I. Navigating the disinflation journey

The global economy withstood strong headwinds better than expected over the past year. Inflation edged down, as disruptions in global supply chains and in commodity markets waned. Growth slowed, although it proved resilient.

At the same time, signs of strain started to emerge. In particular, financial stress rattled the financial system, engulfing both banks and non-bank financial intermediaries (NBFIs) and prompting a forceful policy response to limit contagion. The strains share a common cause: the system is under stress following the era of low-for-long interest rates. Several strategies adopted to take advantage of that era are now proving ill-suited to the new environment. The strains are also a reminder of the tight monetary-fiscal-financial nexus, as the increase in government bond yields played a key role here.

Even stronger headwinds may lie ahead. Despite the most synchronised and intense monetary policy tightening in recent memory, inflation remains far too high. And there is a material risk of further financial stress.

The next phase of disinflation is likely to be more difficult. Mechanically, base effects are fading away. Substantively, inflation is increasingly driven by the more inertial components, particularly services. The longer inflation lasts, the more likely it is that households and firms will adjust their behaviour and reinforce it.

There are widespread macro-financial vulnerabilities in the system. Private and public debt levels are historically high. Asset prices, notably those of real estate, have started softening on the back of rich valuations. Interest rates may need to stay higher and for longer than financial markets are pricing in. The strains that have emerged so far reflect interest rate risk, but credit losses are still to come. This will further test the resilience of the financial system.

Four major policy challenges stand out. First, monetary policy needs to travel the last mile, bringing inflation back to target. Second, fiscal policy needs to support short-term stabilisation and ensure sustainability. Third, prudential and supervisory policies need to safeguard financial stability, thereby supporting the macroeconomic adjustment. Last but not least, policymakers need to wean growth away from excessive reliance on macro-stabilisation policies and bring monetary and fiscal policies firmly back into a “region of stability” (Chapter II takes a closer look at this challenge).

This chapter first describes the key economic and financial developments over the past year. It then discusses the main macroeconomic and financial risks. Finally, it elaborates on the policy challenges.

The year in retrospect

Inflation moderates, but too early to declare victory

After making a remarkable comeback, inflation continued to be a major policy concern in the year under review (Graph 1). Its persistence was systematically underestimated by public and private sector institutions alike. To be sure, headline inflation came down from the peaks reached in 2022, falling quite notably in most cases. But core inflation proved stickier, either stabilising or continuing to rise. Almost everywhere, inflation remained well above inflation targets. And, importantly, its drivers shifted as the year progressed, with the more inertial components gaining ground.

Lower headline inflation reflected, to some extent, both one-off factors and what, in principle, are temporary measures. Strong base effects kicked in, dragging down year-on-year readings. Commodity prices retreated from the highs induced by the war in Ukraine (Graph 2.A). As a result, contributions to inflation from energy and food shrank (yellow bars in Graph 1). In addition, the direct impact of some fiscal measures designed to curb increases in these prices mechanically helped to keep inflation down in the near term.¹ The size of the support reached 3% of GDP in some cases. That said, this impact could be reversed should the measures be phased out as planned and, in the case of cap-based measures, if the price of the subsidised commodities were to rise again. And, in the meantime, the support prevented aggregate demand from falling, thereby contributing to tight product and labour markets.

A longer-lasting amelioration came from easing global supply chain pressures, which largely normalised, allowing backlogs to be cleared (Graph 2.B). This affected primarily the prices of goods, which are much more heavily traded than services. These prices tended to rise more slowly and, in some cases, actually fell (blue bars in Graph 1). The pressure on goods prices was also eased by the ongoing reversion of the pandemic-related shift in consumption patterns away from services to goods (Graph 2.C).

That same rotation, however, boosted services price growth, which continued to rise (red bars in Graph 1). In the United States, the services component once again became the main factor behind inflation. Its contribution also slowly rose in other advanced economies (AEs) and in Latin America.

This shift in drivers of inflation towards services is likely to increase its persistence. The rate of change in services prices has historically been much less volatile than that for goods (dotted lines in Graph 3.A). Part of the explanation is that the share of labour in total costs in services is about twice as large as in manufacturing (Graph 3.B). This tightens the link between prices and wages. Not only are wage increases in general more inertial than other cost components, but they also tend to be more domestically driven in services, as the sector is less exposed to international competition. Indeed, the fraction of the variance of price changes explained by a global common factor has generally been lower for services, although it has risen recently owing to the widespread nature of the inflation surge (Graph 3.C).

Synchronised monetary tightening ends low-for-long

The inflation surge has led to the most synchronised and intense monetary policy tightening in decades.² Almost 95% of central banks hiked their policy rates between early 2021 and mid-2023 (Graph 4.A). Historically, this share has rarely exceeded 50%, surpassing 80% only during the oil price shocks of the 1970s. Emerging market economy (EME) central banks raised policy rates at twice the historical pace, and AE central banks at a roughly similar one.^{3 4} Even so, policy rates are still below inflation and, in some AEs below inflation expectations, implying negative real rates (Graph 4.B and 4.C). At the same time, major AE central banks started to gradually shrink their balance sheets, with Japan as the exception. Quantitative easing turned into quantitative tightening.

The transmission of monetary tightening to lending rates was mostly swift and began to weigh on aggregate demand. Borrowing costs rose for corporates and households alike (Graph 5.A). Bank lending standards tightened and bank credit contracted, especially in AEs (Graph 5.B). Consequently, spending weakened. The deceleration was led by the most interest rate-sensitive components of expenditure, such as consumer durables, and the housing market cooled in many economies (Graph 5.C).

The economy slows, but manages to avoid recession so far

Overall, global growth slowed from 6.3% in 2021 to 3.4% in 2022, weakening further in the first quarter of 2023 (Graph 6.A). The slowdown was most pronounced in AEs, from 5.7 to 2.8%. EMEs fared better, still growing at 4% in 2022 as a whole compared with 7.3% in the previous year. This was despite China recording a growth rate of only 3%, reflecting setbacks from large Covid-19 outbreaks and the drag from the real estate sector.

Still, activity held up better than expected in a number of key jurisdictions, and the much feared global recession did not materialise. Relative to the forecasts made early in the review year, growth outcomes in 2022 surprised on the upside in the United States, the euro area and most EMEs, with China an exception to the pattern. As high-frequency indicators remained robust in many jurisdictions, growth forecasts for 2023 were revised upwards as the new year started, although the consensus still saw a considerable slowdown for the year as a whole, to 2.6%.

The relative strength of economic activity and the upgrade of expectations for 2023 reflected three main factors.

First, consumption remained robust. Excess savings accumulated during the pandemic, not least thanks to higher saving rates and fiscal support (red and yellow bars, respectively, in Graphs 6.B and 6.C). Once Covid-related restrictions were lifted, households drastically cut their saving rates, to pre-Covid levels in most AEs and to even lower ones in the United States. Further, buoyant labour markets bolstered income (purple bars in Graphs 6.B and 6.C). Unemployment rates fell to multidecade lows, especially in AEs (Graph 7.A). Job creation was strong in both AEs and EMEs while job vacancy rates remained high, around record levels in the United States and Europe.

Second, the energy crisis proved far less consequential than expected. A relatively mild winter and the rapid build-up of gas storage helped prevent the deep and widely forecast recession in Europe (Graph 7.B).⁵ And, in many jurisdictions, fiscal support insulated households and firms from the impact of higher energy prices.

Third, the rapid reopening of the Chinese economy in January, after the country abandoned its zero-Covid strategy in December 2022, boosted domestic activity (Graph 7.C). This also lifted activity abroad, although to a lesser extent than in the past, given the services-driven nature of the rebound (Box A).

Financial system shaken by bank failures

Financial markets and the financial system more generally started to adapt to the abrupt end of low-for-long interest rates but the process was far from smooth. A broad disconnect emerged between financial market pricing and central banks’ announced policy path. And rising signs of stress appeared in the financial system.

The disconnect between market expectations and central bank plans was evident in the dynamics of financial conditions. As markets were swayed by the shifting odds of inflation staying high and the economy entering a recession, participants continuously re-evaluated how central bank actions would evolve. Expectations of future rates remained lower than central banks’ projections, with investors anticipating rate cuts already in 2023 (Graph 8.A). After considerable tightening in 2022, by some measures, financial conditions tightened marginally during the period under review (Graph 8.B). They remained tighter than historical averages.

Foreign exchange movements largely followed those of financial conditions, taking their cue from the relative strength of the economies and the corresponding monetary policy outlooks. The US dollar generally appreciated through the third quarter of 2022, before weakening moderately against most currencies. By and large, the depreciation against the dollar was larger for the currencies of countries where the policy rate increased less than in the United States. The Japanese yen and the euro touched multidecade lows. Countries where monetary tightening had started earlier and interest rates had reached higher levels, such as Mexico and Brazil, actually saw appreciations (Graph 8.C). In general, EMEs absorbed the sharp tightening of global monetary conditions in an orderly way.

The disconnect between financial market expectations and central bank communications was also evident from the dynamics of risky assets. Equity markets finished the review period marginally higher (Graph 9.A), despite weak earnings forecasts, especially in the United States (Graph 9.B). Measures of implied equity volatility hovered below historical averages for most of 2023. In credit markets, spreads marginally tightened, remaining in line with historical norms in the United States and somewhat above in Europe (Graph 9.C).

Against this backdrop, increasing signs of stress emerged in the financial system in late 2022 and early 2023, in large part due to higher interest rates.

First, leveraged strategies to hedge against drops in interest rates came under pressure. As the UK “mini-budget” announcement in September 2022 sent gilt rates soaring, such strategies generated losses for the so-called liability-driven investment (LDI) funds in which UK pension funds had invested. To meet the ensuing collateral calls, LDI funds needed cash infusions, which pension funds failed to provide promptly enough. As their solvency positions worsened, LDI funds had to deleverage by selling gilts, putting further upward pressure on yields and setting off a full-fledged spiral. The Bank of England intervened forcefully and swiftly through temporary asset purchases to calm the market.

The sharp increase in interest rates also put the spotlight on banks. To the extent that they could reprice their assets, banks benefited from the impact of rising interest rates on net interest margins (Box B). However, during the low-for-long era, many had accumulated fixed rate mortgages and long-term government bonds (Graph 10.A), which declined steeply in market value when interest rates rose. Banks are generally required to assess and manage their exposure to changes in interest rates, including under scenarios of upward shifts in the yield curve (Graph 10.B). In addition to hedging with derivatives, banks often base their interest rate risk management on deposit stickiness. This feature has traditionally allowed banks to keep their funding costs in check by passing only a fraction of policy rate rises to deposit rates. As the share of short-term – and thus potentially flighty – deposits has risen (Graph 10.C),⁶ an increase in their interest rate sensitivity undermined the risk management strategies of some banks.

Mismanagement of interest rate risk, among other factors, drove the first major bank failures since the Great Financial Crisis (GFC). Already by late 2022, many US banks had sizeable market value losses on their debt securities holdings (Graph 11.A). More than half of the losses were not reflected on balance sheets, on the accounting assumption that banks would hold the attendant assets to maturity.⁷ However, as a loss of confidence in some of the smaller and thus more lightly regulated banks triggered a deposit flight, these banks had to liquidate some of their “held-to-maturity” assets and recognise immediate capital losses (Graph 11.B). These intertwined interest rate and run risks materialised forcefully for Silicon Valley Bank (SVB), a regional bank that collapsed in early March (Box C).

The realisation of interest rate risk reverberated through the US banking sector in the first half of 2023. Small and mid-sized banks suffered significant deposit outflows, forcing the closure of first Signature Bank and then First Republic Bank. At the same time, US global systemically important banks (G-SIBs) saw significant inflows from depositors searching for safe havens.

Investors’ concerns spread to banking sectors in several other AEs. Banks that had already faced persistent market scepticism, as indicated by a low price-to-book ratio (PBR), were hit particularly hard. Credit Suisse – a G-SIB which had been struggling with large fund outflows and a series of setbacks (see Box C) – failed to rebuild market trust and – after writing down its contingent convertible bonds to absorb losses – was taken over by a competitor. Relative to global equity markets, other AE banks with low PBRs also registered deeply negative stock returns (Graph 11.C). This stood in contrast to the more modest decline for high-PBR banks in AEs and banks in EMEs.

Again, authorities responded forcefully to contain contagion and deployed a number of crisis management tools to curb systemic risks. In the United States, authorities invoked the so-called systemic risk exception – previously used in the GFC – to stem more widespread runs by guaranteeing the uninsured deposits of SVB and Signature Bank. In addition, the Federal Reserve established the Bank Term Funding Program (BTFP), offering loans to banks that pledged qualifying government securities, valued at par and thus above market value. The BTFP complemented lending through the Federal Reserve’s discount window, which soared in the immediate aftermath of SVB’s failure but has come down since then (Graph 11.A). In Switzerland, the public sector backed the emergency takeover of Credit Suisse, with the central bank pledging significant liquidity support and the government extending guarantees to shield the central bank from potential losses. Furthermore, to facilitate the takeover, the government guaranteed to cover part of future losses in relation to the disposal of the failed bank’s legacy assets.

Key risks on a turbulent path

Against this broad macroeconomic and financial backdrop, what is the outlook for the global economy?

Consensus forecasts are rather benign. While forecasters do see lower growth and inflation still above target, the slowdown is rather mild and the fall in inflation substantial. Banking woes are expected to be contained.

Two risks loom large, however – quite apart from those of a more political nature, such as an intensification of geopolitical tensions. First, disinflation could well turn out to be harder than expected – the “last mile” challenge. Second, the end of low-for-long could further test the global financial system, with the crystallisation of macro-financial risks to threaten growth.

This combination of risks is rather unique by post-World War II standards. It is the first time that, across much of the world, a surge in inflation has coexisted with widespread financial vulnerabilities. The longer the inflation persists, the stronger and longer the required policy tightening, and hence the bigger the financial stability risks.

The “last mile” may pose the biggest challenge

Getting back to target is likely to be harder than the first phase of the disinflation journey. There are several reasons why. Beyond fading base effects and the increasing role of inertial components of inflation, households and firms may adjust to persistently higher inflation by trying to recoup previous losses and then seeking to avoid future expected ones through their wage- and price-setting decisions.⁸ Moreover, as time goes by and higher policy rates propagate through the system, the economy will weaken and further financial stress may arise. This means less pressure on prices but, at the same time, tougher trade-offs involving activity. In some cases, there may be political pressure on central banks to keep interest rates low, requiring them to reiterate the commitment to deliver price stability through both communication and action. Such dynamics may be especially relevant among those EMEs where institutional safeguards are weaker, inflation expectations are less anchored and indexation is more prevalent.

Admittedly, in previous disinflation episodes, headline inflation typically returned to the pre-peak levels (or even lower) in the space of one to two years (Graph 12.A). Core inflation tended to follow a similar path.

However, a number of features set the current episode apart from previous ones and indicate that disinflation may prove difficult. First, services prices have risen much faster and their rate of change has not yet peaked (Chart 12.B). This could mean a potentially longer disinflation journey. Second, rather than the median episode, the current surge more closely resembles the 1970s – when a “first mile” of disinflation was achieved in the space of about one year but inflation thereafter declined only gradually: after two years, it was still generally above its pre-surge level (Graph 12.C). In fact, the pace of disinflation so far has been even slower than in the 1970s – although the tightening has proceeded at a faster pace (Graph 12.D).

Crucially, then, what is the likelihood of a transition to a high-inflation regime, such as the one in the 1970s?

Several indicators point to possible obstacles along the disinflation journey and suggest that the low-inflation regime will continue to be tested. First, after a steep rise, the share of items in the consumer price index whose prices increased at a fast rate has not come down (Graph 13.A). Second, price spillovers across consumption categories are slightly larger than they were in the recent past when inflation was low (Graph 13.B). This means that increases in the price level due to price shocks in one category will propagate to others, raising the likelihood that they will lead to sustained inflation rather than die out. Third, price changes across categories are becoming increasingly similar (Graph 13.C), implying that differences in consumption patterns across consumers and input costs across firms matter relatively less, so that the general price level becomes more relevant for individual decisions. This tends to be a useful indicator of inflation persistence, ie when the similarity index is high, so is the probability that inflation in the next period will be at least as high as in the current one.⁹ These signals, taken together, suggest that households and firms are responding more strongly to the higher inflation rates.

Looking ahead, two closely related factors could signal a shift in inflation norms and tip the disinflation process off course: self-sustaining wage-price dynamics and a de-anchoring of inflation expectations.

While nominal wage growth has not been exceptionally strong so far, this should not provide too much comfort. Wage adjustments are still influenced by the lingering effects of the norms prevalent in the low-inflation regime, but this could change quickly. The inflation surge has severely eroded the purchasing power of households (Graph 14.A), even more than in past disinflation episodes (Graph 14.B). Some catch-up is on the cards, particularly given the strength of labour markets. While labour’s bargaining power declined significantly over the years of low inflation,¹⁰ recent strikes and calls for unionisation suggest that the environment is evolving. In the euro area, for instance, negotiated wage growth has been on the rise and is now at its highest level since the inception of the common currency. And while multi-year wage contracts generally make the adjustment lags for wages considerably longer than for prices, contract length may shorten in response to higher and more persistent inflation.¹¹ What’s more, the pass-through from prices to wages has been somewhat higher when labour markets have been tight.

In parallel, there are signs that price-setting behaviour is changing. Firms are adjusting prices more frequently than when inflation was low and stable.¹² In addition, corporate profits, which were already on the rise before the inflation surge, have held up remarkably well so far (Graph 14.C). This is a departure from the historical pattern: in past episodes, profit growth tended to fluctuate within a comparatively narrow range around zero. One concern is that, having been able to raise prices more easily than in the low-inflation regime, firms are now more reluctant to accept profit squeezes and will pass on cost pressures to prices more readily.¹³

In the end, a shift to a high-inflation regime would require self-sustaining wage-price increases – a “wage-price spiral” – as workers and firms try to recoup their losses. The feedback between wages and prices has been quite low in the last two decades, below 10%. However, moving to a high-inflation regime would strengthen it.¹⁴

A stylised exercise based on a decomposition of changes in the GDP deflator during disinflations shows that some catch-up in wages would be compatible with inflation returning to target, but only as long as firms accept a reduction in profits.^{15 16} Back-of-the-envelope calculations suggest that, for inflation to go back to a target of 2%, profits on average would need to decline by about 2.5% per year in 2023–24, should real wages rise fast enough to make up for the loss in purchasing power and return to the pre-inflation surge level by end-2025. For comparison, the cross-country pre-pandemic median for profit growth has been slightly more than 1.5% between 2014 and 2019.¹⁷

An alternative exercise based on the historical price-wage relationship reinforces the message that the room for adjustment in real wages without jeopardising the inflation target is limited. The exercise is guided by the cointegration between core CPI and hourly compensation and considers the path inflation could take under two different scenarios of purchasing power recovery (Graph 15.A).¹⁸ In the first scenario, wages gradually recover, growing at an annual rate of 3.5%, which is consistent with an inflation target of 2% and historical labour productivity growth rate of 1.5% (“gradual catch-up”). Real wages would then largely make up for the losses incurred so far by end-2025. In the second one, the pace of nominal wage growth is faster in 2023 and 2024 at 6%, and settles at 4% by 2025 (“fast catch-up”). In that case, the erosion in real wages is remedied by mid-2024. The gradual catch-up scenario seems conducive to bringing inflation down to or below target (solid red line in Graph 15.A), based on the historical relationship between wages and prices that prevailed in a low-inflation environment – here proxied by post-1995. By contrast, inflation would remain well above target up to the end of 2025 in the fast catch-up scenario (solid blue line in Graph 15.A). Further, if the relationship between wages and prices reverts to the pattern that prevailed before 1995 – capturing a high-inflation environment – the implied inflation trajectory would remain above target also in the gradual catch-up scenario (dashed red line in Graph 15.A). This is because wage-price spillovers were stronger when inflation was higher.

A wage-price spiral would be even more likely should workers and firms seek not just to recoup past losses, but also to be compensated for future ones, ie if expectations became “de-anchored”. While a de-anchoring is not yet evident, inflation expectations have edged up visibly in some cases and are generally above target. True, long-term ones – over a five-year horizon – have remained stable. That said, they are higher than before the inflation surge began. This is especially so for German and Japanese households, who had seen inflation being persistently below target before the pandemic (Graph 15.B). Further, short-term inflation expectations – at the one-year horizon – rose much more than their long-term counterparts (Graph 15.C). The longer inflation remains high, the higher the odds that long-term expectations will follow.

Macro-financial vulnerabilities could complicate the inflation fight

Given the economic background, the risk of further financial stress is material. Historically, about 15% of monetary policy tightening episodes are associated with severe banking stress. The frequency of such stress is higher during tightening episodes that start in an environment of high debt, an abrupt inflation surge or rapid house price growth. If the private debt-to-GDP ratio is in the top quartile of the historical distribution at the time of the first interest rate hike, 40% of the episodes are followed by a banking crisis within three years (Graph 16.A). The odds of a banking crisis are 25% for an inflation surge (Graph 16.B) and about 35% for rapid house price growth (Graph 16.C). Very high debt levels, a remarkable global inflation surge, and the strong pandemic-era increase in house prices¹⁹ check all these boxes. Vulnerabilities in the commercial real estate (CRE) sector – historically a common source of stress in the banking sector – raise concerns, too (Box D).

If inflation proves to be more persistent than expected and central banks have to tighten monetary policy by more or for longer, financial stability risks will rise. A key channel is the impact of asset prices and debt burdens on the macroeconomy. Sharply higher mortgage financing costs, coupled with high household debt (Graph 17.A) and falling house prices, translate into lower consumption (see Box D). Evidence shows that, generally speaking, high debt amplifies the impact of monetary tightening²⁰ and that house prices are much more sensitive to a rate hike when debt levels are high.²¹ Countries with higher household debt have already seen a sharper rise in debt service ratios (DSRs) (Graph 17.B). Economies that rely on adjustable-rate mortgages (ARMs) are especially vulnerable (Graph 17.C).

Illustrative simulations, based on historical relationships, shed light on the implications of alternative interest rate paths. For a number of AEs, the simulations trace the behaviour of key variables in three scenarios, assuming that interest rates are constant, follow the “market path” or go “higher-for-longer”, ie remain at the market-implied peak plus 200 basis points until the end of 2027 (Graph 18.A). Average AE private sector DSRs could increase by about 1.5 percentage points and reach their pre-GFC peaks by 2027 if central bank policy rates evolve as financial markets currently expect (Graph 18.B). In the “higher-for-longer” scenario, average DSRs could increase by more than 4 percentage points. The decline in house prices in this adverse scenario could be as large as 30%, relative to the 15% drop in the market-implied path (Graph 18.C). The level of GDP in the adverse scenario could be about 2% lower by end-2027 relative to what would be expected were policy rates to follow the market path (comparing the blue to the yellow bar in Graph 18.D).

Bank vulnerabilities

Further illustrative simulations explore the possible implications for banks. Credit losses on the back of rising debt service ratios could undermine the support that banks receive from higher interest income. If macro-financial conditions follow the “market path” scenario, banks’ expected credit losses in 2025–27 would be close to the average level in AEs over the past three decades (Graph 19.A). In the “higher-for-longer” scenario, those losses could approach the levels seen during the GFC, subject to a large degree of uncertainty (Graph 19.B).

Losses in banks with large exposures to interest rate-sensitive sectors could be heavier. A prime example is the CRE sector, which faces additional risks from the post-pandemic reduction in demand due to hybrid work arrangements. Smaller and more regionally focused banks in many AEs tend to have a greater concentration of loans in this sector.

Low valuations and weak profitability go hand in hand, heightening banks’ vulnerability to losses. A number of GSIBs had persistently low PBRs throughout the low-for-long era. This is a sign of stubbornly sub-par profits and/or persistent investor scepticism about the bank’s ability to create value (Box E). Low profits weaken the first line of defence against losses. In addition, low PBRs limit a bank’s capacity to generate equity capital internally: shareholders prefer that profits be paid out rather than be reinvested at a lower return. When adjustments are necessary at short notice, however, banks may have to seek external capital. This can trigger adverse market responses, especially when investor confidence is fragile.

Post-GFC, financial reforms have greatly bolstered the capitalisation of the banking sector (Graph 19.C) and have encouraged more forward-looking loan loss provisioning. Ultimately, the impact on the banking sector will depend on the extent to which its loss-absorbing capacity helps preserve investor confidence.

Vulnerabilities among NBFIs

The long period of unusually low interest rates provided fertile ground for the build-up of widespread vulnerabilities in the NBFI sector. Moreover, post-GFC, this sector has grown in leaps and bounds relative to the banking sector.²² In the process, risks there have increased and some vulnerabilities have attained systemic importance. Not all of these vulnerabilities have been properly identified because large parts of the NBFI sector are quite opaque.

The NBFI sector can be a source or amplifier of systemic stress through several mechanisms. First, among NBFIs, hidden leverage and liquidity mismatches are rife. In addition, duration management by NBFIs – such as life insurance companies – could have adverse spillovers when a sharp rise in interest rates shortens liability duration and prompts sales of long-duration assets in a falling market. Stress could also stem from the interlinkages between NBFIs and banks via funding or hedging activities.

Vulnerabilities in two specific market segments deserve mention.

First, liquidity mismatches at investment funds can exacerbate existing fragilities in the real estate sector and corporate bond markets. An intensified downturn in real estate markets could, in particular, trigger large withdrawals by investors in REITs. In turn, this would require REITs to sell into inherently illiquid markets, setting in motion a downward price spiral. Similar liquidity mismatches could also affect corporate credit – a market segment that has seen a secular deterioration in credit quality, as reflected in the trend decline in ratings. In this case, large redemptions from bond mutual funds and ETFs could trigger fire sales.²³

Second, even though private equity and private credit funds take on minimal liquidity risk, their contribution to corporate indebtedness is a cause of concern. Private market deals grew more than fivefold after the GFC and reached a multidecade high of almost $500 billion globally at the end of 2021.²⁴ The funds’ highly procyclical risk-taking contributed to the build-up of leverage during the low-for-long era,²⁵ thus sowing the seeds for stress when interest rates rose.²⁶ As borrowing costs increase, the highly leveraged companies that private funds have invested in could face difficulties in refinancing and repaying their debt, a large share of which is estimated to mature in the next three years. A deterioration of these borrowers’ ratings would amplify these difficulties. Debt restructuring for distressed companies could buy time but, in the case of flawed business models, default would be inevitable. Banks could then incur losses directly, since some of them reportedly still warehouse significant amounts of the leveraged loans provided during the 2021 boom in private market deals.

Additional considerations in EMEs

While EMEs have so far been spared from significant spillovers from the financial stress in AEs, this could change. EMEs’ resilience reflects a range of factors, such as early monetary policy tightening (notably in Latin America), implementation of structural reforms, less foreign currency borrowing and reduced foreign investor participation in local currency bond markets. Nevertheless, beyond the home-grown vulnerabilities in some EMEs, such as in real estate and corporate markets, financial stress in AEs could at some point spill over through several channels. The exchange rate continues to play a particularly important role in this context. Furthermore, while the lengthening of debt duration reduces EME borrowers’ rollover risk, it also increases investors’ market risk. It can thus be thought of as the duration equivalent of “original sin redux”, ie the shift of exchange rate exposures from borrowers to lenders.

Navigating from turbulence to safety

Policymakers are facing tough challenges in the near and longer term. In the near term, the overriding challenge is to bring inflation back to target in the context of heightened financial stability risks. This challenge contrasts with those faced from the 1970s up to the mid-1980s, when inflation generally rose against the backdrop of limited financial strains. Thereafter, financial stress broke out during generally quiescent inflation (Chapter II). The combination makes calibration much harder and requires all policies – monetary, fiscal and prudential – to play their part. With the benefit of hindsight, the extraordinary monetary and fiscal stimulus deployed during the pandemic, while justified at the time as an insurance policy, appears too large, too broad and too long-lasting. It contributed to the inflation surge (Graph 20) and to the current financial vulnerabilities. In the longer term, the challenge is to wean growth away from excessive reliance on macroeconomic policies to set the basis for a robust and sustainable expansion.

Monetary policy

While the central bank response to the inflation surge has been forceful and has clearly started to bear fruit, the job is not yet done. To be sure, tighter financial conditions have begun to weigh on expenditures, with economic activity slowing down most in interest rate-sensitive sectors. Labour markets have started to cool. And inflation expectations appear to have remained generally well behaved so far. That said, inflation is receding only slowly and the repeated forecast errors counsel caution in drawing firm inferences. Further, monetary policy is well known to operate with long and variable lags, making it difficult to pin down how large the impact has been so far. There is no room for complacency; perseverance is the name of the game.

Any assessment of the strength of policy transmission needs to consider the influence of factors that pull in different directions. On the one hand, higher debt levels, elevated asset prices and bursts of financial stress raise the sensitivity of the economy to tighter monetary conditions. Moreover, for the first time central banks are tightening not just through higher rates, but also by trimming their balance sheets. On the other hand, inflation-adjusted interest rates remain low or even negative and households and firms have been able to draw on the extraordinary support provided during the pandemic and on borrowing at longer maturities than in the past.

More fundamentally, the risk of shifting to a high-inflation regime greatly complicates the calibration of policy. Historical relationships no longer constitute reliable signposts.²⁷ This makes the task of central banks much more difficult and can put their credibility on the line.

On balance, the biggest risk is to declare victory too soon. From a risk management perspective, policy rates may need to remain higher for longer to ensure that inflation continues to decline and stays low. Transitions to high-inflation regimes tend to be self-reinforcing and the trade-offs involved in restoring price stability worsen once inflation becomes entrenched. What’s more, history highlights the cost of stop-and-go actions, which can introduce unnecessary fluctuations in the economy. The costs of a high-inflation regime are simply too high to take any chances.

Support from other policies will be important for central banks to win the inflation fight, especially against the backdrop of elevated financial stability risks. Central banks can and should address financial stability risks without compromising the price stability objective. In the longer term, the two objectives do not pose a trade-off. But in the near term, the need to bring inflation back to target and the need to stabilise the financial system could pull in different directions. There will be a premium on differentiating central bank actions designed to achieve price stability from those aimed at financial stability – a task complicated by the extensive use of balance sheet policies to set the policy stance in several jurisdictions. If the stress is minor, central banks could address the near-term trade-off on their own, as the gilts market turmoil in the United Kingdom has shown.²⁸ But if the stress is more acute, central banks will need the support of fiscal, prudential and supervisory policies to manage it effectively while retaining sufficient room for manoeuvre.²⁹

Fiscal policy

The role of fiscal policy will be critical. To do its part, fiscal policy needs to consolidate. Consolidation would help tackle both the near-term and the longer-term challenges.

In the near term, consolidation would calm inflation by reducing pressure on productive capacity. And it would contain financial instability risks in several ways. It would reduce the need for monetary policy to tighten further. It would mitigate the risk that the sovereign itself becomes a source of financial instability, such as through the sovereign-bank nexus (Chapter II). And it would create more headroom should public resources be called upon for crisis management in concert with central banks.

In the longer term, consolidation would help rebuild the space necessary to put public sector debt on a firmly sustainable path. This is all the more important given the likelihood of greater demands on public spending, arising from ageing populations, the impact of geopolitical tensions on defence spending, and the green transition (Chapter II).

The recent policy record, however, highlights the risk of a drift in the fiscal stance. The design of the measures deployed to shield households and firms from the fallout of the war in Ukraine on energy and food prices leaves room for improvement. In general, it has not followed the “3T principle”, often for practical and political reasons. Support should be targeted to the most vulnerable groups so that the overall size is in line with the fiscal constraints and the needs of society. It should be tailored to ensure that it does not weaken incentives for needed medium-term adjustments. It should be temporary so as not to unduly add to demand after the shocks have passed.³⁰ Moreover, any support boosts aggregate demand unless offset by higher taxes, regardless of how it is designed, thereby complicating the fight against inflation through that channel.

The recent improvement in fiscal positions reflects, to a considerable extent, only temporary factors. Even though fiscal expenditures exceeded original plans, primary deficits in G7 countries declined from 5.7% of GDP in 2021 to 3.4% in 2022. This largely reflected the inflation surge, which boosted both tax revenues and nominal GDP (Graph 21.A). These benign effects tend to be short-lived: they are one-off level adjustments. Further, it can prove politically difficult to withdraw support measures and the perception of a stronger fiscal position can tempt the authorities to spend rather than save the revenue windfalls.

The ephemeral positive impact of inflation on debt ratios should not be exploited to avoid much-needed, credible consolidation plans. These plans should also aim to rationalise expenditures, improve the quality of spending and create space for supply side reforms (see Chapter II). Public-private partnerships should be part of the formula where possible. Absent consolidation, deficits remain too large to put public debt on a sustainable path. Debt levels in some major economies are at historical peaks or near them (Graph 21.B), and rising interest rates have increased the prospective debt service burden.

The challenge is daunting. To give a sense of the magnitudes involved, in 2019 a primary deficit of 2.1% of GDP would have been sufficient to stabilise debt, on average for G7 countries. In 2023, despite the one-off inflation-induced improvements in fiscal positions, higher interest rates mean that the corresponding figure has fallen to 1.6%. Among major EMEs, the debt-stabilising primary deficit has fallen from 1.1% of GDP in 2019 to 0.1%.³¹ While further shrinking of fiscal deficits is envisaged for most countries in 2023 and 2024 (Graph 21.C), these plans typically fall short of stabilising public debt even if they were meticulously followed. What is more, these figures assume that real long-term interest rates remain lower than real GDP growth rates, which cannot be relied upon. To reduce debt from its historically high levels, primary surpluses must clearly exceed the debt-stabilising ratios. Only this will restore fiscal space.

Prudential policy

Prudential policy, too, has an important role to play, in both the near and the longer term. By focusing on improving the resilience of the financial system, it can provide critical support to monetary and fiscal policies. Actions should address both banks and NBFIs.³² And they will need to be complemented by improvements in elements of the safety net as well as recovery and resolution schemes.

In the near term, the focus should be on actions that can quickly strengthen the loss-absorbing capacity of the financial system. This should be at both the macro- and the microprudential levels.

A premature easing of macroprudential measures should be avoided. Implemented before or during monetary policy tightening, such measures tend to reduce the likelihood of subsequent financial stress.³³ It would be imprudent to ease them in anticipation of a slowdown in economic activity. In accordance with their design, they need to be kept in place and, where appropriate, tightened further and released only when clear risks of a disruptive credit crunch emerge.

At the microprudential level, a priority is tighter supervisory oversight. A culture of supervisory scrutiny should go beyond regulatory metrics and enforce timely remedial actions. Enforcement of stronger risk management practices, underpinned by sound governance, will be key. Given the build-up of indebtedness during the low-for-long era and the subsequent exceptional monetary policy tightening, losses could surpass forecasts based on historical data. This calls for conservatism in loan loss provisioning and in stress tests of exposures to interest rate, credit and liquidity risks.

Other adjustments will take more time.

In the banking sector, beyond the consistent and timely implementation of the post-GFC reforms, there is a need to learn from recent strains. In particular, lessons related to interest rate risk call for a reassessment of accounting rules and regulatory requirements. Historical cost accounting contributes to the accumulation of latent vulnerabilities when applied to assets that also serve liquidity management purposes (eg government securities). An overhaul of this practice would make reported capital more accurately reflect banks’ loss-absorbing resources. Furthermore, assumptions about the stickiness of various funding sources, most notably uninsured demand deposits, should be reassessed to improve banks’ liquidity requirements.

Beyond banking, there is an urgent need to strengthen the regulation of NBFIs from a systemic perspective. Deleveraging spirals and liquidity mismatches have exposed vulnerabilities that, if left unaddressed, could lead to broader systemic repercussions. A system-wide approach to strengthening NBFI resilience would need to build on a balanced mix of activity-based and entity-based regulatory requirements.³⁴ Progress in this area has been disappointingly slow.

Turning to safety nets, an issue that has risen to prominence once again is the design of deposit insurance schemes. These schemes seek to safeguard the savings of retail depositors, who are unable to monitor financial intermediaries, and to facilitate the restructuring of failed banks. Together with central banks’ lender of last resort function, they also enhance the stability of banks’ funding, thereby supporting their ability to provide liquidity and manage maturity transformation.

Concerns about the rising structural instability of uninsured deposits has prompted calls for an expansion of the insurance coverage. Historically, it has proved very difficult to strike the appropriate balance. Arguably, however, experience indicates that, once confidence in an institution evaporates, deterring runs and preventing the institution from losing market access would require nothing short of insuring 100% of demandable and short-term claims, whether collateralised or not. This would encompass all forms of wholesale funding, including liquidity needs arising from margining practices. The upshot would be much weaker market discipline and, ultimately, a rise in solvency risks to unacceptable levels.

Hence, there is a premium on mechanisms to resolve institutions in an orderly way. Much progress has been made since the GFC in implementing the ambitious agenda concerning recovery and resolution frameworks. That said, further work is needed to equip authorities to manage bank failures more effectively. This entails closing the gap between available tools and the resolution requirements arising from banks’ scale, complexity or cross-border footprint. Key focus areas include facilitating the application of bail-in measures on all debt instruments with loss-absorbing features and establishing clear responsibilities and processes for the swift resolution of internationally active banks, especially G-SIBs. In addition, authorities should be in a position to address issues pre-emptively by steering banks towards sustainable business models.

Structural policies to enhance sustainable growth

Looking beyond the immediate challenges of inflation and financial stress, pre-pandemic sluggish growth could well set back in. Indeed, potential output growth estimates are at multidecade lows.³⁵ There will then again be calls for monetary and fiscal policies to boost the economy’s prospects.

Experience offers valuable lessons, however, and indicates how misguided such calls can be. Policymakers should resist these calls. In the decades prior to the pandemic and the war in Ukraine, policymakers came to view the economy mainly through the lens of aggregate demand and assumed that aggregate supply adjusted smoothly in the background. The pandemic and the war were a rude awakening: supply side constraints do matter and macroeconomic policies stimulating aggregate demand to smooth the business cycle had largely run out of space.³⁶ One lesson is that, to prevent unintended consequences, it is essential for monetary and fiscal policy to retain sufficient policy space and remain firmly within a region of stability (Chapter II).³⁷ A second lesson is the need to reboot the supply side of the economy as the only possible source of robust, durable growth.

With a renewed focus on the supply side, policymakers need to identify the opportunities that longer-term trends can offer. The green transition, investments in state-of-the-art efficient facilities during the re-configuration of GVCs, digitalisation and the advancement of artificial intelligence could provide a much-needed push to productivity in many countries – provided that the right policies are in place.

A comprehensive approach to reap the potential benefits involves an array of structural policies. First and foremost, targeted investments in education should aim at continuous upskilling and re-skilling of the workforce. Adequate resources will need to be in place to ensure that workers can adapt and make effective use of the new technologies, so that the skills of a large part of the labour force do not become obsolete. In addition to education and training, policymakers should invest in healthcare, not only to mitigate any scarring effects from the pandemic and be prepared for other public health emergencies but also to maximise the productive potential of the workforce. Investments in human capital could be complemented by investments in physical capital. Infrastructure projects to improve connectivity and access to markets and services, when chosen carefully and implemented efficiently, could prop up productivity growth and enhance economies’ resilience. These investments may require not only better but also more public spending, further underscoring the need for fiscal consolidation through broadening of the tax base and entitlement reforms.

The other area of focus is maintaining competitive and open markets, both domestically and internationally. Economic structures are evolving rapidly, in response to the pandemic-induced shifts in preferences, geopolitical tensions, technological advances and climate change. Lowering barriers to entry would bring in new, innovative firms and help improve the outcomes of these transformations. Promoting free trade and resisting real and financial fragmentation would deliver better outcomes, given the important role trade has played in underpinning global productivity and growth.

Endnotes

¹   For instance, in Brazil energy tax cuts are estimated to have lowered headline inflation by 2.5 percentage points in 2022 (Central Bank of Brazil (2022)). Estimates for France suggest that price caps and rebates have reduced headline inflation by about 3 percentage points between Q2 2021 and Q2 2022 (Bourgeois and Lafrogne-Joussier (2022)).

²   See Cavallino et al (2022).

³   This has given rise to the debate about “front-loading”; see Cavallino et al (2022) for an analysis.

⁴   These averages mask some variation, especially among EMEs: the tightening cycle of Latin American central banks pre-dated that of the Federal Reserve, while Asian economies typically embarked on tightening later, in part because the rise in inflation there was much more modest. Importantly, in China the official interest rate did not follow the global upward trend.

⁵   See Avalos et al (2022) for a discussion on the estimates of the growth impact under a natural gas shutdown scenario.

⁶   US banks seem to hedge little of their interest rate risk with derivatives, such as swaps (McPhail et al (2023)), in part due to reliance on hedges from their deposit franchise and accounting considerations.

⁷   In contrast to trading assets, changes to the market value of available-for-sale (AFS) and held-to-maturity (HTM) assets do not immediately have to be recognised in earnings. AFS and HTM assets, in turn, differ in how they affect banks’ reported equity, as this adjusts only in response to valuation changes on AFS holdings. In the United States, only the largest banks have to reflect such valuation changes in their regulatory capital. Following a change in legislation in 2018, banks with total assets of less than $250 billion, such as SVB before its failure, no longer have to reflect such losses.

⁸   See BIS (2022) and Borio et al (2023) for a detailed account of the transition mechanisms from a low- to high-inflation regime.

⁹   See Borio et al (2023).

¹⁰ See BIS (2022) for a historical perspective on how labour market institutions relate to low- vs high-inflation regimes.

¹¹ Evidence exists of a negative and significant relationship between contract durations and inflation uncertainty. See Rich and Tracy (2004), Christofides and Peng (2006), Fregert and Jonung (2008).

¹² See Cavallo and Kryvtsov (2023).

¹³ This interpretation comes with caveats. First, tight policy and weakened aggregate demand put a limit on profits. Second, a steady rise in profits and prices does not necessarily mean a steady rise in market power (captured by markups). Other factors, such as stronger demand or a temporary pause in new capital investment, could be behind the rising profits. Third, and related, margins 32 BIS Annual Economic Report 2023 and markups are notoriously difficult to measure accurately in real time and vary greatly among sectors. Last but not least, the link between market power and pass-through of costs to consumer prices is ambiguous. On the one hand, more power could allow firms to pass rising costs to consumers. On the other hand, higher markups could give firms headroom to absorb rising costs and compete on market share.

¹⁴ See Graph 9 in Borio et al (2023), which shows the sensitivity of inflation to past wage growth for different time periods. In addition, in Box 2 the authors use a cointegrating model for prices and wages to show that, in a high-inflation regime, changes in prices react in a significant way to changes in wages, and vice versa.

¹⁵ See Mojon et al (2023) for more details of the decomposition exercise and for a discussion of burden-sharing under projected disinflation paths in the euro area and the United States. In this simple accounting-based approach, profits are proxied by the ratio of GDP deflator to unit labour costs. Productivity growth is assumed to be in line with historical norms.

¹⁶ Of course, another margin of adjustment available to firms is the quantity rather than the price of labour. Typically, during disinflation episodes, unemployment increased about six months before peak headline inflation was reached and was almost 1.5 percentage points higher two years later. This time around, by contrast, unemployment actually fell as inflation rose and, to date, it has not risen much from the historically low levels it reached.

¹⁷ The sample covers Canada, Chile, Denmark, the euro area, India, Korea, New Zealand, Peru, Switzerland, Thailand and the United States.

¹⁸ The methodology and the underlying assumptions are explained in the technical annex. Notably, there is no explicit treatment of monetary policy. Its impact comes only indirectly: the exercise implicitly captures a successful monetary policy tightening by assuming that the unemployment gap returns to zero by the end of 2023 in all scenarios. Also, the results largely depend on the strength of the wage-price link estimated over a historical sample, and hence need to be taken with a pinch of salt: by considering the average strength of the relationship over a given sample, they may underestimate that, when inflation runs particularly high, the feedback effect may be even stronger.

¹⁹ See Igan et al (2022).

²⁰ See Ampudia et al (2023).

²¹ Economies with relatively low debt levels tend to see house prices level off after the first rate hike, while those where household debt is in the upper third of the distribution typically see a pronounced and prolonged fall in house prices.

²² See FSB (2020).

²³ ETFs could be less prone to such risks given their advantageous fund structure, see Shim and Todorov (2023).

²⁴ The leveraged loans market also experienced strong growth, see Aramonte et al (2022).

²⁵ See Aramonte and Avalos (2021).

²⁶ For example, leveraged loan volumes reached multidecade highs in 2022, at more than $1.8 trillion in Europe and the United States. See Aramonte et al (2022).

²⁷ For a discussion of how inflation indicators can become less useful during a regime switch, see De Fiore et al (2022). More generally, similar pitfalls plague the assessment of the current tightening. In a low-inflation regime, it may appear that monetary policy plays a minor role: as measured by standard models, the impact of monetary policy shocks – deviations from a policy rule – on inflation declines (eg Borio et al (2023)). This adds to the calibration challenge. But concluding that monetary policy as such does not matter would be a mistake: policy shocks do not capture the broader rule and the broader rule itself is what secures and maintains the low-inflation regime.

²⁸ See Bailey (2023) for elaboration on a recent example.

²⁹ See Chapter II on possible long-term adjustments to monetary policy frameworks to manage the trade-offs.

³⁰ See OECD (2022) for an assessment of where different support measures stand on these dimensions. Governments often focus on price controls, which are in large part non-targeted, can blur price signals that would facilitate adjustment and tend to support rather than curb demand.

³¹ Simple averages of Brazil, China, India, Indonesia, Korea, Mexico and Poland.

³² See Carstens (2021).

³³ See Boissay et al (2023).

³⁴ See Borio et al (2022).

³⁵ See IMF (2023) and OECD (2023).

³⁶ See Carstens (2022).

³⁷ See also Carstens (2023).

Technical annex

Graph 1: “Other AEs” is an average of AU, CA, CH, DK, GB, NO, NZ and SE, weighted by GDP and PPP exchange rates. “Latin America” is a simple average of BR, CL, CO and MX. “Other Asia” is a simple average of KR and SG. “Food and energy” includes alcoholic beverages.

Graph 3.A: Country groups calculated using GDP and PPP exchange rates. “AEs” is based on data for AU, CA, CH, DK, EA, GB, JP, NO, NZ, SE and US. “EMEs” is based on data for BR, CL, CN, CO, CR, CZ, HU, IL, KR, MX, PL, SA, TR and ZA. The coefficient of variation is calculated using data starting from 2012.

Graph 3.C: Calculation based on the principal component decomposition of the full sample. Nine AEs and eight EMEs.

Graph 4.A: For each country, tightening episodes are identified as months between the trough and peak in the policy rate around periods when the seven-month centred moving average of the policy rate is increasing. Episodes in which the policy rate increases by less than 1 percentage point or more than 20 percentage points, or episodes that last less than six months or more than 48 months, are excluded from the analysis. Based on data for 11 AEs and 16 EMEs from Jan 1970 to Feb 2023 (subject to availability); 154 tightening episodes.

Graph 4.B: Policy rate deflated by the weighted average of the current and next year Consensus forecasts for year-on-year inflation. Median based on monthly data for 11 AEs and 23 EMEs.

Graph 4.C Policy rate deflated by realised year-on-year inflation. Median based on monthly data for 11 AEs and 23 EMEs.

Graph 5.A: GDP-weighted average of EA, GB and US. Mortgage rates = for US, average of 15-year and 30-year fixed rate; for GB, average of two-year and five-year fixed rate with 60 and 90 LTV; for EA, new business mortgage rate. NFC loans rate = for US, bank prime loan rate; for GB, new business NFC fixed rate; for EA, new business NFC narrowly defined effective rate.

Graph 6.A: Country groups calculated as weighted averages using GDP and PPP exchange rates. “Other AEs” is based on data for AU, CA, CH, GB and SE. “EMEs excl CN” is based on data for AR, BR, CL, CO, CZ, HK, HU, ID, IL, IN, KR, MX, MY, PE, PH, PL, RO, RU, SA, SG, TH, TR, VN and ZA.

Graph 7.A: “EMEs” is based on data for AE, AR, BR, CL, CO, CZ, DZ, HU, ID, IL, KR, MA, MY, MX, PE, PH, PL, RO, RU, SA, SG, ZA, TH and TR. Calculated as weighted averages using GDP and PPP exchange rates.

Graph 7.C: For economic activity, Yicai Research Institute’s high-frequency economic activity indicator; for box office revenues, one-month rolling average of the Maoyan Entertainment’s box office revenues; for port congestion, the average of Kiel Institute’s traffic indices for Hong Kong SAR and Guangdong, and for Shanghai and Zhejiang; for road congestion, the one-month rolling average of the average China Ministry of Transport’s road congestion index across 101 Chinese regions; for subway traffic, the one-month rolling average of the sum of number of passengers in 10 important Chinese regions; for international flights, the one-month rolling average of the number of operated international flights.

Graph 9.A: S&P 500 index for the United States; Shanghai Shenzhen CSI 300 Equity Index for China. AEs (excl US): weighted average of S&P/ASX 200, S&P/TSX Composite Index, Swiss Market Index, OMX Copenhagen Index, EURO STOXX 600 Index, FTSE 100 Index, Nikkei 225, OBX Stock Index, S&P/NZX 50 Index and OMX Stockholm Benchmark for AEs. EMEs (excl CN): weighted average of Brazil Ibovespa Index, S&P/CLZ IPSA, MSCI Colcap Index, Prague Stock Exchange Index, Hang Seng Index, Budapest Stock Exchange Index, S&P BSE Sensez Index, Jakarta Composite Index, Kospi Index, S&P/BMV IPC Index, FTSE Bursa Malaysia KLCI, S&P/BVL PeruGeneral TRPEN, PSEi Philippine SE Index, WSE WIG Index, Straits Times Index, Stock Exchange of Thailand Index and FTSE/JSE Africa ALL SHR Index for EMEs.

Graph 10.A: Long-duration loans, mortgages and debt securities as a percentage share of total loans, mortgages and debt securities; based on a sample of more than 230 large and mid-size US banks.

Graph 10.B: Estimated impact of a +200 basis point parallel shift in the yield curve on banks’ Tier 1 capital; “Other” comprises G-SIBs from Canada, China and Japan; based on available G-SIB disclosures at end-2022 and end-2021 data for Silicon Valley Bank (SVB).

Graph 10.C: Regional aggregates based on a balanced sample of 341 major banks from 42 countries; four-quarter rolling averages.

Graph 11.A: Outstanding loans through the Federal Reserve’s Bank Term Funding Program and discount window (primary credit) up to latest available.

Graph 11.B: Asset-weighted average based on a sample of 233 US banks.

Graph 12: Each disinflation episode is captured when the 13-month moving average is at its peak, under the conditions that (i) there are no other peaks in the preceding and the following 12 months; (ii) the peak is between 3% to 25%; and (iii) the peak is at least 3 percentage points higher than the lowest troughs in the preceding and the following 12 months. Month = 0 is when the actual headline inflation value is at the highest during that particular episode. Panel of 30 AEs and 28 EMEs, subject to data availability. In Graph 12.D, real interest rate is computed as an ex post rate using the policy rate and the headline inflation.

Graph 13.B: High-inflation regime samples: CA, Q4 1971–Q4 1990; JP, Q4 1970–Q4 1979; KR, Q4 1985–Q4 1997; MX, Q1 1983–Q4 2002; US, Jan 1965–Dec 1985. Low-inflation regime samples: CA, Q1 1991–Q4 2019; JP, Q1 1980–Q4 2019; KR, Q1 1998–Q4 2019; MX, Q1 2003–Q4 2019; US, Jan 1986–Dec 2019.

Graph 14.B–C: See technical annex for Graph 12 for the definition of disinflation episodes. Real wages are computed by deflating nominal wages by headline CPI. Profits are proxied by the ratio of GDP deflator to unit labour costs.

Graph 15.A: Projections are based on country-specific macroeconomic models, the results of which are then aggregated using GDP weights. The models estimate a long-run relationship between the (log-)level of prices (core CPI), wages (average hourly compensation for total economy) and labour productivity, as well as short-run adjustment equations in which deviations from the long-run relationship contribute to the dynamics; the models and the estimates are described in detail in Borio et al (2023), Box B. Conditional projections of inflation are constructed by letting labour productivity grow at the average rate observed over the last 10 years, and assuming a wage growth rate as specified under each of the two scenarios. For the projections in 2023, average residuals of inflation in 2022 are also included, decaying by a factor of 0.25 every quarter. Note that, since core CPI is used as the metric for prices, import prices drive a wedge relative to an exercise where the GDP deflator is used.

Graph 18: Projections are based on country-specific macroeconomic models. The models consist of a VAR linking the behaviour of private sector debt-to-income ratios, real house prices, real equity prices, real income, effective private sector interest rates and real GDP. The coefficients in some VAR equations (eg equity prices) are restricted to reflect realistic information lags. VARs are estimated over the sample Q1 1985–Q4 2019. Policy interest rates are included as an exogenous variable in the model. In each scenario, all variables other than the policy rate evolve according to their estimated relationships in the model.

Graph 19.A–B: Credit losses calculated based on the private sector debt-to-income and credit growth projections shown in Graph 17 using the approach described in Juselius and Tarashev (2022).

Graph 19.C: Total capital ratio is the total capital adequacy ratio under the Basel III framework. It measures Tier 1 plus Tier 2 capital, which includes subordinated debt, hybrid capital, loan loss reserves and the valuation reserves as a percentage of risk-weighted assets and off-balance sheet risks.

References

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II. Monetary and fiscal policy: safeguarding stability and trust

Introduction

For the first time in recent decades, we are seeing high inflation and financial stress emerging in tandem. While each has its own specific causes (Chapter I), they are, to a significant extent, a symptom of the cumulative effect of accommodative monetary and fiscal policy over past decades, culminating in the extraordinary support measures launched in response to the pandemic. In many countries, policy rates, nominal and real, were historically low for a prolonged period and central bank balance sheets surged to levels never seen in peacetime (Graph 1.A). At the same time, persistent and large fiscal deficits led to a progressive increase in public debt to unprecedented levels (Graph 1.B). These policy trajectories gave an important and enduring push to inflation and fostered the build-up of fragilities in the financial system.¹

The current tensions can be seen as a symptom that the two policies were testing the boundaries of what might be called the “region of stability”. The region maps constellations of monetary and fiscal policy that foster macroeconomic and financial stability, and keep the inevitable tensions between the policies manageable. The region’s boundaries are elusive and it is often only fully apparent ex post that they have been tested, since economic systems can appear stable until, suddenly, they are not. The ultimate risk of drifting outside the region is a loss of the trust that society must have in the state and in its decision-making.

The recent challenge to the boundaries is the latest in a long journey that stretches back to at least the 1970s. At each point in time, the policy choices seemed reasonable, even compelling. But cumulatively, they pushed the policies towards the boundaries. The root cause of the drift has been a tendency for policymakers to succumb to a kind of “growth illusion”, ie an overly optimistic view about the ability of macroeconomic stabilisation policies to sustain economic growth.²

Policy adjustments and institutional safeguards are needed to ensure that monetary and fiscal policy remain firmly within the region of stability. The policies should aim to foster a stable financial and macroeconomic environment in which sustainable growth, which is ultimately driven by supply factors, can take hold. And, to do so, they need to retain sufficient safety margins to deal with unexpected untoward events, as well as inevitable recessions. Ultimately, though, the adjustments call for a shift in mindset, that is, a keener recognition of the limitations of stabilisation policies, which cannot act as engines of growth. Having the region of stability as a conscious and explicit policy consideration would help to guide action.

This chapter lays out the enduring challenge for monetary and fiscal policy to stay within the region of stability and how it might be addressed. The chapter first outlines the role of monetary and fiscal policy as core economic functions of the state and introduces the concept of the region of stability. It then describes the journey of monetary and fiscal policy over the past decades to the boundaries of the region, ushering in high inflation and financial fragility. It next discusses the potential risks ahead for macroeconomic and financial stability. The chapter ends by exploring policy implications.

Policy interactions and the region of stability

As two core economic functions of the state, monetary and fiscal policy play a key role in ensuring economic stability and trust in policymaking. Both policies entail privileged powers to access and reallocate economic resources in society. Fiscal policy hinges on the power to raise taxes and the prerogative to issue debt backed by future tax revenues. Monetary policy wields the power to issue “money”, an irredeemable liability of the state used as a means of payment. These powers are mutually reinforcing. The requirement to pay taxes with money sustains money demand, encouraging its use as a payment tool. In turn, a stable monetary system strengthens the tax base. Furthermore, money issuance supports fiscal revenues through seigniorage and can help prevent technical government default as public debt is redeemable against money.

The privileged powers of fiscal and monetary policy ultimately depend on an implicit social contract underpinned by trust in the state. People consent to paying taxes because they trust the government to use the proceeds for the public good. Similarly, people accept the use of money as a means of payment because they trust the central bank to preserve its value.

The need to retain society’s trust sets limits on the privileged powers of the two policies. Monetary and fiscal policies can become a major force for prosperity if used effectively to provide public goods and to ensure a stable financial and macroeconomic environment, underpinned by a sound payment system. If instead their powers are wielded unwisely, the policies can seriously damage the economy and, ultimately, trust in the state.

The main channels through which monetary and fiscal policies influence economic activity differ considerably. Fiscal policy does so primarily through the direct impact of spending on goods and services, and the production of some of those services, as well as through transfers to households and firms. Monetary policy works primarily through the central bank’s operations in financial markets – notably the policy interest rate – which have a pervasive effect on yields, borrowing costs, asset prices and the exchange rate.

That said, overlaps are also substantial. Fiscal policy influences financial conditions through debt issuance. Not only does public debt underpin the functioning of the financial system and the pricing of assets, it can have a far-reaching effect on the yield curve, other asset prices and the exchange rate, as well as on the soundness of the financial system when fiscal soundness is put in doubt. Monetary policy, in turn, influences the state of public finances. It does so directly, by setting interest rates (borrowing costs) and through its effect on the exchange rate (when debt is denominated in foreign currency); and it does so indirectly, through its impact on economic activity and inflation more generally, which can materially alter government expenditures and taxes.

The two policies are further entwined through interlocking balance sheets (Box A). Since the central bank is part of the state, its financial results feed into the financial condition of the government through remittances. The large-scale purchases of government debt, as well as the accumulation of foreign exchange reserves, have made government finances more sensitive to central bank decisions.

The region of stability

The pervasive impact that monetary and fiscal policy have on economic activity, and the overlapping nature of their transmission channels, means that the two policies are joined at the hip. They may work in a coherent fashion to foster a stable financial and macroeconomic environment; but they can, equally, undermine that stability and generate tensions between them that are very difficult to manage.

The concept of the “region of stability” helps identify the appropriate zone of operation of the two policies (Box B).³ This region captures the set of monetary and fiscal policies that are consistent with macroeconomic and financial stability. The boundaries of the region vary across countries and are difficult to pin down with precision ex ante. They cannot be summed up in simple metrics, akin to a constraint on the level of the fiscal deficit or on the policy rate.

Furthermore, the size, shape and locus of the region shift over time. Some changes occur gradually, such as those due to structural developments in the labour market and the structure of production. But the region can also shrink and shift position rapidly, for example due to a sudden loss of confidence in policy or in the economy at large – a risk that has become more acute over time due to the rapid growth and increased fragility of the financial system. This underscores the need for fiscal and monetary policy to operate well within the region and to leave sufficient safety margins at its boundaries.

The cumulative effect of past fiscal and monetary policy decisions crucially shapes the region’s boundaries. For example, prolonged periods of monetary and fiscal accommodation may contribute to the build-up of a broad range of vulnerabilities – including greater leverage and risk-taking – that can eventually constrain the policies’ room for manoeuvre. Hence the typically intertemporal nature of the trade-offs involved. A policy conduct that may appear stabilising in the near term can, over time, inadvertently shrink the region and take policies towards the boundary. The economic system may appear stable for a long time until, suddenly, it is not.

The boundaries are also approached through the interaction of the two policies. For a given interest rate path, a fiscal policy stance that is cumulatively too loose will risk higher inflation and a sovereign crisis, as debt builds up. For a given fiscal policy path, a monetary policy stance that is cumulatively too easy can generate higher inflation and financial stability risks. Along the corresponding paths, the two policies can reinforce each other’s trajectories. Easy monetary policy can induce the government to build up more debt; expansionary fiscal policy can make it harder for monetary policy to be as tight as necessary.

Testing the region’s boundaries can trigger vicious cycles. In that case, both policies end up narrowing their respective rooms for manoeuvre, shocks become increasingly damaging and policies increasingly destabilising. The instability, in turn, threatens or reflects loss of trust in the policies themselves. A common feature is loss of trust in money – as a store of value, means of payment or unit of account – and in the sustainability of public debt.

Instability in the wake of overstepping the boundaries of the region of stability can take different forms. Common manifestations include high inflation, economic slumps, sovereign default and financial stress. A sharp depreciation of the exchange rate is a typical symptom and transmission channel. The most acute manifestation of drifting far outside the boundaries is hyperinflations, such as those experienced in some Latin American emerging market economies (EMEs) in the 1980s and 1990s. These show how fiscal pressures and their monetary policy accommodation can destroy the value of money (Graph 2.A).

Another manifestation is the coincidence of sovereign debt, systemic banking and currency crises (Graph 2.B). Acute financial crises often feature the so-called doom loop between the sovereign’s balance sheet and the financial sector. In such episodes, fiscal and financial instability reinforce each other, as banks suffer losses on government bond holdings while governments need to shore up the failing banking system. In turn, these fiscal and financial crises undermine trust in the currency, and currency depreciation further exacerbates instability.

Testing the boundaries: the long journey so far

The journey: from the 1960s to today

Prior to the pandemic, monetary and fiscal policy were already approaching the boundaries of the region of stability. Interest rates had been historically low for a prolonged period and central bank balance sheets had risen to wartime-like levels following more than a decade of monetary stimulus in the wake of the Great Financial Crisis (GFC). At the same time, public debt had reached historical highs following persistent fiscal deficits. This constellation meant a substantial loss in room for policy manoeuvre and left economies vulnerable to shocks as well as to the inevitable next recession. Then, when the pandemic – a bolt from the blue – struck, the policies tested those boundaries further, ushering in high inflation and financial fragility.

How did monetary and fiscal policies come to approach the boundaries pre-pandemic? It was the result of a long journey. The journey was not linear. The symptoms of an overly expansionary policy stance evolved with the economic landscape that those policies were helping to shape, together with more fundamental structural forces. A consistent underlying factor was the overestimation of how far macroeconomic policies could steer the economy and, by pushing hard enough, ignite the engine of growth – a kind of “growth illusion”. This induced a progressive loss of policy space over time.

It is useful to divide the journey going back to the 1960s into two phases, with the mid-1980s as a rough watershed. Graph 3 illustrates the break, with reference to advanced economies (AEs) – see below for a discussion of similarities and differences with EMEs.

Until the mid-1980s, the key symptom indicating that the policies were testing the speed limits of the economy, and hence the boundaries of the region of stability, was rising inflation. Recessions were typically induced by a tightening of monetary policy to quell inflation. With the financial system hemmed in by regulation, signs of large build-ups and contractions in credit were missing. During this phase, the drift to the boundaries reflected, in part, the belief that policymakers could fine-tune the economy by a carefully calibrated mix of monetary and fiscal policy. Hence the concept of a stable long-run trade-off between unemployment and inflation. The result was the Great Inflation of the 1970s.

In response to the inflation crisis, policymakers took steps to bring monetary and fiscal policies back within the region of stability. Central banks sought to end inflation by aggressively hiking policy rates. Following the disinflation in the first half of the 1980s, monetary regimes prioritising price stability gradually became the norm. Interest rates declined substantially from their previous peak. However, the rise in interest rates on the back of monetary tightening in the early 1980s had exposed fiscal fragilities in many countries. In combination with persistent fiscal deficits, this led to a surge in public debt. Thus, many governments were forced to embark on fiscal consolidation. For more than a decade from the early 1990s, public debt levels, on average, stabilised.

The beginning of the second phase in the mid-1980s reflected, paradoxically, the confluence of these improvements in policy frameworks with fundamental structural change. The combination altered business cycle dynamics in subtle but far-reaching ways. Financial systems were profoundly liberalised. By the early 1990s, a “government-led” financial system had given way to a “market-led” one, both domestically and internationally.⁴ And the globalisation of the real economy soon followed. EMEs, most notably China, joined a seamless global labour force and tight production networks spread across the world.

As a result of these changes, inflation ceased to be the main symptom of policies testing the boundaries of the region of stability. Central banks secured price stability as the globalisation of the real economy was eroding the pricing power of workers and firms. This was a powerful structural tailwind, which helped central banks hardwire the low-inflation regime and meant that a given inflation rate would be consistent with lower real and nominal interest rates. It was the era of the Great Moderation.

The symptoms of overstretch now took the form of financial imbalances, ie outsize expansions in credit and asset prices, notably real estate prices, on the back of strong risk-taking. Inflation-induced recessions gave way to financial recessions. Inflation was on average low and stable and barely rose prior to business cycle contractions, while falling mildly but persistently below the pre-recession level in their wake. Instead, business cycles featured sharp pre-recession financial expansions that turned into contractions. The recessions became commonly associated with financial stress or, with prudential regulation failing to adjust to the new environment, even outright crises, most spectacularly the GFC. These recessions had a longer-lasting impact on growth, as the economy laboured under a legacy of higher debt,⁵ thereby also biasing traditional cyclical adjustment measures.

Over time, the shift from inflationary pressures to financial imbalances contributed to the gradual erosion of policy space. Monetary policy naturally eased during contractions to cushion the economy and fight the headwinds of private sector balance sheet repair. But it had little reason to tighten much during expansions since inflation remained low and stable. Interest rates progressively declined. For fiscal policy, the GFC was a watershed. The outsize financial boom that preceded it greatly flattered government accounts by artificially raising estimates of potential output and boosting tax revenues, thereby disguising the more expansionary stance.⁶ Financial crises then forced sovereigns to backstop the financial system and support faltering economies, as some countries had already done in the banking crises of the 1990s. Public debt initially increased massively, sustained by low interest rates that kept a lid on debt servicing costs.

The challenges intensified in the aftermath of the GFC. Monetary policy struggled to push inflation back up to target: the globalisation tailwinds that had helped to bring inflation down to target pre-GFC were hindering the central banks’ efforts to push it back up. Fiscal policy did seek to regain some of the room for manoeuvre lost in the aftermath of the GFC. But, as a result, monetary policy became the “only game in town”. As time wore on, fiscal policy was then asked to support monetary policy in the fight against low inflation by boosting economic activity. It was a topsy-turvy world compared with the one that had preceded it.

The pandemic gave the final push towards the boundaries. All the policy stops were pulled out to shield households and firms from the full force of the lockdowns put in place to deal with the Covid-19 health emergency. Ostensibly, they could stretch the room for manoeuvre further, but the risks were material. At least with the benefit of hindsight, the support proved to be too large and prolonged. Inflation surged on the back of such macroeconomic stimulus when the economy rebounded with surprising vigour as restrictions were lifted and when supply failed to respond in a sufficiently elastic way.⁷ And this took place against the backdrop of historically high levels of public and private debt, as well as elevated asset prices. For the first time, globally, a surge in inflation coincided with widespread financial vulnerabilities (Chapter I).

The journey: reinforcing effects

Along the journey towards the boundaries of the region of stability, a number of factors reinforced the trajectories of fiscal and monetary policy.

Arguably, one such factor was the waning traction of policies as they approached the boundaries. Changes in policy rates tend to have a smaller effect on aggregate demand when nominal interest rates are very low (Graph 4.A), reflecting, for example, negative income effects on savers and the adverse impacts on bank profitability of persistently low rates.⁸ This loss of traction implies that larger interest rate cuts are needed to produce the same impact on output and inflation, pushing monetary policy closer to the boundary of the region of stability. Moreover, the side effects of monetary easing through higher risk-taking and private debt build-up tend to become stronger when interest rates are low and stay there for a long time, narrowing the region of stability.⁹

Fiscal stimulus also tends to become less powerful when public debt is higher. This likely reflects adverse confidence effects that kick in when doubts about fiscal sustainability grow. Therefore, larger fiscal measures are required to achieve the same stimulus as debt trends up.¹⁰

The self-reinforcing interactions between the two policies constitute a second important factor. Lower interest rates reduced fiscal constraints, diminishing the need and incentive to consolidate in economic expansions. Reductions in the interest rate paid on the debt have indeed been associated with an increase in fiscal deficits, especially during the post-GFC period of ultra-low interest rates (Graph 4.B). Central bank large-scale asset purchases of sovereign debt played a key role in this respect. Across advanced economies, central bank holdings of government debt soared post-GFC (Graph 5.A), driven primarily by large-scale bond purchases of major central banks (Graph 5.B).

High public debt levels, in turn, probably reinforced incentives to maintain an accommodative monetary stance. When debt levels are high, interest rate hikes have a stronger impact on debt servicing costs, raising more acute concerns about adverse macro-financial and fiscal repercussions. By the same token, central bank balance sheet normalisation becomes more difficult when public debt is high because markets must absorb larger amounts of debt. These factors may have made it harder to tighten monetary policy and shrink central bank balance sheets – a kind of “debt trap”.

The journey: how different are EMEs?

The journey of EMEs has several similarities to that of AEs. It was shaped by the same global forces that affected business cycles over time. For one, financial liberalisation – sometimes country-specific – elevated the role of financial cycles and increased the incidence of banking crises. Prominent examples include the Southern Cone crisis in Latin America in the early 1980s, the Tequila crisis in Mexico in 1994 and the Asian crisis of 1997–98. In addition, the globalisation of the real economy weighed on inflation from the 1990s on, reinforcing the impact of the adoption of price stability-oriented monetary policy regimes. These basic similarities are reflected also in the broad evolution of key variables such as inflation, interest rates, fiscal deficits and public debt (Graph 6).

At the same time, there are also important differences, including among EMEs, related to structural factors.

Some of these factors have mainly influenced differences in the journey across EME regions. Political and institutional features can shape attitudes towards fiscal policy, inflation and growth. Partly as a result, inflation has been structurally lower in Asia than in Latin America, which saw hyperinflations in the 1980s and 1990s, often combined with sovereign default and financial stress (Graph 7).¹¹

Other structural factors drive differences, mainly, between EMEs and advanced economies more generally. A key such factor is EMEs’ greater sensitivity to global financial conditions and market sentiment. This greater sensitivity reflects, primarily, less developed financial markets, including fewer FX hedging possibilities, and greater reliance on FX funding.¹² It has four main implications.

First, the region of stability is smaller and more fluid. The margin of error is commensurately narrower and the risk of sudden and abrupt discontinuities higher. As a result, when policies step outside the region of stability, market discipline is typically felt earlier and more intensely than in AEs, forcing a rapid shift back.¹³

Second, the symptoms of breaches of the boundary of the region more often take the form of capital outflows and large depreciations. The exchange rate plays a bigger role, as a force behind fiscal fragility, inflation and financial instability. And given the greater prevalence of fixed or tightly managed exchange rate regimes until the late 1990s, the incidence of currency crises has been higher. This has prompted a shift over time towards more flexible exchange rate arrangements, accompanied by a widespread adoption of inflation targeting frameworks (Graph 8.A).¹⁴

Third, the impact of monetary policy in AEs, notably in the United States, given the dominant role of the US dollar, has been especially prominent. Changes in the US monetary policy stance and swings in the US dollar have been major forces behind the ebbs and flows of global conditions. For example, the Volcker disinflation triggered the Latin American debt crisis, characterised by financial fragilities that had been amplified by strong capital inflows linked to the recycling of petrodollars. The shift to more flexible exchange rate regimes has attenuated, but by no means eliminated, this influence.¹⁵

Fourth, the greater exposure to global financial conditions and repeated crises has, over time, fostered EMEs’ awareness of the boundaries of the region of stability and their fluidity. From the late 1990s, well before the GFC, they took steps to strengthen their policy frameworks, complementing flexible inflation targeting with a more active use of FX intervention (Graph 8.B), macroprudential tools (Graph 8.C), as well as, to a lesser extent, targeted capital flow management measures – key elements of macro-financial stability frameworks.¹⁶ Again, regional differences emerged, with greater concerns about domestic financial imbalances and a lower degree of exchange rate flexibility in Asia than in Latin America.

These enhanced policy frameworks have allowed countries to more successfully weather the GFC and the Covid crises (Graph 7) by increasing shock resilience and enabling countercyclical policies in bad times. They also help explain, for example, why countries in Latin America have tightened monetary policy earlier and more forcefully than many of their AE peers post-Covid. At the same time, these improvements have also somewhat relaxed the policy constraints the countries faced, widening the perceived region of stability. This is, in turn, not without risks going forward and could partly account for the deterioration in fiscal positions and ratings post-GFC (see Graph 6 and below).

Testing the boundaries: risks in the journey ahead

What is the next step in the journey of AEs and EMEs? What are the implications of having tested the boundaries of the region of stability? The ongoing struggle to restore price stability and fend off financial stability risks has triggered tensions between fiscal and monetary policy that raise further challenges down the road.

Three main interrelated challenges stand out. First, public finances are facing major strains owing to the combination of record high levels of public debt, strong spending pressures, higher interest rates and weakening growth prospects. Second, large fiscal deficits and high public debt are at risk of working at cross purposes with monetary policy tightening, potentially complicating the fight against inflation. Third, the deterioration in public finances and the sharp repricing of long-term debt in the wake of interest rate hikes may raise financial stability risks.

Consider each issue in turn.

Risks to fiscal positions and the sovereign’s creditworthiness

The increase in public debt in AEs and EMEs has led to a deterioration in sovereigns’ creditworthiness (Graph 9.A). In AEs, sovereign credit ratings worsened considerably following the surge in debt levels in the wake of the GFC. In EMEs, credit ratings have gradually deteriorated during the past decade in line with the increase in debt levels.

The unexpected inflation surge after the Covid-19 pandemic has temporarily embellished fiscal accounts by boosting nominal GDP and thus mechanically reducing debt-to-GDP ratios. Inflation has also flattered fiscal balances. Since many taxes are levied in proportion to nominal variables – such as wages, sales etc – they tend to increase immediately as prices rise. By contrast, public expenditures are largely fixed in nominal terms from year to year.

Yet improvements in fiscal balances due to inflation are ephemeral. Rising costs will feed into higher public spending and governments will confront pressures to raise public wages and social transfers in line with price increases, if this is not already occurring automatically through indexation mechanisms. Furthermore, the monetary tightening required to bring inflation down will increase borrowing costs and constrain economic growth. Indeed, the historical experience shows that periods of higher inflation tend to be followed, if anything, by rising – not declining – public debt (Graph 9.B).

Looking ahead, fiscal authorities will confront severe challenges due to large new spending pressures, the possibility of higher medium-term interest rates and dimmer growth prospects.

First, consider the implications of new spending pressures for the path of public debt going forward. Estimates for AEs and EMEs suggest that age-related expenditures will grow by approximately 4% and 5% of GDP, respectively, over the next 20 years. Absent fiscal consolidation, this would push debt above 200% and 150% of GDP by 2050 in AEs and EMEs, respectively, even if interest rates remain below growth rates, as was the case in the pre-pandemic years (Graph 10).

Other factors may add to the pressure on public finances. The commitment to supporting a transition towards a sustainable global economy in response to climate change is one. In addition, geopolitical tensions are likely to lead to a material increase in defence spending. An illustrative scenario that includes a rise in public spending by 2% of GDP on top of the increase in age-related spending, would lead to an additional increase in public debt of approximately 50% of GDP by 2050.

These worrying debt projections are, in fact, rather optimistic: they assume that real interest rates will remain 1 percentage point below growth rates, broadly in line with the experience in recent years. As is well known, this configuration tends to ease debt sustainability pressures (Box C).

Indeed, there are two important reasons why it would be imprudent to count on large and permanent negative differentials between interest rates and growth rates. First, inflation may prove stubborn and require higher interest rates for longer than currently expected. High inflation may also lead to a re-assessment of inflation risk, prompting investors to demand higher risk premia to hold government bonds. And attempts to regain price stability may ultimately result in a substantive economic slowdown.

Second, the link between structural factors and low real rates, which is often relied upon to project persistently low interest rates, is not watertight.¹⁷ The economy may thus exit the current period of high inflation by confronting a new reality with higher real rates.

Should real rates increase on a sustained basis, public debt sustainability would come under further considerable pressure. Two factors compound the effect of interest rate hikes on public finances.

The first is the post-GFC large-scale government bond purchases implemented by several central banks. These purchases – which amounted to 25–50% of the outstanding stock in major AEs (Graph 5.B) – were financed with central bank reserves, thus shortening the maturity of the consolidated public debt. This implies that higher interest rates transmit much faster to public finances via reduced remittances from central banks. Indeed, after accounting for approximately 6% of interest payments on public debt in 2010–20, central bank transfers to governments in AEs have already declined to zero in most countries (Graph 11.A).

The second, much more general factor is the historically high levels of public debt, which means that higher interest rates can lead to a large increase in debt service costs. For example, should interest rates return to levels prevailing in the mid-1990s, interest rate payments on public debt would, over time, surge above 6% of GDP – the highest level in the post-World War II period (Graph 11.B).

Pressures on public debt would increase further should medium-term growth prove disappointing. Global growth prospects are the weakest in decades owing to several structural forces, including geoeconomic fragmentation, slower labour force growth, and slowdowns in China and other EMEs.¹⁸ In addition, risks to fiscal positions may themselves weaken economic prospects and raise the risk of adverse non-linear effects. For example, high public debt may constrain the ability of fiscal policy to operate countercyclically during recessions. This could erode confidence in the economic outlook, thus reducing private investment and growth. In turn, weaker growth prospects may exacerbate fiscal risks, increasing risk premia and further undermining economic activity. Countries with higher public debt levels thus tend to experience shorter phases with interest rates lower than growth rates, as well as a higher probability of a reversal.¹⁹

In EMEs, the potential for vicious circles between fiscal sustainability, slowing growth and rising interest rates is higher. One key reason is that exchange rate reactions can suddenly push countries to bump up against debt limits. Loss of confidence in debt sustainability can trigger sharp depreciations that, in the presence of currency mismatches can wreak havoc on public and private balance sheets, leading to exploding debt service costs and severe recessions.

Inflation risks

Pressure on fiscal positions and sovereign risk may increase inflation risks going forward.

In the near term, fiscal deficits remain large in many countries, thus sustaining aggregate demand and inflation. Hence, monetary and fiscal policy are at risk of working at cross purposes, complicating the fight against inflation (Chapter I). This heightens the risk of transitioning to a high-inflation regime – a concern that becomes more acute the longer inflation remains elevated.

Taking a long-term perspective sheds further light on these risks. The evidence indicates that the inflationary effects of fiscal policy depend on the fiscal and monetary policy regime. In AEs, if fiscal policy is prudent – leaning against public debt increases through higher primary balances – and central banks are independent, fiscal stimulus has modest effects on inflation (Graph 12.A).²⁰ But if fiscal policy fails to stabilise debt (ie is profligate) and central bank independence is questioned, the inflationary effects of fiscal policy are much stronger.

The effects of fiscal stimulus on inflation tend to be greater in EMEs (Graph 12.B). This is largely due to the role of the exchange rate. In advanced economies, fiscal stimulus tends to have no significant effect on the exchange rate. By contrast, fiscal expansions in EMEs trigger a significant depreciation of the exchange rate.²¹ In turn, exchange rate depreciations feed into higher inflation, and to a larger extent than in advanced economies (Graph 13.A).

The transmission of fiscal stimulus to exchange rates in EMEs largely reflects concerns about sovereign risks. Fiscal expansions are associated with increases in sovereign risks, as captured by credit default swap (CDS) spreads (Graph 13.B). These increases, in turn, trigger depreciations (Graph 13.C). In this respect, exchange rates act as the proverbial canary in the coal mine, being highly responsive to the first signs of macroeconomic instability. Beyond feeding back into higher domestic prices and thus undermining efforts to contain inflation, exchange rate depreciations can also pose considerable financial stability concerns.

Beyond the impact of fiscal deficits on inflation, high levels of debt may also play a role by constraining the room for manoeuvre of monetary policy. The most acute concern is the risk of fiscal dominance, ie a situation in which monetary policy is unable to tighten due to fiscal constraints (see also Box A).²² Fiscal dominance can arise for two reasons. In some cases, the central bank is subject to political economy pressures to expand fiscal space by keeping interest rates low. In other circumstances, monetary policy faces an economic constraint because interest rate hikes risk precipitating a sovereign debt crisis.

While the two types of dominance tend to go hand in hand and can undermine the central bank’s credibility and independence, they have somewhat different implications. Strong institutional safeguards designed to shield the central bank’s operational autonomy can be effective when pressures are purely of a political nature. By contrast, they can do relatively little when the constraint is economic and reflects trade-offs linked to higher rates.

Even if high debt levels do not lead to outright forms of fiscal dominance, they may still contribute to raising inflationary pressures. For example, survey evidence suggests that high public debt increases household inflation expectations, especially among people that have less confidence in the central bank’s determination to fight inflation.²³

Financial stability risks

The deteriorating sovereign debt outlook in many economies also points to heightened risks for the financial sector. Ultimately, a vulnerable sovereign means a vulnerable financial system. There are two reasons for this, over and above any negative effects on the financial system generated by adverse macroeconomic outcomes.

The first reason is that, most directly, the financial system is exposed to the sovereign. To be sure, sovereign debt can be a cornerstone of a well functioning financial system. It can underpin the system’s smooth functioning, by providing a safe store of value, a solid benchmark for the pricing of assets and a liquid asset that facilitates economic transactions, not least in its role as collateral (eg for repos or to meet margin calls; Box D). Moreover, government debt is a key instrument through which the central bank sets interest rates and implements monetary policy. At the same time, for government debt to fulfil such functions effectively, it is essential that it retains the highest credit quality and that financial institutions manage the associated interest rate risks properly. Otherwise, it can easily turn from a source of stability into one of major instability.

Historically, the spectre of a loss of sovereign creditworthiness has been a major source of risk for the financial system. In the extreme, the sovereign can default on its debt, causing large losses for debt holders.²⁴ Even in the absence of default, a serious erosion of sovereign creditworthiness can trigger stress and higher risk premia in the government bond market. This propagates to banks, other financial institutions and capital markets, weakening balance sheets and tightening funding conditions, possibly even precipitating a crisis.

The second reason why a vulnerable sovereign can threaten the financial system is that the government provides the ultimate backstop for the system. Of course, prudential regulation and strong standalone resolution mechanisms are the first line of defence. Moreover, central banks can act as lender of last resort and market-maker of last resort in times of severe stress, thereby buttressing the liquidity of the system. But only the government can backstop the system’s solvency, through deposit insurance and other guarantees, as well as, when needed, outright recapitalisation of failing institutions.²⁵

This backstop role is visible in bank ratings. The fact that banks’ all-in credit ratings are meaningfully above their stand-alone ratings highlights the importance of implicit government guarantees (Graph 14.A).²⁶ The wider ratings gap for EMEs compared with AEs suggests that reliance on the creditworthiness of the sovereign – and the potential cost for the government – are particularly important for EME banking systems (Graph 14.B).

Indeed, partly because of the sovereign’s backstop function, the fiscal costs (direct and indirect) of financial crises are typically huge, as measured by the change in public debt following a crisis. Historically, public debt has tended to jump in the aftermath of a banking crisis, in both AEs and EMEs (Graph 15). The fiscal cost was especially large in the case of the GFC, reaching a median rise in debt-to-GDP of about 40 percentage points in AEs. A significant portion of crisis costs typically reflect fiscal recapitalisation packages and other outright support for the banking sector, although the bulk represents indirect costs from the macroeconomic fallout and any discretionary fiscal responses.²⁷

The two-way link between the sovereign and the financial sector gives rise to the risk of a costly feedback loop. Through it, deteriorations in the creditworthiness of the sovereign and the banks can reinforce each other – the proverbial doom loop of the sovereign-bank nexus.²⁸ Such episodes have been more common in EMEs. But the sovereign debt crisis in the euro area has shown that AEs are not immune.²⁹ Credit ratings show that the credit risk of sovereigns and banks are tightly connected in both EMEs and AEs (Graph 14.C). Similarly, spreads on CDS referencing sovereign assets and bank assets are typically tightly linked, indicating that bank and sovereign risks tend to move in tandem.³⁰

Over the past decade, the rapid increase in sovereign debt has left investors and financial intermediaries increasingly exposed not only to sovereign credit risk, but also to interest rate risk.³¹ This is particularly the case, as governments increasingly issued longer-maturity debt during the low-yield era to lock in low financing costs (Graph 16.A). And even though large-scale asset purchases by some AE central banks reduced exposures by replacing sovereign debt with bank reserves in private sector portfolios, the average maturity of debt net of central bank purchases has still risen since pre-GFC (Graph 16.B). A hypothetical 300 basis point increase in government bond yields, for example, would result in estimated losses to bondholders (excluding the central bank) corresponding to between approximately 10 and 35% of GDP in major AEs, and up to 10% in major EMEs (Graph 16.C). Those losses would have been even larger had it not been for central banks’ asset purchases, especially among AEs.

Within the financial sector, banks and NBFIs were the main investors in government securities. Banks across advanced and emerging market economies hold large quantities of sovereign bonds, in some cases multiple times their capital (Graph 17.A and 17.B). NBFIs have been playing an increasing role, following their rapid growth post-GFC. The sector, which holds close to half of total financial assets globally,³² on average accounts for approximately 40% of government bond holdings in AEs and 60% in EMEs.³³ The tight interconnections between banks and NBFIs mean that distress can easily spread between the two sectors and intensify in the process (Graph 17.C).³⁴

High sovereign debt heightens the risk to the financial system not just because of the sheer size of the exposures but, importantly, because it increases the likelihood of sharp bond yield moves. In particular, during monetary policy tightening phases, long-term yields have tended to rise more in high-debt countries than in low-debt countries, especially among EMEs (Graph 18.A). To a significant degree, this has been due to higher credit risk premia: sovereign CDS premia have tended to rise markedly for high-debt EMEs when monetary policy is tightened, but not for low-debt EMEs (Graph 18.B). While the effects of rate hikes on yields are smaller for AEs, this is based on a sample that includes a prolonged period of heavy government debt purchases by AE central banks. As these purchases end and begin to reverse, the situation may change.

The risk of sharp yield adjustments is higher when liquidity in bond markets is structurally poor. The Covid-19 crisis showed how quickly market functioning can break down when liquidity conditions in sovereign bond markets are fragile. In March 2020, one-sided selling pressure (the “dash for cash”) – disorderly deleveraging by hedge funds and other players – interacted with intermediation bottlenecks to create a perfect storm that led to dysfunction even in markets that are typically among the most liquid ones in the world.³⁵ The fact that, currently, indicators point to fragile liquidity conditions suggests that risks of market dysfunction should not be underestimated (Graph 18.C).

One factor that has amplified the impact of government debt on market dynamics under stress is its pervasive role as collateral (Box D). On the one hand, this allows greater build-up in leverage. On the other hand, it intensifies fire sales when the system is hit by shocks that induce agents to sell the paper. This can undermine the safe haven status of government bonds even when their credit quality is not in doubt.

In the current hiking cycle, government debt exposures have already been a source of financial stress. So far, the problems have been linked to interest rate risk, not sovereign risk (Chapter I). They have reflected the accumulation of exposures during the long phase of unusually low interest rates. Losses on government bond holdings have been at the heart of recent stress in the banking system in the United States and of NBFIs in the United Kingdom. The stress has prompted broad-based central bank liquidity support and, in the case of the banks, the extension of deposit guarantees, which in turn increases the potential costs to public finances. Looking ahead, however, given prospective further deterioration in the creditworthiness of sovereigns, credit risk could also become, once again, a source of stress.

This analysis suggests that the financial sector is especially vulnerable following a prolonged period of lax fiscal policy and loose monetary policy. This is because the overall size of sovereign exposures is higher, the sensitivity of those exposures to adjustments in yields is greater and the likelihood of those adjustments is also greater. If investors perceive that the policy mix is reaching the boundaries of the region of stability, government bonds could reprice rapidly and forcefully. Yields would rise sharply as investors would require significantly higher compensation to be exposed to inflation risk or, especially in the case of EMEs, to sovereign credit risk. And sovereigns with lower creditworthiness would be particularly vulnerable. This, in turn, would compound risks among banks and other financial institutions.

Policy implications

The analysis of the journey to the boundaries of the region of stability and of the risks ahead raises both near- and longer-term challenges for monetary and fiscal policy.

In the near term, the challenge is to ensure a consistent policy mix that delivers a return to low inflation while tackling financial stability risks (Chapter I), thereby withdrawing from the boundaries of the region of stability. The priority for monetary policy is to restore price stability. Should a shift to a high-inflation regime take place and inflation become entrenched, it would be very costly to return to a regime of low and stable inflation.³⁶ At the same time, monetary policy will have to alleviate financial strains to prevent systemic financial instability. There will be a premium on distinguishing, to the extent possible, the measures designed to achieve the two objectives. Regardless, it will be essential to ensure that the tightening path consistent with lower inflation is not compromised by the immediate needs of the financial sector. Fiscal policy plays an important complementary role. Through consolidation, it would help to reduce pressure on aggregate demand and inflation, limit the risk of being a source of financial instability and provide more headroom, should it be called upon, to support crisis management by tackling solvency concerns.

The longer-term challenge is to ensure that monetary and fiscal policies operate well within the region of stability on a lasting basis, heeding the lessons learnt along the journey. This has implications for strategies, institutions and mindsets.

To avoid testing the boundaries of the region of stability, policy strategies should aim to retain room for policy manoeuvre over time. In the journey to the boundaries over the past decades, these safety margins evaporated to a significant extent due to an asymmetric conduct of policy over the business cycle, with easing in the bust not compensated for by a commensurate tightening in the boom.

To retain greater monetary space, once price stability is re-established, monetary policy could be more tolerant of moderate, even if persistent, shortfalls of inflation from point targets. In a low-inflation regime, inflation has certain self-stabilising properties, so that there is less need to respond forcefully to correct deviations from target. Furthermore, the evidence indicates that monetary policy has less traction in lifting inflation under such conditions. Such a refinement in frameworks would also help limit the side effects that arise from prolonged periods of monetary accommodation. Foremost among such side effects is the build-up of financial vulnerabilities, which tend to further constrain both monetary and fiscal policy headroom when financial stress emerges.

Careful consideration should also be given to keeping central bank balance sheets as small and as riskless as possible, subject to delivering successfully on the mandate. This would have three benefits. First, it would limit the footprint of the central bank in the economy, thereby reducing the institution’s involvement in resource allocation and the risk of inhibiting market functioning. Second, it would lessen the economic and political economy problems linked to transfers to the government. Finally, it would maximise the central bank’s ability to expand the balance sheet when the need does arise. Given the costs of large and risky balance sheets, the initial size is a hindrance, not an advantage. The balance sheet needs to be elastic, not large.

As for fiscal policy, there is an urgent need to consolidate fiscal positions. Relying on inflation to reduce the government debt burden is obviously not an option. It would have only a temporary effect. And, in the longer run, it would generate the very instability that would seriously damage the economy and public finances in the process. Moreover, to support consolidation it would be useful to incorporate the role of financial factors more systematically. For instance, when assessing fiscal space, it would be important to account for the flattering effect of financial booms on fiscal accounts and the possible costs of financial stress. Greater reliance on automatic stabilisers more generally would also help.

Consolidation should go hand in hand with fiscal strategies that boost sustainable growth. For one, efforts could be made to reduce or eliminate the typical bias in tax systems that favours debt over equity. This has encouraged excessive reliance on debt as an engine of growth. In addition, the quality of public spending is crucial. For example, it would be important to rebalance government expenditures towards well chosen and effectively executed investment projects – especially in infrastructure and green energy – as well as human capital building (education and health). Such a rebalancing would correct a decade-long downward trend in public investment that made room for more inflexible spending components, such as entitlements. Quite apart from being an ultimate policy objective, higher growth would also deliver stronger public finances and at higher real interest rates – more in line with an efficient allocation of capital and resources.

Beyond adjustments to monetary and fiscal policy strategies, institutional safeguards are necessary to limit tensions between the two policies and promote their coherence. Central bank independence remains the key pillar to ensure that monetary policy can pursue its price stability mandate, especially in the current context of elevated public debt levels and stubbornly high inflation. On the fiscal side, stronger institutional safeguards would help encourage prudent fiscal policy. To this end, fiscal rules and fiscal councils could play an important role in setting guardrails, all the more so if backed by appropriate constitutional provisions.

But policy adjustments should not be limited to monetary and fiscal policy alone. Other policies can play a complementary role.

Prudential policy is critical, given how disruptive financial instability can be for the region of stability. Both its microprudential and macroprudential dimensions are important.

As regards microprudential regulation and supervision, a lot has been done following the GFC. That said, progress has been uneven. And recent strains in the banking sector indicate that there is still work to do, with respect to both regulatory standards and, equally importantly, supervisory practices (see Chapter I for an elaboration). Some of that work relates more specifically to the risks linked to sovereign exposures. For banks, the Basel III framework continues to apply a preferential regulatory treatment to those exposures, particularly with regard to credit/default, interest rate and liquidity risks for exposures valued at amortised cost and held in the banking book.³⁷ Similarly, while efforts are under way to address NBFI vulnerabilities, these have so far been insufficient, including with regard to the NBFI-sovereign nexus. As such, more could be done to ensure that regulation better mitigates sovereign risk for both banks and NBFI entities and to avoid undue risk concentrations.³⁸ Any such stricter prudential treatment would need to be calibrated and implemented in the light of the special role of sovereign debt in the financial system.

Macroprudential regulation is an important complement to its microprudential counterpart. Well calibrated, it can help deal with, and mitigate, the costs and intensity of domestic financial cycles.³⁹ It can also help address the consequences of ebbs and flows of global financial conditions, supported by foreign exchange intervention and, in case of need, capital flow management measures.

The ultimate objective would be to set up a more holistic macro-financial stability framework. In such a framework, monetary, fiscal and prudential policy would operate in a coherent fashion to foster economic stability. This would considerably alleviate trade-offs and avoid overburdening individual policies. Post-GFC, major steps have been taken in that direction. That said, this is still very much a work in progress, analytically and practically.⁴⁰ And the integration of fiscal policy has not proceeded as far as the others.

Sound structural policies boosting sustainable growth will be key to relieve monetary and fiscal policy from the pressures to act as engines of growth which pushed them beyond the boundaries of the region of stability. Achieving higher and sustainable growth can only be accomplished by boosting the productive potential of the economy through effective measures that enhance the supply side. Over the past decades there has been a worrying slowdown in global growth. The slowdown was driven, in particular, by a marked decline in the growth of total factor productivity (TFP), which measures the efficiency of use of labour and capital inputs. To revive TFP growth, therefore, it is essential to enhance the efficiency of production. This requires renewed efforts to design and implement structural reforms, which have slowed substantially since the early 2000s. Boosting competition in product markets, reducing red tape and facilitating a more efficient allocation of labour are key areas to provide new impetus for innovation and growth.

Ultimately, what is needed is a change in mindsets. Policymakers need to have a keener recognition of the limitations of macroeconomic stabilisation policies. Monetary and fiscal policy can be a major force for good, but, if overly ambitious, can also cause great damage. The journey described in this chapter shows that, if the specific challenges evolve with the economic landscape, the root cause of failures does not. The fallacies of the “growth illusion” highlight that stabilisation policies cannot be engines of lasting economic growth.⁴¹ The concept of the region of stability, hard as it may be to apply in real time, can promote the necessary shift in perspective. This is because the concept embodies the recognition of the limitations of macroeconomic policies. The region is first and foremost not a precise set of numbers, but a lens through which to look at the world and to guide policy. It can help preserve the all-important trust that society must have in the state and its decision-making.

Endnotes

¹   See Carstens (2023).

²   See Carstens (2022).

³   The concept of a region or corridor of stability was coined by Leijonhufvud (2009) in the early 1970s to indicate how the economy can become unstable if it is operating outside a particular range. Borio and Disyatat (2021) have underscored how this region places constraints on the room for manoeuvre for fiscal and monetary policy while in turn being affected by the cumulative fiscal and monetary stance over time.

⁴   See Padoa-Schioppa and Saccomanni (1994).

⁵   See Aikman et al (2022).

⁶   For empirical estimates of the flattering effects of financial booms on fiscal balances, see Borio et al (2017).

⁷   See BIS (2022a) for a detailed analysis.

⁸   See Ahmed et al (2021). In addition, changes in the policy stance appear to have a smaller effect on inflation in low-inflation regimes. This is because, as one might expect, monetary policy has a larger impact on the common component of price changes – a measure closer to the concept of “true” inflation – than on relative price changes, see BIS (2022a) and Borio, Lombardi, Yetman and Zakrajšek (2023).

⁹   This effect is reinforced by larger effects of a given change in the monetary policy stance on asset prices and credit over time, see BIS (2015) and Hofmann and Peersman (2017).

¹⁰ For evidence on the negative link between fiscal multipliers and the level of public debt, see Ilzetzki et al (2013) and Banerjee and Zampolli (2019).

11 For a discussion of the roots of inflation in Latin America, see Bernanke (2005). Kehoe and Nicolini (2021) provide a detailed account of the monetary and fiscal interactions in Latin American countries since the 1960s.

¹² See BIS (2019, 2022b) and CGFS (2019).

¹³ For instance, as a result of a history of inflation and default, the safe level of external debt can be very low for many EMEs due to the “debt intolerance” of investors (Reinhart et al (2003)).

¹⁴ As highlighted by Calvo and Reinhart (2002), there is often a discrepancy between de jure and de facto exchange rate regimes. In particular, many EMEs have flexible exchange rate regimes officially, but in practice pursue managed exchange rate arrangements limiting exchange rate swings and reflecting the vulnerability to such swings.

¹⁵ See BIS (2019, 2020, 2021, 2022b) for analyses of the enduring challenges of capital flow and exchange rate fluctuations for policy frameworks in EMEs.

¹⁶ For a discussion of the features of EME macro-financial stability frameworks, see BIS (2019, 2022b).

¹⁷ Empirical analyses examining the historical relationship between real interest rates and the standard set of saving-investment drivers find – without imposing strong theoretical priors – little evidence of a systematic link; see eg Borio et al (2017) and references therein.

¹⁸ See IMF (2023).

¹⁹ These facts are documented in Lian et al (2020) based on a large panel of advanced and emerging market economies since 1950. See also Mauro and Zhou (2021) for evidence that negative differentials between interest rates and growth rates are not systematically associated historically with a lower risk of government default.

²⁰ The classification of fiscal regimes as prudent or profligate follows Mauro et al (2015).

²¹ See Banerjee et al (2023).

²² The classical statement of fiscal dominance goes back to Sargent and Wallace (1981).

23 Grigoli and Sandri (2023) examine the sensitivity of household inflation expectations to public debt levels using information provision experiments in surveys conducted in Brazil, the United Kingdom and the United States.

²⁴ Sovereign loss-given-default rates have averaged 37% based on a sample of 180 defaults in 68 countries over the period 1970 to 2010; see Cruces and Trebesch (2013).

²⁵ Moreover, to the extent that the sovereign supports the broad economy, it reduces defaults and unemployment, and hence supports the financial system.

²⁶ Stand-alone ratings reflect the intrinsic financial strength of banks, ie the likelihood of default provided that no external support is forthcoming. All-in ratings take into account the likelihood and magnitude of extraordinary external support, in particular from the government, that banks may receive when in distress. See Packer and Tarashev (2011) for a discussion.

²⁷ For banking crises in AEs, the direct fiscal costs related to financial sector support corresponded, on average, to approximately a third of the total increase in public debt following the crisis. Taking into account any subsequent recoveries, the ratio was around one fifth. See Laeven and Valencia (2013, 2018) for details.

²⁸ See eg Farhi and Tirole (2018) and Borio, Farag and Zampolli (2023).

²⁹ See eg Li and Zinna (2018).

³⁰ See the discussion in Borio, Farag and Zampolli (2023) and references therein. Dieckmann and Plank (2012) analyse the sovereign CDS market in AEs and find evidence of a private-to-public risk transfer through expectations of government bailouts.

³¹ See eg English et al (2018).

³² See FSB (2022).

³³ The figure for AEs excludes the United States, where NBFIs hold around 60% of government bonds, and the figure for EMEs excludes China, for which the share is about 40%. See Fang et al (2022).

³⁴ See also BCBS (2022).

³⁵ See Schrimpf et al (2020), Eren and Wooldridge (2021) and FSB (2022).

³⁶ See BIS (2022a) and Borio, Lombardi, Yetman and Zakrajšek (2023).

³⁷ See BCBS (2017).

³⁸ See Borio, Farag and Zampolli (2023).

³⁹ See BIS (2018).

⁴⁰ See BIS (2022b).

⁴¹ See Carstens (2022).

Technical annex

Graph 1: Statistics are computed using a smaller set of countries when data are not available.

Graph 1.A: The sample covers AR, AU, BE, BR, CA, CH, CL, CN, DE, ES, FI, FR, GB, HK, ID, IE, IN, IT, JP, KR, MX, MY, NL, NO, PE, PH, SE, SG, TH and US.

Graph 1.B: General (if not available, central) government core (if not available, total) debt at nominal (if not available, market) value. The sample covers AR, AT, AU, BE, BR, CA, CH, CL, DE, DK, ES, FR, GB, GR, IN, IT, JP, NL, NO, NZ, PT, RU, SE and US.

Graph 2.A: Inflation measured as year-on-year growth rate; mean across countries in sample: AR, BO, BR, MX, PE, UY and VE. Central bank claims on government is the sum of claims on central, state and local government, and public non-financial companies.

Graph 3: Business cycle dates are from National Bureau of Economic Research for US; Economic Cycle Research Institute for AU, CA, CH, DE, ES, FR, GB, IT, JP and SE. For BE, FI, IE, NL and NO business cycles are dated with a business cycle-dating algorithm. Episodes for which data for the previous and next 20 quarters are available are used in computing the medians.

Graph 4.A: Impulse response of real GDP to a 100 bp expansionary monetary policy shock. The threshold for the low rate regime is 2.25%, chosen to maximise empirical fit using a grid-search procedure. See Ahmed et al (2021).

Graph 4.B: From 25-year moving window mean-group panel estimation of fiscal reaction functions. The sample covers: AT, AU, BE, CA, CH, DE, DK, ES, FI, FR, GB, GR, IE, IT, JP, NL, NO, NZ, PT, SE and US. The empirical fiscal reaction function takes a standard form, modelling the primary deficit as a function of the lagged public debt-to-GDP ratio, the output gap and the interest rate paid on the outstanding debt. See Cheng et al (2023).

Graph 5.A: General government gross debt held by domestic central bank. The sample covers AT, AU, BE, CA, CH, DE, DK, ES, FI, FR, GB, GR, IE, IT, JP, NL, NO, NZ, PT, SE and US.

Graph 5.B: Central bank holdings of bonds issued by the central government except the ECB (debt securities issued by the general government).

Graph 6: Median across AEs = AU, BE, CA, CH, DE, ES, FI, FR, GB, IE, IT, JP, NL, NO, SE and US. EMEs = AR, BR, CL, CN, CO, HK, ID, IN, KR, MX, MY, PE, PH, SG, TH and VN. For fiscal balance and public debt, IMF forecasts for 2023.

Graph 7: Median annual inflation across countries within each region, simple average of medians for each period. For crises, data for AE, MT and SA are not available; latest is 2017.

Graph 8.A: The sample covers AE, AR, BR, CL, CN, CO, CZ, DZ, HK, HU, ID, IL, IN, KR, KW, MA, MX, MY, PE, PH, PL, RO, RU, SA, SG, TH, TR and ZA.

Graph 8.C: Cumulative sum of the average number of measures per country. No data available for CY, DZ, JP, KW, MA and MT.

Graph 9.A: Average sovereign debt ratings from Fitch, Moody’s and S&P. The series plotted represent cross-country medians, for a smaller sample when data are not available. AEs = AT, AU, BE, CA, CH, CY, DE, DK, EE, ES, FI, FR, GB, GR, HR, IE, IT, JP, LT, LU, LV, MT, NL, NO, NZ, PT, SE, SI, SK and US. EMEs = BR, CL, CN, CO, CZ, HK, HU, ID, IL, IN, KR, MA, MX, MY, PE, PH, PL, RO, SG, TH, TR, VN and ZA.

Graph 9.B: Change in general government debt as a percentage of GDP between year t and t+5 and over inflation in year t, excluding periods when a debt restructuring took place. The sample includes annual data between 1970 and 2022 for AE, AR, AT, AU, BE, BR, CA, CH, CL, CN, CO, CZ, DE, DK, DZ, ES, FI, FR, GB, GR, HK, HU, ID, IE, IL, IN, IT, JP, KR, MA, MX, MY, NL, NO, NZ, PE, PH, PL, PT, RO, RU, SA, SE, SG, TH, TR, US and ZA. The fitted line is obtained by regressing changes in the debt-to-GDP ratio over inflation and country fixed effects. The sample is restricted to annual inflation rates below 100%. If episodes with inflation above 100% are included, there is no statistically significant relation between changes in debt and inflation.

Graph 10: Baseline projections assume an interest rate-growth differential equal to –1% and constant primary deficits in percent of GDP as of 2022. Age-related spending are based on IMF projections for pension and healthcare spending for 2030 and 2050. For the additional spending increase scenario it is assumed that the primary deficit will increase by 2% of GDP by 2030 and stay at that level afterwards. Historical debt is computed using a smaller set of countries when data are not available. Simple average across AEs = AT, BE, DE, ES, FI, FR, GB, IE, IT, JP, NL, PT and US. EMEs = AR, BR, CL, CN, CO, CZ, HU, ID, IL, IN, KR, MX, PL and ZA.

Graph 11.A: The sample covers AT, AU, BE, CA, CH, DE, DK, EE, ES, FI, FR, GB, GR, IE, IT, JP, LT, LU, LV, NL, NO, NZ, PT, SE, SI, SK and US. For 2022, data not available for GB, JP, NL, PT, SI and SK.

Graph 11.B: The sample covers AR, AT, AU, BE, BR, CA, CH, CL, DE, DK, ES, FR, GB, GR, IN, IT, JP, NL, NO, NZ, PT, RU, SE and US. Statistics are computed using a smaller set of countries when data are not available. Government debt-to-GDP multiplied by the simple average of short-term and long-term interest rates, where government debt is general (if not available, central) government core (if not available, total) debt at nominal (if not available, market) value. The counterfactual median debt service cost is constructed using the interest rate levels prevailing in 1995.

Graph 12.A: Based on Banerjee et al (2022). The sample covers AT, AU, BE, CA, CH, DE, DK, ES, FI, FR, GB, GR, IE, IT, JP, NL, NO, NZ, PT, SE and US. Fiscal regimes are classified as prudent or profligate based on Mauro et al (2015). Monetary policy independence is defined as being high or low based on legal limitations on central bank lending to the public sector in Romelli (2022). Estimation sample from 1972–2011 upon data availability.

Graph 12.B: Based on Banerjee et al (2023). Coefficient intervals at 90% confidence bands clustered by country. The sample covers AEs = AT, AU, BE, CA, CH, DE, DK, ES, FI, FR, GB, GR, IE, IT, JP, NL, NO, NZ, PT, SE and US. EMDEs = BO, BR, CL, CN, CO, DO, GH, HK, HN, HT, HU, ID, IL, IN, KR, MX, NI, PE, PH, PL, RO, RU, TH, TR, UY and ZA. The period covered is 1972–2011 upon data availability.

Graph 13.A: Coefficients are six-year rolling window long-run multipliers from the equation:

The sample starts in Q1 1995. For details, see Jašová et al (2019). The ranges indicate the 90% confidence intervals. AEs = AU, CA, GB, NO, NZ and SE. EMEs = BR, CL, CN, CO, CZ, HK, HU, ID, IL, IN, KR, MX, MY, PE, PH, PL, RO, RU, SG, TH and ZA.

Graph 13.B–C: Estimates following Aguilar et al (2023) based on a sample for BR, CL, CN, CO, CZ, HK, HU, ID, IL, IN, KR, MX, MY, PE, PH, PL, RO, RU, TH, TR and ZA from Q1 2000 to Q1 2023.

Graph 14.A–B: Mean credit ratings across AEs = AU, BE, CA, DE, ES, FI, FR, GB, GR, HR, IE, IT, JP, NL, NO, NZ, PT, SE, SI, SK and US. EMEs = AE, CL, CN, CO, CZ, HK, ID, IL, IN, KR, MT, MX, MY, PH, PL, RO, RU, SA, TH, TR, TW and ZA. For stand-alone, Fitch Viability; for all-in, Fitch LT Issuer Default Rating.

Graph 14.C: Mean bank credit ratings by jurisdiction. For sovereign, S&P Local Currency Long-term Debt Rating; for bank, S&P Local Currency Long-term Issuer Rating. AEs = AU, CA, CH, DE, DK, ES, FR, IT, JP, NO, SE and US; EMEs = AR, BR, CL, CN, CO, CZ, HK, HU, ID, IL, IN, KR, MX, MY, PE, PH, PL, RU, SA, SG, TH, TR and ZA.

Graph 16.A: Simple average maturity of central government debt securities issued across countries in the region upon data availability. AEs = AT, AU, BE, CA, DE, ES, FR, GB, GR, IT, JP, NL and US. EMEs = AR, BR, CL, CO, CZ, HK, HU, ID, IN, KR, MX, MY, PE, PH, PL, SA, SG, TH, TR and ZA.

Graph 16.B: Refers to average remaining maturity. For US, average length of marketable interest-bearing public debt securities held by private investors. For GB and JP, estimated based on outstanding amounts and average maturities excluding holdings of the domestic central bank.

Graph 16.C: For each country, estimated change in the value of outstanding government debt as a percentage of GDP (latest value) following a hypothetical 3 percentage point increase in yields across the term structure. For IN, figures based on total debt securities. For BR, based on domestic federal debt held by the public. For GB, JP and US, based on figures from panel B. For IN, 2007 figures correspond to Q1 2011.

Graph 17.A–B: The sample consists of AEs = AT, DK, ES, FR, IT, JP, LU, NL, PT and US. EMEs = AR, BR, CL, CO, CZ, HU, ID, IN, KR, MX, MY, PE, PH, PL, SG, TH, TR and ZA, where data are available. Other depository corporations net claims on central government and their claims on state and local government by residence, as percentage of banks’ Tier 1 capital. The reporting depository corporations comprise all solo entities resident in the country, including those which are foreign-owned subsidiaries or branches of foreign entities. Branches and subsidiaries abroad of domestically owned entities are not included. Latest corresponds to latest available quarterly figure in 2022. For AT, data up to Q3 2021; for CL, data up to Q4 2021; for SG, data up to Q4 2019.

Graph 17.C: Sample covers: AR, AU, BR, CA, CH, CL, CN, EA, GB, HK ID, IN, JP, KR, KY, MX, RU, SA, SG, TR and US (RU until 2020). Changes in interconnectedness measures may also reflect improvements in the availability of data over time at a jurisdictional level. Banks’ use of funding from OFIs is banks’ liabilities to OFIs as a share of bank assets. Banks’ exposure to OFIs means banks’ claims on OFIs as a share of bank assets.

Graph 18.A–B: Coefficients from a linear regression of quarterly changes of 10-year sovereign bond yields and five-year sovereign CDS spreads on a constant and the policy rate change, conditional on the policy rate being raised. Dots correspond to point estimates and bars to +/– two standard deviations. Low- and high-debt countries correspond to the lowest and highest quartile of the distribution of government debt to GDP. Sample covers AEs = AU, BE, CA, CH, DE, DK, ES, FR, GB, IT, JP, NL, NO, NZ, SE and US. EMEs = AR, BR, CL, CN, CO, CZ, HK, HU, ID, IL, IN, KR, MX, MY, PL, SG, TH, TR and ZA (with varying availability of individual variables).

Graph 18.C: The index displays the average deviation of yields across government securities relative to a fair-value yield curve model. Monthly average of daily data.

References

Abbas, S, N Belhocine, A El-Ganainy and M Horton (2010): “A historical public debt database”, IMF Working Papers, no 245.

Aghion, P, P Bacchetta and A Banerjee (2004): “A corporate balance-sheet approach to currency crises”, Journal of Economic Theory, vol 119, no 1, pp 6–30.

Aguilar, A, C Cantú and R Guerra (2023): “Fiscal and monetary policy in emerging market economies: what are the risks and policy trade-offs?“, BIS Bulletin, no 71, March.

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III. Blueprint for the future monetary system: improving the old, enabling the new

Key takeaways

• Tokenisation of money and assets has great potential, but initiatives to date have taken place in silos without access to central bank money and the foundation of trust it provides.
• A new type of financial market infrastructure – a unified ledger – could capture the full benefits of tokenisation by combining central bank money, tokenised deposits and tokenised assets on a programmable platform.
• As well as improving existing processes through the seamless integration of transactions, a unified ledger could harness programmability to enable arrangements that are currently not practicable, thereby expanding the universe of possible economic outcomes.
• Multiple ledgers – each with a specific use case – might coexist, interlinked by application programming interfaces to ensure interoperability as well as promote financial inclusion and a level playing field.