## _wp11218 — 0.12 percent on foreign GDP for a spending increase and 0.03 percent for a net tax cut

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---

### Key quantitative findings and sample scope
- Estimated spillovers highlighted: "0.12 percent on foreign GDP for a spending increase and 0.03 percent for a net tax cut."
- Sample: 17 countries — Austria, Belgium, Canada, Finland, France, Germany, Greece, Ireland, Italy, Japan, Netherlands, Portugal, Spain, Sweden, Switzerland, United Kingdom, and United States.
- Data: quarterly real PPP-adjusted GDP, from 1975:Q1 to 2010:Q3, from the OECD Economic Outlook database.
- Crisis dummy: takes value 1 from 2008:Q4–2009:Q1 to reflect estimates of “normal times.”
- Country-size thresholds for ordering: countries surpassing the 8 percent threshold are large; countries contributing less than 4 percent are considered small.
- Number of orderings used: 48 different orderings; ordering probabilities (size-based):
  - United States: 50 percent probability of being lead country; 25 percent probability of being ordered second or third.
  - Germany and Japan: each have a 25 percent chance of being ordered first, second, or third and a 12.5 percent probability of being ordered fourth or fifth.
  - United Kingdom, France, and Italy: probability of being ordered second or third of 8⅓ percent, fourth or sixth of 25 percent, and fifth or seventh of 16⅔ percent.
  - Spain: probability of being ordered fifth or sixth of 25 percent and of being ordered seventh of 50 percent.

### Empirical approach and identification
- Baseline model:
  - Reduced-form VAR estimation for stacked vector y of country GDP growth rates.
  - Control vector x includes two oil-shock dummies (1979 and 1990) and a constant; baseline regression additionally includes the 2008:Q4–2009:Q1 crisis dummy.
- Identification and uncertainty:
  - Choleski ordering with averaging across orderings to produce average impulse responses and capture ordering uncertainty.
  - Dynamic growth-contribution algorithm steps:
    1. structural errors via Choleski decomposition;
    2. compute moving average (MA) representation of each country’s growth history;
    3. combine MA representation and structural errors to derive contributions of each country’s shocks to quarterly GDP growth;
    4. apply compounding rule to compute annualized contribution.
- Counterfactual and country-by-country methods:
  - Counterfactual analysis: set structural coefficients associated with third-country effects to zero (kj l α = 0 for all l = 0,...,L and all j ≠ i and j ≠ k) and recalculate impulse responses to isolate direct bilateral effects.
  - Country-by-country regressions: countries grouped into non-EMU (U.S., Japan, Canada, Sweden, Switzerland, United Kingdom) and EMU (rest). Regressions include EMU growth, RoW growth, and real exports to test trade channel relevance and reduce ordering complexity.

### Main empirical results — outward and inward spillovers
- Outward spillovers (aggregate patterns):
  - U.S. remains the largest source of spillovers across the 17-country sample.
  - Germany plays a minor aggregate role but affects some smaller European countries strongly; U.K. and Japan have intermediate roles; France, Italy, and Spain occupy middle positions.
  - Excluding the crisis dummy (i.e., focusing on crisis times) yields much higher outward spillover effects from all regions, especially the U.S., the U.K., and the non-German euro area.
  - Estimates for 1993:Q1–2010:Q3 show increased importance of Italy and the U.S.; no evidence of an increasingly important role for Germany during this period.
  - Within Europe, Germany is more sensitive to growth in the rest of the eurozone than it is a source of outward spillovers; positive shocks in France and Italy generate larger spillovers to the European periphery than comparable German shocks.
  - GIP (Greece, Ireland, Portugal) effects: Germany less prominent than France and Italy; U.S. primary impact on Ireland; U.S. more pronounced for Greece and Portugal in crisis context; Japan and U.K. relatively minor for GIP (U.K. more important during crisis).
  - Spain: shocks to Spain’s growth can have larger impacts on other European countries than shocks from GIP.
- Inward spillovers (sensitivity and conduit roles):
  - Germany exhibits high sensitivity to external shocks: responds more strongly to EMU-country shocks than other large EMU members and exhibits the second largest response (after Italy) to non-EMU shocks.
  - Germany’s sensitivity reflects large trade and banking exposures to the rest of Europe and supports the interpretation that Germany acts more as a conduit for external shocks (e.g., from the U.S.) than as an independent source.
  - Regression results for 1993 onward (large model) show inward spillovers from the U.S. to the four large EMU members have increased, while the U.K. and Japan have become less relevant.
  - Baseline estimation truncated in provided content: "a 1 percent growth shock in the U.S. tends to increase output growth within 10 quarters by about" — (text ends in provided excerpt).

### Spillover magnitudes and temporal/contextual variation
- Aggregate magnitudes (normal times vs crisis and recent episode):
  - In normal times: 0.3 percent in Germany, 0.4 in Italy and France and 0.1 percent in Spain.
  - When not controlling for crisis times: 0.4 percent in Germany and Spain, 0.5 percent in France, and 0.6 percent in Italy.
  - The respective values more than double for Germany and Spain in the more recent episode (estimation for 1993:Q1–2010:Q3 including a crisis dummy), as both become more sensitive to the U.S. than France and Italy.
  - Sample includes 2007 and 2008 which mark the peak of financial linkages; authors find even higher effects in that context.
- Country-specific within-EMU bilateral findings:
  - Germany’s effect on Spain and France: output rise by 0.1–0.2 percent in response to a 1 percent German growth shock.
  - Germany → Italy: Italy’s growth rate rises by around 0.4 percent.
  - France’s effect on Germany and Italy: increase growth by 0.4 percent in normal times and above 0.5 percent in crisis times.
  - Italy → Germany and France: a 1 percent shock in Italy causes German and French growth to increase by 0.4 percent and Spanish growth by 0.2 percent in baseline; effect increases by an additional 0.2 percent for Germany and France and 0.3 percent for Spain in crisis times.
  - Spain as source: under baseline full-sample regression, a 1 percent shock to Spain’s growth increases GDP growth in Germany by 0.7 percent, in France by 0.5 percent, and in Italy by 0.3 percent (text continues in source).

### Transmission channels — trade versus financial and third-country effects
- Prior literature: mixed conclusions with trade and financial channels both important (Helbling et al. 2007; Bagliano and Morana 2011; Bayoumi and Swiston 2009; Galesi and Sgherri 2009).
- This paper’s diagnostics:
  - Two identification strategies:
    - Counterfactual analysis that shuts down third-country propagation to isolate direct bilateral impacts.
    - Country-wise VARs including real exports to test trade channel explicitly.
  - Finding: dominance of non-trade channels, especially for shocks originating within the EMU; trade channels remain relevant for several countries and for non-EMU shocks.
- Quantified trade-channel shares (inward spillovers from non-EMU shocks; preserved exactly as reported):
  - Germany: close to 40 percent of growth spillovers due to trade.
  - France: around 30 percent.
  - Spain: 15 percent.
  - Italy: 10 percent.
- For small open economies (non-EMU shocks), trade accounts for around 50 percent of spillovers for Belgium, Sweden, Austria, and Ireland.
- For EMU shocks, trade shares drop by:
  - Austria and Belgium: about 20 percentage points.
  - Sweden: about 40 percentage points.
  - Ireland: about 5 percentage points.
- Third-country effects:
  - Definition: fraction of the inward spillover from a shock in a given country transmitted via other countries after one year.
  - Germany tends to respond swiftly and directly to U.S./Japan shocks (low third-country indicator).
  - France, Italy and small core euro area members receive shocks to a larger extent via third countries (higher third-country indicator).
  - During crisis times, third-country effects play a larger role, amplifying negative spillovers via confidence and asset-price channels.

### Cross-border exposures and descriptive facts (selected highlights)
- Trade exposures (percent of GDP, 2010; selected):
  - Netherlands: With Germany 18.8; With Euro Area 26.2; With United States 2.7.
  - Belgium: With Germany 16.5; With Euro Area 37.0; With United States 4.6.
  - Ireland: With Germany 4.5; With Euro Area 18.2; With United States 12.1.
  - United States: With Germany 0.3; With Euro Area 0.9; With Rest of World 6.1.
- Banking exposures (percent of GDP, 2010; international bank claims of domestically-owned banks, consolidated - ultimate risk basis; selected):
  - Ireland: With Germany 21.7; With European Developed Countries 67.2; Of which: with Euro Area 41.7; With Rest of World 31.5.
  - Netherlands: With Germany 22.0; With European Developed Countries 57.6; Of which: with Euro Area 32.2; With Rest of World 40.9.
  - Switzerland: With Germany 24.5; With European Developed Countries 53.0; Of which: with Euro Area 47.6; With United States 32.6; With Rest of World 56.2.
  - United States: With Germany 1.6; With European Developed Countries 5.1; Of which: with Euro Area 4.1; With Rest of World 4.4.

### Determinants of spillover size and stylized statistical relationships
- Hypotheses tested:
  - Size (PPP-adjusted GDP) predicts outward spillovers.
  - Presence of autonomous domestic drivers (measured by average contribution of trade to GDP and co-movement of GDP growth and net exports) increases likelihood of generating outward spillovers.
- Country classification by average net trade contribution to GDP:
  - Positive average net contribution of trade: Japan, Germany, Netherlands, Belgium, Sweden, Austria, Switzerland, Finland, Ireland.
  - No positive average net trade contribution: United States, United Kingdom, France, Italy, Spain, Canada, Greece, Portugal.
- Co-movement patterns and spillover risk:
  - High spillover risk (countercyclical domestic/external contributions): U.K., U.S., Canada, Spain, Portugal, Greece.
  - Export-driven growth pattern: Germany, Japan, Austria, Finland.
- Statistical relationships (reported exactly):
  - Increasing size of the country by 10 percent increases outward spillover by 0.1 percentage points.
  - Reducing the correlation of external demand and GDP growth from +0.5 to -0.5 increases outward spillovers by 0.14 percentage points.
  - Relationship holds when excluding the crisis dummy.
  - Outliers: Canada and Spain have larger spillovers than predicted by size alone; Germany has smaller spillovers than expected by size alone.

### Crisis, recovery, and dynamic decomposition findings
- Decomposition method: individual country growth split into own contribution, cyclical contributions from each G7 member and Spain, and long-run growth rate; sample evolution 2005:Q1 to 2010:Q3.
- Pre-crisis: significant domestic contribution to growth; U.S. and Spain major outward contributors; France important for southern peripherals.
- During crisis (2008–09):
  - Large negative domestic contributions in Italy, the U.S., Japan, Sweden, Ireland, the U.K., and since Q1 2010 in Greece.
  - Japan generated negative spillovers for virtually all countries: reduced German output growth by over 1.5 percentage points, Italian growth by 1.4 percentage points, and U.S. growth by 1.2 percentage points.
  - U.S. shock affected almost all countries in 2009: Canada and Ireland (-2 percent), the U.K. (-1.5 percent), Netherlands (-1 percent) and others.
  - Italy had strong negative spillovers on several European countries; Germany’s negative external spillovers primarily hit neighboring countries, strongest on the Netherlands.
- Recovery (through 2010:Q3):
  - Recovery led by the U.S. and Japan, accounting for most countries’ positive external support to growth in 2010 (through Q3).
  - Additional positive domestic momentum in Germany, France, Canada, Switzerland, and Sweden.
  - Recovery hampered by continued negative domestic contributions in Italy, Spain, and Ireland, and falling domestic demand support in the Netherlands, Greece, and Portugal.

### Policy-relevant interpretations and implications
- Spillovers vary with country size but are also governed by how domestically driven growth is; size alone does not determine being an engine of global growth versus a transmitter of foreign shocks.
- Financial linkages are important for short-run spillovers (equity prices, interest rates, bond yields); trade channels remain relevant for several countries — policy responses should account for both channels.
- During crisis periods, non-standard transmission channels (correlated asset price downturns, confidence effects) amplify spillovers relative to normal times; inclusion of crisis dummies materially alters estimated magnitudes.
- For euro area peripheral countries, recovery in Germany alone is unlikely to generate strong positive spillovers; growth in France and Italy can have larger positive effects on the periphery.
- Germany functions more as a conduit/amplifier of external shocks than as an increasingly independent source of global shocks over the sample period.
- Growth spillover risks from European crisis countries to the rest of Europe remain limited in the sample, but stronger effects could occur if the debt crisis spreads to larger countries such as Spain.

*Source — content unit _wp11218 - 0.12 percent on foreign GDP for a spending increase and 0.03 percent for a net tax cut.*

### 0.12 percent on foreign GDP for a spending increase and 0.03 percent for a net tax cut.

### _wp11218 - 0.12 percent on foreign GDP for a spending increase and 0.03 percent for a net tax cut.

### Key quantitative findings and scope
- Estimated spillovers cited: "0.12 percent on foreign GDP for a spending increase and 0.03 percent for a net tax cut."
- Sample: 17 countries — Austria, Belgium, Canada, Finland, France, Germany, Greece, Ireland, Italy, Japan, Netherlands, Portugal, Spain, Sweden, Switzerland, United Kingdom, and United States.
- Data: quarterly real PPP-adjusted GDP, from 1975:Q1 to 2010:Q3, from the OECD Economic Outlook database.
- Crisis dummy: takes value 1 from 2008:Q4–2009:Q1 to reflect estimates of “normal times.”
- Country size thresholds for ordering: countries surpassing the 8 percent threshold are large; countries contributing less than 4 percent are considered small.
- Number of orderings used in the analysis: 48 different orderings.
- Ordering probabilities (size-based procedure highlights uncertainty in contemporaneous ordering):
  - United States: 50 percent probability of being lead country; 25 percent probability of being ordered second or third.
  - Germany and Japan: each have a 25 percent chance of being ordered first, second, or third and a 12.5 percent probability of being ordered fourth or fifth.
  - United Kingdom, France, and Italy: probability of being ordered second or third of 8⅓ percent, fourth or sixth of 25 percent, and fifth or seventh of 16⅔ percent.
  - Spain: probability of being ordered fifth or sixth of 25 percent and of being ordered seventh of 50 percent.

### Empirical approach and methodology
- Baseline specification: reduced-form VAR estimation for stacked vector y of country GDP growth rates; control vector x includes two oil-shock dummies (1979 and 1990) and a constant; baseline regression additionally includes the 2008:Q4–2009:Q1 crisis dummy.
- Identification: Choleski ordering with averaging across orderings to produce average impulse responses and capture ordering uncertainty.
- Dynamic growth contribution algorithm:
  - Step 1: structural errors via Choleski decomposition.
  - Step 2: compute moving average (MA) representation of each country’s growth history.
  - Step 3: combine MA representation and structural errors to derive contributions of each country’s shocks to quarterly GDP growth.
  - Step 4: apply compounding rule to compute annualized contribution.
- Counterfactual analysis: set structural coefficients associated with third-country effects to zero (kj l α = 0 for all l = 0,...,L and all j ≠ i and j ≠ k) and recalculate impulse responses to isolate direct bilateral effects.
- Country-by-country regressions: countries grouped into non-EMU (U.S., Japan, Canada, Sweden, Switzerland, United Kingdom) and EMU (rest). For each country, regressions include EMU growth, RoW growth, and real exports to test trade channel relevance and reduce ordering complexity.

### Transmission channels: trade versus financial
- Prior literature summarized:
  - Helbling et al. (2007): most U.S. spillovers trade-related; effects relatively small.
  - Bagliano and Morana (2011): trade channel relatively more important; U.S. credit spreads affect foreign output, U.S. stock prices less so.
  - Bayoumi and Swiston (2009): largest contributions from financial variables; short-term interest rates, bond yields, equity prices important.
  - Galesi and Sgherri (2009): equity prices main short-run channel; other financial variables become more important over two years.
- This paper’s findings:
  - Confirms U.S. remains main source of growth spillovers across a set of 17 countries.
  - Confirms importance of financial transmission channels for growth spillovers, but finds trade channels also relevant for several countries.
  - Distinction emphasized between autonomous country demand and transmission of global demand shocks: spillovers vary positively with size but also reflect the extent to which growth is domestically driven.

### Cross-border exposures and descriptive facts
- Trade exposures (selected highlights from Table 1, percent of GDP, 2010):
  - Netherlands: With Germany 18.8; With Euro Area 26.2; With United States 2.7.
  - Belgium: With Germany 16.5; With Euro Area 37.0; With United States 4.6.
  - Ireland: With Germany 4.5; With Euro Area 18.2; With United States 12.1.
  - United States: With Germany 0.3; With Euro Area 0.9; With United Kingdom ...; With Rest of World 6.1.
  - (Table 1 source: DOTS, WEO, and IMF staff calculations; "With Euro Area 1/ Excluding Germany.")
- Banking exposures (selected highlights from Table 2, percent of GDP, 2010; international bank claims of domestically-owned banks, consolidated - ultimate risk basis):
  - Ireland: With Germany 21.7; With European Developed Countries 67.2; Of which: with Euro Area 41.7; With Rest of World 31.5.
  - Netherlands: With Germany 22.0; With European Developed Countries 57.6; Of which: with Euro Area 32.2; With Rest of World 40.9.
  - Switzerland: With Germany 24.5; With European Developed Countries 53.0; Of which: with Euro Area 47.6; With United States 32.6; With Rest of World 56.2.
  - United States: With Germany 1.6; With European Developed Countries 5.1; Of which: with Euro Area 4.1; With Rest of World 4.4.
  - (Table 2 source: BIS, WEO, and IMF staff calculations; notes: 2/ Excluding Germany and the UK. 3/ Excluding Germany.)

### Main empirical results: outward and inward spillovers
- Outward spillovers:
  - Baseline (full sample including crisis dummy): U.S. remains largest source of spillovers to all countries in the sample.
  - Germany plays a minor role for the sample in aggregate but affects some smaller European countries strongly.
  - U.K. and Japan have intermediate roles; France, Italy, and Spain occupy middle positions.
  - Excluding the crisis dummy (i.e., focusing on crisis times) yields much higher outward spillover effects from all regions, especially pronounced for the U.S., the U.K., and the non-German euro area during the recent crisis.
  - Estimates for 1993:Q1–2010:Q3 show increased importance of Italy and the U.S. for spillovers to other countries; no evidence of an increasingly important role for Germany during this period.
  - Within Europe: Germany is more sensitive to growth in the rest of the eurozone than it is a source of outward spillovers; positive growth shocks in France and Italy generate larger spillovers to the European periphery than comparable German shocks.
  - GIP (Greece, Ireland, Portugal) effects:
    - Germany less prominent for the GIP than France and Italy overall.
    - U.S. has primary impact on Ireland; more pronounced impact on Greece and Portugal in crisis context.
    - Japan and U.K. play relatively minor roles for GIP (U.K. more important during the crisis).
  - Spain: shocks to Spain’s growth have potentially much larger impacts on other European countries than shocks from GIP.
- Inward spillovers:
  - Germany exhibits high sensitivity to external shocks: responds more strongly to EMU-country shocks than other large EMU members and exhibits the second largest response (after Italy) to non-EMU shocks.
  - Germany’s sensitivity reflects large trade and banking exposures to the rest of Europe and supports the interpretation that Germany acts more as a conduit for external shocks (e.g., from the U.S.) than as an independent source.
  - Regression results for 1993 onward (large model) show inward spillovers from the U.S. to the four large EMU members have increased, while the U.K. and Japan have become less relevant.
  - Baseline estimation: "a 1 percent growth shock in the U.S. tends to increase output growth within 10 quarters by about" — (text ends at this phrase in the provided content).

### Transmission mechanism diagnostics
- Two strategies to identify channels:
  - Counterfactual analysis that shuts down third-country propagation to isolate direct bilateral impacts.
  - Country-wise VARs including real exports to test explicitly for the trade channel.
- Aggregation/grouping implications:
  - Grouping countries (EMU vs RoW) provides parsimony but can introduce aggregation bias—results may be more pronounced relative to fully disaggregated baseline.
  - Robustness checks include alternative control variables; U.S. credit spreads and U.S. real equity prices had some significance, but U.S. credit spread significance diminishes when including the 2008–09 crisis dummy (i.e., credit spreads proxy global financial crisis).

### Interpretations relevant for policy and systemic risk
- Spillovers vary with country size but are also governed by how domestically driven growth is; size alone does not determine being an engine of global growth versus a transmitter of foreign shocks.
- Financial linkages are important channels for short-run spillovers (equity prices, interest rates, bond yields), and trade channels remain relevant for several countries — policy responses should account for both channels.
- During crisis periods, non-standard transmission channels (correlated asset price downturns, confidence effects) amplify spillovers relative to normal times; crisis dummies materially alter estimated magnitudes.
- For euro area peripheral countries, recovery in Germany alone is unlikely to generate strong positive spillovers; growth in France and Italy can have larger positive effects on the periphery.
- Relative systemic importance: the U.S. is the dominant source of outward spillovers across the 17-country sample; Germany is comparatively an important conduit and highly sensitive to intra-European shocks.

*Italic: Source — content unit _wp11218 - 0.12 percent on foreign GDP for a spending increase and 0.03 percent for a net tax cut.*

### 0.3 percent in Germany, 0.4 in Italy and France and 0.1 percent in Spain in normal times.

### _wp11218 - 0.3 percent in Germany, 0.4 in Italy and France and 0.1 percent in Spain in normal times.

### Spillover magnitudes (aggregate estimates)
- In normal times: 0.3 percent in Germany, 0.4 in Italy and France and 0.1 percent in Spain.
- When not controlling for the effect of crisis times: 0.4 percent in Germany and Spain, 0.5 percent in France, and 0.6 percent in Italy.
- The respective values more than double for Germany and Spain in the more recent episode (estimation for 1993:Q1–2010:Q3 including a crisis dummy), as both become more sensitive to the U.S. than France and Italy.
- The increased sensitivity to the U.S. is in line with the increased correlation of the EMU countries’ GDP growth with the lagged GDP growth of the U.S. (Figure 1).
- The sample includes 2007 and 2008 years which mark the peak of financial linkages, and the authors find even higher effects in that context.
- Prior literature: Helbling et al. (2007) find spillovers to be increasing in financial and trade linkages and significantly higher spillovers from the U.S. to other countries in the period from 1987–2006 compared to the entire 1970–2006 period.

### Sample periods, crisis effects, and aggregation bias
- Recent episode estimation period: 1993:Q1–2010:Q3 (including a crisis dummy).
- Crisis years in sample explicitly mentioned: 2007 and 2008.
- Note on methodology: While estimates from the smaller model are directly obtained for “EMU” and “Non-EMU” shocks, the corresponding values from the baseline VAR (large model) are obtained by weighting the responses to the single countries’ shocks which constitute the EMU and the non-EMU group in the country specific VARs.
- Caveat: The small country-specific VARs overestimate the impact, due to the aggregation bias which tends to increase the persistence of the shocks and thus overestimate the response.

### Within-EMU bilateral spillovers (country-to-country findings)
- General statement: Within the EMU, inward spillovers from Germany, Italy, and France to the other large EMU members are relatively stable across the two sample periods and robust to the inclusion of the crisis dummy (i.e., likely to persist even outside of crisis times).
- Germany’s effect on the other three large euro area countries:
  - Ranges at the lower end for Spain and France, causing output to rise by 0.1–0.2 percent.
  - Italy’s growth rate rises by around 0.4 percent in response to a 1 percent growth shock in Germany.
- France’s effect:
  - Affects Italy and Germany roughly by the same order of magnitude, yielding an increase in growth by 0.4 percent in normal times and above 0.5 percent in crisis times.
  - The effect on Spain is only marginally higher.
- Italy’s effect:
  - A 1 percent growth shock in Italy causes German and French growth to increase by 0.4 percent and Spanish growth by 0.2 percent in the baseline estimation.
  - The effect increases by an additional 0.2 percent for Germany and France and 0.3 percent for Spain in crisis times.
  - In the more recent period, Spain’s sensitivity to Italy’s growth shocks has increased to a higher level than its sensitivity to growth shocks in Germany or France.

### Spain as a source of shocks
- Spain has been an important source of growth shocks for other large euro area countries.
- Under the baseline regression for the full sample, a 1 percent shock to Spain’s growth increases GDP growth in Germany by 0.7 percent, in France by

*Source: _wp11218 - 0.3 percent in Germany, 0.4 in Italy and France and 0.1 percent in Spain in normal times.*

### 0.5 percent, and in Italy by 0.3 percent. This position is reaffirmed in the regression

### _wp11218 - 0.5 percent, and in Italy by 0.3 percent. This position is reaffirmed in the regression

### Key empirical findings on growth spillovers
- The U.S. has been the largest positive contributor to long-term growth in other countries (long-run decomposition, Table 3).
- Long-run spillovers from Japan and Spain have been positive and relatively important; Spain is more relevant for European countries.
- Canada and France provide relatively minor long-run growth support to other countries; spillovers from France are particularly relevant for the GIP.
- Long-run external growth spillovers from Germany are close to zero; the U.K. and Italy’s long-run spillovers have been small and negative.
- The average (adjusted) R-squared value of the reduced form equations for the baseline model is around 0.6 (0.4). Including the crisis dummy implies an increase by 0.04 in explanatory power in both cases.

### Domestic and foreign growth contributions during crisis and recovery
- Method: decomposition of individual countries’ growth rate into own contribution (orange), cyclical contributions from each G7 member and Spain, and long-run growth rate (gray); sample evolution from 2005:Q1 to 2010:Q3.
- Pre-crisis (boom period):
  - Significant domestic contribution to each country’s GDP growth.
  - Outward spillovers: U.S. and Spain major sources of positive growth support; U.S. mattered most for Canada, the U.K., and Ireland.
  - France important for southern peripheral countries, Belgium, Austria, and Finland.
  - Germany initially weighed negatively on most countries’ growth but later contributed positively to the Netherlands, Italy, Greece and Austria (at lower levels than the U.S., Spain, Italy, or France).
  - Italy and the U.K. contributed negatively to growth in other European countries in the years preceding the crisis.
- During the crisis (2008–09):
  - Large negative domestic contributions observed in Italy, the U.S., Japan, Sweden, Ireland, the U.K., and since Q1 2010 in Greece.
  - Japan generated negative spillovers for virtually all countries: reduced German output growth by over 1.5 percentage points, Italian growth by 1.4 percentage points, and U.S. growth by 1.2 percentage points.
  - U.S. shock affected almost all countries in 2009: Canada and Ireland (-2 percent), the U.K. (-1.5 percent), Netherlands (-1 percent) and others.
  - Italy had strong negative spillovers on several European countries, most severe for Switzerland and significant for peripheral countries.
  - Germany’s negative external spillovers primarily hit neighboring countries, strongest on the Netherlands.
  - The U.K. dragged down GDP growth in Finland, Sweden, Spain, and Ireland, especially toward the later part of the crisis.
- Recovery (through 2010:Q3):
  - Recovery led by the U.S. and Japan, accounting for most countries’ positive external support to growth in 2010 (through Q3).
  - Additional positive domestic momentum in Germany, France, Canada, Switzerland, and Sweden.
  - Recovery hampered by continued negative domestic contributions in Italy, Spain, and Ireland, and falling domestic demand support in the Netherlands, Greece, and Portugal.

### Channels of growth spillover transmission — third-country effects
- Definition: relevance of third-country effects = fraction of the inward spillover from a shock in a given country transmitted via other countries after one year.
- Germany tends to respond swiftly and directly to shocks to the U.S. or Japan (low third-country indicator).
- France, Italy and small core euro area members receive shocks to a larger extent via third countries (higher third-country indicator).
- Inter-linkages between euro area countries are highly relevant in transmitting shocks from outside the euro area to the non-German euro area members.
- Germany may act as an important transmitter/amplifier of shocks originating outside the euro area due to its directness of response to U.S./Japan shocks and the high third-country indicator for other euro members.
- Regional patterns for intra-European shocks:
  - Italy and Spain affect Dutch growth primarily via third countries.
  - German shocks affect Dutch growth mostly directly.
  - Switzerland directly affected by Italian shocks.
  - Belgium most directly affected by French shocks.
  - Austrian growth most directly affected by France and Germany; less directly by Italy; least by Spain.
  - Italy’s growth most directly affected by Germany, then France, then Spain.
  - Germany’s impact on Greece and Portugal appears less direct than France’s and Italy’s impacts on these countries.
- Crisis times: third-country effects play a larger role, amplifying negative spillovers via confidence and asset price channels.

### Channels of growth spillover transmission — trade vs non-trade
- Approach: small country VAR including real exports to quantify trade channel.
- Main result: dominance of non-trade channels, especially for shocks originating within the EMU.
- Trade channel shares for inward growth spillovers from non-EMU shocks:
  - Germany: close to 40 percent of growth spillovers due to trade.
  - France: around 30 percent.
  - Spain: 15 percent.
  - Italy: 10 percent.
- For EMU shocks, a similar pattern emerges; France proportionally relies more on trade effects than Germany for EMU shocks, though France’s overall sensitivity to EMU shocks is much below Germany’s.
- For small open economies (non-EMU shocks), trade accounts for around 50 percent of spillovers for Belgium, Sweden, Austria, and Ireland.
- For EMU shocks, trade shares drop by:
  - Austria and Belgium: about 20 percentage points.
  - Sweden: about 40 percentage points.
  - Ireland: about 5 percentage points.
- Conclusion: trade effects matter relatively more for non-EMU shocks than for EMU shocks; within the EMU, monetary and credit channels and other non-trade links predominate.

### Determinants of spillover size
- Hypotheses tested:
  - Size (PPP-adjusted GDP) predicts outward spillovers.
  - Presence of autonomous domestic drivers (measured by average contribution of trade to GDP and co-movement of GDP growth and net exports) increases likelihood of generating outward spillovers.
- Countries with a positive average net contribution of trade to GDP: Japan, Germany, Netherlands, Belgium, Sweden, Austria, Switzerland, Finland, Ireland.
- Countries without positive average net trade contribution: United States, United Kingdom, France, Italy, Spain, Canada, Greece, Portugal (Table 4).
- In relevance of external demand for overall GDP growth, ranking: Germany leading, followed by Ireland, Switzerland, Japan, Austria, Sweden, Finland, Belgium, Netherlands.
- Co-movement patterns (Table 5):
  - High spillover risk (countercyclical domestic/external contributions): U.K., U.S., Canada, Spain, Portugal, Greece.
  - Export-driven growth pattern (positive external contribution correlation with GDP): Germany, Japan, Austria, Finland.
  - Less pronounced patterns: Netherlands, Sweden, France, Belgium.
- Statistical relationships:
  - Regressing outward spillover on a constant, log size, and correlation between GDP growth and external contribution: increasing size of the country by 10 percent increases outward spillover by 0.1 percentage points; reducing the correlation of external demand and GDP growth from +0.5 to -0.5 increases outward spillovers by 0.14 percentage points.
  - The relationship holds when excluding the crisis dummy.
  - Presence of outliers: Canada and Spain have larger spillovers than predicted by size alone; Germany has smaller spillovers than expected by size alone.

### Conclusion and policy-relevant implications
- Growth spillovers explain a significant fraction of output growth variation for some euro area members, especially small open economies.
- The U.S. remains the key source of growth spillovers in the recovery considered.
- Germany’s impact remains primarily contained to its smaller neighbors; France and Italy matter more for southern peripheral countries.
- Japan and Spain are significant sources of potential growth spillover risk to European countries; Spain’s positive long-run impact could be lower in future episodes if unwinding of imbalances durably undermines growth prospects.
- Trade channels matter relatively less than financial and other non-trade channels for inward spillovers to euro area members; Germany relies relatively more on trade effects.
- Growth shocks from outside the EMU are transmitted to a relatively larger extent via trade than shocks originating within the EMU.
- Germany does not appear to have become a more important independent source of growth shocks in recent years; it is more sensitive to external shocks and may function as a “third country” transmitter.
- Growth spillover risks from European crisis countries to the rest of Europe remain limited in the sample, but stronger effects could occur if the debt crisis spreads to larger countries such as Spain.
- Caveats and future research directions:
  - Analysis is limited to the sampled countries; role for other countries not inferred.
  - Analysis is backward-looking and does not capture time-varying relationships.
  - Approach does not distinguish supply versus demand sources of shocks.
  - Further exploration of financial transmission channels is warranted given larger spillover estimates and third-country effects during financial distress.

*Italic: Extracted from source content of the provided IMF working paper excerpt.*

### References

### _wp11218 - References

### References cited
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- Arora, Vivek and Athanasios Vamvakidis, 2010, “China’s Economic Growth: International Spillovers?” IMF Working Paper WP/10/165, International Monetary Fund.
- Bagliano, Fabio C. and Claudio Morana, 2011, “The Great Recession: U.S. Dynamics and Spillovers to the World Economy,” Journal of Banking and Finance, forthcoming.
- Banbura, Marta, Domenico Giannone and Lucrezia Reichlin, 2008, "Large Bayesian VARs," Working Paper Series 966, European Central Bank.
- Bayoumi, Tam and Andrew Swiston, 2009, “Foreign Entanglements: Estimating the Source and Size of Spillovers Across Industrial Countries,” IMF Staff Papers, Vol, 56 (2), 353-383.
- Bénassy-Quéré, Agnès and Jacopo Cimadomo, 2006, “Changing Patterns of Domestic and Cross-Border Fiscal Policy Multipliers in Europe and the U.S.” CEPII No. 2006 – 24 December.
- Beetsma, Roel, Massimo Giuliodori, and Franc Klaasen, 2005, “Trade Spillovers of Fiscal Policy in the European Union: A Panel Analysis,” DNB Working Paper No. 52, De Nederlandsche Bank.
- Bussière, Matthieu, Alexander Chudik and Giulia Sestieri, 2009, "Modelling Global Trade Flows - Results from a GVAR Model," Working Paper Series 1087, European Central Bank.
- Canova, Fabio and Matteo Ciccarelli, 2006, “Estimating Multi-Country VAR Models” Working Paper Series 603, European Central Bank.
- Danninger Stephan, 2008, “Growth Linkages within Europe“, in IMF Country Report No. 08/81, Germany: Selected Issues, International Monetary Fund.
- Dees, Stephane, Filippo di Mauro, L. Vanessa Smith and M. Hashem Pesaran, 2007, "Exploring the international linkages of the euro area: a global VAR analysis," Journal of Applied Econometrics, vol. 22(1), pages 1-38.
- Galesi, Alessandro and Silvia Sgherri, 2009, "Regional Financial Spillovers Across Europe: A Global VAR Analysis," IMF Working Papers 09/23, International Monetary Fund.
- Helbling, Thomas, Peter Berezin, Ayhan Kose, Michael Kumhof, Doug Laxton, and Nicola Spatafora, 2007, “Decoupling the Train: Spillovers and Cycles in the World Economy,” Chapter 4 in World Economic Outlook, April 2007, International Monetary Fund.
- Imbs, Jean, Haroon Mumtaz, Morten O. Ravn, Hélène Rey, 2005, ”PPP Strikes Back: Aggregation and the Real Exchange Rate” The Quarterly Journal of Economics Vol. 120, No. 1 (Feb., 2005), pp. 1-43, Oxford University Press.
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- Rudebusch, Glenn D., 2005, “Assessing the Lucas Critique in monetary policy models”, Journal of Money, Credit, and Banking 37, 245-272.
- Vitek, Francis, 2009, "Monetary Policy Analysis and Forecasting in the World Economy: A Panel Unobserved Components Approach," IMF Working Paper WP/09/238, International Monetary Fund.
- Vitek, Francis, 2010, "Monetary Policy Analysis and Forecasting in the Group of Twenty: A Panel Unobserved Components Approach," IMF Working Paper WP/10/152, International Monetary Fund.

### Appendix — Ordering of spillovers between countries
- The appendix lists alternative country ordering strings described as "in order of independence from other regions".
- Example orderings (each line is an ordering string as provided):
  - DEUJPNUSAFRAUKESPITA CAN NLDBELSWEAUT CHEGRCPRTFINIRL
  - DEUJPNUSAFRAITAESPUK CAN NLDBELSWEAUT CHEGRCPRTFINIRL
  - DEUJPNUSAUKFRAESPITA CAN NLDBELSWEAUT CHEGRCPRTFINIRL
  - DEUJPNUSAUKITAESPFRA CAN NLDBELSWEAUT CHEGRCPRTFINIRL
  - DEUJPNUSAFRAJPN... (multiple permutations follow in the source; each ordering string is preserved as given)

### Appendix — Responses to a 1 percent growth shock (country-level impulse responses)
- The document presents repeated response templates for a "Response to a 1 percent growth shock" originating in individual countries. Each template includes the numeric vector and country labels as shown below.
- Numeric axis/tick values (preserved exactly):
  - -0.4
  - 0.1
  - 0.6
  - 1.1
  - 1.6
  - 12345678
- For each shock origin (examples shown in the source), the country-specific rows repeat the numeric axis and country label. The presented origin countries in the source include:
  - USA
  - Japan
  - UK
  - Germany
  - France
  - Italy
  - Spain
- For each origin the following recipient country labels appear (each repeated with the same numeric axis):
  - DEU
  - FRA
  - ITA
  - ESP
  - NLD
  - BEL
  - AUT
  - GRC
  - PRT
  - FIN
  - IRL
  - USA
  - JPN
  - UK
  - CAN
  - SW E
  - CHE
- Specific additional numeric row for IRL in each template:
  - -0.2
  - 0.3
  - 0.8
  - 1.3
  - 1.8
  - 12345678
- Labels accompanying the IRF panels (preserved exactly):
  - IRF
  - Counterf actual IRF
  - Ordering uncertainty
  - Parameter  uncertainty

*Source: _wp11218 - References*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2011/_wp11218.pdf_