The debt situation in the euro area private non-financial sector since the start of monetary policy tightening Monthly Report – April 2025

Article from the Monthly Report

This article uses a wide range of different indicators to describe developments in the debt situation of the euro area’s private non-financial sector since the start of the most recent monetary policy tightening phase.

The monetary policy measures taken in response to the inflation environment left their mark on the balance sheets of the private non-financial sector in the euro area. Significant interest rate hikes caused increases in certain variables, particularly those that are sensitive to interest rates such as interest expenditure and debt service. In spite of that, the debt situation in the private non-financial sector did not fundamentally deteriorate overall. In particular, higher nominal incomes had an alleviating effect.

From a monetary policy perspective, one reason for analysing the debt situation is to identify potential debt-induced balance sheet constraints among non-financial corporations or households. Such restrictions can change these actors’ spending behaviour so much that they amplify the effect of monetary policy. However, current and expected developments in the debt situation of the private non-financial sector do not indicate extensive balance sheet constraints. The results therefore suggest that debt did not amplify monetary policy transmission and is unlikely to amplify it in the near future.

From a central bank perspective, it is necessary to continuously monitor developments in the debt situation. This will enable us to identify associated changes in monetary policy transmission in good time and, where appropriate, to take them into account when calibrating the monetary policy stance. The debt indicators presented in this article can play a key role in this.
  

1 Introduction

Interest rate-sensitive debt indicators have responded in line with expectations since the start of monetary policy tightening. When inflation began to surge in 2021, the Eurosystem responded by tightening monetary policy sharply. This episode left a mark on the balance sheets of the private non-financial sector in the euro area. This suggests that, taken in isolation, the higher interest rates as a result of the Eurosystem’s restrictive monetary policy primarily entailed greater financial burdens for the private non-financial sector in the form of higher interest expenditure and higher debt service. 

Analysing the debt situation in the private non-financial sector can provide valuable insights for monetary policy. Current research indicates that the impact of monetary policy could be amplified if broad-based balance sheet constraints among non-financial corporations and households are reflected in deteriorating debt indicators. 1 With that in mind, it is of particular interest to a central bank to continuously monitor developments in the debt situation of the private non-financial sector. This would make it possible to identify potential consequences for the transmission of monetary policy in good time and, where appropriate, to take them into account when calibrating the monetary policy stance. 2

Multiple indicators need to be used to identify developments in the debt situation that are relevant for monetary policy. This article offers a detailed analysis of how the debt situation of the private non-financial sector in the euro area has evolved since the start of monetary policy tightening. The analysis draws on a wide range of debt indicators. 3 This allows for a broad and differentiated assessment of the debt situation and reduces the risk of relevant developments being overlooked. On this basis, the article examines whether the debt situation in the euro area may have tended to amplify the effect of monetary policy impulses. It also makes a forward-looking assessment on this. Overall, the findings are as follows:

  • Although some debt indicators increased occasionally, the debt situation has not deteriorated significantly since the start of the most recent tightening cycle. Interest rate-sensitive debt indicators, in particular, have recently signalled greater burdens, but ... 

  • ... the higher interest burdens were more than offset by nominally higher incomes.

  • The private non-financial sector is not expected to adjust its spending behaviour any more strongly in response to monetary policy impulses on the basis of current debt developments and those expected in the medium term, which is one reason why …

  • … monetary policy transmission is unlikely to have changed, nor is there likely to be any debt-induced change in the medium term.

2 Balance sheet constraints and monetary policy transmission

Balance sheet constraints can limit the financial flexibility of households and non-financial corporations. The balance sheet situation of households and non-financial corporations largely determines their financial scope for consumption and investment decisions. If their balance sheet situation means they no longer have unrestricted access to financial resources to even out fluctuations in income, for example, they are described as having balance sheet constraints. The balance sheet situation of households and non-financial corporations therefore plays a key role in their consumption and investment decisions. 

Balance sheet constraints can occur in various forms. Balance sheet constraints are financial limitations and can take the form of a lack of liquidity buffers or more difficult access to external financing, for example. 4 In particular, access to external financing is influenced by the level of household income or corporate earnings as well as the value of additional loan collateral – such as real estate or securities – in relation to debt. In addition, financial resilience also plays an important role in this context. 5 This is the ability of borrowers to avoid payment defaults. Typically, the lower the borrower’s financial resilience, the more lenders increase their risk premia – after monetary policy tightening, for example – as lenders consider payment defaults to be more probable in such a situation. 6 Equally, lenders place higher requirements on loan collateral in order to reduce losses in the event of default. The resulting higher interest burdens and tighter loan-to-value ratios, in turn, impair borrowers' creditworthiness and thus their ability to take out new loans or to refinance. During a monetary policy tightening phase, in particular, it is possible for the debt situation of non-financial corporations and households to deteriorate so sharply – for example, due to a higher interest burden – that balance sheet constraints arise or existing limitations are amplified.

Debt-induced balance sheet constraints can amplify the effect of monetary policy tightening. 7 If balance sheet constraints make financing more difficult for households and non-financial corporations, this has implications for monetary policy transmission. Actors facing balance sheet constraints typically have spending that is comparatively sensitive to income changes. 8 Faced with a lack of liquid funds and/or limited access to external financing, these actors reduce their consumption and investment expenditure – after monetary policy interest rate hikes, say – more than unconstrained actors. 9 This can amplify the dampening of aggregate demand as a result of the interest rate hike. 10

Balance sheet constraints can also amplify the effect of monetary policy easing. Monetary policy also influences balance sheet constraints via its impact on asset prices and incomes. When monetary policy is expansionary, rising incomes and asset prices ease existing balance sheet constraints. This gives actors the scope for additional borrowing and thus spending that had previously been forgone. When monetary policy is restrictive, spending has to be limited because of balance sheet constraints. In both cases, the existence of balance sheet constraints amplifies the effect of monetary policy impulses.

Viewed in isolation, the degree of balance sheet constraints in the private non-financial sector changes over the monetary policy cycle. Considered alone, key interest rate hikes during monetary policy tightening lead to a gradual increase in balance sheet constraints, mainly via higher interest burdens. Given the relationships presented here, this is likely to gradually amplify the transmission of monetary policy measures to consumption and investment expenditure in the private non-financial sector. In light of the above, a subsequent phase of monetary policy easing is likely to then reduce the degree of balance sheet constraints again. This also gradually diminishes the amplifying effect of balance sheet constraints on monetary policy measures. 11 The strength of transmission thus fluctuates over the monetary policy cycle. However, this statement refers exclusively to the isolated effect of monetary policy measures on balance sheet debt and thus the strength of transmission. In reality, this effect can be overshadowed by the impact of other developments. This is particularly true of the path of inflation, which monetary policy measures respond to. Inflation also, for example, plays a key role in how nominal incomes develop, out of which debt service is paid.

Balance sheet constraints amplify the effect of monetary policy measures particularly when there are high levels of debt in the private non-financial sector. Overall, the literature suggests that monetary policy impulses are associated with greater effectiveness when balance sheet constraints restrict the spending decisions of the relevant actors. This is most likely to be the case when debt and the associated interest and principal payments are already high relative to income, wealth or liquid assets. 12 It is thus important for central banks, in particular, to regularly review the possible extent of balance sheet constraints, not least in view of any necessary calibration of the monetary policy stance. 

3 Recent developments in the debt situation of the private non-financial sector

A wide range of indicators have to be considered for a comprehensive overall assessment of the debt situation. Generally speaking, the debt situation cannot be sufficiently described using a single indicator. A single indicator typically focuses on just one selected sub-aspect. A low liquidity position can indicate difficulties in meeting short-term payment obligations, for example. However, when it coincides with a low debt level, it may prove to be less of a concern as low total debt tends to imply additional scope for borrowing. Below, the debt situation of the private non-financial sector is therefore examined using several indicators. First, there are income-based metrics, such as the ratio of debt to gross domestic product. Second, there are indicators based on balance sheet metrics. The analysis covers both non-financial corporations and households across the euro area. In addition, the four largest Member States – Germany, France, Italy and Spain – are also considered separately.

The debt indicators are based on sectoral data. The metrics for debt are calculated using data from the financial accounts and national accounts. 13 More precisely, the indicators represent macroeconomic aggregates for the two separately analysed sectors of non-financial corporations and households. 14 The debt of non-financial corporations generally consists of consolidated loans, 15 debt securities, pension provisions and trade credits. Household debt is confined to loans, by contrast. Specifically, the following indicators are analysed: 

  • Debt ratio: The debt ratio expresses debt relative to a sectoral income indicator. An increase in this ratio indicates that debt has risen relative to income. Taken in isolation, this reduces debt sustainability over the medium term. For non-financial corporations, gross value added is used as the income indicator. For households, by contrast, the calculation is based on (gross) disposable income. When defining debt, a distinction is made between gross debt and net debt (gross debt less any highly liquid assets) for non-financial corporations.

  • Leverage ratio: The leverage ratio expresses debt capital relative to the total assets of non-financial corporations or households. 16 In contrast to the debt ratio, which only considers liabilities-side constraints, this indicator also establishes a link to the assets side. This appears useful given that the literature shows that small holdings of (liquid) assets can also constitute a balance sheet constraint. 17 A higher indicator value signals that debt has lower asset coverage. This increases the risk that the proceeds raised by liquidating the assets might not suffice to repay the debt. In turn, this reduces long-term debt sustainability.

  • Liquidity ratio: The liquidity ratio expresses liquid assets relative to total assets. A low liquidity ratio may indicate difficulties in meeting short-term payment obligations. This may mean a lesser ability to settle direct payment obligations by reducing liquidity reserves.

  • Debt service ratio: The debt service ratio is the sum of interest and principal payments as a percentage of disposable income. 18 A higher debt service ratio indicates a lesser ability to settle due payment obligations out of current income. Viewed in isolation, this increases the risk of short-term payment defaults. This indicator is also especially interesting for monetary policy because interest payments are directly influenced by the interest rate environment and thus by monetary policy.

  • Interest expenditure ratio: The interest expenditure ratio describes the interest expenditure of non-financial corporations or households in relation to an income variable. In the case of non-financial corporations, the gross operating surplus is considered for this purpose. The metric thus provides information on the extent to which operating profit is offset by interest expenditure. In the case of households, (gross) disposable income is used. In addition, the net interest expenditure ratio is also considered. Here, interest expenditure is adjusted for interest income. An increase in both indicators points to an increased burden from (net) interest expenditure at a given income level. Like the debt service ratio, this indicator is also directly affected by the interest rate environment and thus by monetary policy.

This article discusses the significance of macroeconomic debt indicators for monetary policy transmission. Heterogeneous developments within a sector are not taken into account. This means that developments emanating from individual actors may be over- or understated. 19 It may therefore be necessary to supplement the aggregate view with disaggregated information in order to obtain a more complete picture. 

3.1 Debt indicators for the non-financial corporate sector

Chart 4.1 shows the development of the debt indicators between end-2021 and the close of the third quarter of 2024 for non-financial corporations as well as the contributions made by the individual components. The analysis covers the period from the start of monetary policy tightening to the current data end. 20 The lower part of the chart depicts developments in the individual indicators over time since 2000. For all the metrics except the liquidity ratio, a higher level is indicative of a worse debt situation.

Debt indicators of the euro area non-financial corporate sector*
Debt indicators of the euro area non-financial corporate sector*

The debt ratio of non-financial corporations has fallen overall since the end of 2021, mainly on account of general nominal increases in income. On aggregate, non-financial corporations in the euro area have increased their debt levels only slightly since the end of 2021. While debt continued to build up in Germany and France, in particular, non-financial corporations reduced their debt in Spain and, in part, also in Italy. Notwithstanding the overall build-up of debt, the debt ratio declined markedly over the entire period. The main driver of this development was the significant nominal rise in income in the wake of the economic recovery that followed the coronavirus pandemic. A similar picture can be seen with regard to the leverage ratio. The increase in debt capital was lower than the increase in total assets, which, taken in isolation, improved the long-term sustainability of debt. 

Following pandemic-related increases, the liquidity ratios of non-financial corporations are broadly in line with the pre-coronavirus trend once more. While the liquidity ratio declined in the euro area as a whole as well as in France and Italy individually – driven in particular by growth in the other asset components – it increased in Germany and Spain. In all cases, this was preceded by a significant increase in these ratios in the context of the coronavirus pandemic. Non-financial corporations built up buffers against any liquidity shortages by substantially increasing their holdings of liquid assets. However, as monetary policy tightened and the associated opportunity costs of holding money increased, liquidity ratios gradually declined again. They are currently approximating pre-coronavirus trend developments once more. 21

In particular, interest rate-sensitive debt indicators of non-financial corporations deteriorated in the context of monetary policy tightening. The restrictive monetary policy measures implemented in response to higher inflation contributed to a rising interest rate level. This significantly increased interest expenditure across all countries: interest expenditure ratios in each of the four countries and in the euro area as a whole rose markedly as monetary policy was tightened. Developments in France were especially pronounced. 22 Taking into account the simultaneous rise in interest income, however, the increased burdens resulting from higher interest expenditure were markedly lower on balance. 23 Ultimately, this development also had an impact on debt service ratios, with increased debt service ratios being observed in Germany and France, in particular. Rising interest burdens have been offset by consistently significant nominal income growth recently, which, taken in isolation, has bolstered debt sustainability. 

3.2 Debt indicators for the household sector

For households, debt ratios fell significantly across all countries (see Chart 4.2). The debt ratio dynamic was primarily driven by steep increases in household income, which also more than offset rising debt; only in Spain did debt additionally fall in absolute terms. That said, the overall moderate household debt dynamic since end-2021 must definitely also be viewed against the backdrop of monetary policy-induced interest rate hikes up to mid-2023. The increased interest rate level is likely to have dampened demand for loans and thus the rise in debt, too. With regard to household leverage ratios, the euro area and Germany, Spain and Italy tended to see similar developments over the period under review. This was partly a result of the acquisition of financial and non-financial assets and partly due to valuation gains on assets. In France, by contrast, the leverage ratio increased, mainly owing to negative valuation effects – on debt securities held indirectly via life insurance policies, inter alia – dampening the increase in total assets.

In some cases, households’ liquidity ratios are continuing to rise significantly. As was the case with non-financial corporations, the liquidity ratios of households developed inconsistently between countries. While they continued to increase in the euro area as a whole and, above all, in Germany and France, they declined in Italy and remained virtually unchanged on balance in Spain. In the case of households, these ratios had previously increased significantly due to the pandemic. This was primarily due to restricted opportunities for consumption, which ultimately generated additional savings, most of which were held in the form of liquid deposits. 24 Although this development began to normalise somewhat after the pandemic, liquid assets in the euro area as a whole recorded rather high inflows in some cases. Despite strong income growth of late, households sometimes remained cautious in their consumption decisions, which meant that household savings and thus liquid forms of investment, too, gained in importance again. 25

Debt indicators of the euro area household sector*
Debt indicators of the euro area household sector*

Increased interest income had a noticeable countereffect on higher interest expenditure. Household interest expenditure ratios rose markedly in the euro area as a whole and in the four individual countries. Developments in France were especially pronounced. The higher interest rate level resulting from monetary policy tightening increased interest expenditure across all countries. However, comparing the increased interest expenditure with the also increased interest income, households benefited in net terms, from a macroeconomic perspective. Only households in Spain were subject to higher interest expenditure, even taking into account higher interest income. The higher interest burdens in Spain are likely to be due, above all, to the comparatively high importance of floating rate loans. 26 A rising interest rate level thus tended to have a faster impact on households’ aggregate interest expenditure. Additionally, it can be seen that debt service ratios improved in the euro area as well as in Germany, Spain and France. In Italy, the debt service ratio remained virtually unchanged at a very low level. The overall positive development in the period under review was mainly attributable to significantly higher income, which more than offset the higher interest and redemption payments.

Macroeconomic developments can have a very varied impact at the level of individual households. Liquidity-constrained households, in particular, are exposed to negative interest rate risk, as they typically have negative interest rate-sensitive net wealth. The corresponding interest rate risk of non-liquidity-constrained households, by contrast, is positive on average. Taken in isolation, these differences ultimately imply that, in the event of an interest rate increase, liquidity-constrained households, also known as hand-to-mouth households, are primarily affected by rising interest expenditure; non-hand-to-mouth households, on the contrary, tend to have rising interest income. Against this background, it should therefore be noted that analyses based on macroeconomic time series can only paint a partial picture. It is thus helpful to supplement these with micro-based analyses – including, for example, the distributional wealth accounts. 27  

4 Quantifying the risks of debt-induced balance sheet constraints

Taken in isolation, the level of the debt indicators does not show any direct balance sheet constraints; critical thresholds are required for this. Adequate conclusions cannot be drawn with regard to the risks of balance sheet constraints by looking at individual debt indicators in isolation and following their developments over time. It is thus impossible to draw direct conclusions about debt-induced balance sheet constraints, either at certain points in time or overall, based on the individual values of the debt indicators. Rather, comparative figures are required for this. Local projections for a panel of the four largest euro area countries are therefore used to determine the level of private non-financial sector debt above which a stronger transmission of monetary policy is expected, in line with the conceptual considerations outlined above. 28 To this end, the response of households’ consumption and non-financial corporations’ investment is conditioned on the levels of various debt indicators. 29 Country-specific critical thresholds are ultimately determined in this manner for all debt indicators under consideration, with a stronger transmission of monetary policy measures being identified where these thresholds are exceeded. 30 By definition, if a debt indicator is higher than the calculated threshold, a sector is in a state in which balance sheet constraints have reached a level that significantly changes the expenditure behaviour of the sector in question. If the values are below the threshold, however, the sector is in a state without such constraints.

At present and during the projection horizon, the individual indicators do not on the whole point to balance sheet constraints that significantly change spending behaviour. Chart 4.3 illustrates the analysis of the risks of debt-induced balance sheet constraints for the euro area. In order to better compare the dynamics of individual debt indicators, the range of values was standardised based on the empirical distribution. The individual values of an indicator were normalised to a value range between 0 and 100 based on the empirical cumulative density function. 31 The points indicate the deviation from the respective sectoral threshold value, measured in percentiles. Values to the right of the vertical zero line therefore indicate possible balance sheet constraints. With few exceptions, the values for all debt indicators considered are significantly below the determined thresholds. For non-financial corporations, only the interest expenditure ratio, which is just below its threshold, points to potential debt-induced balance sheet constraints. This is attributable to the significant increase in interest expenditure as a result of the monetary policy tightening since Q4 2021. It is particularly striking that the debt ratio is now well below its threshold again. This is due to the fact that non-financial corporations’ debt grew only slightly since the start of the tightening, but gross value added rose markedly, especially towards the end of the pandemic. For households, too, the gap to the debt ratio threshold has increased significantly. Here, nominal incomes rose sharply in the context of high inflation rates, while nominal debt grew only slightly over the same period. At the end of 2021, households’ net interest expenditure ratio was still well above the critical threshold. However, the significant increase in household interest income observed since then more than offset the increased interest burdens, meaning that the net interest expenditure ratio is likely to be markedly below the critical threshold both at the current end and, according to Bundesbank projections, up to the end of 2027. 32

Debt-induced balance sheet constraints of the private non-financial sector in the euro area*
Debt-induced balance sheet constraints of the private non-financial sector in the euro area*

A composite indicator provides an overview of the relevance of balance sheet constraints. While a comprehensive assessment of the debt situation requires a multitude of debt indicators to be taken into account, doing so also makes it more difficult to derive an overall picture. An indicator that summarises the results of the individual debt indicators can therefore be a helpful addition to the overall picture. Such an indicator thus provides an immediate overview of the importance of balance sheet constraints stemming from the debt situation of the private non-financial sector.

The composite indicator is calculated as the share of debt indicators that point to balance sheet constraints. For both non-financial corporations and households, it is calculated for each point in time whether the values of the debt indicators under consideration are above the previously derived critical thresholds: indicators that are above the thresholds are assigned a one and the others assigned a zero. The composite indicator thus represents, across all countries and indicators, the unweighted share of debt indicators that point to balance sheet constraints. The higher the share of indicators pointing to balance sheet constraints, the more likely it is that monetary policy transmission will have an amplified effect. In addition to a retrospective analysis, the projections also allow for a forward-looking assessment. One drawback of the composite indicator is that all debt indicators across all countries are included with an equal weighting. This may result in the loss of important information – such as particularly sharp increases in individual indicators. Looking at the composite indicator alone therefore cannot replace an analysis of the individual indicators, but serves, above all, to obtain an initial overall impression. It can also be used more easily than the numerous individual indicators in further empirical analyses.

The composite indicator points to balance sheet constraints above all during the global financial and economic crisis and the European debt crisis. Chart 4.4 shows the indicator for the private non-financial sector as a whole as well as for non-financial corporations and households. It can be seen here that the composite indicators, broken down by sector, show a high degree of co-movement. The peaks were reached during the global financial and economic crisis and the European debt crisis. During this period, slightly more than 60% of all indicators were above critical thresholds for the private non-financial sector as a whole. Subsequently, by contrast, a significant decline was observed up to the outbreak of the coronavirus pandemic. This is due to the fact that both households and non-financial corporations went through a period of deleveraging following the European debt crisis and, additionally, interest burdens were lowered as a result of interest rate cuts. 33

Debt indicators in the euro area that point to balance sheet constraints*
Debt indicators in the euro area that point to balance sheet constraints*

From a forward-looking perspective, too, the composite indicator does not currently point to a debt-induced amplification of monetary policy transmission. The level of the composite debt indicator (black line) shown in Chart 4.4 does not point to balance sheet constraints that could amplify monetary policy transmission, either at the current end or over the projection horizon. Nevertheless, slight sectoral differences are observable over the projection horizon. The debt situation of euro area households, in particular, appears to be largely inconspicuous. Among non-financial corporations, elevated burdens in relation to the interest expenditure ratio and debt service ratio are observable in some cases.

In general, monetary policy impulses have a stronger impact on balance sheet constrained households and non-financial corporations. By condensing the information from the overall view, the composite indicator is suitable for econometric purposes. For example, it can be used to check whether a higher degree of balance sheet constraints is generally associated with stronger monetary policy transmission (see the supplementary information on local projections for estimating non-linear effects ). To this end, a monetary policy impulse is interacted with the composite indicator using local projections for a panel dataset of the four largest euro area countries. In this case, the overall response is non-linear and depends on the level of the composite indicator. Chart 4.5 shows the stylised average responses over twelve quarters of households’ consumption expenditure and of non-financial corporations’ investment expenditure to a monetary policy impulse. The grey bars refer to the average responses where the sector under review is not, on aggregate, balance sheet constrained. This is the case when the composite indicator has a value of zero. By contrast, the blue bars show the average responses where households and non-financial corporations are significantly balance sheet constrained. 34 Taking into account the extent of balance sheet constraints, the results reflect the following responses: In an environment of broad-based balance sheet constraints, non-financial corporations and households reduce their expenditure considerably more strongly in response to a monetary policy impulse than in a situation without balance sheet constraints. As the extent of balance sheet constraints is rather small at the current end, the impact of monetary policy transmission is currently not assumed to be amplified.

State-dependent responses to a restrictive monetary policy impulse
State-dependent responses to a restrictive monetary policy impulse
Supplementary information

Using local projections to measure non-linear effects

Local projections are useful for investigating possible non-linear effects of exogenous shocks. Put simply, local projections can be used to directly estimate the time profile of a response to an exogenous shock. The idea is to regress an endogenous variable in multiple individual estimates at different horizons, t+h, on a shock at time t. The sequence of coefficients of the exogenous shock can then be interpreted as the impulse response. Local projections are easy to implement and do not require any complex assumptions to be made about potential data-generating processes. 1 Another benefit of local projections is that they make it possible to directly estimate non-linear effects of exogenous shocks. 2 This can be done by interacting the effect of the shock with an additional explanatory variable, say. Such interaction terms are particularly suitable in cases where the aim is to analyse whether the transmission of exogenous shocks is amplified or weakened by external influences. 3 In this exercise, the specification itself is linear in the parameters and can thus be estimated using the least-squares method. 4 As a result, the overall effect is the sum of the average effect and the additional effect, the latter being a function of the value of the interaction variable. The overall effect is therefore non-linear.

The effect of monetary policy measures is estimated by means of local projections that take into account the scale of debt-induced balance sheet constraints. The effect of monetary policy measures, accounting for the scale of balance sheet constraints, is estimated using simple local projections for a panel dataset. Specifically, consumption expenditure by households and investment expenditure by non-financial corporations are regressed on a monetary policy impulse as well as other control variables. One way of determining the non-linear responses is to take the share of debt indicators in the private non-financial sector that point to balance sheet constraints, and to interact them with the monetary policy shock. The overall response to the monetary policy shock is therefore non-linear and a function of the scale of the debt-induced balance sheet constraints. 

By exploiting quarterly data from multiple countries, a higher panel dimension makes the estimates more precise. The estimation uses quarterly data for Germany, Spain, France and Italy from the first quarter of 2001 to the fourth quarter of 2023. The number of observations is increased via the panel dimension by combining data across different countries. 5 This helps to compensate for the loss of observations caused by lags and leads, thus yielding more precise estimates. By specifying the estimation equation, it is possible to identify how the endogenous variables respond on average across the euro area to changes in the explanatory variables. 6 Country-specific fixed effects are considered here. 

The estimation equation takes into account the scale of the debt-induced balance sheet constraints. The responses to the monetary policy impulse are interacted with the scale of the balance sheet constraints, with the result that the overall response to the monetary policy impulse is a function of the scale of the balance sheet constraints. Specifically, the estimation equation reads as follows:

y_{i,t+h} = \alpha_{i,h} + \beta_h \varepsilon_t + \delta_h \left(\text{BilRes}_{i,t-1} \times \varepsilon_t\right) + \gamma_{i,h}(L) x_{i,t} + \psi_h(L) y_{i,t} + u_{i,t+h}

Here, y_{i,t+h} is the macroeconomic indicator in country i at time t+h. 7 \alpha_i is a country-specific constant, x_{i,t} is a vector with (lagged) control variables, 8 \varepsilon_t is a monetary policy shock, and u_{i,h,t} is an error term. Lagged values of the endogenous time series in each case are also considered. 9 The interaction variable BilRes_{i,t-1} stands for the share of the indicators that point to balance sheet constraints at time t-1. More specifically, the interaction variable takes the value of one if all the debt indicators considered in all the countries under observation point to debt-induced balance sheet constraints. If, on the other hand, none of the debt indicators considered point to balance sheet constraints in any of the countries, the interaction variable will take the value of zero. Furthermore, BilRes_{i,t-1} can also take values of between zero and one – for example, if only certain debt indicators point to balance sheet constraints in any of the countries. 10  

Monetary policy shocks are identified by changes in market interest rates during ECB press conferences. The monetary policy impulse is identified based on high-frequency financial market data, with changes in market interest rates for different maturities being measured around what is known as an event window. 11 Put simply, the changes in market interest rates around the press conference following meetings of the ECB’s Governing Council are interpreted as a proxy for monetary policy shocks. 12

The impulse responses show how macroeconomic indicators respond to monetary policy shocks over time. The coefficient of the monetary policy shock \beta_h at different horizons determines the size of the average effect. The overall effect, on the other hand, is the sum of the average effect and of effect \delta_h, multiplied by the size of the interaction variables. 13 Using the estimated coefficients, it is therefore possible to investigate whether greater debt-induced balance sheet constraints amplify the effect of monetary policy measures. That is the case when the coefficients of the average effect and the interaction term have the same sign. If, on the other hand, the coefficients have different signs, the overall effect is weakened by the interaction. 

 

5 Conclusion

Debt-induced balance sheet constraints are of relevance for monetary policy. This analysis underscores that balance sheet constraints can play a significant role in monetary policy by amplifying the impact of monetary policy measures. This is particularly relevant if actors affected by balance sheet constraints are constrained in their consumption and investment decisions.

As expected, interest rate-sensitive debt indicators deteriorated during the monetary policy tightening. Monetary policy measures in response to the inflation environment left their mark on the balance sheets of the euro area private non-financial sector. Owing to steep interest rate hikes, interest-sensitive components such as interest expenditure and debt service were the main indicators to deteriorate. However, despite these isolated increases, the debt situation of the private non-financial sector did not deteriorate significantly overall. Higher incomes, in particular, provided relief. 

The current and expected debt situation does not point to broad-based balance sheet constraints in the private non-financial sector. With regard to the current and expected developments in the debt situation of the private non-financial sector, this analysis does not reveal any broad-based debt-induced constraints. In this respect, the results suggest that debt has not led to an amplification of monetary policy transmission and will not do so in the near future. 

From a central bank perspective, it is necessary to monitor developments in the debt situation of the private non-financial sector on an ongoing basis. This is the only way to ensure that any changes in monetary policy transmission that may arise from the debt situation are detected at an early stage and, where appropriate, taken into account when calibrating the monetary policy stance. Such analyses should ideally also be complemented by micro-based studies, for example on the basis of distributional wealth accounts. Otherwise, relevant heterogeneous developments could be overlooked that typically remain hidden when looking at macroeconomic aggregates alone. 35
 

List of references

Altavilla, C., L. Brugnolini, R. S. Gürkaynak, R. Motto and G. Ragusa (2019), Measuring euro area monetary policy , Journal of Monetary Economics, Vol. 108, pp. 162-179.

Altavilla, C., R. S. Gürkaynak and R. Quaedvlieg (2024), Macro and micro of external finance premium and monetary policy transmission , Journal of Monetary Economics, Vol. 147, No 103634.

Bank for International Settlements (2024), Interest rate risk exposures of non-financial corporates and households – Implications for monetary policy transmission and financial stability (Committee on the Global Financial System) , CGFS Papers, No 70.

Bank for International Settlements (2017), BIS database for debt service ratios for the private non-financial sector , Data documentation.

Bayer, C., R. Luetticke, L. Pham-Dao and V. Tjaden (2019), Precautionary Savings, Illiquid Assets, and the Aggregate Consequences of Shocks to Household Income Risk , Econometrica Vol. 87(1), pp. 255-290.

Bernanke, B., M. Gertler and S. Gilchrist (1999), The financial accelerator in a quantitative business cycle framework , Handbook of Macroeconomics, Vol. 1, pp. 1341-1393.

Cloyne, J., C. Ferreira, M. Froemel and P. Surico (2023), Monetary Policy, Corporate Finance and Investment , Journal of the European Economic Association, Vol. 21(6), pp. 2586-2634.

Deutsche Bundesbank (2024), Distributional wealth accounts: timely data on the distribution of household wealth, Monthly Report, April 2024.

Deutsche Bundesbank (2022a), Development of the debt situation in the euro area private non-financial sector since the outbreak of the COVID-19 pandemic , Monthly Report, April 2022, pp. 31-48.

Deutsche Bundesbank (2022b), Distributional Wealth Accounts for households in Germany – results and use cases , Monthly Report, July 2022, pp. 15-38.

Deutsche Bundesbank (2021), The impact of monetary policy depending on the debt situation in the non-financial private sector: Evidence for the euro area , Monthly Report, April 2021, pp. 15-32.

Deutsche Bundesbank (2019), The impact of an interest rate normalisation on the private non-financial sector in the euro area from a balance sheet perspective , Monthly Report, January 2019, pp.13-30.

European Central Bank (2024), What explains the high household saving rate in the euro area? , Economic Bulletin, Issue 8/2024, pp. 59-63.

European Central Bank (2022), Estimating quarterly non-financial assets and household housing wealth for the euro area: a methodological update , unpublished memo.

European Central Bank (2021), Monetary policy decisions , Press release of 16 December 2021.

Geiger, F. and F. Schupp (2018), With a little help from my friends: Survey-based derivation of euro area short rate expectations at the effective lower bound , Deutsche Bundesbank Discussion Paper No 27/2018.

Greenwald, D. (2019), Firm Debt Covenants and the Macroeconomy: The Interest Coverage Channel , MIT Sloan School Working Paper, No 5909-19.

Gürkaynak, R. S., H. G. Karasoy‐Can and S. S. Lee (2022), Stock Market’s Assessment of Monetary Policy Transmission: The Cash Flow Effect  , The Journal of Finance, Vol. 77(4), pp. 2375-2421.

Jeenas, P. (2023), Firm Balance Sheet Liquidity, Monetary Policy Shocks, and Investment Dynamics , BSE Working Paper, No 1409.

Jordà, Ò. (2023), Local Projections for Applied Economics , Annual Review of Economic, Vol. 15(1), pp. 607-631.

Jordà, Ò. (2005), Estimation and Inference of Impulse Responses by Local Projections , American Economic Review, Vol. 95(1), pp. 161-182.

Jordà, Ò. and A. M. Taylor (2025), Local Projections , Journal of Economic Literature, Vol. 63(1), pp. 59-110.

Kaplan, G. and G. L. Violante (2022), The Marginal Propensity to Consume in Heterogeneous Agent Models , Annual Review of Economics, Vol. 14(1), pp. 747-775.

Kaplan, G. and G. L. Violante (2018), Microeconomic heterogeneity and macroeconomic shocks , Journal of Economic Perspectives, Vol. 32(2), pp. 167-194.

Lian, C. and Y. Ma (2021), Anatomy of Corporate Borrowing Constraints , The Quarterly Journal of Economics, Vol. 136(1), pp. 229-291.

Montiel Olea, J. L., M. Plagborg-Møller, E. Qian, and C. K. Wolf (2025), Local Projections or VARs? A Primer for Macroeconomists , mimeo.

Ottonello, P. and T. Winberry (2020), Financial Heterogeneity and the Investment Channel of Monetary Policy , Econometrica, Vol. 88(6), pp. 2473-2502.

Slacalek, J., O. Tristani and G. L. Violante (2020), Household Balance Sheet Channels of Monetary Policy: A Back of the Envelope Calculation for the Euro Area , Journal of Economic Dynamics and Control, Vol. 115, No 103879.

Swanson, E. T. (2021), Measuring the effects of federal reserve forward guidance and asset purchases on financial markets , Journal of Monetary Economics, Vol. 118(C), pp. 32-53.

Tenreyro, S. and G Thwaites (2016), Pushing on a String: US Monetary Policy Is Less Powerful in Recessions , American Economic Journal: Macroeconomics, Vol. 8(4), pp. 43-74.

Tillmann, P. (2020), Monetary Policy Uncertainty and the Response of the Yield Curve to Policy Shocks , Journal of Money, Credit and Banking, Vol. 52(4), pp. 803-833.

Tzamourani, P. (2021), The interest rate exposure of euro area households , European Economic Review Vol. 132(C), pp. 1-26.

Weidner, J., G. Kaplan and G. L. Violante (2014), The Wealthy Hand-to-Mouth , Brookings Papers on Economic Activity, Vol. 45(1), pp. 77-153.

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