France
Financial Sector Assessment Program-Technical Note-Nonfinancial Corporations and Households Vulnerabilities

This technical note on nonfinancial corporations and households vulnerabilities on France analyzes the structure of nonfinancial corporate financing in the French economy, potential vulnerabilities of the corporate sector, and their possible channels of transmission through interconnections with the financial system. The objective of this paper is to document the evolution of French corporate debt since the global financial crisis, analyze the riskiness of this debt, the quality of allocation of this debt, and uncover potential heterogeneity across sectors and firms which may have implications at the macroeconomic level. This paper also complements existing studies by the Institut National de la Statistique et des Études Économiques, the Haut Conseil de Stabilité Financière and the Banque de France by undertaking a cross-country comparative analysis. Empirical analysis suggests that corporate debt may be allocated efficiently across publicly listed companies, but the picture is less clear among nonpublicly listed firms.

Abstract

This technical note on nonfinancial corporations and households vulnerabilities on France analyzes the structure of nonfinancial corporate financing in the French economy, potential vulnerabilities of the corporate sector, and their possible channels of transmission through interconnections with the financial system. The objective of this paper is to document the evolution of French corporate debt since the global financial crisis, analyze the riskiness of this debt, the quality of allocation of this debt, and uncover potential heterogeneity across sectors and firms which may have implications at the macroeconomic level. This paper also complements existing studies by the Institut National de la Statistique et des Études Économiques, the Haut Conseil de Stabilité Financière and the Banque de France by undertaking a cross-country comparative analysis. Empirical analysis suggests that corporate debt may be allocated efficiently across publicly listed companies, but the picture is less clear among nonpublicly listed firms.

Executive Summary and Recommendations

Nonfinancial private sector debt has risen in recent years in France and requires close monitoring:

  • Corporates. The debt of French nonfinancial corporations has been on a rising trend in percent of GDP, especially in recent years, in contrast what is observed in peer European countries. This trend on non-consolidated data is mostly accounted for by bond issuances and loans among nonfinancial corporations (NFCs) while bank credit to NFCs has also grown but at a slower pace. While, across countries, French firms do not appear to be more indebted on average or to be more likely to have their debt-at-risk than their peers, there exists a tail of firms with debt-at-risk that has remained fatter than before the global financial crisis, despite the low interest rate environment. Moreover, some banks may have somewhat significant exposures to individual large indebted corporates. Stress tests show that under downside macrofinancial scenarios, corporate debt may increase significantly (up to around 11 percent of GDP in the broad sample of firms) but would remain broadly manageable. However, banks’ large exposures to corporates with debt at risk would increase significantly under the adverse scenario and in aggregate would amount to a significant share of capital.

  • Households. There is no clear evidence of vulnerabilities in households’ balance sheets at an aggregated level. Households have continued to build their financial net worth by accumulating financial assets even faster than debt. Their saving rate is healthy, and they appear to invest their inflows primarily in safe assets. Household debt is not high in international comparisons. However, some households—lower income, younger—may have experienced a deterioration of their balance sheet along certain dimensions. Such potential pockets of vulnerabilities should be further studied when data are available. The residential real market appears to be broadly aligned with its supply-side and demand-side fundamentals, and there are limited near-term downside risks to housing prices. However, there is a need to remain prudent, because the likelihood of adverse price developments is sensitive to negative shocks to macrofinancial conditions.

Table 1.

France: Recommendations for Nonfinancial Sector Sheets

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Nonfinancial Corporations1

A. Introduction

1. This paper analyzes the structure of nonfinancial corporate financing in the French economy, potential vulnerabilities of the corporate sector, and their possible channels of transmission through interconnections with the financial system. The objective of this paper is to document the evolution of French corporate debt since the global financial crisis, analyze the riskiness of this debt, the quality of allocation of this debt, and uncover potential heterogeneity across sectors and firms which may have implications at the macroeconomic level. The paper undertakes various firm level panel regressions analysis on large sample of French firms including small- and medium-sized enterprises (SMEs), and on a cross-country sample of publicly listed firms to assess: (i) determinants of debt-at-risk, including the role of macrofinancial conditions; (ii) whether there are any France-specific factors that affect the capital structure of firms, or whether instead French firms are on average no more reliant on debt finance than peers; to develop empirical models used for the purpose of macrofinancial stress test scenarios and to characterize exposures of the financial system. Such a cross-country study is particularly timely, given the recent decisions by the Haut Conseil de Stabilité Financière (HCSF) to set a limit to banks’ exposures to individual large indebted corporates and to activate the countercyclical capital buffer to 50 bps. This paper also complements existing studies by the Institut National de la Statistique et des Études Économiques (INSEE), the HCSF and the Banque de France by undertaking a cross-country comparative analysis.2

2. The main findings of this paper are as follows:

  • The debt of French nonfinancial corporations has been on a rising trend in percent of GDP, especially in recent years, in contrast what is observed in peer European countries. This trend on unconsolidated data is mostly accounted for by bond issuances and loans among NFCs while bank credit to NFCs has also grown but at a slower pace;

  • This increase is mitigated by an increase in cash holding at the macro level. Moreover, the fall in interest rates has helped contain the debt service ratios;

  • At the firm level, consolidated debt-to-asset ratios and interest-coverage-ratios are on average broadly in line with peer countries, and have been on a somewhat long-term declining trend, with an uptick for large firms in recent years. There is evidence that the stock in debt and its recent increase are concentrated in several sectors, as in other countries, while cash buffers, which are good at an aggregate level, tend to be thinner among firms with debt-servicing difficulties;

  • An empirical model developed on French firms shows that macrofinancial conditions impact firm average profitability as well as the likelihood that a firm may belong to the left tail of the distribution of debt-servicing capacity (debt-at-risk, defined as debt of firms with an interest coverage ratio below 1 or below 2), after controlling for various firm characteristics;

  • The tail of the distribution of the number of firms with debt-at-risk has remained fatter than before the global financial crisis but the amounts are broadly similar, despite the low interest rate environment. While SMEs are more likely to experience debt servicing difficulties, large firms account for the lion’s share of debt-at-risk at an aggregate level, reflecting the importance of large firms in the French business environment;

  • Across countries, French firms do not appear to be more indebted on average or to be more likely to have their debt-at-risk than their peers. There are significant common time effects affecting leverage on average and the tail of the distribution across all countries; leverage has been on a rising trend since 2010 with the common factor impacting the tail of debt-at-risk have remained above the pre-global financial crisis;

  • Empirical analysis suggests that corporate debt may be allocated efficiently across publicly listed companies, but the picture is less clear among non-publicly listed firms;

  • Stress tests suggests that, under the France specific adverse macrofinancial scenarios with a severity calibrated based on the growth-at-risk (GaR) approach and comparable to the through of the global financial crisis, corporate debt may increase significantly (from around 8 percent of GDP up to around 11 percent of GDP in the broad sample of firms). Existing cash buffers would attenuate the impact of the shock, but their use may be constrained by liquidity needs and precautionary motives. In the cross-country adverse scenario targeting an unconditional 2 standard deviation shock to macrofinancial condition, debt-at-risk of French listed firms would be in the top half among peer countries in such scenarios and could reach up to 5 percent of GDP under an interest coverage ratio (ICR) threshold of 2, from 3 percent of GDP in 2017;

  • The analysis of large exposures of individual banks to large indebted corporates shows that there is some risk in the balance sheet of individual banks related to total large exposures to individual large indebted corporates with debt-at-risk. Moreover, under the adverse stress scenarios, the expected number of large exposures at risk would increase for each individual bank and the total expected amounts of debt at risk would become a non-negligible share of bank capital; and

  • Nonresidents hold 50–60 percent of debt or equity securities issued by resident sectors, reflecting the international integration of French capital markets. The role of the nonresident sector through debt and equity markets may not remain going forward if financial stress arises from a France specific shock and could even become destabilizing.

3. The paper is organized as follows. Section B presents cross-country stylized facts on debt, while Section C characterizes macrofinancial conditions in France and the evolving structure of corporate debt financing. Section D studies the empirical determinants of debt-at-risk among French firms. Section E presents a cross-country comparative analysis of corporate debt-at-risk among publicly listed firms. Section F analyses the efficiency of allocation of debt financing among French firms. Stress test scenarios are presented in Section G. Section H studies the interconnections of French NFCs with the financial system, and section I uncovers large concentrated exposures of French banks. Section J concludes.

B. Stylized Facts on Corporate Debt

4. Unconsolidated nonfinancial corporate debt in France has increased by more than 25 percent of GDP between 2010 and 2017 and stands at 140 percent of GDP, among the highest in advanced countries.3 This contrasts with developments in other large euro area countries which have experienced either a stabilization of their corporate debt (Germany) or a significant decrease (Italy and Spain).4 The increase in French corporate debt as a share of GDP since 2010 can be explained mostly by an increase in debt claims within the French NFC sector and bond financing until 2015, while after 2015 bank credit and bond finance increased at a similar pace.5 A particularity of French firms’ corporate debt is that bonds account for about half of nonfinancial companies’ debt, consistent with the importance of large firms in the French business environment. This feature has been reinforced since the global financial crisis, with large firms substituting from bank credit to bonds, in particular in 2009–10.

uA01fig01

Nonfinancial Corporate Debt

(Percent of GDP)

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Sources: Haver Analytics; and IMF staff calculations.
uA01fig02

Unconsolidated NFC Debt

(Percent of GDP)

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Sources: Haver Analytics; and IMF staff estimates.
uA01fig03

NFC Unconsolidated Debt Outstanding

(Percent of GDP)

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Source: Haver Analytics (ECB Sector Accounts).

5. Netting out intercompany loans, consolidated corporate debt is lower at 89 percent of GDP, and more in line with peers. Nonetheless, it has still experienced an increase of some 11 percentage points of GDP since 2010, mainly resulting from net bond issuances. Subtracting cash holdings from consolidated debt, aggregate net consolidated debt has barely increased during the crisis and stands at 60 percent of GDP, close to the euro area average, suggesting that, in the aggregate, French firms used part of the proceeds to accumulate liquid financial assets, which also account for a larger share of their assets.6

uA01fig04

Consolidated NFC Debt

(Percent of GDP)

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Sources: Haver Analytics; and IMF staff calculations.
uA01fig05

Net Consolidated Debt

(Percent of GDP)

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Sources: Haver Analytics; and IMF staff calculations.Note: Euro area latest value is from 2016.

6. As in other countries, the consolidated debt stock of listed firms as well as the post-crisis debt increase is concentrated in a few sectors (Figure 1). The manufacturing and utilities sectors account each for around 20 percent of the debt stock of listed firms in France and the transportation and retail sector each for about 10 percent. In Germany the manufacturing sector accounts for 60 percent of the debt stock, while network sectors account for over 60 percent of the debt stock in Italy and Spain. Similarly, the debt increase in the post crisis period was mainly caused by the transportation sector and, to a lesser extent, oil and gas, manufacturing, healthcare and retail sector in France, while the manufacturing and healthcare sectors were responsible for the debt increase in Germany. The construction and utilities sectors contributed to the decrease in debt in Spain, while the utilities sector contributed to the decrease in debt in Italy. The concentration of debt to some extent reflects the distribution of assets and of output across sectors among listed firms.

Figure 1.
Figure 1.

France: Distribution of Debt Stock

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Sources: Worldscope; and IMF staff calculations.

7. While some sectors are more leveraged in general, there is no evidence that leverage of publicly listed firms is on average higher in France (Figure 2).7 Sectoral debt to assets ratios constructed from aggregated firm-level data are not particularly high in France compared to peer countries, while network sectors tend also to be more leveraged in peer countries.8 A particularity of France is that highly leveraged sector (utilities, retail, and telecom) have also a high debt to income ratio, suggesting a low capacity to service the debt despite the low interest rate environment. While cash buffers are high on average, they are not equally distributed among firms: firms with low ICR typically also have lower cash buffers. Moreover, evidence from simple averages of consolidated data show a long-term declining trend in consolidated debt-to-asset ratio—with however an increase in this ratio for large firms in recent years (text figure).

Figure 2.
Figure 2.

France: Leverage and Buffers of Publicly Listed Companies

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Sources: Worldscope and IMF staff calculations.
uA01fig06

Average Consolidated debt-to-Asset Ratios

(Percent)

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Sources: Banque de France; and IMF staff.

8. A risk mitigating factor is that firms have used their debt to increase their buffers of liquid assets. Aggregate data show that the ratio of total cash holdings to total consolidated debt is large in many countries. However, our firm-level dataset on listed firms shows that the aggregated cash to debt ratio among firms with debt-at-risk (ICR<2) in France is lower than the cash to debt ratio of nonvulnerable firms. In addition, this ratio has decreased recently for vulnerable firms while it has increased for nonvulnerable firms.

uA01fig07

Cash to Debt Ratios

(Percent)

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Sources: Worldscope and IMF staff calculations.

9. A large share of debt in France is owed by firms which have a low interest coverage ratio and a high net debt to equity ratio.9 A high net debt to equity ratio may be the consequence of a financing choice of large firms which have ample access to cheap borrowing and does not necessarily reflect a risk to service its debt. However, a large net debt to equity ratio and at the same time a low ICR signals that the firm concerned has chosen a capital structure that could be vulnerable to shocks to interest rates and/or profitability. The share of debt owed by listed firms with a net debt to equity ratio above 100 percent is lower in France than in other large euro area countries.

uA01fig08

Distribution of Total Debt

(Percent)

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Sources: Worldscope and IMF staff calculations.
uA01fig09

Marginal Impact of the CIT on the Debt-to-Asset Ratio

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

10. The link between corporate taxation and firm capital structure is well established, and this effect, while declining as a result of recent reforms, has been significant in France.10 Recent research has confirmed that firm capital structures are sensitive to corporate taxation, among various factors.11 Based on the Feld et al. (2013) study, the French authorities estimated that the marginal impact on the debt-to-asset ratio (compared to a neutral tax system) of the Corporate Income Tax (CIT) rate is 10.6 percentage points (respectively 7.5 percentage points) before (respectively after) the 2018 budget law reform, and compared it to several peer European countries (text figure). Further incentivizing corporate to finance through equity rather than debt would help reduce firm’s leverage and debt-at-risk.

C. Macrofinancial Conditions and the Changing Structure of Debt Financing

11. Borrowing conditions of NFCs has remained accommodative in recent years in an environment of sustained low policy interest rates and unconventional monetary easing (Figure 3). Banks have transmitted to nonfinancial corporations the low interest rate policy in an environment of generally loose financial conditions, while keeping spreads broadly stable. Financing conditions have also become more accommodative on the bond market across large advanced economies, while the share of bonds issued by non-investment grade borrowers has increased—suggestive of a search for yield in financial markets. The nonperforming loans (NPL) ratio for NFCs has been on a long-term declining trend; it increased modestly as a result of the global financial crisis to 2.4 percent and has dropped below 2 percent in recent years.12

Figure 3.
Figure 3.

France: Borrowing Conditions

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Sources: Dealogic; and IMF staff calculations.

12. Domestic investment and outward FDI by French nonfinancial corporations are correlated with bank credit and overall corporate debt cycles, and bank credit seems to have played a stabilizing role (Figure 4). Over the longer term, there has been a clear trend of increasing reliance on nonbank debt, while bank credit to firms—the bulk of which finances SMEs and mid-tier firms—has remained broadly stable as a share of GDP. Bank credit tends to be less volatile than overall borrowing by firms, which appears associated with outward FDI cycles, suggesting that nonbank sources of debt financing are used to finance foreign activities of firms. At the macroeconomic level, the volatility of nonbank debt seems driven by loans within the NFC sector—suggesting that such debt linkages could potentially transmit financial conditions across firms, in particular between head offices of conglomerates and related companies, but also reflecting the possible double counting of some of these loans.13 However, the cyclical and structural determinants and use of these loans within the NFC sector is not well studied. During episodes of financial stress (global financial crisis, euro area crisis) bank credit to NFCs seems to have played a stabilizing role, with loans for working capital purposes often adjusting the most but seemed to have contracted with a lag after these episodes. During such past episodes, gross bond financing inflows seemed broadly stable, and foreign investors have absorbed the largest share of these issuances.

Figure 4.
Figure 4.

France: Macrofinancial Conditions

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

13. Unconventional monetary policies, including quantitative easing programs, likely boosted the demand for corporate bonds. Corporate bond issuance has risen in euro area countries since the global financial crisis. The ECB’s purchase of government bonds and asset-backed securities led investors into buying assets with similar characteristics but higher yields, such as corporate bonds, reducing the costs of bond financing. The ECB’s corporate sector purchase programme (CSSP) initiated in mid-2016 brought corporate bond yields even further down.

14. The secular decline in the share of bank credit in total firm debt financing reflects the combined growing importance of bond finance and loans among NFCs (Figure 5). Between 1991:Q1 and 2018:Q2, the cumulative flows of bonds issued reached more €500 billion and of loans among NFCs about €680 billion, compared to about€ 600 bn of credit from domestic banks. In the recent past, this tendency has continued, being supported by unconventional monetary policies implemented since the global financial crisis. This evolution of the structure of debt financing raises new questions about the transmission of shocks to and among French NFCs.

Figure 5.
Figure 5.

France: Evolution in the Composition of NFC Debt by Counterparty Sector and Instrument

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

D. Empirical Determinants of Debt at Risk among Nonfinancial Corporations

15. This section presents an empirical model of debt at risk developed on firm level balance sheet and financial statement data. The model aims relates the analysis of firm level cash flows to firm level characteristics and macrofinancial conditions. The section illustrates the fit of the model—e.g., how it explains the tail of the distribution of firm level debt servicing capacity, and the evolution of predicted debt at risk in the baseline macrofinancial scenario.

Approach

16. An econometric analysis is performed to assess the determinants of French firms’ cash flow vulnerabilities (Box 1). The data source is ORBIS, covering around 180,000 firms incorporated in France over the period 2005–2015, after cleaning the data. In our sample, 61 percent of firms are SMEs and the rest are large firms. The data cleaning process closely follows the approach described in Kalemli-Ozcan et al (2015) and Gopinah et al. (2015). Our sample keeps only unconsolidated balance sheets. The main reason for selecting only unconsolidated firm balance sheet is to be able to include in our analysis not only consolidated debt but also trade credit.14 In that respect, a particularity of ORBIS is that it includes a breakdown for debt to suppliers and contractors.15

France Specific Empirical Models

The analysis aims to understand the extent to which firms’ ability to service their debt are influenced by their characteristics and macrofinancial conditions. A panel Probit empirical model explains the likelihood that a nonfinancial firm could experience debt servicing difficulties:

P[Riskit=1]=Afirmcharit1+δmacrofinancialt1+ϵit(1)

Where Riskit is a binary variable taking a value of 1 if the interest coverage ratio ICR<ICR¯ and zero otherwise, where ICR¯ a threshold level (1, or 2), firm_c harit is a vector of firm level characteristics. These include the debt-to-income ratio of the firm, a measure of the size of the firm (total assets), the turnover ratio (defined as operating revenues as a percent of total assets), the return on assets, asset composition (the ratio of net fixed assets to total assets), and the age of the firm since it was incorporated. The variable macro_f inancialt synthetizes the state of macrofinancial conditions in the economy at date t (see below). εit is an error term which is assumed to be potentially correlated across firms in any given year, and thus clustered by year. In robustness tests, the error term is modelled to account for industry characteristics: ϵit=Δindustrycharit1¯+γitwhereindustrycharit1¯ is a vector of time varying firm characteristics averaged at the industry level and year, and λit is clustered by year.1

We also consider an empirical model of the determinants of profitability. This model will allow assessing to what extent macrofinancial conditions have an impact of the profitability of French firms. Such effects will generate second round feed-back effects to the debt-at-risk of firms. Specifically, we consider the following empirical model:

ROAit=αROAit1+Afirmcharit1+βmacrofinancialt1+υit(2)
1 We consider the four digits NACE sectoral classification. Results are robusts to including sector fixed effects at the NACE 1 classification.

17. The state of macrofinancial conditions in France is embodied in the predicted one-year ahead tail of the growth distribution in a GaR empirical model estimated in a first stage. The premise of the GaR approach is that the distribution of growth outcomes is sensitive to shocks to financial conditions: an adverse shock to financial conditions tends to widen the distribution of growth outcome and increase the likelihood of adverse outcomes and is an indicator of the extent to which the financial system tends to amplify shock. We consider the one year ahead predicted GaR at the 5th percentile (lagged one year in the regression) as the state of macrofinancial conditions and of the related risks: a decline in the percentile of the predicted real GDP growth indicates a rise in the severity of financial stress tail events that would result in a sharp decline in real GDP growth. Such evidence can be seen as indicating that the financial system has become more likely to amplify shocks with a macroeconomic impact. In the second stage, we assess the extent to which heightened risk of financial volatility impacts firms’ ability to service their debt and their profitability.

Findings

18. Firm level characteristics play an important role in predicting the likelihood of cash flow difficulties at the firm level (Table 2). Firms that are initially more leveraged, that are less profitable, that are younger, that have a higher proportion of fixed assets and have larger turnover, are more likely to be at risk of experiencing difficulties in servicing their debt. Most of these findings hold if we control for these characteristics averaged by industry-year, suggesting that we are not merely capturing industry effects. We also find that the 5th percentile of the predicted GaR is significant in many specifications, but significance drops in specifications based on an ICR threshold of 2: a fatter left tail of the growth distribution results in a higher likelihood of debt servicing difficulties at the firm level, after controlling for firm and industry characteristics.16

Table 2.

France: Baseline Probit Estimations

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Sources: ORBIS; and IMF Staff.Note: Note: error term clustered at the year level. Sectors with at least 300 firms included. Within Pseudo-R2 reported for regressions with fixed effects.***; **; *: significant at the one percent (respectively 5 percent, and 10 percent) level.

19. The predicted probabilities of ‘debt-at-risk’ differentiate firms with ICR above and below the thresholds relatively well. Table 3a reports moments of the distributions of the predicted probabilities that the ICR of a firm i falls below 100 percent during year t based on specification (2), and Table 3b report frequencies of Type I and Type II errors. The model seems to perform relatively well in separating out firms with an ICR below 100 percent from firms with an ICR above 100 percent.

  • Among SMEs, the average predicted probability of debt-at-risk is more than twice larger for those with an ICR below 100 percent (0.28) than for those with an ICR above 100 percent (0.13). 90 percent of SMEs with an ICR below 100 percent have a predicted probability of debt-at-risk above 0.1 while about ½ of those with an ICR above 100 percent have a predicted probability of debt-at-risk below 0.1. Conversely, about ½ of SMEs with an ICR below 100 percent have a predicted probability of debt-at-risk above 0.25, while about 90 percent of SMEs with an ICR above 100 percent have a probability of debt-at-risk below 0.27. Using as threshold the unconditional probability of selecting an SME with debt-at-risk (0.16), the frequency of Type I error (missed positive) is 0.2 (meaning that 80 percent of SMEs with debt-at-risk are correctly classified) and the frequency of Type II errors (false positive) is 0.3 (meaning that 70 percent of SMEs that do not have their debt-at-risk are correctly classified).

  • Among large firms, the average predicted probabilities of debt-at-risk are smaller, reflecting the fact that large firms are on average less likely to experience low ICRs in any given year and/or may find it easier to exit a low ICR zone. For firms with ICR below 100 percent, the average probability of debt-at-risk is 0.17 compared to 0.11 for those with an ICR above 100 percent. About ½ of firms with an ICR below 100 percent have a predicted probability above 0.16 while only ¼ of those with an ICR above 100 percent have a predicted probability above 0.14. Conversely, about ½ of firms with an ICR above 100 percent have a predicted probability below 0.1 while ¾ of those with an ICR below 100 percent have a predicted probability above 0.11. The frequency of errors are somewhat larger than for SMEs using the same definition of the threshold (0.11 for large firms): the frequency of Type I error (missed positive) is 0.3 (meaning that 70 percent of SMEs with debt-at-risk are correctly classified) and the frequency of Type II errors (false positive) is 0.4 (meaning that 60 percent of SMEs that do not have their debt-at-risk are correctly classified).

Table 3a.

France: Distribution of Predicted Probabilities

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Sources: ORBIS; and IMF staff.
Table 3b.

France: Type I and Type II Errors

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Source: IMF staff.Note: Type I errors are missed firms with ICR<1, and type II are false positive. Threshold used is average frequency of firms with debt-at-risk, defined as firms with an ICR<1.

20. The empirical model performs relatively well in tracking the aggregate tail of firms experiencing debt servicing difficulties (Table 4). First, the model is re-estimated separately for SMEs and for large firms, using the ICR threshold of one. Second the predicted probabilities of experiencing debt servicing difficulties, are averaged by year. The following patterns emerge:

  • First: SMEs have on average a higher likelihood of having low ICR than large firms;

  • Second: the tail of firms with debt-at-risk fattened at the time of the global financial crisis, and this change in the tail was more marked for SMEs (+0.8 pp. between 2007 and 2009) than for large firms (+0.3 pp.);

  • Third: the tail of firms with debt-at-risk has remained somewhat above the pre-crisis level for SMEs and for large firms and was in 2015 was about the same as at the time of the global financial crisis; and

  • Fourth: the model estimated probabilities of debt servicing difficulties track the actual tail of the distribution and its time evolution quite well.

Table 4.

France: Macroeconomic Fit of the Model

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Sources: ORBIS and IMF Staff.Note: Computed for Interest Coverage Ratio < 100 percent.

21. The amount of debt at risk appears to be macroeconomically significant in the baseline, and its extent mostly accounted for by large firms (Tables 5a and b). Overall, using the stricter definition of debt-at-risk (ICR<1), we find that the model tends to slightly underestimate at the aggregate level the level of financial debt-at-risk (bonds+bank loans), with a difference on average of 0.8 percent of GDP, but with the largest temporary underestimation in 2009. Depending on the definition adopted for debt at risk (interest coverage ratio below 100 percent, or below 200 percent), and the scope of corporate debt (only bank debt and corporate bonds, or also including trade credits), the estimated amount of corporate debt at risk in the baseline scenario varies between about 3 percent of GDP (under the most restrictive definition) and 9 percent of GDP (under the less strict definition). Nevertheless, this looser definition of debt includes intercompany loans that have a low economic meaning. It is noticeable, that, under the less restrictive definition of debt at risk—ICR < 200 percent—the amount of debt at risk has remained at levels not so different from the peak of the global financial crisis (with however a decline in 2015), despite a more favorable macrofinancial environment. About 80 percent of the debt at risk is usually accounted for by large firms, and about 20 percent by SMEs. This does not imply that the leverage and debt at risk of SMEs may not be important to consider: first, SMEs may have business relationships with related large firms; financing problems in large firms could cascade to SMEs through these links, making debt at risk correlated across such related firms, especially if SMEs is already significantly indebted; second, in recent years, lending to SMEs has been the most dynamic segment of bank credit—while large firms may be able to access bond markets—and account for a relatively larger share of bank credit than implied by firm level data.

Table 5a.

France: Comparison Actual and Predicted Financial Debt at Risk

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Sources: ORBIS; and IMF Staff.Note: Debt include bank debt and bonds only.Aggregation of actual debt at risk is the total debt of firms with CIR<1 during the year considered. Aggregation of predicted debt-at-risk based on sum of firm level debt weighted by the predicted firm level probability of ICR<1.
Table 5b.

France: Model Predicted Corporate Debt at Risk

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Sources: ORBIS; and IMF Staff.Note: Debt include bank debt, bonds and trade credit. Financial debt excludes trade credit. Intragroup loans are excluded. Aggregation based on sum of firm level debt weighted by the predicted firm level probability of facing cash flow problems. Different empirical models are estimated for large firms and SMEs.

E. Cross-Country Comparative Analysis of Debt at Risk Among Publicly Listed Corporates

22. This section undertakes a cross-country comparative analysis of corporate debt for large firms listed on the stock market. The objective is, first, to assess how large French firms compare among their peers in other developed economies in term of their debt levels and likelihood of experiencing potential debt servicing difficulties, and second, to understand how macrofinancial conditions affect firms’ debt servicing capacities of French firms and in peer countries. Focusing on listed firms makes sense given the findings of section D that most of aggregate debt at risk originates among these large firms.

23. A cross-country econometric analysis is performed to assess the determinants of publicly listed firms’ leverage, debt cash flow vulnerabilities and profitability (Box 2). Based data from Worldscope, we rely upon consolidated balance sheets and financial statement of publicly listed firms based on country of incorporation over the period 2005–2017, for eight countries: Canada, France, Germany, Italy, Japan, Spain, the United Kingdom, and the United States. In this analysis the focus is the group level debt and debt servicing capacity, thus netting out all debt claims among firms that belong to the same corporate group.

Cross-country Empirical Models

As in the previous section, the analysis aims at understanding the extent to which firms’ ability to service their debt are influenced by their characteristics and macrofinancial conditions. A panel Probit empirical model explains the likelihood that a nonfinancial firm could miss a debt payment:

P[Riskijst=1]=Afirmcharijst1+BMacrofinancialjt+cj+ds+ϵijst(3)

Where Riskijstis a binary variable taking a value of 1 if the interest coverage ratio of firm i in country; and sector s is such that ICRijt<ICR¯ and zero otherwise, where ICR¯ is a threshold level (1, or 2), firm_charijst is a vector of firm level characteristics. These include the debt-to-income ratio of the firm, a measure of the size of the firm (total assets), the turnover ratio (defined as operating revenues as a percent of total assets), the return on assets, asset composition (the ratio of net fixed assets to total assets). The vector representing the state of macrofinancial conditions Macro _f inancialjt is captured by two country specific variables: a financial condition index and real GDP growth. sijst is an error term which is assumed to be potentially correlated across firms in any country and year, and thus is clustered by country and year. We also include a full set of country fixed effects cj and industry fixed effects ds.

We also assess empirically the firm-level and macrofinancial determinants of firm profitability and leverage. Specifically, we consider the following firm level Ordinary Least Square (OLS) panel specification with standard errors robust of heteroscedasticity and clustered by country and year:

Yi,s,j,t=αYi,s,j,t1+Δfirmcharijstt+φMacrofinancialjt+Cj+Ds+νijst(4)

24. Descriptive statistics of firms with debt-at-risk (ICR< 100 percent). In our sample of French firms, firms with debt-at-risk tend to be less profitable than others (and are often loss making), they have lower current assets relative to their current liabilities and have lower cash-to-debt ratios. In our entire sample of eight countries, firms with debt-at-risk also tend to be less profitable (and often loss making) than others, and also have lower cash buffers than other firms.

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Source: Worldscope and IMF Staff.

Findings

25. Firms ability to service their debt is explained by a combination of firm level characteristics and macrofinancial conditions (Tables 6 and 7). Firms that are more indebted, less profitable, are smaller and have lower turnover tend to be more likely to experience difficulties to service their debt. Profitability, in turn, is positively associated with a capital structure relying relatively more on debt financing, with size, turnover and the share of fixed assets in total assets. Tighter financial conditions negatively impact firms’ servicing capacity directly (Table 6) and with a lag through lower profitability (Table 7), while higher real GDP growth positively affect debt servicing capacity directly (Table 6) as well as with a lag through higher profitability (Table 7). The direct effect of financial conditions is likely to reflect the combination of higher financing costs (at large, e.g., including not only the cost of debt finance but also the cost of equity finance) and lower overall profitability. The lagged effect through past profitability likely reflects the fact that profitability tends to exhibit some persistence so that a shock to profits will exhibit some persistence over time.

Table 6.

France: Baseline Probit Regressions

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Sources: Worldscope; World Economic Outlook; and IMF Staff.***; **; *: significant at the one percent (respectively 5 percent, and 10 percent) level.
Table 7.

France: Baseline Profitability Regressions

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Sources: Worldscope; World Economic Outlook; and IMF Staff.***; **; *: significant at the one percent (respectively 5 percent, and 10 percent) level.

26. French large corporates are on average not more indebted than their peers and are on average not more likely to experience debt-service difficulties (Figure 6, right panel). This confirms and broadens the findings of the 2018 France Article IV Selected Issues Paper. Specifically, we find that, after controlling for firm and industry characteristics:

  • Firms from Canada, Italy, Spain and the US have higher leverage than French firms on average, while those form Germany, Japan and the UK have lower leverage;17 and

  • The likelihood of debt servicing risk is higher for firms from Canada, the UK and the US and is lower for Japanese firms than for French firms; the difference with French firms is unclear for German, Italian and Spanish firms.

Figure 6.
Figure 6.

France: Year and Country Fixed Effects

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Sources: Worldscope; and IMF staff estimates.Note: time fixed effects from firm level panel regressions of ICR and leverage.

27. Average debt levels and tails of firms with debt servicing difficulties are affected by common shocks (Figure 7, left panel). We estimate versions of empirical models (2) and (3), replacing the country specific Financial Condition Index (FCI) and real GDP growth by time fixed effects. The estimated fixed effects show very clearly the presence of common time shocks that affect both the average firm leverage, and the likelihood of debt servicing difficulties. These findings are robust to controlling for firm characteristics, country fixed effects and industry fixed effects. Specifically, we find that, after controlling for firm characteristics and industry fixed effects:

  • Average firm leverage and likelihood of debt at risk follow broadly similar evolutions over time;

  • Average leverage and likelihood of debt at risk rose sharply at the time of the global financial crisis;

  • Both declined in 2010;

  • Leverage has been on a rising common trend since 2010; and

  • The average likelihood of debt at risk has remained above pre-crisis levels since 2010.18

Figure 7.
Figure 7.

France: Indicators of the Riskiness in the Allocation of Corporate Debt

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Comparative Debt-at-risk Estimates

28. The empirical model provides relatively good estimates of debt-at-risk under the baseline macrofinancial scenario for France, but with differences across countries. The estimated likelihoods of debt service difficulties are based on equations (4) of models (3) and (4) as reported below.19 In particular the estimates take into effect the additional impact through lagged profitability. The model provides a good baseline estimate of debt-at-risk for French firms at around 2 percent of GDP with an ICR threshold of 100 percent. It also provides a good estimate for Japanese firms and US firms. It tends to under-predict the aggregate debt at risk for Canadian, German, Italian and UK firms. If we use a threshold of 200 percent, the actual debt-at-risk of large French firms is about 5 percent of GDP, and the predicted one at about 3 percent of GDP.

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Sources: Worldscope; and IMF Staff.Note: Estimates based on an ICR threshold of 100 percent and for 2017 (or 2016 due to data availability).

F. Is Corporate Debt Well Allocated in France?

29. This section complements the previous analysis of debt at risk by taking a different approach and assesses whether debt financing has been well allocated across French firms in the recent past (Box 3). A surge in debt financing may not be fundamentally a concern for financial stability if it is well allocated and it results in productive investments and higher profits that would firms to repay their debt. However, a surge in borrowing that would be misallocated and used relatively more to finance less-productive investments could add to financial stability risks down the road. Such patterns could occur when lending standards have been loosening for a sustained period of time and in situations of easy financial conditions—as is to some extent the case in the euro area. For instance, Chapter 2 of the Spring 2018 Global Financial Stability Report finds that the extent to which borrowing is well allocated across firms (the riskiness of debt allocation) is another indicator of downside risk to growth, and of the probability of financial stress, beyond early warning standard indicators of leverage and aggregate credit growth.

Empirical Methodologies To assess the allocation of borrowing across French firms, we rely on two empirical methodologies:

Riskiness of debt borrowing allocations comparing vulnerabilities between firms with large increase in debt and firms with small increase (or decline in debt). Following the methodology developed in Chapter 2 of the Spring 2018 Global Financial Stability Report (GFSR), we construct indicators of the riskiness of corporation borrowing allocation for France firms based on several firm level variables (interest coverage ratio, profitability, debt-to-income, debt-to-assets, and the market-to-book ratio for firms listed on the stock market). For each of these firm level indicators of vulnerability, an index ranging 0–10 is created based on its distribution of the indicator in the sample of firms, with a lower (respectively higher) value meaning higher (respectively lower) vulnerability. Second, each firm is assigned to a quintile of the distribution of the change in its debt level over the past three years (scaled by initial total assets). Third, the average difference in the value of the indicator is computed between firms with large increase in debt and firms with small increase (or decline) in debt. A higher (positive) value on this difference is consistent with the hypothesis of good allocation of corporate debt. A smaller (and negative) value is consistent with the hypothesis of a misallocation of corporate debt.1

Regression analysis of profitability and total factor productivity growth on changes in corporate debt. Specifically, we consider the following panel firm level specification:

Yi,t=αYi,t1+βΔDebttAssetst1+Σfirmcharit1+φMacrofinancialt+Dst1+νijst(5)

Where Yi,t is either profitability or TFP growth, ΔDebttAssetst1 is the change in total indebtedness between date t and date t — 1 scaled by total assets at date t – 1, with a set of firm level characteristics (firm_c harijt), macro financial conditions (Macro_f inancialt) as controls and industry controls (Dst1=industrycharit1¯).

1 See GFSR Chapter 2, Box 2.1 for a detailed description of the methodology.

Findings

30. Indicators of riskiness of debt allocation across firms do not suggest that there could be some misallocation of corporate debt in the broad sample of firms, or among publicly listed companies (Figure 7):

  • There is no definitive evidence that corporate debt allocation (including trade credit) is related to firm performance in the broad sample of firms. There is evidence that firms that experienced the largest increase in debt during 2013–2015 have somewhat relatively less strong ratios (profitability, debt-to-asset ratio and debt-to-income ratio) than firms that experienced the smallest increase (or a decline) in debt (tope left chart of Figure 7). This is consistent with stylized facts from earlier periods (2005–2007; 2010–2013). The exception during 2013–2015 is the ICR indicator which reflects slightly lower vulnerability among the top quintile than in the fifth quintile, as indicated by a positive differential. However, when we look at the actual characteristics of the median firm in the top quintile of the debt change distribution, we find that the various indicators (ICR, return on assets (ROA), debt-to-assets and debt-to-income) did not display clear vulnerabilities (bottom left table in Figure 7).

  • Corporate debt does not appear be misallocated among publicly-listed companies during 2015–2017. Among publicly-listed companies, firms that are at the top of the distribution of debt issuance appear to be more vulnerable in term of leverage, but they also have higher profitability, higher ICR and higher market-to-book ratios than firms at the bottom of the distribution of the change in debt. Moreover, for the median firm, the various ratios (ROA, ICR, leverage and market-to-book ratio) improved in 2017 relative to previous periods.

31. The regression analysis however is suggestive that more productive and profitable firms increase their debt by less than others in a broad sample of firms, but there is no clear pattern among publicly listed companies (Table 8). Among non-listed firms, there is evidence that firms that increase their indebtedness tend to be less profitable than other firms, after controlling for past profitability, size, turnover, the share of fixed assets in total assets and the age of the firm. The effect is economically significant: firms that increased their indebtedness by one standard deviation more than others experienced a decline in profitability of 0.8 percentage points relative to others (given an average profitability of 8 percent).20 In contrast, there is no evidence of any association between the change in firm indebtedness and profitability in the sample of firms that are publicly listed on the stock market.

Table 8.

France: Allocation of Debt Among Firms

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Sources: ORBIS; and IMF staff estimates.***; **; *: significant at the one percent (respectively 5 percent, and 10 percent) level.

G. Scenario Analysis

32. To assess how the left tail of the corporate debt distribution responds to shocks, stress scenarios are designed, accounting for shocks to growth and financing conditions (Figure 8). Second round effects on the ICR could materialize through a decline in profitability and an increase in debt burden under specific assumptions on the structure of the balance sheet. Each scenario’s output is based upon individual firms’ predicted ROA and probabilities of missing cash flow payments under stress under different thresholds (ICR of 100 percent or ICR of 200 percent). The scenarios also allow taking into account potential cash buffers that could be used to reduce the debt burden subject to liquidity constraints (assuming that liquid assets cannot be fall below short-term liabilities). This section presents aggregate debt-at-risk and its distribution among firms of different characteristics with for instance a breakdown between large firms and SMEs. In contrast to the banking stress tests, the shocks are temporary (occurring at date t) and the output of the stress tests presents aggregate debt-at-risk at date t+1.

  • France specific scenario: The sample includes all firms (including firms not listed on the stock exchange) of the ORBIS sample, with 2015 as the base year, and firm debt includes not only bank credit and bonds, but also intercompany trade credit. The scenarios are designed based on models (1) and (2). Stress scenarios rely on the 5 percent GaR during past stress events (including the Euro Area crisis and the global financial crisis) to calibrate the shock to firms’ balance sheets.21 The scenario is calibrated on the shock occurring at the time of the global financial crisis, which is similar but slightly more severe to the growth shock considered in the bank solvency stress test (where growth falls to -2.0 percent compared to -2.8 percent in this scenario. An additional scenario allows firms to adjust their leverage by making use of cash buffers.

  • Cross-country stress scenarios: The sample includes firms at a consolidated level and publicly listed on the stock market in Canada, France, Germany, Italy, Japan, Spain, the UK and the US. The empirical models (3) and (4) allow to shock both real GDP growth and an index of financial conditions. The scenarios based on a shock to growth assume a decline in real GDP growth from the 2017 (or 2016 for countries with incomplete firm data in 2017) of 2 standard deviation.22 The scenarios considering a shock to financial conditions assume a shock to financial conditions of about ½ of the level reached at the end of 2008 at the height of the global financial crisis. As in the France specific analysis, the additional scenario takes into account the possibility that firms rely on their cash buffers to reduce their leverage subject to a liquidity constraint.

Figure 8.
Figure 8.

France: Stress Scenarios Models

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

33. The France specific scenarios show that corporate debt-at-risk can rise substantially in the event of stress, and that cash buffers can help mitigate the debt servicing challenge (Table 9). Depending on the ICR threshold considered, the amount of unconsolidated debt-at-risk rise to about 8 or 11 percent of GDP, but the largest share of debt-at-risk located in large firms. However, in a second round, cash buffers can help reduce leverage and the amount of debt-at-risk particularly among large firms to between 5 and 7 percent of GDP, taking into account liquidity constraints. However, the decision to use cash buffers under the stress event may also be impacted by precautionary motives.

Table 9.

France: Specific Scenarios

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Sources: ORBIS; and IMF staff estimates.

34. In the cross-country stress scenario applied to the consolidated balance sheet of publicly listed companies, the debt-at-risk of French corporates appears to be in the top half of the sample (Table 10). French firms, together with Canadian, Spanish and US firms appear, in aggregate to hold the largest amounts of debt at risk. A combination of shocks to real GDP growth and financial conditions bring the total amount of debt at risk to around 4 percent of GDP. The use of cash buffers can help mitigate the vulnerabilities but to a relatively small extent at the consolidated level. This is consistent with the stylized fact established in section II that cash buffers are more likely to be located among firms that are less likely to be vulnerable to cash flow difficulties.

Table 10.

France: Cross-Country Stress Scenarios

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Sources: Worldscope; and IMF estimates.Scenario 1: scenario with shock to financial conditions only.Scenario 2: scenario with shock to real GDP growth.Scenario 3: scenario with combined FCI and real GDP growth shock.Scenario 4: scenario with combined FCI and real GDP growth shock and use of cash to reduce debt level under the constraints of a current ratio greater or equal to 100 percent.

H. Interconnections of Nonfinancial Corporations with the Financial System

35. This section examines interconnections of the NFC sector with the financial system and other sector, and finds that:

  • The NFC sector may be the most interconnected sector of the French economy. This is mainly because of linkages through equity claims, but loans and debt securities also play an important role.

  • In the past, the nonresident sector has played a stabilizing role in time of financial stress. While banks continued to supply loans to NFCs, nonresidents purchased debt securities issues by French corporates while loans among NFCs contracted (in particular around the time of the euro area crisis).

  • Banks do not appear to have excessively large concentrated exposures to indebted firms with debt-at-risk.

36. The NFCs sector has the largest stock of gross financial liabilities or gross financial assets, exceeding those of the banking system, suggesting that it could be the most interconnected sector of the French economy (Table 11 and Figure 9). At the end of 2018:Q2, total gross financial liabilities of NFCs reached about €11 trillion, about €1.7 trillion more than the banking system. Out of these €11 trillion, about €6 trillion are financial liabilities vis-à-vis other institutional sectors, compared to €7 trillion for the banking system. About €2.4 trillion are liabilities vis-à-vis the rest of the world (which includes related firms established abroad), compared to €3.2 trillion for resident banks and €1.9 trillion for the general government. The NFC sector appears to be the domestic sector the most interconnected with itself in the French economy, with liabilities vis-à-vis itself of €5.3 trillion. Intra-sectoral claims are mostly accounted for by equity claims followed by loans. Of all sectors, the NFC sector has by far the largest stock of equity liabilities (€1.8 trillion) among which €600 billion vis-à-vis the rest of the world. Its stock of debt securities liabilities is about €600 billion, about half of which held by nonresidents, compared to €1.2 trillion for the banking system and about €2.3 trillion for the sovereign (which has about €1.2 trillion held by nonresident investors). Monetary and Financial Institutions (MFIs) hold €70–80 billion of corporate debt securities and insurance companies €140–150 billion.

Table 11.

France: Interlinkages Among Institutional Sectors in France, 2018:Q2

(All instruments, in billions of euros)

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Sources: Banque de France; Sectoral Financial Accounts; and IMF staff.

Also includes non-profit institutions serving households.

Figure 9.
Figure 9.

France: Interconnections by Instruments: 2017:Q4 and 2018:Q2

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Source: Banque de France, Sectoral Financial Accounts.

37. When examining flows of debt liabilities across sectors during periods of financial stress, it appears that bond financing from nonresidents and intercompany loans complemented loans supplied by the domestic banking sector (Table 12a and b):

  • Global financial crisis (2007:Q4–2009:Q4). NFCs obtained loans, among which ⅔ coming from domestic resident banks and ⅓ from nonresidents (which could be foreign offices of French Banks). They issued debt securities which were in aggregate all held by nonresidents, while residents reduced their holdings of corporate bonds.

  • Euro area crisis (2011:Q2–2012:Q4). NFCs obtained debt financing for about €150 billion as loans (with domestic banks providing only €38 billion, or about ¼ of the total) and €70 billion as debt securities held by nonresidents (about ½ of the total) and domestic insurance companies (about 40 percent).

Table 12a.

France: NFCs Intersectoral Debt Flows During Episodes of Financial Stress: Global Financial Crisis

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Sources: Banque de France; and IMF Staff.
Table 12b.

France: NFCs Intersectoral Debt Flows During Episodes of Financial Stress: Euro Area Crisis

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Sources: Banque de France; and IMF Staff.

38. Going forward, corporates would be more vulnerable to financial stress than in the past in the event that nonresidents become reluctant to hold corporate bonds. The shock could be transmitted through bond market but also through the equity market, given the large proportion of nonresident investors. Firms not directly relying on financial market financing could also be indirectly impacted as the shock would likely be transmitted from large related companies or head offices of corporate groups through the web of intercompany loans.

39. Given their international reach, large French banks hold corporate exposures diversified geographically outside of France, including in the US, the UK, Belgium, and Italy. The domestic corporate loan market of the five largest banks appears to be broadly equally split among them. Among the four large international banks, two are more directly exposed to corporates, which account respectively for 39 percent and 24 percent of their total credit exposures, compared to 23 percent and 14 percent for the other two banks which are relatively more exposed to retail loans.23 Several banks have substantial corporate exposures in the US, the UK but also in Italy where some corporate debt may be at risk (see paragraphs 30, Table 8 and lower-right chart of Figure 10).

Figure 10.
Figure 10.

France: Individual Banks’ Exposures to Corporates

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

I. Concentrated Exposures of Individual Banks to Large Indebted Corporates

40. This section analyzes the large exposures of French domiciled banks to large indebted corporates. The objective is to understand whether individual banks may be subject to residual risks arising from their concentrated exposures to large indebted corporates. First, we assess the extent which individual banks may have large exposures to one or several large indebted corporates. Second, to examine how banks’ large exposures to indebted publicly listed corporates may evolve under the cross-country stress scenario described in section G, as more corporates may have their debt at risk.

41. Based on data provided by the authorities, large French banks’ total exposures to large indebted corporates have declined in percent of bank capital in recent years. Based on data consistent with the HCSF definition of large indebted corporates based on an ICR<300 percent, the exposures in percent of capital of the five largest banks reached about 20 percent in 2015 and declined in 2016 and 2017 to 13 percent in 2017. If the sample is further restricted to firms with a debt-to-equity ratio above 100 percent, the exposures is 5.4 percent of capital in 2017.24

uA01fig10

Large Banks’ Exposures to Large Firms with Cash Flows at Risk (ICR<3), including with Debt-Equity>100 percent

(Percent of bank common equity)

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Sources: ACPR; SNL; and IMF staff.Note: Banks include BNP-Paribas, BCPE, Groupe Credit Agricole, Societe Generale and Credit Mutuel Group.

42. To further assess residual risks that may arise from concentrated exposures to large indebted corporates, we match firm level data with supervisory data on large exposures. We consider publicly listed corporates from Belgium, France, Germany, Italy, the Netherlands, Spain, the United States, and the United Kingdom. Firm level consolidated balance sheets and financial statements are for 2017, or when unavailable for 2016. Banks included in the sample include BNP-Paribas, Banque Populaire Caisse d’Épargne (BPCE), Société Générale, La Banque Postale, Crédit Mutuel Group, and HSBC France. We consider their large exposures as of 2017:Q4. Large exposures of French banks are matched manually to the firm level data. Out of 600 large bilateral exposures amounting to €293 billion, 237 were matched to the list of publicly listed companies considered, for a total exposure amount of €157 billion, so a match rate of 53 percent. Among the 237 bilateral exposures, 67 percent are to French corporates (total exposures of €93 billion) and 33 percent to foreign corporates (total exposures of €64 billion); and €16 billion. (respectively €33 billion.) are to corporates with an ICR below 100 percent (respectively 200 percent). We consider two additional splits of corporates: (i) firms with a debt-to-equity ratio above 100 percent; (ii) French corporates with state participation.25

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Sources: ECB COREP Large Exposure reporting; Worldscope; and IMF staff.

43. The stress scenario considered is the cross-country scenario described in section G combining a tightening of financial conditions and a decline in real GDP growth. The model captures a channel through which concentrated exposures could worsen under stress: as macrofinancial conditions deteriorates, the number of corporates with debt-at-risk would increase, thus aggravating concentration risks on the balance sheets of banks. The scenario allows for use of cash buffers and some deleveraging by corporates to contain their debt service. Their use of cash buffers must meet a liquidity constraint, e.g., that the current ratio remains above 100 percent.26 Given the probabilistic nature of the model, we can compute the expected exposure under stress of each bank to each individual corporate that was matched to its large exposure file.

44. At the end of 2017, individual bank large exposures to corporates with debt-at-risk were already significant for several banks (Figure 11). On average, for the sample of the 5 largest banks, total concentrated exposures to large indebted corporates reached on average around 5 percent of CET1 using an ICR threshold of 1, and 11 percent of CET1 using an ICR threshold of 2. If in addition, we restrict to corporates with debt-to-equity ratios above 100 percent, total concentrated exposures are 2 percent of CTE1 for an ICR threshold of 1, and 6.5 percent of CET1 for an ICR threshold of 2. Large exposures to vulnerable corporates with state ownership reach almost 4 percent of CET1 for an ICR threshold of 2.

Figure 11.
Figure 11.

France: Individual Bank Total Exposures to Large Indebted Corporates

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

Sources: COREP large exposures reporting; WEO; Worldscope; and IMF staff estimates.Note: Sample includes five banks.1 SNCF not included. Stress scenario estimates the expected debt at risk.

45. Banks’ total large exposures to individual corporates with debt-at-risk would increase significantly under the adverse scenario (Figure 11). Under an ICR threshold of 1, the total expected large exposures of individual banks to corporates with debt-at-risk would rise to almost 9 percent of CET1 on average, and to about 15 percent of CET1 under an ICR threshold of 2. Total expected large ‘debt-at-risk’ exposures to French firms with state participation would reach 5.5 percent of CET1 on average and expected large ‘debt-at-risk’ exposures to firms with a debt-to-equity ratio above 100 percent would reach about 9 percent of CET1 on average.

46. At of the end of 2017, most individual large exposures of French banks to vulnerable corporates remained small (Table 13). Under an ICR threshold of 2, one exposure was already slightly above 4 percent of CET1 for one bank, and seven other exposures were above 2 percent of CET1 for three banks. Under a stress situation with more difficult access to market borrowing, each of these corporates might require to increase their borrowing beyond existing credit lines. To anticipate such possibilities, the authorities should ensure that the macroprudential measure remains counter-procyclical.

Table 13.

France: Individual Large Exposures to Corporates with Debt-at-Risk

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Sources: Worldscope; COREP large exposure reporting of French banks; WEO; and IMF Staff.Note: Each column reports, for a given bank, its 10 largest exposures to individual corporates with debt-at-risk.*** Highlighted cells indicate debt-to-equity above 100 percent.

J. Conclusion

47. Corporate debt has increased significantly in France since the global financial crisis, in contrast to many peer countries. The increase in corporate debt as a share of GDP can be explained to a significant extent by an increase in intercompany loans and bond financing. The increase in debt is concentrated among several sectors as in peer countries. Firms have used their borrowing to invest in physical capital, to accumulate financial assets (mainly equity and cash) and to extend intercompany loans. The average debt-to-asset ratio has been more stable over time, but the left tail of the distribution of debt-at-risk has remained above its pre-global financial crisis level despite the low interest rate environment.

48. Regression analysis shows that, after controlling for firm and sectoral characteristics and time fixed effects, macrofinancial conditions affect the left tail of the distribution of corporate debt (debt-at-risk). While SMEs are more likely to have their debt-at-risk, they account for a much smaller proportion of aggregate debt-at-risk than large firms. While the increase in corporate debt seems to have been appropriately allocated among publicly listed companies, this does not appear to be as clear among firms that are not listed on the stock market.

49. Stress tests scenario suggests that, under tighter financial conditions or/and low real GDP growth comparable to the global financial crisis, debt-at-risk would rise to levels observed at that time, despite the use of cash buffers. A combination of lower real GDP growth and tighter financial conditions would cause an increase in debt-at-risk above 11 percent of GDP. While cash buffers could be used to mitigate the impact of the shock, their use as a deleveraging mechanism could be further constrained by potential liquidity and borrowing constraints. Under such scenarios, the aggregate debt-at-risk of publicly listed firms would be slightly above the average among peer countries but would seem manageable.

50. The authorities should remain vigilant and prevent the build-up of imbalances in the corporate sector that could have spillovers to the banking system. They should consider:

  • Building buffers in the banking system to limit potential spillovers. The decision to limit bank exposures to large indebted corporates and the activation of the countercyclical capital buffer are welcome decisions. They should be reviewed periodically and pro-actively, and further action—such as further tightening of the large exposure limit—should be taken if it appears that there is additional procyclical build-up of concentration risk;

  • Engaging with the ECB the possible use of Pillar II measures to address bank specific residual risks arising from concentrated corporate exposures;

  • Enhancing communication on corporate risks with the public to raise awareness of market participants;

  • Further reducing incentives favoring debt finance relative to equity, going beyond the recent reforms including of the corporate income tax that brings the level to 25 percent by 2022;27

  • Advocating at the European Union (EU) level for bank-based macroprudential instruments targeting specific sectors (such as large corporates, or SMEs), such as: sectoral risk weights and a sectoral systemic risk buffer in the context of Capital Requirement Directive (CRD) V, and for a discussion of macroprudential tools for nonbanks; and

  • Studying the structural and cyclical characteristics, determinants and use of loans among NFCs.

Households and Residential Real Estate Market28

A. Introduction

51. Over the past 10 years since the Global Financial Crisis, French households’ debt has continued to rise. This is raising concerns of vulnerabilities that could have accumulated in their balance sheet, in the context of a low interest rate environment, declining but still high unemployment, and high debt in the balance sheet of the public sector and of nonfinancial corporations. In spite of the increase in indebtedness, aggregate households’ balance sheets seem solid because households have in the meantime continued to accumulate financial assets at a faster pace. To further understand the evolution of households’ balance sheets and whether pockets of vulnerabilities may be developing, we rely upon survey data and study the balance sheets of households at a more granular level including by income group and by age. We find that, as for other income groups, the debt-to-service ratio of lower income households with a housing loans has increased while their financial buffers declined. Moreover, the debt-to-income ratio of younger households seem to have increased. 29

52. The note analyzes conditions in the residential real estate (RRE) market and potential risks to the French market going forward. Given that housing loans are typically the dominant, if not the only one, financial liability of households, while real estate account for a large share of their assets, it is important to understand the evolution of the French residential housing market, its characteristics, and its outlook.30 Indeed, signs of overvaluation would not bode well for new borrowers, as it would suggest their “overpaid” real estate relative to other assets, which could stretch their balance sheets. To analyze developments in the real estate market and understand risks going forward, we adopt two approaches:

  • First, by relying on a battery of indicators and an empirical model, we assess whether the residential real estate market is aligned with fundamentals at the current juncture or whether there are signs of overvaluation. At this juncture, the residential real estate market does not appear to be excessively dynamic or overvalued at the national level, and the recent price inflation seems related to specific local conditions, in particular around Paris. Housing affordability seems to have on average improved in recent years despite the observed moderate increase in household’s debt to income ratios and the higher loan-to-value ratios since the Global Financial Crisis.

  • Second, we study potential downside risks to the real estate market going forward, following the methodology of the Spring 2019 GFSR Chapter 2 which applies the growth-at-risk framework to RRE prices. In particular, we study future downside risks at various horizons, and find that they are limited. We also characterize the impact of macrofinancial shocks to the distribution of residential real estate prices.

53. The paper is organized as follows. Section L establishes stylized facts on households’ balance sheets at the macroeconomic level. Section M analyzes recent developments in the credit market and the evolution of the structure and lending standards for housing loans. Section N tackles the question whether residential real estate prices are aligned or not with their fundamentals. Section O presents the analysis of downside risks to the real estate market. Section P focuses on distributional issues, housing policies and related state intervention through the financial system. Section Q concludes.

B. Household Balance Sheet and the Structure of Savings

54. At the aggregate level, French households’ balance sheets appear reasonably solid in international perspective (Figure 12). French households have on average accumulated a net worth of 553 percent of their net disposable income, above the Organization for Economic Cooperation and Development (OECD) average of 440 percent, and about at the same level as Italian and Danish households. In the past 10 years, this ratio has increased by about 18 percent. Household debt was at about 120 percent of net disposable income in 2017, which is just below the average for OECD countries, and at 58.4 percent of GDP in 2018:Q1, close to the European average. The ratio of debt to disposable income has risen quite significantly since 2007, by some 20 percentage points, in contrast to what happened in other large European countries—as a comparison, German households, which started at about the same level of debt close to 100 percent of disposable income in 2007, have experienced a decline in their indebtedness by 9 percentage points of their net disposable income.

Figure 12.
Figure 12.

France: International Comparisons of Households’ Balance Sheets

Citation: IMF Staff Country Reports 2019, 321; 10.5089/9781513517759.002.A001

55. French households on average tend to save a relatively large share of their income. The households’ saving rate has been broadly stable, at almost 14 percent of gross disposable income. This is below the saving rate of German households (which is at almost 18 percent), but above the saving rates of households in Italy, Spain, the UK or the US. French households’ saving rate net of the increase in indebtedness stands at about 4.5 percent of disposable income, implying that the financial net worth of households continues to rise at an aggregate level—this net saving rate is below German households’ net saving rate of about 8 percent, but above that of households in Italy, Spain, the UK or the US who have net saving rates below 2 percent.31

56. While real estate continues to account for the lion’s share of households’ assets, the composition of financial assets has shifted toward safe, fixed income products (Figure 13). About 60 percent of households’ assets are accounted for by land and dwellings (and about 60 percent of households own a property), and the remaining 40 percent are financial assets.32 In 2017, listed shares and other equity accounted for 30 percent of total financial assets, compared to 34 percent in 2007 and 38 percent in 2000. At the end of 2018:Q3, household financial assets amounted to €5.1 trillion, about 30 percent in bank deposit/saving accounts, 35 percent in life insurance and 25 percent in equities.33 The share of liquid or low-risk assets (life insurance, bank saving and deposit accounts) in households’ total financial assets has increased in the context of the low interest rates environment, while the share of stocks has declined over time.34 Households’ debt is almost matched by liquid bank accounts, suggesting that, in the aggregate, the household sector’s balance sheet does not appear to be vulnerable to shocks affecting debt service.

Figure 13.