesale financiers have lower incentives to conduct costly monitoring, and instead may withdraw based on negative public signals, triggering inefficient liquidations. Comparative statics suggest that such distortions of incentives are smaller when public signals are less relevant and project liquidation costs are higher, e.g., when banks hold mostly relationship-based small business loans.
JEL Code
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
G33 : Financial Economics→Corporate Finance and Governance→Bankruptcy, Liquidation
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ECB Lamfalussy Fellowship Programme
20 April 2020
WORKING PAPER SERIES - No. 2395
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Abstract
This paper presents a new dataset on the dynamics of non-performing loans (NPLs) during 88 banking crises since 1990. The data show similarities across crises during NPL build-ups but less so during NPL resolutions. We find a close relationship between NPL problems—elevated and unresolved NPLs—and the severity of post-crisis recessions. A machine learning approach identifies a set of pre-crisis predictors of NPL problems related to weak macroeconomic, institutional, corporate, and banking sector conditions. Our findings suggest that reducing pre-crisis vulnerabilities and promptly addressing NPL problems during a crisis are important for post-crisis output recovery.
JEL Code
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
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
N10 : Economic History→Macroeconomics and Monetary Economics, Industrial Structure, Growth, Fluctuations→General, International, or Comparative
N20 : Economic History→Financial Markets and Institutions→General, International, or Comparative
Annexes
20 April 2020
ANNEX
27 May 2020
RESEARCH BULLETIN - No. 71
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Abstract
During crises, the number of loans that cannot be paid back increases. What are the lessons from past crises for non-performing loan resolution after COVID-19? In this article we use a new database covering non-performing loans (NPLs) in 88 banking crises since 1990 to find out. The data show that dealing with NPLs is critical to economic recovery. Compared with the 2008 crisis, some factors are conducive to NPL resolution this time: banks have higher capital, the forward-looking IFRS 9 accounting standards can help NPL recognition, and the COVID-19 crisis was not preceded by a credit boom. However, other factors could make NPL resolution more challenging: government debt is substantially higher, banks are less profitable, and corporate balance sheets are often weak.
JEL Code
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E61 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Policy Objectives, Policy Designs and Consistency, Policy Coordination
E63 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Comparative or Joint Analysis of Fiscal and Monetary Policy, Stabilization, Treasury Policy
26 June 2020
WORKING PAPER SERIES - No. 2429
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Abstract
We study the composition of bank loan portfolios during the transition of the real sector to a knowledge economy where firms increasingly use intangible capital. Exploiting heterogeneity in bank exposure to the compositional shift from tangible to intangible capital, we show that exposed banks curtail commercial lending and reallocate lending to other assets, such as mortgages. We estimate that the substantial growth in intangible capital since the mid-1980s explains around 30% of the secular decline in the share of commercial lending in banks' loan portfolios. We provide suggestive evidence that this reallocation increased the riskiness of banks' mortgage lending.
JEL Code
E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
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Research Task Force (RTF)
3 July 2020
WORKING PAPER SERIES - No. 2438
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Abstract
We study the effects of technological change on financial intermediation, distinguishing between innovations in information (data collection and processing) and communication (relationships and distribution). Both follow historic trends towards an increased use of hard information and less in-person interaction, which are accelerating rapidly. We point to more recent innovations, such as the combination of data abundance and artificial intelligence, and the rise of digital platforms. We argue that in particular the rise of new communication channels can lead to the vertical and horizontal disintegration of the traditional bank business model. Specialized providers of financial services can chip away activities that do not rely on access to balance sheets, while platforms can interject themselves between banks and customers. We discuss limitations to these challenges, and the resulting policy implications.
JEL Code
G20 : Financial Economics→Financial Institutions and Services→General
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
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Discussion papers
17 July 2020
WORKING PAPER SERIES - No. 2444
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Abstract
We contrast how monetary policy affects intangible relative to tangible investment. We document that the stock prices of firms with more intangible assets react less to monetary policy shocks, as identified from Fed Funds futures movements around FOMC announcements. Consistent with the stock price results, instrumental variable local projections confirm that the total investment in firms with more intangible assets responds less to monetary policy, and that intangible investment responds less to monetary policy compared to tangible investment. We identify two mechanisms behind these results. First, firms with intangible assets use less collateral, and therefore respond less to the credit channel of monetary policy. Second, intangible assets have higher depreciation rates, so interest rate changes affect their user cost of capital relatively less.
JEL Code
E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
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Research Task Force (RTF)