## _cr13275

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---

### Economic performance and fiscal position
- The Nordic-4 (Denmark, Finland, Norway, and Sweden) combine high income levels with very low levels of inequality, a very competitive and innovative business environment, and sound public finances.
- Gross government debt is about 40 percent of GDP, on average.
- Macroeconomic performance: low rates of inflation and unemployment around the average of OECD peers.
- Government size: among the largest relative to other advanced OECD countries; redistribution via taxes and transfers supports robust welfare states.

### Lessons from past crises and institutional reforms
- Early 1990s banking crises in Finland, Norway, and Sweden caused large output contractions and surges in unemployment; public finances moved from surpluses into large deficits.
- Denmark was spared a more severe crisis in part because of earlier reform efforts.
- Post-crisis reforms implemented:
  - Strengthening of banking systems.
  - Rendering central banks independent and setting clear monetary policy targets.
  - Restoring fiscal discipline.
  - Enacting employment and pension reforms.
- Result: fiscal buffers accumulated before the global crisis, helping the Nordics act as “safe havens” during the crisis.

### Integration with global economy and intra-regional linkages
- The Nordic-4 are tightly interconnected and open to global markets.
- Trade openness: exports + imports to GDP equals 62 percent for Norway and 70 percent for Sweden.
- Cluster/network findings:
  - Sweden and Finland act as gatekeepers for the Baltics via banking ties and portfolio investment links.
  - Financial links within the Nordic cluster are much stronger than with the rest of the world, increasing potential for regional shock propagation.
- Market perceptions:
  - Since the start of the euro area crisis, Nordic spreads to U.S. interest rates declined while spreads for some other advanced economies increased.
  - 10-year bond yield correlation increased substantially for Denmark and Finland; Norway and Sweden made the largest leap to “safe haven” status.
  - All Nordic sovereigns are rated triple-A.
  - A shared “prospectus” to investors implies a sudden change in perception about any one Nordic-4 could trigger excessive reversal of capital flows region-wide.

### Size of financial sectors and private leverage
- Banking sector scale (relative to GDP, consolidated unless noted):
  - Sweden and Denmark: banking sector assets worth three to four times GDP.
  - Finland: on a nonconsolidated basis, banking sector assets almost three and a half times GDP.
  - Norway: banking sector somewhat smaller compared with other Nordics.
- Household and corporate debt:
  - Household debt increased by more than 60 percentage points of disposable income between 2000 and 2011 on average in the Nordics.
  - Denmark’s household debt-to-disposable income is twice the average of six OECD peers.
  - Denmark’s household debt levels reached roughly 300 percent of disposable income.
  - Households also highly leveraged in Sweden and Norway, though to a lesser extent than Denmark.
  - Nonfinancial corporate debt: Sweden stands out with high debt ratios; Norway and Finland have debt ratios still above average.
- Vulnerabilities:
  - High private sector debt and large banking systems imply large possible contingent liabilities for sovereigns.
  - Illiquidity of household assets (real estate and pension fund holdings) and uneven net worth distribution (e.g., young families more exposed).
  - House price declines could trigger deleveraging, negative household–bank feedback loops, and slower corporate activity.

### House prices and household debt — background and valuation gaps
- Historical price developments:
  - House prices rose in tandem across the Nordic-4 from mid-1990s until peaks in 2007.
  - House prices increased by more than 120 percent on average in the Nordic countries between 1995 and 2007.
- Post-2007 divergence:
  - Norway: real house price increased by more than 10 percent relative to the 2007 peak.
  - Denmark: house prices fell by close to 30 percent from the 2007 peak.
  - Finland and Sweden: house prices broadly constant around 2007 levels.
- Drivers:
  - Demand-side: household disposable income rose at the speed of house prices in Finland and Norway during 2000–07; prices outpaced income in Sweden and Denmark.
  - Working-age population growth correlated with house price dynamics in Norway and Sweden.
  - Supply constraints: strict planning and zoning, lengthy permit processes, highly regulated rental markets limited housing supply in some urban areas.
  - Financial innovations: increased use of interest-only and flexible-rate loans since early 2000s, particularly in Denmark.
- Country supply notes:
  - Denmark: early-2000s construction boom amplified downward movement during crisis.
  - Finland: milder house price increases and relatively stable housing starts during 2000–2007.
  - Norway and Sweden: limited housing supply elasticity; housing completions lagged population growth.
- Valuation gap methodology (three measures for 2012, OECD data):
  1. Time-series model regressing house price growth on multiple fundamentals, averaged over five base years (1997–2001).
  2. Deviation from long-run price-to-income ratio (1970:Q1–2013:Q1).
  3. Deviation from long-run price-to-rent ratio (1970:Q1–2013:Q1).
- Valuation gap estimates (range and mean across three measures; level in 2012):
  - Norway: average valuation gap just over 40 percent.
  - Sweden: average house prices moderately overvalued by 22 percent.
  - Finland: average house prices moderately overvalued by 12 percent.
  - Denmark: average valuation gap less than 10 percent.

### Price-to-rent caveat and robustness
- Rental market biases:
  - Highly regulated rental markets and rent controls can limit rent fluctuations.
  - Measured rent series may not capture changes occurring at new leases; price-to-rent may overstate valuation gaps when rents are rigid.
- Robustness checks excluding price-to-rent:
  - Excluding price-to-rent lowers average valuation gaps for all four countries.
  - Impact most pronounced in Finland (high level of social housing provision).
  - Norway: average overvaluation falls to 30 percent without price-to-rent, but Norway remains most overvalued relative to others.
  - Sweden and Denmark: average estimates also become smaller without price-to-rent; impact moderate.

### Transmission channels and feedback loops from house price corrections
- Transmission channels:
  - Private consumption: wealth and collateral effects reduce consumption and borrowing capacity; consumer confidence and risk aversion fall.
  - Private investment: lower collateral reduces finance access and attractiveness of new housing investment.
  - Government revenue: housing-related revenues decline, constraining spending for entities under balanced-budget or fiscal rules.
  - Bank lending: funding and balance-sheet effects reduce banks’ lending ability; declines in collateral quality lead to higher losses and rollover/funding pressures.
- Feedback loops and funding risks:
  - Wealth effects reduce demand, amplifying aggregate demand fall; higher unemployment further reduces demand.
  - Deterioration in asset quality and borrower repayment ability weakens bank balance sheets; funding complications further reduce credit.
  - Nordic-specific vulnerabilities: historically low default and low LGD; loans are full recourse financing primary residences; reliance on foreign/short-term wholesale funding raises risk.
  - Covered bond funding costs can rise with house price corrections or broader external market risks; increased covered-bond use may require higher overcollateralization as LTVs rise.

### Household balance sheet structure and vulnerabilities
- Household assets and liquidity:
  - Household gross debt is high; total assets exceed gross liabilities, but household assets as a share of disposable income are not as high in most Nordic-4 as in many advanced economies.
  - Large share of household assets are illiquid or price-risky (housing; pension accounts).
  - Excluding housing and pension/insurance assets, net liquid assets as a share of disposable income are negative in Denmark and Norway and low in Finland and Sweden.
  - Debt rises concentrated among younger households.
- Micro-level findings:
  - Denmark: share of highly indebted households (debts more than 500 percent of incomes) reached 10 percent in 2010 (comparable to Norway).
  - Norway: debt burdens relatively evenly distributed across income groups; limited buffers for most groups in adverse shocks.

### Estimated macroeconomic impacts of house price corrections
- VAR-based point estimates (Igan and Loungani, 2012):
  - A 10 percent decline in property prices reduces aggregate GDP by as much as 2½ percent and private consumption and private residential investment by as much as 3½ and 28½ percent, respectively.
  - Estimated impact on GDP for Norway is not available (zero effect for Norwegian GDP mostly due to difficulty controlling for oil export effects).
- Combined impacts using country-specific valuation gaps (correction back to estimated equilibrium implies GDP declines of):
  - Sweden: -2.6 percent
  - Finland: -2.3 percent
  - Denmark: -2.1 percent
- Uncertainty and adverse scenarios:
  - Sensitivity may be higher because of nonamortizing mortgages, elevated indebtedness, confidence or funding effects.
  - Estimated ranges incorporate one standard deviation around elasticities and country-specific valuation estimates.
  - Adverse-end scenarios could yield GDP declines of 5 to 13 percent.

### Empirical maximum impacts by country (Decline of 10 percent 1/)
- Maximum impacts (GDP / Consumption / Residential Investment):
  - Denmark: -2.5 -3.5 -10.8
  - Finland: -1.9 -3.4 -18.0
  - Norway: - -0.9 -6.8
  - Sweden: -1.2 -1.7 -28.3
  - Australia: -1.0 -1.8 -13.1
  - Belgium: -1.1 -0.2 -8.4
  - Canada: -1.2 -1.3 -2.1
  - France: -2.1 -1.1 -9.8
  - Germany: -4.6 -5.7 -38.5
  - Italy: -0.1 -0.5 -9.5
  - Netherlands: -0.3 -0.4 -9.8
  - New Zealand: -4.2 -5.7 -28.8
  - Spain: -1.8 -2.5 -7.0
  - Switzerland: -0.5 -0.5 -4.2
  - UK: -1.0 -1.4 -12.2
  - Average: -2.1 -2.2 -14.0
- Note: Based on VAR estimated for 1986:Q1-2010:Q1; for the four Nordics estimates come from an updated dataset ending 2012Q4 used in IMF EWE.

### Policy measures and macroprudential responses
- National measures:
  - Sweden FSA proposed increasing risk weights for mortgage loans to 15 percent.
  - Norway: stricter proposals for risk weights under consideration; FSA proposed further measures.
- Regional coordination:
  - Raise regulatory risk weights on residential mortgages in a coordinated way to avoid regulatory arbitrage (e.g., Norwegian regulation may not apply to EEA branches).
  - Agree that home country supervisors align policies in host country markets when market conditions differ.
  - Improve cross-border bank resolution mechanisms at regional level given close Nordic interlinkages; orderly resolution frameworks for cross-border institutions are critical.

### Wholesale funding, covered bonds, and funding vulnerabilities
- Loan-to-deposit (LTD) ratios (six largest Nordic banks):
  - Danske Bank, Svenska Handelsbanken (SHB), Swedbank: about 220 percent.
  - DNB and Nordea: about 180 percent.
  - SEB: about 130 percent.
- Five of the largest banks rank among top six globally by LTD; SEB number 15.
- Covered bonds:
  - Six largest banks issued close to EUR 460 billion in covered bonds as of end-2012, accounting for 70 percent of covered bonds issued across the Nordic-4.
  - The four Nordic countries account for 33 percent of global outstanding covered bonds and 60 percent of global issuance in 2011.
  - Over three quarters of outstanding Nordic bonds issued in domestic (noneuro) currencies; 20 percent issued in euros.
- Risks from covered bonds:
  - Asset encumbrance reduces capital available for bail-in and deposit insurance, potentially increasing loss-given-default and taxpayer risk.
  - Excessive issuance reduces funds for senior unsecured creditors, raising unsecured funding costs and possibly default probability.
  - Banks vulnerable to funding interruptions from adverse exchange rate developments given foreign-currency covered bonds.

### Geographic concentration and systemic scale of the big six
- Regional concentration and importance:
  - About 85 percent of total credit exposures and customer deposits of the six largest banks originate from one of the Nordic-4.
  - About 80 percent of their operating income comes from the Nordic countries.
  - 74 percent of full-time employees are located in the Nordic countries.
  - About 75 percent of total sovereign bond holdings are in Nordic sovereigns.
- Total assets to home country GDP for the big six range from 50 to 200 percent.
  - Nordea’s total assets relative to Swedish GDP in 2012: about 160 percent.
  - Danske Bank’s total assets relative to Danish GDP: 200 percent.
  - Total assets of each of Nordea, Danske Bank, and DNB represent over 30 percent of Nordic GDP.
- Sweden’s central role:
  - Four of the big six have parent banks in Sweden; combined assets about 120 percent of Nordic area GDP.
  - Sweden has four of the six largest publicly-listed Nordic banks; contingent-liability risks for the Swedish government may be particularly high.

### Fiscal-cost experiment: synthetic large regional bank failure
- Synthetic bank construction:
  - Weighted-average features of the big 6 banks.
  - Assets: EUR 444 billion (or 36 percent of combined Nordic-4 GDP).
  - Credit exposure: EUR 336 billion.
  - Total deposits: around EUR 99 billion.
- Resolution assumptions and three scenarios:
  - Scenario A: insured depositors bailed out; uninsured depositors and unsecured creditors expropriated 100 percent.
  - Scenario B: insured and uninsured depositors bailed out; senior unsecured creditors expropriated 100 percent.
  - Scenario C: insured and uninsured depositors bailed out; senior unsecured creditors bailed out.
- Key assumptions:
  - Fraction of deposits insured (SWE, DNK, FIN) 70%; coverage €100,000.
  - Fraction of deposits insured (NOR) 56%; coverage approx. €264,000.
  - Fraction eventually recovered by DIF from BE of failed bank 40%.
  - Levy on uninsured depositors and haircut on senior unsecured creditors are either 100% or 0% depending on scenario.
- Liquidity and fiscal costs (selected results):
  - Liquidity costs (initial DIF payout):
    - Scenario A: around 3.5–5.5 percent of GDP across the Nordic-4.
    - Scenario B: from 6–8 percent of GDP in each country.
  - Additional sovereign funds required (DIF insufficient):
    - Scenario A: around 2.5–5 percent of GDP additional funds required by the four sovereigns.
    - Scenario B: around 5–7.5 percent of GDP additional funds required.
  - Eventual loss to government after BE recoveries:
    - Scenario A (50% recovery): eventual loss of order 1.5–2.5 percent of GDP for each Nordic-4 country.
    - Scenario B (40% recovery): eventual loss between 3.5–5 percent of GDP for each Nordic-4 country.
  - Scenario C: bailing out senior unsecured creditors raises fiscal costs computed for Scenario B by over 130 percent to approximately 6.5–10 percent across the four countries.
- Selected country-level estimated fiscal costs (percent of GDP, excluding DIF equity):
  - Denmark: Scenario A 5.4; Scenario B 7.7; Scenario C 9.9 (estimated fiscal costs).
  - Finland: Scenario A 4.8; Scenario B 6.9; Scenario C 8.6.
  - Norway: Scenario A 3.4; Scenario B 6.1; Scenario C 6.7.
  - Sweden: Scenario A 5.2; Scenario B 7.4; Scenario C 8.4.
  - Nordic-4 Region: Scenario A 4.6; Scenario B 7.0; Scenario C 8.2.
- DIF recoveries and shortfalls (selected EUR bil. and percent of GDP):
  - Nordic-4 DIF's Recovery from BE 1,238.7 (EUR bil.); DIF Shortfall 2,280.4 (EUR bil.); Deposit Insurance Payout 12.5 (EUR bil.); Estimated Fiscal Costs Scenario A 22.7 (EUR bil.); Scenario B 46.7 (EUR bil.); Scenario C 12.5 (EUR bil.).
  - Country examples:
    - Denmark: DIF's Recovery from BE 245.0; DIF Shortfall 482.8; Deposit Insurance Payout 11.2.
    - Sweden: DIF's Recovery from BE 409.2; DIF Shortfall 1,475.9; Deposit Insurance Payout 17.0.
    - Norway: DIF's Recovery from BE 390.0; DIF Shortfall 321.8; Deposit Insurance Payout 10.2.
    - Finland: DIF's Recovery from BE 194.5; DIF Shortfall 0.0; Deposit Insurance Payout 9.3.

### Amplifying factors, interlinkages, and aggregate failure sensitivity
- Sovereign equity stakes:
  - Nordic-4 sovereigns hold large equity stakes in big banks directly and via state pension funds.
  - DNB example: around 40 percent of equity held by Norwegian government; direct stake 34 percent.
  - Swedish government reduced direct stake in Nordea from 13.5 percent to 7 percent in June 2013, raising approximately EUR 3 billion.
- Cross-border sovereign debt holdings: in 2012, six largest banks held roughly EUR 66 billion of Nordic-4 sovereign debt (about 75 percent of their total sovereign holdings).
- Bank-to-bank equity holdings: except Danske Bank and DNB, between 6 and 8 percent of equities of large Nordic banks are held by other Nordic banks.
- Aggregated failure of big six:
  - Aggregation yields very large fiscal costs under burden-sharing rules:
    - By depositor base (DB) and by location of parent (LP/asset weights) produce wide cost ranges.
    - Sweden: costs range from 17–62 percent of GDP (DB) and 24–92 percent of GDP (LP).
    - Finland: zero under location-of-parent rule because financial sector dominated by foreign subsidiaries.
    - Norway: second largest fiscal costs by depositor base due to roughly 30 percent of regional deposits recorded in Norway.
- Uncertainty: estimates sensitive to strategies for bail-in vs bail-out and are large relative to ex-post costs of 1990s Nordic crises due to larger banking system size, increased asset encumbrance, and cross-border resolution complications.

### Wholesale funding, regional spillovers, and contagion analysis
- Covered-bond and wholesale funding dependence amplifies funding risk; LTD ratios almost twice global large-bank averages.
- Asset-pricing decomposition (2000–2012, annual):
  - Global factor explains 60 to 70 percent of bond, money, and stock market variation on average across the four countries.
  - Regional factor accounts for approximately 9 to 11 percent of variation.
  - Country-specific factor accounts for remaining 20 to 30 percent.
- Macroeconometric spillovers:
  - Inward output spillovers to Nordic-4 come mainly from neighbors and systemic advanced economies (U.S., Germany, U.K.).
  - Regional comovement amplifies inward output spillovers by about 42 percent on average across the Nordics.
  - Amplification particularly large for Norway; Sweden dominates inward spillovers within the Nordics (one third of total Nordic GDP).
  - Finland particularly susceptible to spillovers from Sweden (2.5–3 times greater than from Denmark and Norway).
  - Sweden mainly affected by spillovers from Norway (one quarter larger than from Denmark and Finland).
  - Outward spillovers from Nordics to rest of world are small to moderate and largely concentrated within the Nordic-4 region.
- Policy implication: given global dominance but meaningful regional factors and strong cross-border exposures, Nordic policy coordination is important to manage systemic risk and resolution.

### Fiscal policy coordination experiment and gains
- Experiment: temporary expenditure-based fiscal stimulus of 1 percent of GDP, uncoordinated vs coordinated, under negative output shocks (e.g., EA crisis modeled as 300 basis point increase in long-term yields in EA periphery).
- Output effects:
  - Uncoordinated stimulus reduces initial output losses by 0.6 percentage points on average for the Nordic-4.
  - Coordinated stimulus reduces initial output losses by 0.8 percentage points on average for the Nordic-4.
  - Implied coordination gain is 35 percent in 2013.
- Fiscal multipliers and channels:
  - Main transmission: domestic demand via intra-regional trade.
  - Denmark and Finland suffer larger output losses from spillovers; Norway and Sweden face smaller losses due to monetary policy space.
  - Coordination increases multipliers:
    - Multipliers on revenue rise by 27 percent after accounting for endogenous monetary policy.
    - Multipliers on expenditure rise by 13 percent after accounting for endogenous monetary policy.
  - Heterogeneity in gains: highest for Denmark and Sweden; lowest for Norway; Finland’s gains muted.
- Policy implications:
  - Strong national policies yield collective benefits; shocks originating in one Nordic country affect all due to high comovement.
  - Macroeconomic policy examples: macroprudential measures to manage private balance sheets and housing markets.
  - Build national and regional fiscal buffers to insure against potential large contingent liabilities from bank failures.
  - Coordinated fiscal impulses can prevent sub-optimal competitive policy responses and reinforce regional demand.

### Core policy implications and recommendations (concise)
- Strengthen macroprudential frameworks to manage household leverage and housing market vulnerabilities (e.g., higher mortgage risk weights).
- Coordinate regulatory calibration regionally to avoid arbitrage and align home/host supervision where market conditions differ.
- Improve pan-Nordic cross-border resolution frameworks and ex ante burden-sharing arrangements to reduce policy uncertainty and enable quick resolution.
- Accumulate sufficient fiscal buffers at national and regional levels to insure against potential large sovereign contingent liabilities from banking-sector stress.
- Explore coordinated fiscal responses in adverse shocks to amplify output support given strong intra-regional trade and spillovers.

*Prepared by IMF staff as presented in the source content provided.*

### 1.      The economic performance of the four continental Nordic economies (Denmark,

### _cr13275 - 1.      The economic performance of the four continental Nordic economies (Denmark,

### Economic performance and fiscal position
- The four continental Nordic economies (Denmark, Finland, Norway, and Sweden—the Nordic-4) combine high income levels with very low levels of inequality, supported by a very competitive and innovative business environment and sound public finances.
- Gross government debt is about 40 percent of GDP, on average.
- Macroeconomic performance is characterized by low rates of inflation and levels of unemployment around the average of their OECD peers.
- The sizes of government are among the largest relative to other advanced OECD countries, with a large degree of redistribution via taxes and transfers underpinning robust welfare states.

### Lessons from past crises and institutional reforms
- Finland, Norway, and Sweden experienced large contractions in output and surges in unemployment in the early 1990s due to severe banking crises; public finances moved from surpluses into large deficits.
- Denmark was spared a more severe crisis in part because of earlier reform efforts.
- Reforms implemented after these crises include:
  - Strengthening of banking systems.
  - Rendering central banks independent and setting clear monetary policy targets.
  - Restoring fiscal discipline.
  - Enacting employment and pension reforms.
- These reforms led to fiscal buffers accumulating before the global crisis, helping the Nordics serve as “safe havens” during the crisis period.

### Integration with the global economy and intra-regional linkages
- The Nordic-4 are tightly interconnected and open to global markets.
- Trade openness: the sum of exports and imports to GDP is 62 and 70 percent for Norway and Sweden, respectively.
- Cluster and network analysis findings:
  - Sweden and Finland act as gatekeepers for the Baltics, reflecting strong banking ties and portfolio investment links.
  - Financial links within the Nordic cluster are relatively much stronger than with the rest of the world, increasing the potential for regional shock propagation.
- Safe-haven dynamics and market perceptions:
  - Since the beginning of the euro area crisis, Nordic spreads to U.S. interest rates have declined while spreads for some other advanced economies increased.
  - The 10-year bond yield correlation increased substantially for Denmark and Finland; Norway and Sweden made the largest leap to “safe haven” status given initial positions.
  - All Nordic sovereigns are rated triple-A.
  - A shared “prospectus” to investors implies that a sudden change in perception about any one Nordic-4 could trigger excessive reversal of capital flows for the entire region.

### Size of financial sectors and private leverage
- Nordic banking sectors are large relative to GDP:
  - Sweden and Denmark: banking sector assets worth three to four times of GDP (on a consolidated basis).
  - Finland: on a nonconsolidated basis, banking sector assets are almost three and a half times the size of GDP.
  - Norway: the banking sector is somewhat smaller compared with other Nordics.
- Household and corporate debt:
  - Household debt increased by more than 60 percentage points of disposable income between 2000 and 2011 on average in the Nordics.
  - Denmark’s household debt-to-disposable income is twice the average of six of its OECD peers.
  - Denmark’s household debt levels reached roughly 300 percent of disposable income.
  - Households are also highly leveraged in Sweden and Norway, though to a lesser extent than Denmark.
  - Nonfinancial corporate debt: Sweden stands out with high debt ratios; Norway and Finland have debt ratios still above average.
- Vulnerabilities:
  - High private sector debt and large banking systems imply large possible contingent liabilities for sovereigns.
  - Illiquidity of household assets (real estate and pension fund holdings) and uneven distribution of net worth across households (e.g., young families more exposed) raise risks.
  - House price declines could trigger deleveraging, negative feedback loops between households and the banking sector, and slower corporate activity.

### House prices and household debt — background
- House prices rose in tandem across the Nordic-4 from the mid-1990s until peaks in 2007:
  - House prices increased by more than 120 percent on average in the Nordic countries between 1995 and 2007.
- Post-2007 divergence:
  - Norway: real house price increased by more than 10 percent relative to the 2007 peak level.
  - Denmark: house prices fell by close to 30 percent from the 2007 peak.
  - Finland and Sweden: house prices remained broadly constant around 2007 levels.
- Drivers:
  - Demand-side: household disposable income rose at the speed of house prices in Finland and Norway during 2000–07; prices outpaced income in Sweden and Denmark.
  - Working age population growth appears correlated with house price dynamics in Norway and Sweden, less so in Finland and Denmark.
  - Supply-side constraints (strict planning and zoning regulations, lengthy building permit processes, highly regulated rental markets) limited housing supply in some countries, especially urban areas.
  - Financial innovations: increasingly liberal use of interest-only and flexible-rate loans since the early 2000s contributed to higher housing demand and prices, particularly in Denmark.
- Country-specific supply notes (Box 2.1):
  - Denmark: early 2000s house price increases triggered a construction boom that later amplified the downward price movement when the crisis hit.
  - Finland: milder house price increases and relatively stable housing starts during 2000–2007.
  - Norway and Sweden: limited elasticity of housing supply due to strict regulations and lengthy permitting processes; housing completions lagged population growth, supporting higher prices.

### House price valuation gaps (2012/2013 assessment)
- Methodology: three measures were used to estimate valuation gaps for 2012 (using OECD data):
  1. Time-series model regressing house price growth on price-to-income ratio growth, construction costs, credit growth, changes in income per capita, share prices, proportion of working age population, and short- and long-term interest rates; five base years (1997–2001) considered and averaged.
  2. Deviation from long-run price-to-income ratio (long-run average computed from 1970:Q1 to 2013:Q1).
  3. Deviation from long-run price-to-rent ratio (long-run average computed from 1970:Q1 to 2013:Q1).
- Valuation gap estimates (range and mean across the three measures; level of house prices in 2012):
  - Norway: average estimate of the valuation gap is just over 40 percent.
  - Sweden: average estimate suggests house prices are moderately overvalued by 22 percent.
  - Finland: average estimate suggests house prices are moderately overvalued by 12 percent.
  - Denmark: average estimate of the valuation gap is less than 10 percent.

_Italic: Prepared by IMF staff as presented in the source content provided._

### 6.      A caveat for this approach is that the price-to-rent ratio may overestimate house price

### _cr13275 - 6.      A caveat for this approach is that the price-to-rent ratio may overestimate house price

### Price-to-rent caveat and robustness
- Rental market features that bias price-to-rent:
  - Rental markets are highly regulated in some of the Nordic-4, and rent controls may limit fluctuations in rent.
  - Measured rent series may not fully capture actual changes in rent if the rental survey covers only part of new leases (rent is likely to change at the time of a new lease).
  - In such cases, the price-to-rent ratio is likely to overstate house price valuation gaps because rent will not adjust even when housing demand is rising and pushing up house prices.
- Robustness checks and impact of excluding price-to-rent:
  - An alternative average measure was calculated by excluding the price-to-rent ratio from the baseline estimate to take account of possible rigidity in rental prices.
  - Once the price-to-rent ratio is excluded, average valuation gaps become lower for all four countries than in the baseline estimate.
  - The impact of the price-to-rent ratio is most pronounced in Finland, where the level of social housing provision is high.
  - For Norway, the average estimate of overvaluation comes down to 30 percent, but this does not change the conclusion from the baseline estimate that house prices in Norway are likely to be more overvalued than others.
  - Average estimates for Sweden and Denmark also become smaller without the price-to-rent ratio, but the impact is relatively moderate.

### Transmission channels of house price corrections
- Private consumption:
  - Declining house prices reduce private consumption through negative impacts on household wealth and access to finance (household borrowing capacity depends on collateral value).
  - Declines may depress consumer confidence and increase risk aversion, further depressing consumption.
- Private investment:
  - Lower property prices reduce access to finance (lower collateral value) and the attractiveness of investment in new housing for builders and buyers.
- Government revenue:
  - Declines in house prices generally reduce housing-related fiscal revenue (e.g., property taxes and construction-related income taxes), which can constrain government spending for entities subject to balanced-budget or other fiscal rules.
- Bank lending:
  - Disruptions in funding and balance sheet effects reduce banks’ ability to lend.
  - Declines in house prices are often linked to higher bank losses and declines in collateral quality—triggering rollover problems and funding/liquidity pressures.
  - Banks with concentrated mortgage exposures might see funding costs rise more sharply.
  - Literature (Claessens et al., 2008) suggests recessions that coincide with house price busts and credit crunches tend to be longer and deeper.
  - Recent FSAPs for the Nordics (Denmark 2007 and Sweden 2011) suggest bank capital buffers would be sufficient to deal with the direct impact of lower house prices through credit losses, though assumptions are confidential.
  - Sveriges Riksbank finds a fall in house prices is not expected to seriously affect financial stability through credit losses in Sweden, though funding problems could create more serious difficulties.

### Feedback loops and funding risks
- Interactions and amplification:
  - Wealth effects reduce consumption and investment, amplifying the fall in aggregate demand; higher unemployment reduces demand further.
  - Deterioration in asset quality and borrowers’ ability to service debt weakens bank balance sheets and—if combined with funding complications—reduces banks’ ability to extend credit.
- Specific Nordic vulnerabilities:
  - Mortgage lending in Nordics historically exhibits low default and low LGD; most loans finance primary residences and are full recourse.
  - Generous social benefits and high and rising house prices have insulated households historically.
  - Continued low default and loss rates cannot be taken for granted due to banks’ heavy dependence on foreign or short-term wholesale funding.
  - Riksbank (2011) reports house price corrections associated with an increase in spread over swap for covered bonds in euro during 2007–10; covered bond issuance costs could rise even without a fall in house prices if external financial market risks increase.
  - Increased use of covered bonds may require higher overcollateralization if declines in house prices raise loan-to-value ratios.

### Household balance sheet structure and vulnerabilities
- Household debt and assets:
  - Household gross debt is high in the Nordic-4; household total assets are higher than gross liabilities in the Nordic-4, but household assets as a share of disposable income are not as high in most Nordic-4 as in many other advanced economies.
  - Household debt in Denmark is among the highest in the OECD.
- Liquidity and distribution:
  - A large share of household assets in the Nordics are illiquid, subject to price risk, or both (nonfinancial assets largely housing; large share of financial assets in pension accounts).
  - Excluding housing and pension/insurance assets, net liquid assets as a share of disposable income are negative in Denmark and Norway and low in Finland and Sweden.
  - Household assets and debt may be unevenly distributed; debt levels have been rising particularly for younger households.
- Micro-level findings (Box 2.2):
  - Denmark: share of highly indebted households (debts more than 500 percent of incomes) reached 10 percent in 2010 (comparable to Norway).
  - Norway: debt burdens relatively evenly distributed across income groups; most groups tend to have relatively limited buffers in the event of adverse shocks.

### Estimated macroeconomic impacts of house price corrections
- VAR-based point estimates (Igan and Loungani, 2012):
  - A 10 percent decline in property prices will reduce aggregate GDP by as much as 2½ percent and private consumption and private residential investment by as much as 3½ and 28½ percent, respectively.
  - The estimated impact on GDP for Norway is not available (zero effect for Norwegian GDP mostly due to difficulty controlling for effects of oil exports).
- Combined impacts using country-specific valuation gaps:
  - Corrections that bring prices back to estimated equilibrium would trigger declines in GDP of about:
    - Sweden: -2.6 percent
    - Finland: -2.3 percent
    - Denmark: -2.1 percent
  - These corrections imply larger relative declines in private consumption and residential investment (see Figure 2.8 in source).
- Uncertainty and adverse scenarios:
  - Sensitivity may be higher due to increases in nonamortizing mortgages, elevated household indebtedness, confidence or funding effects.
  - Estimated ranges of effects incorporate one standard deviation around elasticities and country-specific average, maximum, and minimum overvaluation estimates.
  - Impacts at the adverse end of scenarios could be a decline in GDP by 5 to 13 percent.

### Empirical maximum impacts by country (Decline of 10 percent 1/)
- Table 2.1: Maximum Impact of a Negative Shock to House Prices (GDP / Consumption / Residential Investment)
  - Denmark: -2.5 -3.5 -10.8
  - Finland: -1.9 -3.4 -18.0
  - Norway: - -0.9 -6.8
  - Sweden: -1.2 -1.7 -28.3
  - Australia: -1.0 -1.8 -13.1
  - Belgium: -1.1 -0.2 -8.4
  - Canada: -1.2 -1.3 -2.1
  - France: -2.1 -1.1 -9.8
  - Germany: -4.6 -5.7 -38.5
  - Italy: -0.1 -0.5 -9.5
  - Netherlands: -0.3 -0.4 -9.8
  - New Zealand: -4.2 -5.7 -28.8
  - Spain: -1.8 -2.5 -7.0
  - Switzerland: -0.5 -0.5 -4.2
  - UK: -1.0 -1.4 -12.2
  - Average: -2.1 -2.2 -14.0
  - Source note: Based on VAR estimated by Igan and Loungani (2012) for the period 1986:Q1-2010:Q1; identification via Cholesky decomposition with ordering: real GDP, real private consumption, real private residential investment, CPI, nominal short-term interest rates, and real house prices. For the four Nordics the estimates come from an updated dataset that ends in 2012Q4 used in IMF EWE.

### Policy implications and recommendations
- Recent and proposed national measures:
  - The FSA in Sweden proposed increasing risk weights for mortgage loans to 15 percent.
  - In Norway, stricter proposals for risk weights are under consideration and the FSA has proposed further measures.
- Regional coordination to contain common vulnerabilities:
  - Regulatory risk weights on residential mortgages could be raised in a coordinated way to avoid regulatory arbitrage (e.g., Norwegian regulation does not apply to branches of banks based elsewhere in the European Economic Area).
  - Coordination could include agreeing that home country supervisors align policies in individual host country markets where different market conditions prevail.
  - Mechanisms for cross-border bank resolution could be further improved at the regional level given close interlinkages of Nordic-4 financial systems; orderly resolution frameworks for cross-border institutions are critical to promote financial stability in the region.

*Source: NORDIC REGIONAL REPORT, INTERNATIONAL MONETARY FUND (selected excerpts from the provided content).*

### 3. Despite some heterogeneity within

### 3. Despite some heterogeneity within

### Wholesale funding and loan-to-deposit (LTD) ratios
- The six largest Nordic banks have the highest LTD ratios on an individual basis among global banks.
- Individual LTD ratios:
  - Danske Bank, Svenska Handelsbanken (SHB), and Swedbank: about 220 percent
  - DNB and Nordea: about 180 percent
  - SEB: about 130 percent
- Five of the largest banks rank among the top six globally by LTD; SEB is number 15.
- Heavy reliance on wholesale funding increases vulnerability of the Nordic banking system to liquidity shocks and funding risks.
- Loan-to-deposit ratios are almost twice as high as the average of the largest banks elsewhere in the world.
- Drivers of high LTD ratios:
  - Households tend to save through pension and mutual funds rather than deposits or mortgage amortization (in part due to tax incentives such as MID).
  - Households increase leverage via mortgage borrowing while savings are channeled back via institutional investors to banks, mostly in the form of covered bonds and often through international (swap) markets.
  - A self-reinforcing cycle between credit growth and increasing wholesale funding needs has developed.

### Covered bonds: scale, currency, and market share
- Covered bonds are an important source of wholesale financing for both the largest banks and other institutions in domestic and foreign currency.
- The six largest banks have issued close to EUR 460 billion in covered bonds as of end-2012, accounting for 70 percent of covered bonds issued across the Nordic-4.
- Overall Nordic covered bond statistics:
  - The four Nordic countries account for 33 percent of global outstanding covered bonds and 60 percent of global issuance in 2011.
  - Denmark and Sweden markets are the largest as a percent of GDP.
  - Over three quarters of outstanding bonds in the Nordics were issued in domestic (noneuro) currencies while 20 percent were issued in euros.

### Risks from asset encumbrance and currency exposure
- Covered bonds as secured assets:
  - Provide low and stable long-term funding costs for banks and reduce probability of default and risk to taxpayers.
  - Raise concerns over asset encumbrance and the availability of capital for bailing in creditors during bank resolution.
- Consequences of asset encumbrance:
  - Covered bonds deplete capital available for deposit insurance funds, increasing potential loss-given-default and risk to taxpayers.
  - Excessive covered bond issuance reduces funds available for senior unsecured creditors, forcing higher rates for unsecured bonds and potentially raising probability of default.
  - Overuse of covered bonds could cause markets to penalize banks with higher funding costs as banks set aside more collateral to back these bonds.
  - Banks could be vulnerable to interruptions in funding due to adverse exchange rate developments given the share of foreign currency-denominated covered bonds.

### Geographical exposure and concentration of the big six
- Regional concentration:
  - About 85 percent of both total credit exposures and customer deposits in the six largest banks originate from one of the Nordic-4.
  - About 80 percent of their operating income comes from the Nordic countries.
  - 74 percent of their full-time employees are located in the Nordic countries.
  - About 75 percent of their total sovereign bond holdings are in Nordic sovereigns.
- Cross-border operations:
  - The six largest banks operate largely as regional (pan-Nordic) banks rather than national banks.
  - Nordea and Danske Bank have the most geographically dispersed credit exposure and depositor base across the region; DNB limits almost all operations to Norway.
- Size and systemic importance:
  - Total assets to home country GDP for the six largest banks range from 50 to 200 percent.
  - Examples: Nordea’s total assets relative to Swedish GDP in 2012: about 160 percent; Danske Bank’s total assets relative to Danish GDP: 200 percent.
  - The total assets of each of the three largest home banks (Nordea, Danske Bank, and DNB) represent over 30 percent of Nordic GDP.
- Sweden’s central role:
  - Four of the big six have parent banks in Sweden, with combined assets representing about 120 percent of Nordic area GDP.
  - Sweden has four of the 53 publicly-listed banks in the Nordic area (Nordea, Swedbank, Svenska Handelsbanken, and SEB) that are among the six largest in the Nordic area.
  - Possible contingent-liability risks for the government may be particularly high for Sweden.

### Fiscal-cost experiment: synthetic large regional bank failure
- Construction of the synthetic bank:
  - Weighted-average of features of the big 6 banks.
  - Assets: EUR 444 billion (or 36 percent of the combined Nordic-4 GDP)
  - Credit exposure: EUR 336 billion
  - Total deposits: around EUR 99 billion
- Resolution timeline and assumptions:
  - Failed bank assets placed in a bankruptcy estate (BE).
  - Insured depositors reimbursed by government through the depositor insurance fund (DIF).
  - Eventual cost to the government derived as residual payable to secured creditors after offsetting liquidation value of the BE.
  - Governments may choose to bail out additional creditors (uninsured depositors, unsecured bondholders).
- Three alternative scenarios for creditor compensation (see Figure 3.8):
  - Scenario A: only insured depositors are bailed out (insured depositors bailed out with certainty; uninsured depositors and unsecured creditors expropriated 100 percent).
  - Scenario B: uninsured depositors are also bailed out completely (upper bound for costs where uninsured depositors are fully compensated).
  - Scenario C: senior unsecured creditors are also compensated (adds to costs from Scenario B).

### Key quantitative results of the synthetic-bank failure experiment
- Liquidity costs (initial payout from deposit insurance funds):
  - Scenario A: around 3.5–5.5 percent of GDP across the Nordic-4
  - Scenario B: from 6–8 percent of GDP in each country
- Need for additional sovereign funds (deposit insurance funds insufficient):
  - Scenario A: around 2.5–5 percent of GDP additional funds required by the four sovereigns
  - Scenario B: around 5–7.5 percent of GDP additional funds required
- Eventual loss to the government after recoveries from the bankruptcy estate:
  - Scenario A: recovery assumed 50 percent → eventual loss of the order of 1.5–2.5 percent of GDP for each of the Nordic-4
  - Scenario B: recovery assumed 40 percent → eventual loss between 3.5–5 percent of GDP for each of the Nordic-4
- Scenario C impact:
  - Bail-out of senior unsecured creditors raises fiscal costs computed for Scenario B by over 130 percent to approximately 6.5–10 percent across the four countries

### Amplifying factors and systemic linkages
- Sovereign equity stakes in banks:
  - Nordic-4 sovereigns have large equity stakes in the large banks, both directly and through state pension funds.
  - Norway and Sweden are particularly exposed as large shareholders.
  - Example: DNB — around 40 percent of equity held by the Norwegian government, with a direct stake of 34 percent.
  - Swedish government reduced direct stake in Nordea from 13.5 percent to 7 percent in June 2013, raising approximately EUR 3 billion.
- Cross-border sovereign debt holdings:
  - In 2012, Nordic-4 sovereign debt held by the six largest banks constituted roughly 75 percent of their total sovereign debt holding (amounting to EUR 66 billion of gross direct long sovereign debt exposure).
- Cross equity holdings among banks:
  - Except for Danske Bank and DNB, between 6 and 8 percent of the equities of the large Nordic banks are held by other Nordic banks.
- Aggregated failure of the big six:
  - Aggregating the six largest banks into a single entity and repeating the experiment yields very large fiscal costs.
  - Two burden-sharing rules examined:
    - By depositor base (DB)
    - By location of parent (LP / asset weights)
  - Sensitivity of costs:
    - For Sweden, costs range from 17–62 percent of GDP using depositor-base approach and 24–92 percent of GDP using location-of-parent approach.
    - Finland has a share of zero under the location-of-parent rule because its financial sector is dominated by foreign subsidiaries.
    - Norway’s estimated fiscal costs are the second largest by depositor base due to roughly 30 percent of regional deposits held at the big 6 being recorded in Norway.
- Uncertainty:
  - Estimates are subject to uncertainty due to competing strategies for bailing in and bailing out depositors and creditors.
  - Contribution to overall fiscal costs from bailing out unsecured bondholders is significant and depends on government approaches.
  - These estimated costs are very large relative to the ex-post cost of the 1990s Nordic banking crises, explained by larger banking system size, increased asset encumbrance from covered bonds, and resolution complications from cross-border operations.

### Policy implications
- Sovereigns need to accumulate sufficient fiscal buffers to insure against potential problems arising in the banking system, especially in the large banks.
- Risk concentration in a handful of pan-regional banking institutions that heavily rely on external funding implies:
  - In the event of a failure of any of these six large banks, the fiscal burden could be large and may lead to a substantial increase in sovereign debt levels within a very short period.
  - Total economic costs in terms of GDP growth and contagion are likely to be much larger than the direct costs calculated.
- Sufficient fiscal buffers are key to meet these types of risk.

*Source: _cr13275 - 3. Despite some heterogeneity within (PDF chapter).*

### 24. As problems in any of the big 6 banks could affect the entire region, there are strong

### 24. As problems in any of the big 6 banks could affect the entire region, there are strong

### Advantages of a coordinated pan-Nordic resolution framework
- Coordinated pan-Nordic resolution framework and well-defined burden sharing arrangement deliver strong advantages because problems in any of the big 6 banks could affect the entire region.
- Cooperation benefits extend beyond the continental Nordic region to other European markets given nonnegligible exposures to the Baltic countries (Estonia, Latvia, and Lithuania), Poland, and other parts of Europe.
- Clearly defined ex ante burden sharing arrangements minimize policy uncertainty ex post and facilitate quick resolution.

### Burden sharing of costs (displayed breakdowns)
- By depositor base (Percent of total costs): Denmark 18%; Finland 11%; Norway 26%; Sweden 45%.
- Determined by location of parent (Total Assets) (Percent of total costs): Denmark 21%; Finland 14%; Norway 65%; Sweden (percent not separately listed in figure but totals imply remaining share).

### Synthetic bank characteristics by geography (EUR mil. / persons)
- Credit Exposure (EUR mil.): Denmark 71,281; Finland 48,313; Sweden 104,249; Norway 61,613; Other Europe 28,268; Baltics + Poland 10,875; Rest of World 9,925; Total 335,559.
- Total Deposits (EUR mil.): Denmark 18,919; Finland 13,427; Sweden 30,245; Norway 23,827; Other Europe 5,994; Baltics + Poland 5,478; Rest of World 1,065; Total 98,954.
- Operating Income (EUR mil.): Denmark 1,301; Finland 676; Sweden 1,778; Norway 1,331; Other Europe 678; Baltics + Poland 400; Rest of World 211; Total 6,376.
- Employees (persons): Denmark 5,684; Finland 3,029; Sweden 5,211; Norway 2,655; Other Europe 1,257; Baltics + Poland 3,016; Rest of World 721; Total 21,573.
- Memorandum item, Total assets (Hypothetical Synthetic bank) 443,780 (EUR mil. implied).
- Total assets, public banks listed: Nordea 677,420; Danske bank 482,779.

### Largest publicly-listed banks: location, total assets, share of market (displayed)
- Nordea — Location of Parent: Sweden; Total Assets (EUR bil.) 677.4; Percent of GDP 164.9; Share of Total Market 26.9.
- Danske Bank — Denmark; 482.8; 197.7; 19.1.
- DNB — Norway; 321.8; 81.5; 12.8.
- Svenska Handelsbanken — Sweden; 297.7; 72.5; 11.8.
- Skandinaviska Enskilda Banken — Sweden; 285.7; 69.5; 11.3.
- Swedbank — Sweden; 215.0; 52.3; 8.5.
- Total Big 6 banks: Total Assets (EUR bil.) 2,280.4; Percent of GDP 90.4.

### Scenario assumptions and calibration (selected exact assumptions)
- Fraction of deposits that are insured (SWE, DNK, FIN) 70%. Deposit insurance coverage is €100,000.
- Fraction of deposits that are insured (NOR) 56%. Deposit insurance coverage is approx. €264,000.
- Fraction eventually recovered by DIF from BE of failed bank 40%. (Relatively high due to senior secured liabilities.)
- Levy on uninsured depositors in some scenarios 100% or 0% depending on scenario.
- Haircut on senior unsecured creditors 100% or 0% depending on scenario.

### Scenario definitions (explicit)
- Scenario A. Insured Depositors Bailed Out; Uninsured Depositors Bailed In; Senior Unsecured Creditors Bailed In.
- Scenario B. Insured Depositors Bailed Out; Uninsured Depositors Bailed Out; Senior Unsecured Creditors Bailed In.
- Scenario C. Insured Depositors Bailed Out; Uninsured Depositors Bailed Out; Senior Unsecured Creditors Bailed Out.

### Timeline of Events under scenarios (time t actions)
- Time, t = 1: Bank fails.
- t = 2: Assets put into Bankruptcy Estate (BE).
- t = 3: Bailed out depositor claims moved to health bank; financed by DIF/State ("Liquidity Payout").
- t = 4: DIF/State is senior-most claimant against the BE (after secured creditors claimed collateral).
- t = 5: Payout by BE to DIF/State (Liquidity Payout minus this payment determines "Eventual Payout").

### Synthetic bank failure experiment results — selected estimated fiscal costs (Percent of GDP and EUR bil. where given)
- Estimated Fiscal Costs (1/ Excluding Deposit Insurance Funds) — Percent of GDP (Scenario columns A, B, C in table format):
  - Denmark: existing equity in DIF 0.3; Scenario A 5.4; Scenario B 7.7; Scenario A DIF shortfall 5.1; Scenario B DIF shortfall 7.4; Cost of bailing out senior unsecured creditors Scenario A 2.2; Scenario B 3.1; Scenario C 5.6; Scenario A estimated fiscal costs 2.9; Scenario B 4.3; Scenario C 9.9.
  - Finland: existing equity in DIF 0.4; Scenario A 4.8; Scenario B 6.9; Scenario A DIF shortfall 4.4; Scenario B DIF shortfall 6.5; Cost of bailing out senior unsecured creditors Scenario A 1.9; Scenario B 2.8; Scenario C 4.9; Scenario A estimated fiscal costs 2.5; Scenario B 3.7; Scenario C 8.6.
  - Norway: existing equity in DIF 0.8; Scenario A 3.4; Scenario B 6.1; Scenario A DIF shortfall 2.6; Scenario B DIF shortfall 5.3; Cost of bailing out senior unsecured creditors Scenario A 1.4; Scenario B 2.4; Scenario C 3.8; Scenario A estimated fiscal costs 1.3; Scenario B 2.9; Scenario C 6.7.
  - Sweden: existing equity in DIF 0.8; Scenario A 5.2; Scenario B 7.4; Scenario A DIF shortfall 4.4; Scenario B DIF shortfall 6.6; Cost of bailing out senior unsecured creditors Scenario A 2.1; Scenario B 3.0; Scenario C 4.8; Scenario A estimated fiscal costs 2.3; Scenario B 3.6; Scenario C 8.4.
  - Nordic-4 Region: existing equity in DIF 0.6; Scenario A 4.6; Scenario B 7.0; Scenario A DIF shortfall 4.0; Scenario B DIF shortfall 6.3; Cost of bailing out senior unsecured creditors Scenario A 1.8; Scenario B 2.8; Scenario C 4.7; Scenario A estimated fiscal costs 2.1; Scenario B 3.5; Scenario C 8.2.
- DIF's recovery from Bankruptcy Estate and Deposit Insurance Payout (EUR bil. / Percent of GDP listed):
  - Denmark: DIF's Recovery from BE 245.0 (EUR bil.); DIF Shortfall 482.8; Deposit Insurance Payout 11.2; Estimated Fiscal Costs Scenario A 19.1; Scenario B 39.2; Scenario C 13.3; By location of parent Estimated Fiscal Costs (EUR bil.) 24.3; 50.0.
  - Finland: DIF's Recovery from BE 194.5; DIF Shortfall 0.0; Deposit Insurance Payout 9.3; Estimated Fiscal Costs Scenario A 15.9; Scenario B 32.6; Scenario C 0.0; By location of parent Estimated Fiscal Costs (EUR bil.) 0.0; 0.0.
  - Norway: DIF's Recovery from BE 390.0; DIF Shortfall 321.8; Deposit Insurance Payout 10.2; Estimated Fiscal Costs Scenario A 21.8; Scenario B 44.7; Scenario C 5.6; By location of parent Estimated Fiscal Costs (EUR bil.) 10.2; 20.9.
  - Sweden: DIF's Recovery from BE 409.2; DIF Shortfall 1,475.9; Deposit Insurance Payout 17.0; Estimated Fiscal Costs Scenario A 29.1; Scenario B 59.7; Scenario C 24.4; By location of parent Estimated Fiscal Costs (EUR bil.) 44.6; 91.5.
  - Nordic-4: DIF's Recovery from BE 1,238.7; DIF Shortfall 2,280.4; Deposit Insurance Payout 12.5; Estimated Fiscal Costs Scenario A 22.7; Scenario B 46.7; Scenario C 12.5; By location of parent Estimated Fiscal Costs (EUR bil.) 22.7; 46.7.
- Total Assets of Big 6 Banks (consolidated basis) 2012 expressed alongside National GDP used in cost calculations.

### Geographic exposures of six largest banks (2012)
- Credit Portfolio Exposure (share of combined exposure, EUR 1.7 tn) displayed by bank and geography: exposures shown across DNK, FIN, NOR, SWE, Other Europe, Baltics and Poland, RoW for each bank (Handelsbanken, SEB, Swedbank, DNB, Danske, Nordea).
- Total Deposits (Percent of combined deposits, EUR 552 bn) and Full-Time Employees (Percent of combined employees, 113,272 employees) and Total Operating Income (Percent of combined operating income, EUR 34 bn) shown by bank and geography.

### Bank-to-bank and government-bank interlinkages (2012)
- Government Ownership (Percent of total shares outstanding; direct holdings + state pension fund holdings, 2012) charted for each bank by country (Finland, Sweden, Norway).
- Gross Direct Long Sovereign Exposures, by Geography 2012 (Percent of combined exposure, EUR 87.8 bn) shown across banks and geographies.
- Bank-to-Bank Ownership (Percentage of total external shares outstanding, 2012) displayed for each bank.

### Shock propagation and contagion: model findings
- Asset pricing factor model decomposes excess returns into global, regional, and country-specific factors using annual data for 35 economies, sample period 2000 through 2012.
- Global factors explain most variation in excess returns: variation in the global factor accounts for 60 to 70 percent of bond, money, and stock market variation, on average across the four countries.
- Regional factor accounts for approximately 9 to 11 percent of money, bond, and stock market variation.
- Country-specific factor accounts for the remaining 20 to 30 percent.

### Propagation of macro-financial shocks to output (macroeconometric model findings)
- An unobserved components macroeconometric model on 35 economies is used to estimate bilateral spillovers; cyclical components determined by lags, interest rates, terms of trade, and other macro-financial variables; trend components follow random walk.
- Inward output spillovers to the Nordic-4 come predominantly from neighbors and systemic advanced economies (U.S., Germany, U.K.), reflecting higher export exposures within the region and high direct and indirect financial exposures.
- Regional comovement across financial shocks amplifies inward output spillover coefficients by about 42 percent on average across the Nordics.
- Amplification is particularly large for Norway (example: output effects of incoming financial shocks transmitted from Sweden increase by about approximately 50 percent because Sweden’s shock feeds back through Nordic neighbors).
- Within the Nordics, inward spillovers are dominated by Sweden (the largest economy, one third of total Nordic GDP); Finland is particularly susceptible to spillovers from Sweden (between 2.5 and 3 times greater than those from Denmark and Norway).
- Sweden is primarily affected by spillovers from Norway (one quarter larger than those from Denmark and Finland).
- Outward output spillovers from the Nordics to the rest of the world are small to moderate and largely concentrated within the Nordic-4 region.
- For macroeconomic shocks, outward spillover coefficients are highest from other countries to Sweden, and highest from Sweden to Denmark. For financial shocks, outward spillover coefficients are greatest to Sweden from Norway and Finland.

### Policy implications and coordination experiments (implicit from findings)
- Given dominance of global factors in asset price variation but nontrivial regional factors and strong cross-border exposures, policy coordination within the Nordic region is important to manage systemic risk.
- Ex ante, clearly defined burden sharing and a coordinated resolution framework would reduce policy uncertainty and enable quicker resolution when a major bank fails.
- Cooperation should extend to broader European markets given exposures to Baltic countries, Poland, and other parts of Europe.

*Source: Fund staff calculations and analysis as presented in the provided content unit.*

### 13. Greater fiscal policy coordination can generate short-run output gains. The strong fiscal

### _cr13275 - 13. Greater fiscal policy coordination can generate short-run output gains. The strong fiscal

### Experiment design and shock scenarios
- Objective: understand potential gains from fiscal policy coordination in response to a negative output shock to the Nordic-4 (Denmark, Finland, Norway, Sweden).
- Shock examples cited: macroeconomic deterioration in major trading partners; correction in house prices in one country with negative implications for confidence and consumption and therefore output; an intensification of the euro area (EA) sovereign debt crisis.
- EA crisis intensification modeled as a temporary but persistent 300 basis point increase in long-term government bond yields in the EA periphery.
- Policy responses compared: each country engages in a temporary uncoordinated fiscal stimulus versus a coordinated fiscal stimulus.
- Fiscal stance baseline note: the analysis also considers a case that reduces fiscal balances (as a percent of GDP) of the four Nordics by 1 percent due to a combination of temporary and mildly persistent expenditure reductions and revenue increases.

### Key quantitative findings on output effects
- A temporary but persistent expenditure-based fiscal stimulus of 1 percent of GDP is estimated to reduce initial output losses by:
  - 0.6 percentage points on average for the Nordic-4 region if uncoordinated.
  - 0.8 percentage points on average for the Nordic-4 region if coordinated.
- The implied coordination gain is 35 percent in 2013 (calculated from the above stimulus effects).
- Over the outer years the four economies consolidate with a similar impact on output between the coordinated and uncoordinated cases.

### Fiscal multipliers and channels
- Main transmission channel: changes in domestic demand operating via intra-regional trade flows.
- Relative country effects:
  - Denmark and Finland show larger output losses due to macroeconomic and financial spillovers.
  - Norway and Sweden face smaller output losses as they can deploy conventional monetary policy loosening.
- Coordination increases fiscal multipliers:
  - Multipliers on revenue rise by 27 percent after accounting for endogenous monetary policy changes in interest rates.
  - Multipliers on expenditure rise by 13 percent after accounting for endogenous monetary policy changes in interest rates.
- Heterogeneity in coordination gains:
  - Highest coordination gains observed for Denmark and Sweden (reflecting regionally concentrated export exposures).
  - Lowest coordination gains for Norway (reflecting high energy commodity export intensity).
  - Finland’s gains are more muted (lower share of overall trade within the region).

### Policy implications and recommendations
- Strong national policies have collective benefits:
  - Negative episodes originating in a single Nordic country will be felt by all members due to high comovement within the Nordic-4.
  - Example policy: macroprudential policies aimed at managing private sector balance sheets and the housing market.
- Build national and regional buffers:
  - Regional factors help explain part of risk premia in financial markets; contagion risk from neighboring markets is evident.
  - With potentially large contingent liabilities from bank failures, fiscal buffers provide advantages both nationally and for regional stability.
- Advantages from coordination:
  - Different fiscal rules and external policy constraints (e.g., EU Excessive Deficit Procedure rules) exist across the Nordics, but coordinated fiscal impulses can create a virtuous circle reinforcing demand when authorities act concertedly.
  - Coordination can prevent strategic or competitive domestic policy responses that might place the region on a sub-optimal output growth trajectory.

*Source: Fund staff calculations.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/scr/2013/_cr13275.pdf_