Differences in country-specific financing conditions may account for a dispersion of responses to a turnaround in the credit cycle across Europe. Moreover, by reinforcing the role of financial assets as borrowing collaterals, developments in national housing and corporate finance systems have the potential to make bank lending procyclical. In this way, the financial sector can amplify business cycle fluctuations as well as the impact of monetary policy shocks and asset price movements on real activity. Cross-border ownership of assets further bolsters this mechanism. By affecting the behavior of banks’ capital buffers over the cycle, banking regulation might have some role to play in mitigating procyclical swings in domestic credit conditions and, thereby, in lessening macroeconomic volatility.
Overview
The ongoing financial market turmoil has drawn considerable attention to the impact of a tightening in financial conditions on real activity in European economies and on cross-border financial linkages.22 From a theoretical perspective, two stylized facts appear to be widely recognized. First, financial systems are inherently subject to cycles—with growth in lending, leverage, and asset prices often magnifying underlying economic dynamics—leading, at times, to a buildup of financial imbalances followed by sharp corrections. Second, financial cycles can, in turn, have an impact on the macroeconomy both by affecting lenders’ capital adequacy—and, hence, their ability to extend loans—and by altering asset prices and value of collaterals, thereby impinging on borrowers’ creditworthiness and their ability to borrow.23 From a policy viewpoint, the recent distress in the financial system has required regulators and policymakers to devise new ways of containing systemic risks and lessening the likelihood of boom-bust episodes in the future.24
Against such a background, this chapter evaluates the responses of individual (advanced and emerging) European economies to changes in asset prices and credit supply and examines how differences in national financing conditions may account for the dispersion in their responses. Specifically, answers are sought to the following questions: (1) to what extent have financing conditions affected growth in European countries over the latest credit cycle? (2) what drives divergences in the strength and in the timing of macrofinancial linkages across European countries? (3) which European countries are more susceptible to a turnaround in the credit cycle and asset prices? (4) how can policy contribute to mitigating the effects of boom-bust dynamics? (5) in which European economies are such stabilization policies most needed? and (6) how—and to what extent—do cross-country spillovers complicate this picture?
The evolution of financial positions in European Union (EU) countries over the latest credit expansion and the macroeconomic impact of financial conditions among selected European economies since 1999 offer a broad view of the mechanisms through which financial shocks affect Europe’s macroeconomic stability—the so-called macrofinancial linkages. In the process, the chapter provides an overview of the state of household and firm balance sheets, the dynamics of credit and asset prices over the business cycle, and the importance of financial spillovers across Europe. Calibrated simulations provide a first gauge of the effectiveness of policies aimed at smoothing the cyclical pattern of lending standards. The key findings are as follows:
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First, the latest credit expansion had a very limited impact on the growth of the advanced economies of Europe as a whole, while contributing substantially to the growth of emerging European economies. Within these country groups, the dispersion of performance was considerable, both across countries and across sectors. With the economic effects of a downturn in the credit cycle still playing out, such a dispersion is expected to remain wide, if not widen further.
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Second, cross-country divergences in households’ borrowing/saving decisions over the cycle appear to be strictly related to domestic mortgage market characteristics: in countries where the loan-to-value (LTV) ratios are high, the level of mortgage debt relative to GDP also tends to be high, while consumption is likely to be more volatile and more sensitive to underlying financial shocks.
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Third, the stringency of collateral constraints in bank lending seems to have a bearing on cross-country dissimilarities in debt and investment dynamics in the corporate sector. In this context, in economies with more rationed access to credit, equity prices are found to be more sensitive to underlying changes in fundamentals. This greater sensitivity is likely to induce higher volatility to investment, debt, and the current account balance.
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Fourth, country-specific financial condition indices for the corporate sector reveal important divergences in the timing and the strength of macrofinancial linkages across European countries. Possibly more interestingly, country-specific financial condition indices provide a clear picture of the extent to which bank lending to the corporate sector tends to be procyclical.
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Fifth, a cross-country scrutiny shows that the responsiveness of credit growth to changes in asset prices is positively related to the degree of procyclicality in corporate leverage. In turn, procyclicality in lending tends to increase the volatility of capital accumulation. This relationship implies that, wherever credit conditions are more likely to co-move with the cycle, credit availability becomes more sensitive to variations in equity prices—and boom-bust dynamics are thereby magnified.
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Sixth, a reduction in the procyclicality of bank lending following, for example, the introduction of a countercyclical element into banks’ regulatory provisions, is found to substantially reduce the volatility of investment of financially integrated economies. In particular, stability gains appear to become more important in economies that are more financially constrained.
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Finally, greater financial integration and the increasing prevalence of cross-border ownership of assets are found to be associated with better growth opportunities, with the link stronger in countries where integration is faster. At the same time, though, these developments in international financial markets have the potential to further amplify business cycle fluctuations and the impact of asset price movements on real activity by increasing the strength of cross-border financial spillovers.
All in all, this chapter points to the perils of procyclicality in bank lending in a number of European countries, while suggesting that banking regulation might have some role to play in mitigating procyclical swings in credit conditions by affecting the behavior of banks’ capital buffers over the cycle, particularly in financially integrated economies with tighter borrowing limits. The analysis also suggests that financial integration and adequate coordination of financial policies across Europe, and especially within the European Monetary Union, are essential to foster smooth and growth-oriented adjustment. It also underscores the need for supervision to keep pace with increasingly complex linkages across borders.
Vulnerability to Changes in Financial Conditions
According to the so-called financial accelerator mechanism, a credit cycle is set in motion by any shock—from monetary policy, financial liberalization, or technology—that pushes asset prices up. This financial cycle then tends to get amplified over time: as asset price gains drive the value of borrowers’ collateral up and as banks’ capital positions improve (with fewer defaults and delinquencies), banks are willing to supply more credit and households and corporates are willing to borrow more (as rising asset prices and improving business conditions increase their perception of net worth). The recent credit cycle—in Europe as elsewhere—was mainly driven by a low interest rate environment and by developments in mortgage market securitization, although these effects were probably magnified by investor complacency (see Box 9).
European Securitization and the Possible Revival of Financial Innovation
Collapsing global securitization volumes in the wake of the subprime crisis have raised fundamental questions over the viability of the originate-to-distribute (O2D) business model.1 Issuance has dropped precipitously in both Europe and the United States, with banks keeping more loans on their balance sheets and tightening lending standards as a result (first figure). The decline has been particularly sharp for mortgage-backed securities (MBSs) and MBS-backed collateralized debt obligations (CDOs). The O2D model was thought to have made the financial system more resilient by dispersing credit risk to a broad range of investors. Ironically, however, the O2D model itself became the source of financial instability.
Mortgages constituted the vast majority of loans securitized in Europe in 2006–07. Of these, about 54 percent were originated in the United Kingdom; Spain (14 percent) and the Netherlands (11 percent) followed. Total European MBS issuance dropped from €307 billion in 2007 to €28 billion in the first quarter of 2008. During the same period, CDO issuance plummeted from €471 billion to €63 billion, and asset-backed securities (ABS) issuance2 dropped from about €124 billion in 2007 to €9 billion in the first half of 2008.
What Went Wrong?
In many cases, the risk transfer from securitization proved to be less complete than believed, and investors to whom risks were transferred were too complacent. The adoption of new international financial accounting standards in Europe forced the recognition on the balance sheet of substantial securitization volumes (IMF, 2008b, Box 1.3). Also, the efficacy of some risk transfers (e.g., to asset-backed commercial paper conduits and structured investment vehicles) relied on market liquidity, which broke down in 2007. As a result, banks have had to take back onto their balance sheets assets they had earlier securitized. Some banks also retained supposedly lower-risk CDO and MBS tranches, but have been forced to drastically write down these holdings as their market values have fallen and bond insurers have been downgraded.
Issuance of Securitized Products
(Billions of U.S. dollars)
Sources: JPMorgan Chase; Inside Mortgage Finance; European Securitization Forum; and IMF staff estimates and calculations.Investor complacency resulted in overreliance on credit ratings. Furthermore, the rating agencies’ key assumptions on some risks (e.g., subprime mortgage delinquencies and recovery rates) turned out to be overly optimistic. As credit fundamentals deteriorated, many of the more complex and multilayered securities became nearly impossible to value, and market liquidity disappeared as leveraged investors (primarily hedge funds) reduced their exposures. The disappearance of market liquidity and the reliance on models for valuations triggered uncertainty about losses and loss exposures. The interaction of credit and liquidity risk drove market valuations into downward spirals of mark-to-market losses and forced liquidations.
Road to Recovery
Reviving securitization requires structural change. Investor confidence in the instruments, the originators, and the rating agencies needs to be restored. Originators will have to simplify security structures and improve the disclosure of their underlying assets in a timely and comprehensive manner. Rating agencies will need to provide more information on the models and inputs that underpin their ratings and on the potential for rating volatility.
The American and European Securitization Forums are engaged in coordinating standardized reporting and originator principles. This process will take many years. Also, the major rating agencies are consulting over whether to supplement rating letter grades with rating volatility and loss sensitivity metrics. However, they have been slow to address the conflict of interest that arises because of their parallel activities as consultancy services.
It has been proposed that originators in Europe retain some meaningful economic interest in the underlying securities, so that their incentives can be more closely aligned with those of investors. A European Commission proposal regarding implementation of the Capital Requirements Directive suggests requiring minimum levels of originator risk retention. However, this proposal could easily make securitization uneconomic for originators and faces considerable monitoring and enforcement difficulties. It is, therefore, unlikely to restart the market.
Covered Bonds
In Europe, covered bonds have provided banks with cost-efficient secured financing for over 200 years, and U.S. authorities recently launched an initiative to encourage their use by U.S. banks. Covered bonds are backed by identifiable and legally “ring-fenced” pools of loans. They remain on the balance sheet, however, so that the bank retains the ultimate credit risk and is encouraged to maintain loan quality. Nevertheless, yield spreads on U.K. and Spanish covered bonds have widened sharply during the crisis owing to declining housing markets.
European Covered Bond Issuance
(Billions of U.S. dollars)
Sources: Datastream; and IMF staff estimates and calculations.Meanwhile, German and French spreads have remained relatively low (second figure). Although secondary market liquidity has dried up, issuance of “jumbo” bonds is continuing; however, these are mostly German Pfandbriefe.
Covered bond issuance is expected to remain below trend for some time, but the market is likely to continue broadening. The first Greek covered bond issue is expected in 2008, and the four largest U.S. banks have committed to issuing covered bonds, while an electronic trading platform in Europe is planned. The covered bond market has not been immune from recent turbulence, but it does provide a less complex alternative to outright securitization.
Conclusion
The risk transfer and capital saving benefits of securitization, combined with underlying investor demand for securities, should eventually revive issuance. But the products are likely to be simpler and more transparent, and trade at significantly wider spreads.
Note: The main authors of this box are John Kiff and Paul Mills, with assistance from Carolyne Spackman. 1 Securitization involves the transformation of pools of loans and other types of assets into marketable securities. 2 European ABS issuance is primarily of business loans and vehicle leases.Although bank balance sheets have continued to expand over recent months and bank lending to euro area nonfinancial corporations has so far remained strong—reaching a record nominal annual growth rate of 15 percent in March 2008 (see Chapter 1, Figure 5)—the credit cycle seems to have turned in most advanced and emerging European economies. Higher borrowing costs, tighter bank lending standards, and the effective closing of some credit market segments are all evidence of this turn.25
Data also confirm a gradual moderation in house price inflation that is broadly based, notwithstanding a certain degree of heterogeneity across countries.26
As a result of these developments, lending growth is expected to slow across the board over the coming months, with due allowance for some lags owing to the average maturity of precommitted credit agreements.
To what extent have financing conditions affected growth in European countries over the latest credit cycle? Which economies are more susceptible to a turnaround in the credit cycle and asset prices? An economy’s vulnerability to a turn in the credit cycle largely depends on the degree of overextension of household and corporate balance sheets, the stock of outstanding debt, and the extent of overvaluation in asset prices.27 If corporates or households are running large financial deficits, when corrections in asset prices start—and banks begin to respond to collateral valuations and to their own capital positions by rationing the availability of credit—then there is no alternative to a cutback in private sector spending. As a result, absolute declines in asset prices, in the stock of outstanding debt, and in real activity are likely to ensue.
A simple (and admittedly imprecise) way to gauge the impact of credit conditions on individual European economies would thus be to look at the evolution of their household and corporate financial positions over the latest credit expansion.28 Indeed, if saving rates were mean reverting and initial financial positions were at equilibrium, then the ultimate dampening effect of a turn in the credit cycle might be the reverse of what happened in the upswing. However, in the current environment—with the ongoing sharp repricing in credit risk—the downturn of the credit cycle is likely to be much more abrupt than the upswing.
Recent balance sheet data for EU countries indicate that, for advanced economies as a whole, the credit expansion had virtually no impact on growth over the latest cycle.29 However, it contributed substantially to the (nominal) growth of emerging economies, where corporates and households were running large financial deficits, averaging—on aggregate—around 7 and 4 percent of nominal GDP, respectively. Such a general picture masks a significant dispersion of performance across countries (Figure 21). For example, credit expansion had essentially no impact in Germany and Poland—where household and corporate savings actually increased over the period—but it had a much larger impact, say, on the Spanish and Baltic economies, where the overextension of both household and corporate balance sheets was considerable. More generally, euro area household savings actually increased during the credit expansion (by almost 3 percent), more than offsetting the surge in the financial deficit of the euro area corporate sector (about 2 percent).30 In non–euro area advanced economies, the impact of the credit expansion was largely neutral, with small (about 1 percent) corporate financial surpluses compensating for household financial deficits of similar magnitude. Overall, more developed credit markets (like the Netherlands, Finland, the United Kingdom, and Denmark) were featuring significant deficits in household financial positions, while exhibiting strong corporate balance sheet positions.
Flow of Borrowing in Selected EU Countries: Corporate and Household Sectors, 2002–06
(Percent of nominal GDP)
Sources: Eurostat; and IMF staff calculations.Altogether, the impact for advanced economies in Europe is likely to be more contained than in previous credit downturns—even with nonnegligible asymmetries within the region. Although asset prices have risen, the cumulative gain over recent years looks modest, especially if compared with the experiences of those countries in the second half of the 1980s.31 Meanwhile, households are still running sizable financial surpluses in the euro area and modest deficits in non–euro area advanced economies, with the opposite holding true for the corporate sector. Hence, while the credit cycle will no doubt be a dampening factor—and severely so in some countries—it is unlikely to weigh substantially on growth in the aggregate of advanced European economies, partly because Germany did not participate in the upswing of the credit cycle.
However, the same benign conclusion cannot be reached for emerging Europe, even if dispersion in performance remains wide in this region too. Recent flows of borrowing by households and corporates (Figure 21), recent debt accumulation (Figure 22), and recent gains in asset prices (Figure 23) in some of the emerging European economies—such as the Baltics—recall the imbalances characterizing the Nordic countries in the early 1990s, before the onset of their financial crises.
Corporate and Household Debt in Selected EU Countries, 2002–06
(Percent)
Source: Eurostat; and IMF staff calculations.Average Changes in Asset Prices, 2002–06
(Annual percentage change over 2002–06)
Sources: Bloomberg L.P.; Bank for International Settlements; and IMF staff calculations.Borrowing against Collateral: How Do Financial Cycles Get Amplified?
In the Household Sector . . .
European housing finance systems share a number of common features that have strengthened the resilience of the region to the recent subprime crisis.32 The satisfactory debt-servicing capacity of European borrowers has played a key role in sheltering homegrown mortgage loans from downturns in the real estate market. Although European covered bonds have not been immune from investors’ recent dislike for securitized instruments, they have proved to be a cost-efficient and less complex alternative to outright securitization.33 Indeed, prudent property valuation rules and special investor protection diminish the risks of European mortgage-covered bond markets, while allowing lenders to obtain comparatively cheap funds in capital markets and to benefit from lower regulatory risk weightings.
However, this general picture masks significant heterogeneity in the institutional characteristics of national mortgage markets across (both advanced and emerging) European economies (Box 10). With the intention of identifying clusters of countries on the basis of shared characteristics of their mortgage markets, a number of empirical studies tend to concur that, in economies where LTV ratios are high, the level of mortgage debt relative to GDP also tends to be high. In countries where households are able to borrow more easily against their housing wealth, elevated LTV ratios and relatively large mortgage debts are generally accompanied by longer contract durations and more widespread home equity release.34
Institutional Features of Mortgage Markets in Europe
Mortgage markets differ significantly across European countries in terms of both size and key institutional characteristics, such as the prevailing contractual arrangements and the available product range; these differences largely reflect national traditions and cultural factors, as well as the institutional settings of the local banking sector. The table summarizes some of the institutional indicators that have been identified in the literature as most likely to have a bearing on the relationship between housing wealth and consumption, as well as on the channels of monetary policy transmission. 1
The indicators included in the table are (1) average cost and time of mortgage enforcement procedures; (2) maximum LTV ratio; (3) typical mortgage contract duration; (4) type of interest rate structure; (5) diffusion of home equity release products; and (6) securitization.
Cross-country heterogeneity is pervasive in all indicators considered. In particular, LTV ratios vary significantly across countries, ranging between 50 percent in Italy and over 110 percent in the Netherlands. Overall, it is now typical for borrowers to have available loans worth 70–80 percent of the house value. Cross-country variations in these ratios partly reflect differences in legal and regulatory frameworks. The heterogeneity in terms of interest rate adjustment is also substantial across countries. Among the EU countries, the United Kingdom, Spain, and Ireland mainly have variable or adjustable rate mortgages. In contrast, Germany, France, Austria, Belgium, Denmark, and the Netherlands are mainly characterized by fixed rate mortgages.
Many of the mortgages offered in eastern Europe are foreign currency loans, and their increasing popularity—because their interest rates are lower than domestic currency mortgages—has brought even more dramatic convergence in the nominal interest rate on debt between eastern and western Europe. For example, Latvian and Polish mortgage rates are just over 1 percent above their German equivalent. In Poland, mortgage lending denominated in foreign currency accounted for approximately 60 percent of the stock of mortgages by mid-2005. Lending in foreign currency has also been rising very rapidly in Hungary, and reached almost 30 percent of the stock of lending by early 2006, up from only 1 percent in 2003. The overwhelming majority of new mortgages in Hungary have recently been in foreign currency—often denominated in Swiss francs.
Finally, an important element of divergence among national mortgage markets is the extent of recourse to home equity release. Following changes in house prices and mortgage interest rates, collateral-constrained agents can adjust their net borrowing positions or refinance the terms of their existing mortgages according to the changed conditions. For instance, following rises in house prices, borrowers may increase the amount of their mortgage loans or apply for a second mortgage against the increased value of their collateral. The released mortgage equity may subsequently be used for a variety of purposes, such as debt refinancing, acquisition of durable goods, purchase of financial assets, or home improvements. When mortgage interest rates decrease, agents may be willing to refinance their mortgages to take advantage of lower interest payments, to free liquidity for other expenditures; alternatively, they may want to increase their borrowing to reflect their increased debt-servicing capacity.
Overall, the use of home equity release remains limited in most countries, though mortgage equity extraction and refinancing have become significant at the aggregate level in a few (e.g., the United Kingdom and the Netherlands). In some cases, the limited recourse to home equity release may reflect scarce availability of suitable mortgage contracts (e.g., owing to regulatory constraints). However, in most countries borrowers are deterred from refinancing their contracts by administrative obstacles and prohibitive transaction costs. In such countries, mortgage lending is likely to interact with interest rate and house price developments only to a very limited extent (namely, for the new mortgage contracts only and not for the existing ones, which mostly reflect the market conditions prevailing at the time they were signed rather than current conditions).
Characteristics of National Mortgage Markets
Characteristics of National Mortgage Markets
| Mortgage Enforcement Procedures | Financial Sector Indicators | Mortgage Products | ||||||
|---|---|---|---|---|---|---|---|---|
| Administrative costs (percent) | Usual time required (months) | Maximum LTV (percent) | Typical mortgage maturity (years) | Typical rate structure (fixed/variable) | Equity withdrawal (yes/no) | Restriction on early repayment fees | Securitization (yes/no) | |
| Albania | … | … | 70-75 | 20 | Variable | Possible, but rarely used. | Commission of 2-5%. | No |
| Austria | … | 6 | 60-80 | 20-30 | Fixed | … | … | … |
| Belgium | 18.7 | 18 | 80-85 | 20 | Fixed | No | Max. 3-monthinterest on remaining loan. | Limited |
| Bosnia and Herzegovina | 1-1.7 | 18-60 | 75-100 | 10-20 | Variable | No | Fee set on bank-by-bank cases. | No |
| Bulgaria | … | … | 75-90 | 5-25 | Both | … | No | Yes |
| Croatia | … | … | 75 | 20 | Variable | … | … | No |
| Czech Republic | Limited | 10-12 | 70-100 | 20-25 | Fixed | No | Yes | No |
| Denmark | … | 6 | 80 | 30 | Fixed | Yes | No | Covered bonds. |
| Estonia | … | … | 90 | 20-30 | Variable | Yes | … | No |
| Finland | 2.5 | 2-3 | 75-80 | 15-20 | Variable | Yes | Creditor compensated for interest rate difference. | Limited |
| France | 7 | 15-25 | 80 | 15 | Fixed | Not used. | Fees limited to 6 month interest and 3% of balance. | Limited |
| Germany | 4.2 | 12 | 60-80; 60 for loansbacked by mortgage bonds. | 25-30 | Fixed | Not used. | Lender can seek compensation for forgone earnings within first 10 years. | Pfandbriefe |
| Greece | 16 | 3 | 70-80 | 15-20 | Variable | Yes, but limited use. | Usual fee equals 2.5% of remaining loan. | Limited |
| Hungary | … | … | 100 | 15 | Variable | Yes | No | No |
| Ireland | 8.6-10.6 | 11-14 | 90 | 20 | Variable | Yes, but limited use. | … | Limited |
| Israel | … | … | 60 | … | … | … | … | … |
| Italy | … | 60-84 | 50 | 10-25 | Mostly fixed for 1-5 years. | Not used. | No | No |
| Latvia | 3-15 | 24-36 | 100 since June 2008. | 20-40 | Variable | Yes | No explicit regulations. | Limited |
| Lithuania | 4-20 | 4-7 | 100 | 20-25 | Variable | Yes | No | No |
| Luxembourg | … | … | 80-100 | 20-25 | Variable | Not used. | … | Limited |
| Macedonia, FYR | Costs for auction fixed. | Approx. 6 months. | 65-100 | 20 | Varies. But variable rates are more prevalent. | … | No | No |
| Malta | … | … | 90 | <40 | Variable | Yes | No | No |
| Netherlands | 3 | 6 | 110-115 | 30 | Fixed | Yes | No | Yes |
| Norway | … | … | 80 | 15-20 | Variable | Yes | … | No |
| Poland | … | … | >100 | 20 | Variable | Possible, but rarely used. | Fees are allowed, but rarely used. | Yes, but used marginally. |
| Portugal | 8 | 18-30 | 90 | 15-30 | Variable | Not used. | Only for older contracts. | … |
| Romania | … | … | Central bank approves banks' credit policies. | 5-25 | Both | … | … | Yes |
| Russia | … | … | 85 | 10-30 | Both | … | … | Yes |
| Slovak Republic | … | … | 70 | 15 | Variable | Yes, but not used. | No | No |
| Spain | 17 | 7-9 | 80-100 | 15-25 | Variable | Yes, but limited use. | Max. 1% and 2.5% cancellation commission. | Yes |
| Sweden | 5 | 4-6 | 60-80 | <30 | Variable | Yes | None | Limited |
| Switzerland | 7-10 | 8-12 | 80 | 15 | Mixed | Yes | Yes | Yes |
| Turkey | … | … | 75 | 5-10 (longer maturities available but very rare). | Fixed | No | 2 percent maximum penalty. | Being developed. |
| Ukraine | … | 6-10 | 100 | >25 | Variable | … | … | Very limited |
| United Kingdom | 2.6-7 | 8-12 | 100 | 25 | variable | Yes | … | Yes |
Characteristics of National Mortgage Markets
| Mortgage Enforcement Procedures | Financial Sector Indicators | Mortgage Products | ||||||
|---|---|---|---|---|---|---|---|---|
| Administrative costs (percent) | Usual time required (months) | Maximum LTV (percent) | Typical mortgage maturity (years) | Typical rate structure (fixed/variable) | Equity withdrawal (yes/no) | Restriction on early repayment fees | Securitization (yes/no) | |
| Albania | … | … | 70-75 | 20 | Variable | Possible, but rarely used. | Commission of 2-5%. | No |
| Austria | … | 6 | 60-80 | 20-30 | Fixed | … | … | … |
| Belgium | 18.7 | 18 | 80-85 | 20 | Fixed | No | Max. 3-monthinterest on remaining loan. | Limited |
| Bosnia and Herzegovina | 1-1.7 | 18-60 | 75-100 | 10-20 | Variable | No | Fee set on bank-by-bank cases. | No |
| Bulgaria | … | … | 75-90 | 5-25 | Both | … | No | Yes |
| Croatia | … | … | 75 | 20 | Variable | … | … | No |
| Czech Republic | Limited | 10-12 | 70-100 | 20-25 | Fixed | No | Yes | No |
| Denmark | … | 6 | 80 | 30 | Fixed | Yes | No | Covered bonds. |
| Estonia | … | … | 90 | 20-30 | Variable | Yes | … | No |
| Finland | 2.5 | 2-3 | 75-80 | 15-20 | Variable | Yes | Creditor compensated for interest rate difference. | Limited |
| France | 7 | 15-25 | 80 | 15 | Fixed | Not used. | Fees limited to 6 month interest and 3% of balance. | Limited |
| Germany | 4.2 | 12 | 60-80; 60 for loansbacked by mortgage bonds. | 25-30 | Fixed | Not used. | Lender can seek compensation for forgone earnings within first 10 years. | Pfandbriefe |
| Greece | 16 | 3 | 70-80 | 15-20 | Variable | Yes, but limited use. | Usual fee equals 2.5% of remaining loan. | Limited |
| Hungary | … | … | 100 | 15 | Variable | Yes | No | No |
| Ireland | 8.6-10.6 | 11-14 | 90 | 20 | Variable | Yes, but limited use. | … | Limited |
| Israel | … | … | 60 | … | … | … | … | … |
| Italy | … | 60-84 | 50 | 10-25 | Mostly fixed for 1-5 years. | Not used. | No | No |
| Latvia | 3-15 | 24-36 | 100 since June 2008. | 20-40 | Variable | Yes | No explicit regulations. | Limited |
| Lithuania | 4-20 | 4-7 | 100 | 20-25 | Variable | Yes | No | No |
| Luxembourg | … | … | 80-100 | 20-25 | Variable | Not used. | … | Limited |
| Macedonia, FYR | Costs for auction fixed. | Approx. 6 months. | 65-100 | 20 | Varies. But variable rates are more prevalent. | … | No | No |
| Malta | … | … | 90 | <40 | Variable | Yes | No | No |
| Netherlands | 3 | 6 | 110-115 | 30 | Fixed | Yes | No | Yes |
| Norway | … | … | 80 | 15-20 | Variable | Yes | … | No |
| Poland | … | … | >100 | 20 | Variable | Possible, but rarely used. | Fees are allowed, but rarely used. | Yes, but used marginally. |
| Portugal | 8 | 18-30 | 90 | 15-30 | Variable | Not used. | Only for older contracts. | … |
| Romania | … | … | Central bank approves banks' credit policies. | 5-25 | Both | … | … | Yes |
| Russia | … | … | 85 | 10-30 | Both | … | … | Yes |
| Slovak Republic | … | … | 70 | 15 | Variable | Yes, but not used. | No | No |
| Spain | 17 | 7-9 | 80-100 | 15-25 | Variable | Yes, but limited use. | Max. 1% and 2.5% cancellation commission. | Yes |
| Sweden | 5 | 4-6 | 60-80 | <30 | Variable | Yes | None | Limited |
| Switzerland | 7-10 | 8-12 | 80 | 15 | Mixed | Yes | Yes | Yes |
| Turkey | … | … | 75 | 5-10 (longer maturities available but very rare). | Fixed | No | 2 percent maximum penalty. | Being developed. |
| Ukraine | … | 6-10 | 100 | >25 | Variable | … | … | Very limited |
| United Kingdom | 2.6-7 | 8-12 | 100 | 25 | variable | Yes | … | Yes |
The correlation between private consumption and house price fluctuations over the cycle is found to be related to mortgage market characteristics, with that correlation larger in those countries where mortgage refinancing is feasible and variable rate contracts are more common. In addition, the size of the peak effect of a monetary policy shock on consumption and real house prices appears to be positively related to the mortgage debt–to-GDP ratio, the LTV ratio, and the existence of equity release products. The evidence that private consumption is more responsive to monetary impulses in economies with more developed mortgage markets is due to the presence of collateralized borrowing, as private borrowing is constrained by the value of the collateral. That value is endogenously tied to the evolution of the nominal price of housing. Thus, in a context where housing credit markets can more easily convert asset values into borrowing and, therefore, spending, consumption is likely to be more sensitive to underlying financial shocks (Figure 24).
Borrowing Against Collateral in the Mortgage Market, 2002–06
Sources: Bloomberg L.P.; Bank for International Settlements; and IMF staff calculations.Note: Country names are abbreviated according to the ISO standard codes.. . . and in the Corporate Sector
Do similar conclusions hold true with respect to the relationship between private investment and equity price fluctuations over the cycle? Does the responsiveness of capital accumulation to shifts in credit conditions and asset prices differ on a country-by-country basis, depending on the level of development of each country’s corporate finance market? Given the remarkable importance of bank lending for European corporate financing (see footnote 30) and the extent of cross-country divergences in corporate financial positions, these questions are of considerable relevance. In order to address these issues, a macroeconomic model of a stylized two-country economy is developed to illustrate how the double role of equities—as collateral in the (international) lending process and as value of the capital used for production—may affect the volatility of investment, corporate debt, and the current account.35 This model captures the idea that observed cross-country differences in investment and current account dynamics may be consistent with the fact that lending conditions and discount factors are not symmetric across countries. This is achieved by assuming that in one of the two economies agents are credit constrained and “impatient”: that is, they do not smooth consumption based on permanent income, but have preferences tilted toward current consumption. Their access to credit on international financial markets is constrained by the value of their collateral, which is endogenously tied to the evolution of equity prices.36 A more developed financial market is represented by a higher borrowing limit (LTV = 0.7)—a parameter that determines the extent to which capital can be used as collateral for borrowing to invest and to produce goods. Despite its stylized nature, this structural model is consistent with the empirical findings that investment and current account dynamics are more responsive to changes in financial conditions in economies with less developed corporate financing. In economies with lower borrowing limits (LTV = 0.4)—as equity prices have fallen following either a technology shock or an exogenous tightening to the lending standard—impatient agents see their borrowing curtailed more against the declining value of their collateral, and are thus able to borrow less against collateral for any given value of their capital, compared with those in economies with higher borrowing limits (Figure 25). Although the model is highly stylized—abstracting from many factors affecting monetary policy decisions—the exercise is nevertheless instructive: it provides some insight into how macroeconomic volatility varies according to the characteristics of financial markets in economies where firms’ borrowing limits are tied to collateral values and where agents do not behave in the farsighted way that is more traditionally supposed.
The Financial Accelerator in Economies Characterized by Different Borrowing Limits: Impulse Response Functions to an Adverse Shock to Underlying Productivity
(Percent deviations from baseline)
Source: Gruss and Sgherri (forthcoming).From Financial Conditions to the Macroeconomy
To examine more closely the dynamic relationship between corporate financial conditions and real activity and to understand what drives divergences in the strength and in the timing of macrofinancial linkages across European countries, financial conditions indices (FCIs) for the corporate sector of 16 advanced and 12 emerging European economies have been constructed by means of vector autoregression and impulse response functions (Figure 26 and Table 6). National FCIs are meant to account for the timing of transmission from financial markets to real activity and to incorporate the endogenous response of financial variables to the business cycle, as well as to each other.37 Allowing for these dynamic interrelations is important when attempting to disentangle the impact of multiple variables that are highly correlated.
Financial Conditions Indices for the Corporate Sector: Dynamics and Contributions, 2003–08
(Percentage points of year-on-year real GDP growth, unless otherwise noted)
Sources: IMF, International Financial Statistics ; Haver Analytics; national authorities; and IMF staff calculations.Selected European Countries: Financial Conditions and Real Activity: Correlations and Variance Decompositions
Selected European Countries: Financial Conditions and Real Activity: Correlations and Variance Decompositions
| Correlation with Overall FCI | Correlation with Output Growth | Variance Decomposition Output Growth | ||
|---|---|---|---|---|
| Financial Variable (Contribution to FCI) | (Latest cycle) | (Latest cycle) | (One year ahead) | |
| Austria | ||||
| Overall/leading FCI | 1 | 0.70/0.73 | 51 | |
| Credit | 0.56 | 0.16 | 39.5 | |
| Equity prices | -0.31 | 0.05 | 9.3 | |
| Interest rate | 0.82 | 0.76 | 2.2 | |
| Belgium | ||||
| Overall/leading FCI | 1 | 0.11/0.27 | 11.4 | |
| Credit | 0.95 | 0.11 | 1.7 | |
| Equity prices | -0.38 | 0.27 | 0.1 | |
| Interest rate | 0.57 | 0.24 | 9.6 | |
| Denmark | ||||
| Overall/leading FCI | 1 | -0.24/0.41 | 22.2 | |
| Credit | 0.41 | 0.3 | 0.2 | |
| Equity prices | 0.66 | -0.09 | 6.9 | |
| Interest rate | -0.47 | 0.53 | 15.1 | |
| Finland | ||||
| Overall/leading FCI | 1 | 0.00/0.33 | 45.7 | |
| Credit | 0.56 | -0.36 | 1.8 | |
| Equity prices | 0.56 | 0.33 | 37.5 | |
| Interest rate | -0.09 | 0.1 | 6.5 | |
| France | ||||
| Overall/leading FCI | 1 | 0.27/0.55 | 38.9 | |
| Credit | 0.18 | -0.01 | 0.9 | |
| Equity prices | 0.65 | 0.61 | 37.9 | |
| Interest rate | -0.35 | -0.38 | 0.1 | |
| Germany | ||||
| Overall/leading FCI | 1 | 0.09/0.02 | 21.4 | |
| Credit | 0.36 | 0.08 | 4.8 | |
| Equity prices | 0.73 | -0.04 | 10 | |
| Interest rate | -0.19 | 0.16 | 6.6 | |
| Greece | ||||
| Overall/leading FCI | 1 | 0.24/0.23 | 25.3 | |
| Credit | 0.58 | 0.54 | 9.7 | |
| Equity prices | 0.59 | 0.03 | 14.4 | |
| Interest rate | -0.14 | -0.33 | 1.2 | |
| Ireland | ||||
| Overall/leading FCI | 1 | 0.09/-0.10 | 10.3 | |
| Credit | 0.2 | 0.58 | 2.2 | |
| Equity prices | -0.17 | -0.31 | 2.2 | |
| Interest rate | 0.73 | -0.14 | 5.9 | |
| Italy | ||||
| Overall/leading FCI | 1 | -0.15/0.19 | 21.6 | |
| Credit | 0.75 | 0.13 | 0.2 | |
| Equity prices | 0.04 | 0.1 | 21.1 | |
| Interest rate | -0.1 | -0.28 | 0.2 | |
| Netherlands | ||||
| Overall/leading FCI | 1 | 0.21/0.48 | 40 | |
| Credit | 0.57 | 0.43 | 0.2 | |
| Equity prices | 0.54 | 0.56 | 37.3 | |
| Interest rate | 0.37 | -0.43 | 2.5 | |
| Norway | ||||
| Overall/leading FCI | 1 | 0.58/0.04 | 27.1 | |
| Credit | 0.66 | 0.22 | 2.6 | |
| Equity prices | 0.84 | 0.52 | 19.8 | |
| Interest rate | -0.34 | -0.37 | 4.7 | |
| Portugal | ||||
| Overall/leading FCI | 1 | 0.39/0.68 | 17.5 | |
| Credit | 0.54 | -0.12 | 0.4 | |
| Equity prices | 0.66 | 0.62 | 10.3 | |
| Interest rate | 0.21 | 0.61 | 6.8 | |
| Slovenia | ||||
| Overall/leading FCI | 1 | 0.40/0.35 | 43 | |
| Credit | -0.13 | 0.07 | 12.4 | |
| Equity prices | 0.62 | 0.17 | 8.2 | |
| Interest rate | 0.51 | 0.25 | 22.5 | |
| Spain | ||||
| Overall/leading FCI | 1 | -0.34/-0.44 | 10.7 | |
| Credit | 0.32 | 0.09 | 3.4 | |
| Equity prices | 0.55 | -0.51 | 3.8 | |
| Interest rate | -0.33 | -0.05 | 3.5 | |
| Sweden | ||||
| Overall/leading FCI | 1 | 0.31/0.50 | 55.6 | |
| Credit | 0.83 | 0.45 | 23.1 | |
| Equity prices | 0.66 | 0.04 | 8 | |
| Interest rate | 0.03 | 0.26 | 24.4 | |
| Switzerland | ||||
| Overall/leading FCI | 1 | 0.57/0.50 | 21.1 | |
| Credit | 0.18 | -0.09 | 5.1 | |
| Equity prices | 0.47 | 0.76 | 5.5 | |
| Interest rate | 0.23 | -0.15 | 10.6 | |
| United Kingdom | ||||
| Overall/leading FCI | 1 | 0.68/0.70 | 30.1 | |
| Credit | 0.31 | 0.09 | 11.4 | |
| Equity prices | 0.6 | 0.5 | 18 | |
| Interest rate | 0.04 | 0.34 | 0.7 | |
| Bulgaria | ||||
| Overall/leading FCI | 1 | 0.14/0.43 | 49.4 | |
| Credit | 0 | 0.13 | 1.2 | |
| Equity prices | 0.23 | -0.25 | 4.3 | |
| Interest rate | 0.52 | 0.43 | 44 | |
| Croatia | ||||
| Overall/leading FCI | 1 | 0.47/0.40 | 23.4 | |
| Credit | 0.53 | 0.2 | 6.3 | |
| Equity prices | 0.77 | 0.38 | 4.8 | |
| Interest rate | 0.11 | 0.25 | 12.3 | |
| Czech Republic | ||||
| Overall/leading FCI | 1 | -0.1/-0.24 | 20.9 | |
| Credit | 0.32 | 0 | 0.7 | |
| Equity prices | 0.34 | -0.24 | 19.6 | |
| Interest rate | -0.05 | -0.24 | 0.6 | |
| Estonia | ||||
| Overall/leading FCI | 1 | 0.27/0.47 | 72.9 | |
| Credit | 0.08 | 0.6 | 15.5 | |
| Equity prices | 0.83 | -0.08 | 41.2 | |
| Interest rate | 0.47 | 0.58 | 16.2 | |
| Hungary | ||||
| Overall/leading FCI | 1 | 0.26/0.04 | 80.9 | |
| Credit | -0.21 | 0.17 | 8.4 | |
| Equity prices | -0.49 | -0.79 | 7.5 | |
| Interest rate | 0.44 | 0.6 | 64.9 | |
| Latvia | ||||
| Overall/leading FCI | 1 | 0.66/0.67 | 72.4 | |
| Credit | 0.63 | 0.74 | 35.7 | |
| Equity prices | 0.05 | 0.14 | 35 | |
| Interest rate | 0.21 | 0.29 | 1.7 | |
| Lithuania | ||||
| Overall/leading FCI | 1 | 0.37/0.46 | 55.3 | |
| Credit | 0.29 | 0.36 | 30.9 | |
| Equity prices | 0.36 | 0.21 | 20.5 | |
| Interest rate | 0.43 | 0.07 | 3.9 | |
| Poland | ||||
| Overall/leading FCI | 1 | -0.25/0.01 | 35.5 | |
| Credit | 0.56 | 0.13 | 0.7 | |
| Equity prices | 0.12 | 0.56 | 12.8 | |
| Interest rate | 0.23 | -0.81 | 22 | |
| Russia | ||||
| Overall/leading FCI | 1 | 0.42/0.57 | 78.1 | |
| Credit | 0.55 | 0.67 | 39.3 | |
| Equity prices | 0.57 | 0.35 | 1.2 | |
| Interest rate | 0.51 | 0.4 | 37.6 | |
| Slovak Republic | ||||
| Overall/leading FCI | 1 | -0.59/-0.40 | 16 | |
| Credit | 0.39 | -0.06 | 9.3 | |
| Equity prices | 0.1 | -0.1 | 3.3 | |
| Interest rate | 0.34 | -0.66 | 3.4 | |
| Turkey | ||||
| Overall/leading FCI | 1 | 0.32/0.37 | 32.9 | |
| Credit | 0.9 | 0.31 | 23.3 | |
| Equity prices | 0.45 | 0.53 | 0.7 | |
| Interest rate | -0.34 | -0.21 | 8.9 | |
Selected European Countries: Financial Conditions and Real Activity: Correlations and Variance Decompositions
| Correlation with Overall FCI | Correlation with Output Growth | Variance Decomposition Output Growth | ||
|---|---|---|---|---|
| Financial Variable (Contribution to FCI) | (Latest cycle) | (Latest cycle) | (One year ahead) | |
| Austria | ||||
| Overall/leading FCI | 1 | 0.70/0.73 | 51 | |
| Credit | 0.56 | 0.16 | 39.5 | |
| Equity prices | -0.31 | 0.05 | 9.3 | |
| Interest rate | 0.82 | 0.76 | 2.2 | |
| Belgium | ||||
| Overall/leading FCI | 1 | 0.11/0.27 | 11.4 | |
| Credit | 0.95 | 0.11 | 1.7 | |
| Equity prices | -0.38 | 0.27 | 0.1 | |
| Interest rate | 0.57 | 0.24 | 9.6 | |
| Denmark | ||||
| Overall/leading FCI | 1 | -0.24/0.41 | 22.2 | |
| Credit | 0.41 | 0.3 | 0.2 | |
| Equity prices | 0.66 | -0.09 | 6.9 | |
| Interest rate | -0.47 | 0.53 | 15.1 | |
| Finland | ||||
| Overall/leading FCI | 1 | 0.00/0.33 | 45.7 | |
| Credit | 0.56 | -0.36 | 1.8 | |
| Equity prices | 0.56 | 0.33 | 37.5 | |
| Interest rate | -0.09 | 0.1 | 6.5 | |
| France | ||||
| Overall/leading FCI | 1 | 0.27/0.55 | 38.9 | |
| Credit | 0.18 | -0.01 | 0.9 | |
| Equity prices | 0.65 | 0.61 | 37.9 | |
| Interest rate | -0.35 | -0.38 | 0.1 | |
| Germany | ||||
| Overall/leading FCI | 1 | 0.09/0.02 | 21.4 | |
| Credit | 0.36 | 0.08 | 4.8 | |
| Equity prices | 0.73 | -0.04 | 10 | |
| Interest rate | -0.19 | 0.16 | 6.6 | |
| Greece | ||||
| Overall/leading FCI | 1 | 0.24/0.23 | 25.3 | |
| Credit | 0.58 | 0.54 | 9.7 | |
| Equity prices | 0.59 | 0.03 | 14.4 | |
| Interest rate | -0.14 | -0.33 | 1.2 | |
| Ireland | ||||
| Overall/leading FCI | 1 | 0.09/-0.10 | 10.3 | |
| Credit | 0.2 | 0.58 | 2.2 | |
| Equity prices | -0.17 | -0.31 | 2.2 | |
| Interest rate | 0.73 | -0.14 | 5.9 | |
| Italy | ||||
| Overall/leading FCI | 1 | -0.15/0.19 | 21.6 | |
| Credit | 0.75 | 0.13 | 0.2 | |
| Equity prices | 0.04 | 0.1 | 21.1 | |
| Interest rate | -0.1 | -0.28 | 0.2 | |
| Netherlands | ||||
| Overall/leading FCI | 1 | 0.21/0.48 | 40 | |
| Credit | 0.57 | 0.43 | 0.2 | |
| Equity prices | 0.54 | 0.56 | 37.3 | |
| Interest rate | 0.37 | -0.43 | 2.5 | |
| Norway | ||||
| Overall/leading FCI | 1 | 0.58/0.04 | 27.1 | |
| Credit | 0.66 | 0.22 | 2.6 | |
| Equity prices | 0.84 | 0.52 | 19.8 | |
| Interest rate | -0.34 | -0.37 | 4.7 | |
| Portugal | ||||
| Overall/leading FCI | 1 | 0.39/0.68 | 17.5 | |
| Credit | 0.54 | -0.12 | 0.4 | |
| Equity prices | 0.66 | 0.62 | 10.3 | |
| Interest rate | 0.21 | 0.61 | 6.8 | |
| Slovenia | ||||
| Overall/leading FCI | 1 | 0.40/0.35 | 43 | |
| Credit | -0.13 | 0.07 | 12.4 | |
| Equity prices | 0.62 | 0.17 | 8.2 | |
| Interest rate | 0.51 | 0.25 | 22.5 | |
| Spain | ||||
| Overall/leading FCI | 1 | -0.34/-0.44 | 10.7 | |
| Credit | 0.32 | 0.09 | 3.4 | |
| Equity prices | 0.55 | -0.51 | 3.8 | |
| Interest rate | -0.33 | -0.05 | 3.5 | |
| Sweden | ||||
| Overall/leading FCI | 1 | 0.31/0.50 | 55.6 | |
| Credit | 0.83 | 0.45 | 23.1 | |
| Equity prices | 0.66 | 0.04 | 8 | |
| Interest rate | 0.03 | 0.26 | 24.4 | |
| Switzerland | ||||
| Overall/leading FCI | 1 | 0.57/0.50 | 21.1 | |
| Credit | 0.18 | -0.09 | 5.1 | |
| Equity prices | 0.47 | 0.76 | 5.5 | |
| Interest rate | 0.23 | -0.15 | 10.6 | |
| United Kingdom | ||||
| Overall/leading FCI | 1 | 0.68/0.70 | 30.1 | |
| Credit | 0.31 | 0.09 | 11.4 | |
| Equity prices | 0.6 | 0.5 | 18 | |
| Interest rate | 0.04 | 0.34 | 0.7 | |
| Bulgaria | ||||
| Overall/leading FCI | 1 | 0.14/0.43 | 49.4 | |
| Credit | 0 | 0.13 | 1.2 | |
| Equity prices | 0.23 | -0.25 | 4.3 | |
| Interest rate | 0.52 | 0.43 | 44 | |
| Croatia | ||||
| Overall/leading FCI | 1 | 0.47/0.40 | 23.4 | |
| Credit | 0.53 | 0.2 | 6.3 | |
| Equity prices | 0.77 | 0.38 | 4.8 | |
| Interest rate | 0.11 | 0.25 | 12.3 | |
| Czech Republic | ||||
| Overall/leading FCI | 1 | -0.1/-0.24 | 20.9 | |
| Credit | 0.32 | 0 | 0.7 | |
| Equity prices | 0.34 | -0.24 | 19.6 | |
| Interest rate | -0.05 | -0.24 | 0.6 | |
| Estonia | ||||
| Overall/leading FCI | 1 | 0.27/0.47 | 72.9 | |
| Credit | 0.08 | 0.6 | 15.5 | |
| Equity prices | 0.83 | -0.08 | 41.2 | |
| Interest rate | 0.47 | 0.58 | 16.2 | |
| Hungary | ||||
| Overall/leading FCI | 1 | 0.26/0.04 | 80.9 | |
| Credit | -0.21 | 0.17 | 8.4 | |
| Equity prices | -0.49 | -0.79 | 7.5 | |
| Interest rate | 0.44 | 0.6 | 64.9 | |
| Latvia | ||||
| Overall/leading FCI | 1 | 0.66/0.67 | 72.4 | |
| Credit | 0.63 | 0.74 | 35.7 | |
| Equity prices | 0.05 | 0.14 | 35 | |
| Interest rate | 0.21 | 0.29 | 1.7 | |
| Lithuania | ||||
| Overall/leading FCI | 1 | 0.37/0.46 | 55.3 | |
| Credit | 0.29 | 0.36 | 30.9 | |
| Equity prices | 0.36 | 0.21 | 20.5 | |
| Interest rate | 0.43 | 0.07 | 3.9 | |
| Poland | ||||
| Overall/leading FCI | 1 | -0.25/0.01 | 35.5 | |
| Credit | 0.56 | 0.13 | 0.7 | |
| Equity prices | 0.12 | 0.56 | 12.8 | |
| Interest rate | 0.23 | -0.81 | 22 | |
| Russia | ||||
| Overall/leading FCI | 1 | 0.42/0.57 | 78.1 | |
| Credit | 0.55 | 0.67 | 39.3 | |
| Equity prices | 0.57 | 0.35 | 1.2 | |
| Interest rate | 0.51 | 0.4 | 37.6 | |
| Slovak Republic | ||||
| Overall/leading FCI | 1 | -0.59/-0.40 | 16 | |
| Credit | 0.39 | -0.06 | 9.3 | |
| Equity prices | 0.1 | -0.1 | 3.3 | |
| Interest rate | 0.34 | -0.66 | 3.4 | |
| Turkey | ||||
| Overall/leading FCI | 1 | 0.32/0.37 | 32.9 | |
| Credit | 0.9 | 0.31 | 23.3 | |
| Equity prices | 0.45 | 0.53 | 0.7 | |
| Interest rate | -0.34 | -0.21 | 8.9 | |
For each economy, the estimated FCI contains statistically significant effects on GDP growth from shocks to domestic (real) credit growth, (real) equity prices, and (real) interest rates.38
Specifically, impulse responses from these financial variables are combined with estimates of the shocks to each of these variables to calculate the total impulse to growth in a given month. As the FCI contains information from three financial shocks over a period of 12 months preceding the month in which GDP is measured, it also appears to be an important leading indicator of real GDP growth. Measurement of the FCI in terms of its contribution to growth means that both the level of the index and the direction of its changes have implications for economic activity. For example, a value of 1 means that the total impulse of financial conditions to GDP in a given quarter is 1 percentage point, annualized. A decline from 1 to ½ implies that financial conditions are expected to erode ½ percentage point from growth, although the total contribution to growth remains positive. In this way, it is possible to distinguish between tight financial conditions and a tightening in financial conditions that are, however, still accommodative.
Estimated FCIs appear to account for a substantial portion of the variation in real GDP growth over the business cycle of almost all European countries in the sample (Figure 27). Turning to the role of individual financial variables, credit is found—among the advanced economies—to have contributed substantially to annual growth in Austria (40 percent), Sweden (25 percent), and, to a lesser extent, the United Kingdom and Greece (10 percent). Changes in equity prices explain 40 percent of growth variation in Finland, France, and the Netherlands, while interest rate variations play an important role in Sweden and Denmark. Among emerging economies, financial conditions play—overall—a much greater role. They account for over 70 percent of growth variation in Hungary, Russia, Latvia, and Estonia, underscoring, once again, the vulnerability of these economies’ corporate sector to downswings in financing conditions.
Share of Output Variation Explained by Credit and Asset Price Shocks
(Percent)
Sources: IMF, International Financial Statistics ; Haver Analytics; national authorities; and IMF staff calculations.Looking at the path of FCIs over time corroborates the view that, by end-2007, the financial cycle had already turned in most advanced European economies. However, financial conditions appear to be generally still accommodative in the region, with few exceptions (Figure 26). In emerging Europe, the tightening in credit conditions seems—on balance—to have started earlier, over the course of 2006, and to have already begun crunching into growth in a few countries. On the other hand—and in contrast to the prevailing trend in international credit markets—Turkey, Poland, and the Slovak Republic appear to enjoy rather favorable financing conditions, sustaining growth in these economies.
Are country-specific financial conditions co-moving with the cycle? In which countries are lending conditions more responsive to underlying shocks to asset prices? Once again, the answers vary on a country-by-country basis (Table 6). Some empirical regularities can, however, be identified. First, credit growth tends to be more sensitive to changes in asset prices in those economies where the firms’ leverage tend to co-move more closely with the business cycle (Figure 28). Second, a higher degree of procyclicality in firms’ leverage seems to be associated with higher volatility in private investment (Figure 29). Remarkably—and in line with the findings of the theoretical model economy described above—oversensitivity of credit availability to asset price changes, greater procyclicality in firms’ leverage, and higher investment volatility appear to be features mostly characterizing the least advanced financial markets in the sample. This finding corroborates the idea that, in a context in which firms’ financing conditions are more stringent, capital accumulation—and, therefore, production—appears to be more responsive to the underlying financial shocks, which may affect the value of collaterals.
Cyclicality of Lending and Sensitivity of Credit Growth to Changes in Asset Prices, 2003–08
Sources: IMF, International Financial Statistics ; Haver Analytics; national authorities; and IMF staff calculations.Note: Country names are abbreviated according to the ISO standard codes.Cyclicality of Lending and Macroeconomic Volatility, 2003–08
Sources: IMF, International Financial Statistics ; Haver Analytics; national authorities; and IMF staff calculations.Note: Country names are abbreviated according to the ISO standard codes.Cross-Border Lending: Further Benefits and Risks
Financial systems in advanced and emerging economies of Europe have undergone remarkable changes over the past decade. Cross-border ownership of assets has increased, revealing not only important benefits associated with financial integration, but also new risks.
Greater financial integration has clearly shown its ability to disperse claims to a broader range of portfolios, so that risks are better spread. In particular, financial integration holds great potential to smooth incomes through cross-border asset diversification, and thus stabilize the economy in the face of asymmetric shocks. Empirical work on the United States estimates that two-fifths of the income effect from local shocks is smoothed away through asset holdings across state lines. A similar analysis for European countries shows that, since 1999, risk sharing has also begun to emerge across these economies, although the extent to which financial integration is able to insure incomes against country-specific shocks is still limited (with estimates below 10 percent in all regions) and uneven across regions (Figure 30).39
Measuring Risk Sharing across European Countries
(Percent)
Sources: Eurostat; IMF, World Economic Outlook; and IMF staff calculations.Note: Advanced = Austria, Belgium, Denmark, Greece, Finland, France, Germany, Ireland, Italy, Netherlands, Norway, Portugal, Slovenia, Spain, Sweden, Switzerland, and the United Kingdom; central-eastern Europe = the Czech Republic, Hungary, Poland, and the Slovak Republic; Baltics = Estonia, Latvia, and Lithuania; southeastern Europe = Albania, Bosnia and Herzegovina, Bulgaria, Croatia, FYR Macedonia, Moldova, Romania, and Serbia; other emerging markets = Russia, Turkey, and Ukraine.Adjusting well to shocks means having a system that is not only resilient but also reallocates resources more efficiently across sectors and across firms, thereby fostering growth. Also, improved, risk-adjusted growth opportunities appear to be related to future advances in integration. This empirical regularity indicates that the countries whose integration has been faster benefit most from a virtuous dynamic in which financial integration and improved real prospects are mutually reinforcing. Europe is found to be the region that has benefited the most from such dynamics (see Box 11).
Financial Integration and Growth: Are They Related, and How?
Theory predicts that financial integration should bring about beneficial real effects resulting from a more efficient resource allocation. A recent IMF study finds that advances in financial integration are indeed associated with better growth opportunities, and the effect is stronger in countries where the process of integration is faster.1 Europe is the region that appears to have integrated the fastest, reaping the largest real gains in the process. The study also finds that some of the channels through which financial integration affects growth include faster globalization and financial market development, and higher liquidity.
Measuring the advances in financial integration as a degree of cross-country convergence in equity premiums (following Adjaouté and Danthine, 2004), the analysis indicates the following:
-
Financial integration has increased worldwide, but especially so in emerging markets. Regional integration has proceeded faster in Europe, including in emerging Europe.
-
The faster rate of financial integration has been associated with higher subsequent risk-adjusted growth.2 At the same time, improved risk-adjusted growth opportunities have been related to future advances in integration. This indicates that the countries whose integration has been faster benefit most from a virtuous dynamics, in which financial integration and improved real prospects are mutually reinforcing. Europe is the region that has benefited the most from such dynamics.
In addition, the investigation of possible channels through which advances in financial integration might affect growth finds the following:
-
Financial integration fosters globalization and financial development, and boosts market liquidity.
-
Coupled with findings in other studies that relate globalization and growth (Bekaert, Harvey, and Lundblad, 2005) and liquidity and growth (De Nicolò and Ivaschenko, 2008), these results suggest that globalization and liquidity are two of the channels through which the benefits of integration translate into higher real growth.
At the same time, though, financial integration poses new challenges to market investors and policymakers. Cross-border ownership of assets exposes financial institutions such as banks to macroeconomic, financial, and asset price fluctuations in the countries where they hold positions. Increasingly complex linkages across market segments and borders make the transmission of shocks in the international economy and the pattern of risk dispersion more opaque, creating uncertainty for agents and policymakers about where the ultimate risks lie.
In order to shed light on potential international spillovers and the feedback between the real and the financial sectors, it is crucial to look into the time profile of the cross-country transmission of financial shocks, while explicitly accounting for regional interdependencies.40 In this perspective, country-specific vector error-correction models are estimated, where the domestic macroeconomic variables are related to the corresponding foreign variables constructed exclusively to match the international financial flows of the country under consideration. The individual country models are then combined consistently and cohesively to generate predictions for all the variables in the world economy simultaneously. The resulting global vector autoregressive (GVAR) model is estimated for 28 European countries, grouped into 6 regions plus the United States, using monthly data on real GDP growth, real growth in credit to the corporate sector, real equity prices, and real interest rates from January 1999 to March 2008.
Looking at generalized impulse response functions for an exogenous one-standard-error negative shock to U.S. equity prices (equivalent to a fall of around 4¼ percent in U.S. real equity prices, annualized) confirms the significant interdependence of international equity markets (with the exception of southeastern European markets) and strong financial co-movements between credit conditions in Baltic countries and non euro–area advanced economies (namely, Sweden). Interestingly—and consistent with results in previous sections—empirical evidence from the GVAR seems to support the view of a decoupling between credit conditions in advanced economies and those in selected emerging European markets (e.g., Turkey and Russia) and central-eastern Europe, in the face of a common adverse shock stemming from U.S. financial markets (Figure 31).
Measuring Cross-Border Financial Spillovers: Response of Financial Variable to a One-Standard-Error Reduction in U.S. Equity Prices
(Percent)
Sources: IMF, International Financial Statistics ; Haver Analytics; national authorities; and IMF staff calculations. See Galesi and Sgherri (forthcoming) for detail.Note: Central-eastern Europe = the Czech Republic, Hungary, Poland, and the Slovak Republic; Baltic countries = Estonia, Latvia, and Lithuania; southeastern European countries = Albania, Bosnia and Herzegovina, Bulgaria, Croatia, FYR Macedonia, Moldova, Romania, and Serbia; other emerging market economies = Russia, Turkey, and Ukraine; Euro area = Austria, Belgium, Greece, Finland, France, Germany, Ireland, Italy, Netherlands, Portugal, Slovenia, and Spain; other developed European economies = Denmark, Norway, Sweden, Switzerland, and the United Kingdom.How does the evidence of significant financial spillovers affect conclusions on macrofinancial linkages? Ultimately, does financial integration weaken or reinforce the relationship between the procyclicality of firms’ leverage and macroeconomic volatility? Using GVAR estimates for calibration purposes shows that significant financial cross-border spillovers have the potential to amplify the macroeconomic effects of leverage procyclicality, though only marginally. In other words, all else being equal, an increase in the procyclicality of lending behavior might boost investment (and output) volatility even further in the presence of financial cross-border spillovers than it would do in their absence (Table 7).
Increase in Volatility Due to a Rise in the Procyclicality of Lending with and without Financial Cross-Border Spillovers
(Percent)
Percent increase in the volatility of each aggregate following a rise in the degree of correlation between lending and asset prices from 0 to 0.5.
As contribution to growth.
As a ratio to GDP.
Increase in Volatility Due to a Rise in the Procyclicality of Lending with and without Financial Cross-Border Spillovers
(Percent)
| Percentage Increase in Volatility 1/ | Real GDP | Consumption 2/ | Investment 2/ | Trade Balance 3/ | Current Account 3/ | Debt-to-GDP Ratio | Real Exchange Rate |
|---|---|---|---|---|---|---|---|
| Without spillovers | 3.2 | 20.9 | 20.2 | 20.8 | 20.7 | 22.7 | 18.5 |
| With spillovers | 3.5 | 20.7 | 20.3 | 20.9 | 20.5 | 22.4 | 18.0 |
Percent increase in the volatility of each aggregate following a rise in the degree of correlation between lending and asset prices from 0 to 0.5.
As contribution to growth.
As a ratio to GDP.
Increase in Volatility Due to a Rise in the Procyclicality of Lending with and without Financial Cross-Border Spillovers
(Percent)
| Percentage Increase in Volatility 1/ | Real GDP | Consumption 2/ | Investment 2/ | Trade Balance 3/ | Current Account 3/ | Debt-to-GDP Ratio | Real Exchange Rate |
|---|---|---|---|---|---|---|---|
| Without spillovers | 3.2 | 20.9 | 20.2 | 20.8 | 20.7 | 22.7 | 18.5 |
| With spillovers | 3.5 | 20.7 | 20.3 | 20.9 | 20.5 | 22.4 | 18.0 |
Percent increase in the volatility of each aggregate following a rise in the degree of correlation between lending and asset prices from 0 to 0.5.
As contribution to growth.
As a ratio to GDP.
What Are the Implications for Policy?
The empirical analysis carried out in this chapter suggests that domestic asset price dynamics are likely to reinforce economic boom-bust dynamics. Specifically, the rapid growth of asset prices, particularly stocks and real estate prices, during booms raises the value of collateral, thus stimulating credit growth. Speculation on price swings will also become an additional source of demand for credit. In turn, the resulting wealth effects accentuate the spending boom. This process is further reinforced by the greater liquidity that characterizes fixed assets during periods of financial euphoria. However, this behavior also increases the vulnerability of the financial system during the subsequent downswing, when it becomes clear that the loans did not have adequate backing. Asset price deflation will be reinforced as debtors strive to cover their financial obligations and creditors seek to liquidate the assets received in payment for outstanding debts, in conditions of reduced asset liquidity.
The basic problem in this regard is the inability of individual financial intermediaries to internalize the collective risks assumed during boom periods. This is because these risks are essentially of a macroeconomic character and therefore entail coordination problems that exceed the capabilities of any one agent. Moreover, risk assessment and traditional regulatory tools tend to have a potential procyclical bias in the way they operate.41 The traditional focus on microeconomic risk assessment, with inadequate attention paid to the effects of external financial cycles on domestic financial markets, and on exchange and interest rates, further reinforces this bias. In fact, it is during crises that the excess of risk assumed during economic booms becomes evident and ultimately makes it necessary to write off loan portfolios. In a system where loan loss provisions are tied to loan delinquency, the sharp increase in such delinquency during crises reduces financial institutions’ capital and, hence, their lending capacity. This, in conjunction with the greater perceived level of risk, triggers the credit squeeze that characterizes such periods, further reinforcing the downswing in economic activity and asset prices, and thus the quality of the portfolios of financial intermediaries.
To mitigate these cyclical effects, some supervisors (for example, in Spain) have advocated (and implemented) the use of countercyclical provisioning methodologies (sometimes referred to as “dynamic” or “statistical”), which require banks to provision more (than evidenced by losses) in good times, when the identified need for provisioning is smaller, and draw against these reserves in bad times, when the need for provisions is larger. Given the interaction between provisions and capital, it is argued that such forward-looking provisioning methods could reduce the procyclicality of regulatory requirements (see Box 12).
Countercyclical Credit Risk Provisioning: The Spanish Experience
Conceptually, the framework for bank credit risk management views provisions as covering “expected losses,” and capital as covering “unexpected losses.” These provisions can either be “specific” or “general” (depending on whether they are related or unrelated to any specific loans or impairments). Risk-based bank capital regulations can have a procyclical propensity—in a downturn, as credit risks are heightened, capital requirements increase and banks may resort to reduced lending, accentuating the downturn. Provisioning requirements for credit risk may also be similarly procyclical—as credit losses mount in a downturn, banks may be required to provision more. This in turn reduces the earnings, thus affecting banks’ ability to bolster their capital. To mitigate these cyclical effects, some supervisors have advocated (and implemented) the use of countercyclical provisioning methodologies (sometimes referred to as “dynamic” or “statistical”), which require banks to provision more (than evidenced by losses) in good times, when the identified need for provisioning is small, and draw against these reserves in bad times, when the need for provisions is larger. Given the interaction between provisions and capital, such forward-looking provisioning methods could reduce the procyclicality of regulatory requirements.
In practice, while the use of ad hoc countercyclical methods is not uncommon—for instance, through a temporary increase of provisioning or risk-weight requirements in the face of rapid credit growth—few countries use full-fledged countercyclical provisioning systems. Spain has been the leading practitioner of countercyclical provisioning, requiring banks to make statistical provisions based on either a supervisory formula or own internal estimates of historical expected loss, which form part of the general provisions. Specific provisions in the accounting period are compared with this statistical provision. If the former are less than the latter, then the difference is charged to income for the period; otherwise, the accumulated statistical provisions can be drawn down to meet any increase in required specific provisions. This reduces the volatility of earnings as well as the associated procyclical effects. This system appears to have served Spain well. Although several Spanish banks have been faced with more nonperforming loans in recent periods on account of their exposure to real estate, investor sentiment has not faltered, as reflected in the resilience of these banks’ share prices.
If countercyclical provisions are the way to go, why have they not been adopted more widely? Unlike bank capital, there are no internationally agreed standards on supervisory provisioning prescriptions. However, guidance has been provided on a country-by-country basis. National practices vary, partly because banks’ provisioning decisions are influenced by an interaction of the regulatory, accounting, and taxation regimes, as well as management objectives regarding earnings. Elements of these different dimensions tend to conflict with forward-looking provisions, especially those that are more general (not identified with any particular exposure or impairment).
Historically, regulatory prescriptions on provisioning have tended to be backward looking, that is, focusing on relating provisioning levels to the extent of deterioration in the outstanding value of the loan. In recent times, many countries have included forward-looking elements by requiring identified, though not incurred, impairments to be provisioned, and some have also encouraged the creation of across-the-board general provisions, a limited portion of which can qualify as capital. However, these practices are sometimes interpreted as being in conflict with the impairment provisioning laid out in the revamped International Financial Reporting Standards (IFRS). These standards champion a fair valuation of all assets, including loans; this valuation must reflect any incurred losses or impairment events, but restrict the ability to include (with some exceptions) losses that may occur in the future, an essential element of countercyclical provisioning. Market regulators, too, are wary of the possibility that such methods can allow banks to manipulate their earnings through “income smoothing,” and thus hinder transparency for investors. Finally, the tax treatment of provisions (specific provisions are more likely to be tax deductible while general provisions are usually not) may also create disincentives for bank management.
However, as the experience of Spain (and a few other countries, including Portugal and Australia) suggests, none of these issues is insurmountable, and it is likely that, in the context of the ongoing credit crunch, more supervisors will seek to interpret the accounting standards in a manner that supports their ability to dampen the procyclical effects of bank regulation. Supervisory discussions in international forums are also focusing on mitigating the unintended procyclical effects of bank regulation, particularly in the context of Pillar 2 of the Basel II framework, which requires supervisors to ensure that systems to manage bank risk take cyclical effects into account. Countercyclical methods for credit risk provisioning may, therefore, just be in the headlines once again.
Note: The main author of this box is Aditya Narain.
Indeed, model simulations of a decrease in procyclicality of bank lending—following, for example, the introduction of a countercyclical element into prudential banks’ capital regulation—suggest substantial reductions in the volatility of investment in financially integrated economies. Not surprisingly, stability gains appear to become more significant in those economies exhibiting tighter financial borrowing constraints (Figure 32).
Improved prudential regulation, including the introduction of countercyclical components that take into account the macroeconomics of boom-bust cycles, is a complement to but not a substitute for appropriate policies in other areas. Two types of policies are crucial in this regard: countercyclical macroeconomic policies that reduce the intensity of boom-bust cycles, and policies aimed at deepening domestic financial development. In general, having sufficient room for maneuver on the policy side substantially reduces the pressures that are likely to be felt on the real economy as financial conditions deteriorate.
Last but not least, the empirical evidence presented above argues in favor of greater financial integration supported by adequate coordination of national financial policies. Indeed, regulatory and supervisory convergence remains essential to foster smooth and growth-oriented adjustment among economies characterized by increasingly complex linkages across market segments and borders—and even more so within a monetary union. In this context, further, bold steps are needed to commit EU member states to put in place national and cross-border arrangements to deal with financial stability issues (Box 13).
Cross-Border Financial Stability in the European Union: Where Do We Stand?1
The European Union needs a more integrated approach to financial stability—a fact highlighted by the ongoing financial turmoil. Since the Treaty of Rome in 1957, the European Union has sought to establish a single financial market. It has made major progress toward this objective, but completing the process and managing the related risks require an integrated approach to financial stability. 2 Political preference, as well as legal and institutional considerations, has thus far limited the progress on cross-border financial stability arrangements; however, the increased sense of urgency created by the ongoing financial turmoil has bolstered support for reforms in this area.
The fundamental problem is that national supervisors’ fiduciary responsibilities are toward national governments and parliaments. This limits their incentives to work toward common EU objectives. The IMF staff has for some time argued that the European Union needs joint responsibility and accountability for financial stability, and that this undertaking should be underpinned by more complete information sharing (including with the European Central Bank) and better crisis prevention, management, and resolution frameworks.
The European Union has adopted a set of cross-border crisis management principles and a supporting memorandum of understanding (MoU). These principles, adopted by the October 2007 Economic and Financial Affairs Council (ECOFIN), commit member states to act in crises to minimize the “potential harmful economic impacts at the lowest overall collective costs.” If public resources are needed to achieve a cost-minimizing solution, then direct budgetary net costs are to be “shared among Member States on the basis of equitable and balanced criteria.” The recently agreed MoU seeks to implement these principles. It commits member states to putting in place national and cross-border arrangements to manage financial stability problems, a set of common guidelines for crisis management, and a common assessment framework to determine the systemic nature of a crisis. Meanwhile, work is ongoing to overhaul the legal framework to deal with solvency problems in cross-border banks. This work covers improvements to deposit guarantee schemes, a framework for early intervention and reorganization measures, and an assessment of obstacles to the transfer of assets across borders.
The Lamfalussy framework, aimed at achieving regulatory and supervisory convergence, is being reinforced. This framework was set up to facilitate financial sector rule making at the EU level and achieve a more consistent application of these rules at the national level. The so-called Level 3 Committees of this framework bring together national supervisors and have been tasked with much of the burden of achieving the desired convergence. The December 2007 ECOFIN launched a road map of reforms to reinforce these committees by giving them more resources, introducing scope for qualified majority voting, and strengthening the national application of guidelines issued by these committees, while maintaining the nonbinding nature of the guidelines.
Strong political leadership will be needed to move decisively toward greater joint responsibility and accountability. The crisis management principles, with their recognition of a collective responsibility and a need to share costs, have broken the mold. However, in a severe crisis, national interests may still prevail over the good intentions embedded in these principles and the nonbinding MoU. The MoU also risks adding further complexity to the cross-border financial stability setup. All in all, timely and collective cost-minimizing solutions may still prove out of reach. The key challenge is to align the legal underpinnings of nationally anchored financial stability frameworks and the incentives of the relevant agents with the commonly agreed principles. In this context, an important step was taken at the May 2008 ECOFIN meeting, which called on member states to endow their supervisors’ statutes with a European mandate so that they “are able to take into account the EU dimension in the performance of their duties, including having regard to the financial stability concerns in other Member States in exercising their duties.” However, bolder steps will be needed. These will require strong political leadership—of the kind that led to the introduction of the euro as a common currency 10 years ago.
Note: The main authors of this box are Martin Čihák and Wim Fonteyne. 1 For details, see also IMF (2007). 2 See Decressin, Faruqee, and Fonteyne (2007).Note: The main author of this chapter is Silvia Sgherri. Analytical underpinnings are provided in Gruss and Sgherri (forthcoming) and Galesi and Sgherri (forthcoming).
For recent studies on the impact of a “credit squeeze” on European economies, see IMF (2008c), Čihák and Koeva Brooks (forthcoming), and references therein. An analysis of the scope for cross-border spillovers among major EU banks is provided in Čihák and Ong (2007).
The role of balance sheet effects and collateral in credit cycles was first singled out by Bernanke and Gertler (1989), and later developed by Kiyotaki and Moore (1997) and Bernanke, Gertler, and Gilchrist (1999). A well-known exposition of the procyclical feature of financial systems is Minsky’s financial instability hypothesis (Minsky, 1992).
In particular, in the United Kingdom and in Ireland house prices have dropped quite sharply over the past few months. In Belgium, Spain, France, and Italy, property prices have continued on a path of gradual deceleration, while in the Netherlands and Austria house price increases in the first half of 2007 were roughly unchanged compared with the increases recorded in 2006 (European Central Bank, 2008).
For an assessment of house price developments across Europe, see also Box 1.2 in IMF (2008a) and Hilbers and others (forthcoming).
This approach is based on some simplifying assumptions. By deriving the impact of credit expansion on growth as the sum of changes in the financial positions of households and nonfinancial corporates, this assessment implicitly rules out any accelerator mechanism in the economy, thereby underestimating the actual impact of credit growth. On the other hand, this approach also implies that the total flow of dividends (which are deducted from corporate income before the financial position is calculated) is paid out to the households—an assumption that might exaggerate the impact of credit growth if, instead, not all dividends have boosted household incomes.
Calculations rely on balance sheet Eurostat data from 2003 to 2006. The sample includes the following countries: Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Italy, Latvia, Lithuania, Netherlands, Poland, Portugal, the Slovak Republic, Spain, Sweden, and the United Kingdom. Aggregation has been carried out using PPP-weighted GDP.
Although euro area household sector indebtedness has continued to increase over recent years, the overall assessment of household sector balance sheets as a potential source of risk from a financial stability perspective is still one of ongoing strength. Vulnerabilities may be growing for households in those parts of the euro area where the debt buildup has been most pronounced, where the majority of debt is financed at variable interest rates, and where housing valuations appear tight. On the other hand, euro area firms’ leverage has increased since 2005, fueled by improved investment opportunities and favorable financing conditions. Firms’ reliance on bank lending accounted for around 85 percent of the total debt of euro area firms in 2006 and is likely to have further increased as a result of ongoing stress in corporate bond markets. The gradual move of firms toward holding more debt has certainly made them more vulnerable to adverse shocks (European Central Bank, 2008).
European securitization in mortgage markets mainly relies on covered bonds—debt instruments regulated by EU legislation and secured against a pool of mortgages that remains on the balance sheet of the issuer. Box 9 provides an account of recent developments in European covered bond markets.
For an extensive survey of the literature on housing financing and its business cycle implications, see IMF (2008f) and references therein.
The analytical underpinnings of the model, details of its calibration, and relevant policy and sensitivity analysis are provided in Gruss and Sgherri (forthcoming).
Thus, firms can borrow up to a fraction of the market value of their capital. This constraint resembles a debt contract with a margin clause (on this point, see also Mendoza, 2006). Margin clauses typically require borrowers to surrender the control of collateral assets when the debt contract is entered and give creditors the right to sell the assets when their market value falls below the contract value. There are also other arrangements that operate in a similar way. These include value-at-risk strategies of portfolio risk management used by investment banks and capital requirements imposed by regulators on financial institutions. In both cases, if an aggregate shock hits the asset value, banks are required to reduce their corresponding exposure; however, since the shock is aggregate, the resulting sale of assets increases price volatility, thereby requiring further portfolio adjustments.
By ruling out both direct and indirect effects of house price shocks on the corporate sector’s growth, the estimated FCIs are likely to forgo the impact of construction-driven booms—such as those recently experienced in Spain or Ireland.
Following Kalemli-Ozcan, Sorensen, and Yosha (2004), the following panel regression is estimated over the years 1993– 2006 for each group of countries indexed by subscript i and reported in Figure 30:
ΔlogGNPit − ΔlogGNPt = const + β(ΔlogGNPit − ΔlogGNPt) + εit
Since GNP equals GDP plus net factor income flows, this regression provides a measure of the extent to which net factor income flows provide income insurance—the lower the β, the higher is income insurance within the group. In other words, 1 – β provides a measure of risk sharing through international factor income flows. Figure 30 reports point estimates for 1 – β for the different country groups, before and after 1999.
Model and estimation details underlying the assessment of regional financial spillovers across Europe are provided in Galesi and Sgherri (forthcoming). The GVAR methodology was originally developed by Pesaran, Schuermann, and Weiner (2004) and extended by Dees and others (2007).
There is a growing literature on the potential procyclicality of the new risk-sensitive bank capital regulation—known as Basel II—mirroring the concern that the increase in capital requirements during downturns might severely contract the supply of credit. On this point, see, among others, Jokipii and Milne (2006), Taylor and Goodhart (2006), Jiménez and Saurina (2006), Saurina and Trucharte (2007), and Repullo and Suarez (2008). For recent policy discussions, see also Caruana and Narain (2008) and Goodhart and Persaud (2008).
