Digital euro
The Eurosystem is preparing for the potential issuance of a digital euro to complement physical cash.
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SPEECH
22 April 2026
Expanding the supply of euro area safe assets
There are several complementary routes to expand the stock of common euro debt and thereby help to meet the demand for euro-denominated safe assets, says Chief Economist Philip R. Lane at a joint workshop of the ESRB Advisory Technical Committee and Advisory Scientific Committee.
Read Mr Lane's keynote speech
INTERVIEW
22 April 2026
A more competitive Europe
In these uncertain times, we must urgently finish the work that is still incomplete: the banking union, the capital markets union and the Single Market, says Executive Board member Frank Elderson.
Read the interview
PODCAST
21 April 2026
Will AI steal my job?
How widespread is AI use? Will it create or replace jobs? And who stands to benefit the most in the new world of work? In our latest What the Euro?! episode, our host Catherine speaks to Laura – economist specialising in AI and the labour market – about all this and more.
Listen to the latest episode of Euro Matters- 21 April 2026
- WEEKLY FINANCIAL STATEMENTEnglishOTHER LANGUAGES (22) +Annexes
- 21 April 2026
- WEEKLY FINANCIAL STATEMENT - COMMENTARY
- 17 April 2026
- BALANCE OF PAYMENTS (MONTHLY)
- 16 April 2026
- MONETARY POLICY ACCOUNTRelated
- 19 March 2026
- MONETARY POLICY DECISIONEnglishOTHER LANGUAGES (23) +
- 14 April 2026
- WEEKLY FINANCIAL STATEMENTEnglishOTHER LANGUAGES (22) +Annexes
- 14 April 2026
- WEEKLY FINANCIAL STATEMENT - COMMENTARY
- 14 April 2026
- PRESS RELEASE
- 22 April 2026
- Keynote speech by Philip R. Lane, Member of the Executive Board of the ECB, at the joint workshop of the European Systemic Risk Board Advisory Technical Committee and Advisory Scientific Committee on “A European Safe Asset and Financial Stability”
- 20 April 2026
- Keynote speech by Christine Lagarde, President of the ECB, at the annual reception of the Association of German Banks on the occasion of their 75th anniversary
- 17 April 2026
- Statement by Christine Lagarde, President of the ECB, at the fifty-third meeting of the International Monetary and Financial Committee
- 16 April 2026
- Slides by Isabel Schnabel, Member of the Executive Board of the European Central Bank, at the event “The future economic architecture of the eurozone” organised by the Peterson Institute for International Economics in Washington, D.C., United States.
- 15 April 2026
- Keynote address by Piero Cipollone, Member of the Executive Board of the ECB, at the 24th Annual Symposium on “Building the Financial System of the 21st Century: an Agenda for Europe and the United States”, hosted by the Harvard Law School and the Program on International Financial Systems
- 22 April 2026
- Interview with Frank Elderson, Member of the Executive Board of the ECB and Vice-Chair of the Supervisory Board of the ECB, conducted by Eva Smal on 15 April 2026
- 23 March 2026
- Interview with Luis de Guindos, Vice-President of the ECB, conducted by Carlos Segovia on 20 March 2026
- 8 March 2026
- Interview with Christine Lagarde, President of the ECB, conducted by Benedetta Poletti on 12 February 2026
- 3 March 2026
- Interview with Philip R. Lane, Member of the Executive Board of the ECB, conducted by Olaf Storbeck on 26 February 2026
- 21 February 2026
- Interview with Christine Lagarde, President of the ECB, conducted by Emma Tucker, Chelsey Dulaney, Greg Ip, Nick Timiraos, Daniel Colarusso and Amol Sharma on 19 February 2026
- 21 April 2026
- Artificial intelligence (AI) can help track inflation risks in real time. A new ECB model based on machine learning informs experts how likely it is that inflation will be much higher or much lower than they expect.Details
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 13 April 2026
- During the latest tightening episode, interest rate hikes were especially effective. This ECB Blog finds a strong policy transmission to inflation during 2022 and 2023, a forceful response to supply-driven shocks and a low “sacrifice ratio”.Details
- JEL Code
- E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
- 9 April 2026
- Many Bulgarians feared large price increases when the euro replaced the lev. However, preliminary evidence shows that the changeover in Bulgaria has so far had a limited impact on consumer prices and on perceptions of inflation.Details
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E42 : Macroeconomics and Monetary Economics→Money and Interest Rates→Monetary Systems, Standards, Regimes, Government and the Monetary System, Payment Systems
Related - 7 April 2026
- Europe’s energy dependence increasingly complicates the task of maintaining price stability. Meeting the continent’s clean‑energy targets would weaken the link between volatile global markets and domestic prices. Crucially, the tools to make this transition are already within reach.Details
- JEL Code
- E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
Q40 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Energy→General
Q50 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→General
- 2 April 2026
- As the Eurosystem normalises its balance sheet, central bank reserves – banks’ most liquid asset – keep declining. This post examines how banks adapt to lower levels of reserves and explains why take-up in the Eurosystem’s standard refinancing operations is expected to increase.Details
- JEL Code
- E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
- 22 April 2026
- RESEARCH BULLETIN - No. 142Details
- Abstract
- We model central bank communication when there is disagreement between the markets and the central bank about the central bank’s confidence surrounding its point forecast. We show that such a disagreement leads the markets to misunderstand a given announcement, so that the markets either over- or underreact to the bank’s announcement. Communicating only a part of the central bank’s information set is a way to correct the markets’ over- or underreaction. The model also produces predictions for how the central bank’s statement drafting process can take the disagreement about uncertainty into account, which we find support for in data on Federal Reserve System communication.
- JEL Code
- E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
C49 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Other
- 21 April 2026
- OCCASIONAL PAPER SERIES - No. 386Details
- Abstract
- This paper studies the effectiveness of risk management, one of the two channels identified by the Network for Greening the Financial System (NGFS, 2024) as those through which the financial system contributes to physical risk adaptation in the European Union (EU). We assess the efficacy of Level 3 prudential regulations in encouraging banks to include physical risk adaptation in their risk management and client engagement strategies. Our analysis adopts a broad perspective, encompassing not only prudential risk management but also, and in our view more importantly, prudential transparency regulation, given the positive leverage that stakeholders can exert to incentivise adaptation efforts. Our findings suggest that banks should consistently integrate physical risk adaptation into their stress tests, transition plans and Pillar III disclosures. Transition plans must address physical hazards, exposure and vulnerability and must set adaptation targets. Adaptation measures should be treated as risk mitigants reflected in losses given default (LGDs), with the severity and consistency of those losses being reflected in transition plans and stress tests.
- JEL Code
- K23 : Law and Economics→Regulation and Business Law→Regulated Industries and Administrative Law
O52 : Economic Development, Technological Change, and Growth→Economywide Country Studies→Europe
Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
Q58 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Government Policy
- 16 April 2026
- WORKING PAPER SERIES - No. 3220Details
- Abstract
- We analyze how bank lending to non-bank financial institutions (NBFIs) affects credit supply to the real economy. Using granular supervisory and loan-level data, we document rapid growth in bank lending to NBFIs relative to lending to non-financial firms. This growth is driven primarily by reverse repos to NBFIs that invest in securities, e.g., investment funds, rather than by loans to NBFIs that extend credit to firms, e.g., private credit funds. We show that the expansion in bank–NBFI lending reflects rising NBFI borrowing demand to fund government securities, which stems in part from the tapering of QE and the expansion of government bond supply in the Euro area, US, UK, and Japan. Importantly, loans to NBFIs disproportionately crowd out loans to non-financial firms rather than securities on bank balance sheets, which ultimately contracts credit supply to the real economy. A model rationalizes our empirical findings and quantifies the aggregate crowding-out effect. Taken together, our results imply that the rise of bank lending to NBFIs represents a narrowing of bank business models and a contraction in bank credit intermediation.
- JEL Code
- 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
G24 : Financial Economics→Financial Institutions and Services→Investment Banking, Venture Capital, Brokerage, Ratings and Ratings Agencies
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
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
- 14 April 2026
- WORKING PAPER SERIES - No. 3219Details
- Abstract
- We propose a new approach to estimate selection-corrected quantiles of the gender wage gap. Our method employs instrumental variables that explain variation in the latent variable but, conditional on the latent process, do not directly affect selection. We provide semiparametric identification of the quantile parameters without imposing parametric restrictions on the selection probability, derive the asymptotic distribution of the proposed estimator based on constrained selection probability weighting, and demonstrate how the approach applies to the Roy model of labor supply. Using German administrative data, we analyze the distribution of the gender gap in full-time earnings. We find pronounced positive selection among women at the lower end, especially those with less education, which widens the gender gap in this segment, and strong positive selection among highly educated men at the top, which narrows the gender wage gap at upper quantiles.
- JEL Code
- C14 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Semiparametric and Nonparametric Methods: General
C21 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Cross-Sectional Models, Spatial Models, Treatment Effect Models, Quantile Regressions
J16 : Labor and Demographic Economics→Demographic Economics→Economics of Gender, Non-labor Discrimination
J21 : Labor and Demographic Economics→Demand and Supply of Labor→Labor Force and Employment, Size, and Structure
J31 : Labor and Demographic Economics→Wages, Compensation, and Labor Costs→Wage Level and Structure, Wage Differentials
- 14 April 2026
- CONSULTATION RESPONSE
- 13 April 2026
- WORKING PAPER SERIES - No. 3218Details
- Abstract
- Policymakers often cite the risk that inflation expectations might “de-anchor” as a key reason for responding forcefully to inflationary shocks. We develop a model to analyze this trade-off and to quantify the benefits of stable long-run inflation expectations. In our framework, households and firms are imperfectly informed about the central bank’s objective and learn from its policy choices. Recognizing this interaction, the central bank raises interest rates more aggressively after adverse supply shocks and accepts short-run output costs to secure more stable inflation expectations. The strength of this reputation channel depends on how sensitive long-run inflation expectations are to surprises in interest rates. Using high-frequency identification, we estimate these elasticities for emerging and advanced economies and find large negative values for Brazil. We fit our model to these findings and use it to quantify how reputation building motives affect monetary policy decisions, and the role of central bank’s credibility in promoting macroeconomic stability.
- JEL Code
- E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
- 13 April 2026
- MACROPRUDENTIAL BULLETIN - ARTICLE - No. 33Details
- Abstract
- Stablecoins denominated in US dollars have attracted considerable attention in the context of their growing influence in US Treasury markets. However, the potential effects of euro-denominated stablecoins on euro area sovereign debt markets have been less explored, partly owing to their currently limited market presence. This article explores how the growth of euro-denominated stablecoins could affect demand for euro area sovereign bonds. By determining the pass-through rate of stablecoin demand to sovereign bond holdings by way of several illustrative examples, we demonstrate how the effect varies based on whether stablecoins are issued by banks or e-money institutions (EMIs), on the composition of stablecoin reserve assets, and on the liquidity management preferences of banks and EMIs. Moreover, the net effect hinges on the sectoral origins of stablecoin inflows, which vary according to what stablecoins are, and will be, used for. We also argue that on the one hand, the deposit requirement for EMIs set out in the European Union’s Markets in Crypto-Assets Regulation (MiCAR) can act as a liquidity buffer during periods of stress, reducing the likelihood of immediate sales of other reserve assets, on the other hand it could also transmit stress arising from a stablecoin run to the banking system.
- JEL Code
- E42 : Macroeconomics and Monetary Economics→Money and Interest Rates→Monetary Systems, Standards, Regimes, Government and the Monetary System, Payment Systems
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
- 13 April 2026
- MACROPRUDENTIAL BULLETIN - ARTICLE - No. 33Details
- Abstract
- The market for tokenised money market funds (TMMFs) – money market funds (MMFs) whose shares are issued as tokens on distributed ledgers – remains small but is expanding rapidly. This article explores the specific design features of TMMFs, including the tokenisation of their underlying assets, liabilities and operational processes. It analyses key economic differences between TMMFs and traditional MMFs, with a particular focus on their implications for financial stability. Tokenisation has the potential to enhance efficiency by enabling faster settlement together with near-24/7 availability and programmability, while unlocking new use cases, such as employing TMMF tokens as collateral. However, TMMFs could also amplify risks related to liquidity mismatches and operational fragilities. A dedicated box in this article compares TMMFs with stablecoins, assessing their financial stability implications and interlinkages. Ultimately, the net financial stability impact of TMMFs will depend on how the market evolves, how it will affect prevailing business models and how it will integrate and interact with traditional financial markets.
- JEL Code
- G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
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
O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
- 13 April 2026
- MACROPRUDENTIAL BULLETIN - ARTICLE - No. 33Details
- Abstract
- This article describes the current landscape of tokenised assets, illustrating the potential benefits across the entire asset value chain – from issuance to distribution and sales. As the Eurosystem is working towards enabling the settlement of distributed ledger technology (DLT) transactions using central bank money with a pilot by the end of the third quarter of 2026, we examine key enablers and barriers to unlocking the benefits of tokenisation for a digital capital market in Europe while safeguarding financial stability. These include the need for on-chain secondary market liquidity to enable scaling, as well as adaptations and harmonisation of the regulatory framework. Based on these findings, this article highlights how tokenisation, if it scales more widely, could contribute to the savings and investments union (SIU) agenda in two major ways. First, it offers an opportunity to create a European digital asset ecosystem from the early stages, in contrast to the fragmented market for traditional financial instruments, which developed from national markets. Second, it has the potential to improve market liquidity and efficiency, which can ultimately increase the scalability and development of capital markets in Europe. In turn, this could facilitate a more efficient allocation of capital within the economy. Lastly, developing a DLT ecosystem relying on European governance and based on assets denominated in euro is essential to maintaining monetary sovereignty and strategic autonomy. Finally, this article discusses the role of public authorities – including central banks, in providing the conditions for innovation to develop in a safe and resilient manner.
- JEL Code
- F36 : International Economics→International Finance→Financial Aspects of Economic Integration
G10 : Financial Economics→General Financial Markets→General
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
- 13 April 2026
- MACROPRUDENTIAL BULLETIN - ARTICLE - No. 33Details
- Abstract
- Tokenisation holds the promise to automate the issuance process for bonds, reduce settlement times and enable more efficient and cheaper processes for conducting transactions. Given the transformative potential of tokenisation and distributed ledger technology (DLT) for capital markets and for the savings and investments union, this article investigates empirically whether the tokenisation of bonds – while still at an early stage – improves bond issuance efficiency and market liquidity. The tokenised bond market is currently still small but has seen an uptick in issuance over the past two years. To overcome the challenge presented by the limited availability of data on tokenisation, we construct a unique dataset for our analysis, primarily composed of financial and non-financial corporate bonds issued predominantly in Europe. Employing a matching procedure at the issuer-bond level, we ensure that tokenised and conventional bonds are comparable before assessing whether tokenisation has the potential to boost issuance efficiency, for example by automating processes, and to improve market liquidity by lowering entry and transaction barriers. We find that tokenised bonds reduce borrowing costs and improve market liquidity, but with no visible reduction in operational costs (all relative to the group of matched conventional bonds). Given that the market is still in its infancy, our results indicate that there may be greater benefits as the market grows. However, the future impact of tokenisation and the realisation of its potential benefits in terms of efficiency and liquidity will hinge on the underlying infrastructure and the possibility for the market to scale. Central banks initiatives – such as the Eurosystem’s explorations on the acceptance of DLT-based collateral and initiatives to improve and modernise market infrastructures - serve as key enablers that could support a scaling up of the market.
- JEL Code
- G10 : Financial Economics→General Financial Markets→General
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
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
O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
- 13 April 2026
- MACROPRUDENTIAL BULLETIN - ARTICLE - No. 33Details
- Abstract
- This overview of the [33rd] Macroprudential Bulletin explores how the different articles in this issue speak to the opportunities and challenges presented by Europe’s rapidly evolving digital financial ecosystem. In particular, the overview explains how tokenisation – and DLT more specifically – can support deeper, more integrated and more efficient EU capital markets, noting that its benefits will only be realised safely if European policy action keeps pace in key areas.
- JEL Code
- F36 : International Economics→International Finance→Financial Aspects of Economic Integration
G10 : Financial Economics→General Financial Markets→General
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
- 13 April 2026
- SURVEY OF MONETARY ANALYSTS
- 10 April 2026
- LEGAL ACT
- 10 April 2026
- THE EXCHANGE OF BALANCE OF PAYMENTS, INTERNATIONAL INVESTMENT POSITION STATISTICS – BPM6 - BOOKLETAnnexes
- 10 April 2026
- THE EXCHANGE OF BALANCE OF PAYMENTS, INTERNATIONAL INVESTMENT POSITION STATISTICS – BPM6 - BOOKLET
- 10 April 2026
- THE EXCHANGE OF BALANCE OF PAYMENTS, INTERNATIONAL INVESTMENT POSITION STATISTICS – BPM6 - BOOKLET
- 10 April 2026
- THE EXCHANGE OF BALANCE OF PAYMENTS, INTERNATIONAL INVESTMENT POSITION STATISTICS – BPM6 - BOOKLET
- 9 April 2026
- WORKING PAPER SERIES - No. 3217Details
- Abstract
- We revisit the credit channel of monetary policy when firms face multiple financing constraints, a common feature of corporate financing we document empirically. Our theory shows that the multiplicity of constraints dampens the transmission of expansionary policy to firm borrowing and investment notably but amplifies the transmission of policy tightening. This asymmetry arises because, when policy tightens (eases), the most (least) responsive constraint binds. Using U.S. firm-level data and exploiting a quasi-natural experiment, we find strong support for these predictions and for our proposed channel. Embedding the mechanism into a New Keynesian framework, we find that the drop in investment after contractionary shocks is twice as large as its increase following equally-sized expansionary shocks, thus providing an explanation for why monetary policy tightenings have stronger effects than easings, a longstanding puzzle in monetary economics. Moreover, our analysis implies that the effectiveness of monetary policy is strongly determined by the distribution of financial constraints across firms and that similar asymmetries likely characterize the transmission of other macroeconomic shocks.
- JEL Code
- D22 : Microeconomics→Production and Organizations→Firm Behavior: Empirical Analysis
D25 : Microeconomics→Production and Organizations
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
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy - Network
- Challenges for Monetary Policy Transmission in a Changing World Network (ChaMP)
- 9 April 2026
- OTHER PUBLICATION
- 8 April 2026
- WORKING PAPER SERIES - No. 3216Details
- Abstract
- We use a comprehensive Swedish credit register to document that firms across the size distribution have access to substantial borrowing capacity via credit lines. However, most firms choose not to use all available credit, even though interest rates are low compared to their return on equity. The low utilization of credit is consistent with a theoretical model in which utilization rates decrease with both real and financial uncertainty. We estimate the model structurally at the firm level and find that financial uncertainty driven by liquidity shocks is much more important than real uncertainty driven by cash flow shocks for explaining the low utilization of credit.
- JEL Code
- D22 : Microeconomics→Production and Organizations→Firm Behavior: Empirical Analysis
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
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
- 7 April 2026
- WORKING PAPER SERIES - No. 3215Details
- Abstract
- Using a survey of 39,507 adults in 17 euro-area countries, I find that crypto-asset owners and the niche subgroup of payers have distinct profiles. Owners – typically younger, male, and financially active – exhibit mixed preferences, valuing both cash-like privacy and card-like speed. Crypto payers display a cash-centric profile, seeking to replicate physical cash’s privacy and ease of use in digital form. While standard specifications show that holding cash reserves is positively associated with owning crypto – challenging the view that early adopters reject cash –, a multiple-instrument IV strategy exploiting pandemic-related payment shocks reveals a causal sign reversal: for compliers, building precautionary cash buffers reduces the probability of crypto ownership under uncertainty. These findings (1) explain the ownership-payment wedge as driven by user profiles beyond merchant-acceptance frictions, (2) show crypto and cash act as portfolio complements but substitutes under stress, and (3) may inform crypto regulation and CBDC design.
- JEL Code
- E41 : Macroeconomics and Monetary Economics→Money and Interest Rates→Demand for Money
E42 : Macroeconomics and Monetary Economics→Money and Interest Rates→Monetary Systems, Standards, Regimes, Government and the Monetary System, Payment Systems
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G11 : Financial Economics→General Financial Markets→Portfolio Choice, Investment Decisions
O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
- 7 April 2026
- OCCASIONAL PAPER SERIES - No. 385Details
- Abstract
- This article provides a novel insight into whether earnings manipulation signals are reflected in banks’ internal credit risk estimates, as measured by the probability of default (PD) estimates, and whether such manipulation has an impact on credit risk (point in time or deferred). The hypothesis is that firms engaging in manipulation may be exposed to increased credit risk over time, which should be reflected in higher PD values. Using AnaCredit – a granular dataset covering credit exposures from European banks between 2019 and 2022 – and financial statement data from Orbis, we constructed a sample of 4,649 publicly traded corporations, for which we computed the Beneish M-Scores that are used to detect potential earnings manipulation. This allowed us to determine the interrelation with PDs. Our results reveal a weak and negative correlation between M-Scores and PDs, suggesting that earnings manipulation signals are not fully absorbed by banks’ internal models. Further analysis shows that these results are driven by the high prevalence of firms with no earnings manipulation signals. Firms for which the M-Score effectively indicates potential earnings manipulation (8.9% of the sample) are observed to have higher PDs, which also increase further as the M-Score worsens. These findings support the hypothesis that earnings manipulation signals are not fully reflected in credit risk estimates over time, indicating that their impact – when it occurs – is deferred instead of being captured immediately in internal models. Our results indicate that the relationship between potential earnings manipulation and banks’ internal credit risk estimates is highly context-dependent and non-linear. Cross-sectional analyses by country and industry show consistent patterns linking default risk to M-Scores in selected countries and sectors. [...]
- JEL Code
- G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
M41 : Business Administration and Business Economics, Marketing, Accounting→Accounting and Auditing→Accounting
M42 : Business Administration and Business Economics, Marketing, Accounting→Accounting and Auditing→Auditing
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
- 2 April 2026
- WORKING PAPER SERIES - No. 3214Details
- Abstract
- Repo markets clear either bilaterally over the counter (OTC) or through central counterparties (CCPs), which differ in how counterparty risk is priced. In bilateral markets, repo rates reflect borrower-specific risk, while CCP clearing pools counterparties and applies a common pricing rule. We develop a model of security-driven repo in which repo rates are non-linear in borrower risk. As a result, averaging borrower-specific OTC prices yields more negative rates than pricing the pooled borrower in CCP markets. The model predicts that the CCP–OTC specialness gap compresses during periods of counterparty uncertainty and varies with borrower and collateral characteristics. Using transaction-level data from the euro-area interbank repo market around the March 2020 COVID-19 shock, we find evidence consistent with these predictions. Our results show that central clearing dampens specialness in normal times but stabilizes repo pricing during stress.
- JEL Code
- D47 : Microeconomics→Market Structure and Pricing→Market Design
D82 : Microeconomics→Information, Knowledge, and Uncertainty→Asymmetric and Private Information, Mechanism Design
G14 : Financial Economics→General Financial Markets→Information and Market Efficiency, Event Studies, Insider Trading
G15 : Financial Economics→General Financial Markets→International Financial Markets
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
Interest rates
| Deposit facility | 2.00 % |
| Main refinancing operations (fixed rate) | 2.15 % |
| Marginal lending facility | 2.40 % |
Inflation rate
More on inflationExchange rates
| USD | US dollar | 1.1733 | |
| JPY | Japanese yen | 186.81 | |
| GBP | Pound sterling | 0.86903 | |
| CHF | Swiss franc | 0.9175 |
Financial stability
Our tasks Institutional framework Financial Stability Review Macroprudential policy measuresMarket operations
Open market operations Asset purchase programmes Lendings of holdings under PSPPNOT AN EXPERT? CHECK OUT OUR EXPLAINERS
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