Welcome address by Philip R. Lane, Member of the Executive Board of the ECB, at the 5th WE_ARE_IN Macroeconomics and Finance Conference 2025
It is an honour to participate in the fifth edition of the WE_ARE_IN Macroeconomics and Finance Conference and I congratulate the organising committee for putting together an excellent programme.
Let me start this speech by outlining how the ECB makes monetary policy decisions.[1] I would like to thank Paola Di Casola, Matías Lamas Rodríguez, Johannes Pöschl, Tilman Bletzinger, Giulia Martorana, Jakub Mistak and Enrico Sette for their contributions to this speech.
See the updated ECB monetary policy strategy statement.
The Governing Council is determined to ensure that inflation stabilises at its 2% target in the medium term. It will follow a data-dependent and meeting-by-meeting approach to determining the appropriate monetary policy stance. In particular, the Governing Council's interest rate decisions will be based on its assessment of the inflation outlook and the risks surrounding it, in light of the incoming economic and financial data, as well as the dynamics of underlying inflation and the strength of monetary policy transmission. The Governing Council is not pre-committing to a particular rate path.
My aim today is to review one dimension of this multi-pronged assessment: how we assess the strength of monetary policy transmission. In what follows, I describe some of the analysis that has underpinned this assessment in recent monetary policy meetings.
I will begin by outlining the contribution of monetary policy to financial conditions before reviewing aggregate credit dynamics. Next, I will move to three key factors in determining monetary transmission: first, heterogeneity across member countries; second, the implications of a high level of uncertainty for monetary transmission; and third, the transmission impact of external factors, namely trade tensions and the exchange rate.
Between July 2022 and September 2023, the ECB raised interest rates from -50 basis points to 400 basis points.[3] The tightening of monetary policy also includes the contraction of the Eurosystem balance sheet through the end of asset purchases under the APP and PEPP and the end of the TLTRO III programme.
In capturing the impact of changes in policy rates on the wider financial environment, it is useful to assess blended measures such as financial conditions indices (FCIs), which synthesise the information from a variety of financial asset prices. As such, FCIs extend the concept of the monetary policy stance to a wider set of financial markets and beyond the level of accommodation or restrictiveness that is under the central bank's direct control. Akin to a stance measure, loose or tight financial conditions tend to stimulate or dampen economic activity, thus representing an upside or downside force acting on inflation.
Typically, FCIs combine - in a static manner that does not allow for feedback from the economy - a broad set of financial variables, including risk-free rates, sovereign and corporate spreads, equity valuations and exchange rates. It is a standard part of our assessment to study a range of FCI measures, including those developed at the ECB, international policy organisations and private-sector versions. Today, I will focus on a new addition to the family of FCI measures: a new "Macro-Finance" FCI that has been developed by ECB staff in order to overcome the "lack of feedback" problem. [4] The new FCI is estimated within a single macro-finance vector autoregression (VAR) model. See Bletzinger, T., Martorana, G., Mistak, J. (forthcoming), "Looser, Tighter, Clearer: a new Financial Conditions Index for the euro area", mimeo.
The new methodology incorporates mutual feedback between macroeconomic and financial dynamics, such that the Macro-Financial FCI reflects the joint dynamics of macroeconomic variables and financial conditions. As can be seen from the left panel of Chart 1, the overnight rate (€STR), which is closely tied to our policy rates, typically comoves with and sets the direction of the overall index. But there are also several phases in which financial conditions have moved even when the policy rate was stable (Chart 1, left panel).
The decomposition (Chart 1, middle panel) illustrates that, at the onset of the global financial crisis in 2008, plummeting risk asset prices (dark green area) turned from being a stimulative influence on the FCI to acting as a sudden and sharply tightening factor. The widening of sovereign bond spreads during the European debt crisis (light blue area) also provided extra restriction in the years around 2012. During the episode when policy rates were close to their lower bound, compressed long-term nominal rates and negative real interest rates were important sources of accommodation. As a result, the Macro-Finance FCI reached historically supportive levels in late 2021. It then climbed rapidly in the run-up to the first interest rate hike in July 2022, since the term structure of interest rates sequentially moved higher well ahead and in anticipation of our rate hikes and quantitative tightening.
Chart 1
A new "Macro-Finance Financial Conditions Index"
(percentages)

Source: Bletzinger T., Martorana, G. and Mistak, J. (forthcoming).
Notes: The left panel plots the Macro-Finance FCI alongside the €STR. The middle panel shows the index and its decomposition, with contributions estimated in a macro-finance model (Bletzinger, T. et al., forthcoming). The "Short rate" refers to the €STR, the "Long rate" to the ten-year nominal OIS rate, "Real rates" to the one-year real OIS rate in one year's time and the five-year real OIS rate, "Sov. spreads" to the two- and ten-year euro area GDP-weighted sovereign bond spreads over OIS rates, "Risk assets" to investment-grade corporate bond spreads and the CAPE ratio, and "Euro fx" to the NEER of the euro. The right panel compares the joint fit of euro area HICP inflation and the composite PMI when substituting the index with other measures in the model. The fit of the Macro-Finance FCI is normalised to 100, and the fit of the other models is expressed relative to that benchmark. The Goldman Sachs FCI refers to Stehn et al. (2019) and the weighted average FCI to Arrigoni et al. (2020). The principal component is the statistical factor that explains most of the variation among the financial market variables entering the Macro-Finance FCI.
The latest observations are for 17 October 2025.
In recent years, the Macro-Finance FCI peaked around the end of the 2022-23 monetary tightening cycle. The increase in the index during this period was primarily driven by rising risk-free rates, with adjustments in risk assets playing a more limited role. Since the peak of the tightening cycle, the index has indicated that financial conditions have become noticeably less restrictive, supported by lower short-term interest rates and higher valuations for risk assets, although this has been partly offset by a stronger euro.
Despite this easing, the level of the Macro-Finance FCI remains well above its historical sample average. In part, this can be attributed to a permanent component to the 2022 shift in the monetary policy stance: the re-anchoring of inflation expectations at the two per cent target means that markets do not expect a return to the "low for long" rate environment that had been expected before the pandemic to continue on an open-ended basis.
The new index outperforms other measures when it comes to describing the macroeconomic dynamics of the euro area (Chart 1, right panel). In this regard, it is key to understand that the financial prices and yields that are aggregated into the Macro-Finance FCI influence bank loan dynamics and loan pricing: this summary statistic of (mostly market-based) financial conditions can be interpreted as an important determinant of broader funding conditions, including those set by the banks, which can be collectively labelled as "financing conditions". In the next section, we turn to a review of credit dynamics.
Lending rates have been declining broadly in line with historical regularities (Chart 2). But there is a detectable difference between developments in the lending rates to households and to firms: the relatively muted decrease in long-term market rates has contained the decline in the cost of household loans, which tend to be priced off the longer end of the term structure of interest rates and have longer fixed-rate periods, relative to loans to enterprises. As outlined above, this is consistent with a permanent component in the 2022 upward shift in policy rates, with no return expected to the "low for long" zone.
Chart 2
Lending rates across hiking and easing cycles
(percentages per annum, series normalised at 0 in t, where t corresponds to the beginning of the policy hike)

Sources: ECB (MIR) and ECB calculations.
Notes: The ECB relevant policy rate is the lombard rate up to December 1998, the MRO up to May 2014 and the DFR thereafter. The chart reports differences with respect to June 1988, October 1999, November 2005, May 2022 in each of the two panels. Dates are selected as the first change in policy rates in a hiking cycle.
The latest observations are for August 2025.
In terms of credit volumes, household borrowing, primarily for home purchases, has increased steadily. According to the bank lending survey (BLS), the recovery in mortgage demand is supported by improved housing market prospects and lower interest rates (Chart 3, panel A). Corporate borrowing is also gradually recovering, though BLS responses suggest that corporate demand for credit remains subdued, also reflecting global uncertainty and trade tensions.[5] See the results of the latest bank lending survey. I delve more into the topic of uncertainty and external factors below.
This evidence raises the question of how credit is evolving compared to past regularities, given macroeconomic conditions and considering the current phase of the policy cycle. The strength of credit dynamics relative to the broader economy can be gauged through a credit-to-GDP gap analysis, which captures the deviation of the credit-to-GDP ratio from historical benchmarks.[6] The most known measure of credit-to-GDP gap is the Basel credit-to-GDP gap, introduced under Basel III as a common reference point to guide decisions on banks' countercyclical capital buffers. The methodology for its calculation is defined in Borio, C. and Lowe, P. (2002), "Asset prices, financial and monetary stability: exploring the nexus", BIS Working Paper, No 114.
The analysis relies on other univariate filtering techniques suggested by the literature, apart from the use suggested by BIS, and multivariate models, as well as different types of credit data.
A number of structural shifts have been cited to explain a diminished role of credit in advanced economies. For example, households spend less on durable goods and more on services, for which they do not typically need to borrow. Demographic trends can reinforce these trends and explain why mortgages might be in lower demand than in the past. Also, spending on intangible assets - including intellectual property, software and code - has surpassed tangible investments as a share of GDP in major economies since the global financial crisis. And intangibles tend to be financed using internal funds or equity, being harder to pledge as collateral for loans. Even the AI-related investment boom in physical infrastructure, including data centres, has been primarily financed by equity.
But such structural shifts matter less for the euro area than for other economies, which leaves the effects of the previous tightening cycle as an important candidate explanation for the persistent weakness in credit that we observe today.[8] See the discussion in Kamps, C. et al. (2025), "Report on monetary policy tools, strategy and communication", Occasional Paper Series, No 372, ECB.
Chart 3
Credit dynamics
Changes in demand for loans to firms and households |
Credit-to-GDP gap across univariate filters and multivariate model-based approaches |
---|---|
(net percentages of banks reporting an increase in demand) |
(percentages of GDP) |
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Sources: Left panel: ECB (Bank Lending Survey). Right panel: BIS, ECB and ECB calculations.
Notes: Left panel: the indicators report net percentages for the questions on demand for loans, defined as the difference between the sum of the percentages of banks responding "increased considerably" and "increased somewhat" and the sum of the percentages of banks responding "decreased somewhat" and "decreased considerably". The indicator for households refers to loans for house purchases. Right panel: the shaded area reports the range of gap estimates across an ensemble of methods and definitions of total credit, using univariate filtering techniques and multivariate models.
The latest observations are the second quarter of 2025 (July 2025 BLS) for the left panel and the first quarter of 2025 for the right panel.
A range of other factors that are not unrelated to the cycle may also help explain why the credit gap indicators remain negative. Heightened risk perceptions and higher bank funding costs, combined with declining excess liquidity, have played a role. In addition, pressures from supervisory and regulatory requirements to maintain solid balance sheets amid rising uncertainties, alongside the goal of supporting financial stability, have kept credit standards tight through the cycle, even as monetary policy has been eased in recent quarters. At the same time, financing from non-bank lenders has remained contained since the start of the monetary policy tightening, despite their secular increasing role in funding the real economy.
Looking in more detail at the sources of external financing for firms other than borrowing from banks, corporate bond issuance has benefited from foreign inflows into euro area bond funds in recent quarters, amid a shift in investor cross-border funds in favour of the euro area. Non-listed equities have also increased recently, likely reflecting activities of private equity funds. One segment of non-bank financing that has been growing significantly in recent years is private credit. Private credit generally refers to non-bank corporate credit provided through bilateral agreements or small "club deals" involving lenders outside the realm of securities investors or commercial banks. Despite a clear expansion in the euro area over recent years, the lion's share of private credit is originated in the United States.[9] See Avalos, F., Doerr, S. and Pinter, G. (2025), "The global drivers of private credit," BIS Quarterly Review, March for one part of the range. What distinguishes private credit in Europe from the one in the United States is the reliance on equity financing, rather than debt financing, and the competition with banks, rather than the reliance on bank financing. See Block, J., Jang, Y.S., Kaplan, S. and Schulze, A. (2024), "A survey of private debt funds", Review of Corporate Finance Studies, Vol. 13, No 2, pp. 335-83 for a survey comparing the US and European market and Acharya, V., Cetorelli, N. and Tuckman, B. (2024), "Where Do Banks End and NBFIs Begin?", CEPR Discussion Paper, No 18939 for the analysis on the linkages between banks and non-banks in the United States. European banking supervision is monitoring risks coming from banks' exposure to non-bank financing, see Buch, C. (2025), "Hidden leverage and blind spots: addressing banks' exposures to private market funds", The Supervision Blog, 3 June.
These estimates are based on market data sources, which might underestimate the real size of the private credit market, while aggregate unconsolidated statistics from national accounts do not disentangle private credit exactly from all non-bank financing.
Taken together, non-bank financing has not grown enough to counteract the weakness in bank lending. The dynamics of all the sources of external finance for euro area firms, including equity financing, but also trade credit and non-bank financing, remain contained by historical standards (Chart 4), hence overall measures of the credit gap, as shown in Chart 3, remain negative.
On net, the ongoing transmission of monetary policy easing to credit volumes has been more gradual than anticipated building on past regularities. Equally unusual has been the pronounced heterogeneity across sectors and across borrower characteristics, which I will discuss next.
Chart 4
Firms' external financing over time
(annual percentage change and percentage point contributions)

Sources: ECB (QSA, BSI, FVC), Eurostat and ECB calculations.
Notes: MFI loans are corrected for cash polling, loan sales and securitisation. Loans from non-MFIs are corrected for securitisation and they comprise loans from insurance corporations and pension funds (ICPFs) and other financial intermediaries (OFIs). "Other" is the difference between the total and the instruments singled out in the chart; it includes loans from general government, inter-company loans, financial derivatives (net) and other accounts payable other than trade credits.
The latest observations are for the first quarter of 2025.
Heterogeneity in the transmission of monetary policy can affect its overall macroeconomic impact. Differences in sectoral balance sheets and sectoral exposures to macroeconomic shocks can influence the responses of households, firms and banks to changes in financing conditions.[11] Here, I will not discuss heterogeneity of monetary policy transmission relating to sovereign bond yields. I discussed those issues in Lane, P.R. (2024), "The Analytics of the Monetary Policy Tightening Cycle", speech at Stanford Graduate School of Business, 2 May, Stanford and Lane, P.R., (2024), "Macroeconomics of Sovereign Debt", speech at the Bank of Greece Conference on Public Debt: Past Lessons, Future Challenges, 7 November.
For instance, the growth rate of loans to the manufacturing sector, although recently supported by the surge in activity due to frontloading of euro area shipments to the United States, has been weaker than that of loans to the services sector (Chart 5, Panel A).[12] See Meinen, P. (2019), "The effects of tariff hikes in a world of global value chains", Economic Bulletin, Issue 8, ECB.
Chart 5
Heterogeneous credit dynamics across sectors and type of firm
Loans to firms by sector |
Lending by firm size and riskiness |
---|---|
(left panel: index = 0 for January 2024, right panel: percentages per annum) |
(left panel: index = 0 for January 2024, right panel: annual percentage changes) |
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Sources: ECB (ECS, RIAD, BSI, AnaCredit) and ECB calculations.
Notes: Left panel: in the left-hand side chart, the super-sectors are identified from the following NACE sectors: Manufacturing (C), Services (G, H, I, J, L, M, N O, P, Q, R, S, T, U). The industry survey is sourced from ECS and represents the production trend observed in recent three months, while the services production is sourced from STS. The series for the loans to firms in the manufacturing sector and for the industry survey have been smoothed using a three-month moving average. The right-hand side chart represents the growth contribution of selected sectors for April 2025. Right panel: the left-hand side chart represents the index (January 2024 = 0) of the stock of loans by size. Company sizes are defined as small for 50 employees or less, medium for 51 to 250 employees, and large above 250 employees. In the right-hand side chart, loan growth by PD group has been rescaled to match BSI aggregates and purged from PD migrations. High (resp. low) risk firms are those with a PD above (resp. below) 1.6%, the third quartile of PD in lending flows.
The latest observations are for May 2025 for AnaCredit, July 2025 for ECS.
At the firm level, credit growth is increasingly concentrated among larger and less risky firms (Chart 5, panel B). Results from the survey on the access to finance of enterprises (SAFE) confirm that small firms have experienced a more muted decline in external financing costs than larger producers. This points to contained transmission via the balance sheet channel and the risk-taking channel of monetary policy. Smaller firms, being more vulnerable to current macroeconomic risks, have therefore suffered sharper balance sheet losses. At the same time, banks have been more reluctant to extend credit to riskier borrowers.[13] Altavilla, C., Gürkaynak, R.S., and Quadvlieg, R. (2024), "Macro and Micro of External Finance Premium and Monetary Policy Transmission", Journal of Monetary Economics, Vol. 147 show that the transmission of monetary policy to smaller firms in the euro area depends on the effect of monetary policy on the external finance premium. For other studies on the heterogeneous effect of euro area monetary policy on banks, see Altavilla, C., Boucinha, M., Holton, S., and Ongena, S. (2021), "Credit Supply and Demand in Unconventional Times", Journal of Money, Credit and Banking, Vol. 53, Issue 8 and Altavilla, C., Canova, F., and Ciccarelli, M. (2020), "Mending the Broken Link: Heterogeneous Bank Lending Rates and Monetary Policy Pass-through", Journal of Monetary Economics, Vol. 110.
See Greenwald, D.L., Krainer, J., Pascal, P. (2025), "The Credit Line Channel", The Journal of Finance, August.
Chart 6
Heterogeneous monetary policy pass-through in mortgage and housing markets
Growth momentum of bank loans to households by country |
Changes in new mortgage applications by households by income quintile |
---|---|
(percentages per annum) |
(percentage points) |
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Sources: ECB (BSI, CES) and ECB calculations.
Notes: Left panel: momentum is defined by the difference between the (3m-o-3m annualised) and the annual growth rate. Right panel: The chart reports the percentage point change in the share of households that applied for mortgages relative to before the monetary policy tightening, broken down by income quintile. Income quintiles are computed over the weighted distributions of the variable at the country level and by wave.
The latest observations are for August 2025 for the left panel and July 2025 for the right panel.
Household loan dynamics have also shown dispersion across countries, highlighting the role of both the collateral and cash-flow channels in monetary transmission during the tightening and easing phases of the cycle (Chart 6, panel A). Differences in national mortgage markets are a key factor, reflecting institutional features such as the share of adjustable-rate mortgages (ARMs) and their maturities.[15] The role of financial structure in the transmission of a European monetary policy is, incidentally, a topic that is as old as the ECB, going back at least to the discussion of "a number of issues for the newly constituted Board of the ECB" by Dornbusch, R. et al. (1998). See Dornbusch, R., Favero, Carlo A., and Giavazzi, F. (1998), "The Immediate Challenges for the European Central Bank", NBER Working Paper, No 6396.
Badarinza, C., Campbell, J.Y., and Ramadorai, T. (2018), "What Calls to ARMs? International Evidence on Interest Rates and the Choice of Adjustable-Rate Mortgages, Management Science, Vol. 64, No 5 show that the share of adjustable-rate mortgages varies widely across countries, and systematically responds to changes in interest rates. Garriga, C., Kydland, F.E., and Sustek, R. (2017), "Mortgages and Monetary Policy", The Review of Financial Studies, Vol. 30, No 10 show the importance of interest rate fixation for monetary policy transmission. See also Corsetti, G., Duarte, J.B., and Mann, S. (2021), "One Money, Many Markets", Journal of the European Economic Association, Vol. 20, Issue 1.
Indeed, over the past two decades, floating-rate mortgages - which are more reactive to the policy rates - have become less popular in the major euro area economies. The shift in the types of mortgages means monetary policy takes longer to work its way into households' debt payments. This delay in transmission means that, despite recent rate cuts, average mortgage rates are expected to rise further and drag on consumption for a number of years to come as households remortgage on to higher rates after completing long-term fixed deals.[17]
See Baptista, P., Dossche, M., Hannon, A., Henricot, D., Kouvavas, O., Malacrino, D., and Zimmermann, L. (2025), "The transmission of monetary policy: from mortgage rates to consumption", Economic Bulletin, Issue 4, ECB, for an elaboration on this point.
Moreover, through the collateral channel, recent interest rate cuts have pushed up asset values more in countries with high ARM shares, thereby boosting collateral values.
After a period of declining mortgage applications during the tightening period, mortgage applications have started to increase in recent quarters. Higher income households, however, have maintained lower mortgage applications compared to the pre-tightening period (Chart 6, panel B). Instead, mortgage application growth has come mostly from lower-income households, possibly reflecting the need to maintain consumption or housing purchase plans in spite of declining real wages and with less savings, especially if they spend a large share of their income on basic goods. Thus, we see a shift in the composition of mortgage demand.[18] Of course, it is also important to take into account that the success rate for mortgage applications is lower for lower-income households.
Summing up, the change in borrower composition and the muted risk appetite of banks point towards the risk-taking and balance sheet channels of monetary policy operating less strongly for lower-income households and smaller firms during the easing cycle. Since these groups typically have higher marginal propensities to consume and invest, this heterogeneity in transmission may reduce the effectiveness of recent interest rate cuts in stimulating aggregate demand in the current context of high global uncertainty.[19] Crawley, E. and Kuchler, A. (2023), "Consumption Heterogeneity: Micro Drivers and Macro Implications", American Economic Journal: Macroeconomics, Vol. 15, No 1 show that households with low liquidity have higher MPCs.
An important factor that may distort and at times suppress the transmission of monetary policy is uncertainty. Over the past year, economic policy uncertainty has risen sharply, reaching record levels in April, largely driven by trade tensions and geopolitical risks (Chart 7, left panel). Financial market volatility has, instead, remained subdued (Chart 7, right panel). While uncertainty has eased somewhat in recent months, it remains at historically high levels on both sides of the Atlantic according to newspaper-based measures, close to the peak seen during the COVID-19 pandemic.
Monitoring elevated uncertainty is crucial in analysing credit dynamics for two main reasons.
First, it directly lowers credit demand and credit supply. ECB staff finds that unexpected increases in economic policy uncertainty have a negative effect on bank lending in the euro area.[20] See Allayioti, A., Bozzelli, G., Di Casola, P., Mendicino, C., Skoblar, A. and Velasco, S. (2025), "More uncertainty, less lending: how US policy affects firm financing in Europe", The ECB Blog, 2 October. For evidence on the effect of uncertainty on monetary policy transmission to inflation and unemployment, see Falconio, A. and Schumacher, J. (2025), "Economic uncertainty weakens monetary policy transmission", The ECB Blog, 1 September.