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---

### Definitions and measurement
- Fiscal multipliers = ratio of a change in output (ΔY) to a discretionary change in government spending or tax revenue (ΔG or ΔT).
- The fiscal multiplier measures the effect of a $1 change in spending or a $1 change in tax revenue on the level of GDP.
- Two expenditure-focused multipliers:
  - Impact multiplier = (ΔY(t))/(ΔG(t))
  - Multiplier at horizon i = (ΔY(t+i))/(ΔG(t))
  - Note: t can be a quarter or a year depending on data frequency.

### Types of multipliers
- “Overall” multiplier: output response to an unspecified fiscal shock.
- “Revenue” (“spending”) multiplier: output response to a discretionary change in revenue (spending).

### Data and estimation constraints
- SVAR and DSGE methods demand high-frequency data and long time series.
- Long quarterly series do not exist in many AEs, most EMEs, and LICs.

### Key empirical findings (normal times / literature averages)
- DSGE simulations and SVAR models (since early 1990s) suggest first-year multipliers generally lie between 0 and 1 in “normal times.”
- Spending multipliers tend to be larger than revenue multipliers.
- Mineshima and others (2014) literature survey (41 studies) — first-year averages in AEs:
  - 0.75 for government spending
  - 0.25 for government revenues
- Baseline “normal times” composition assumption for AEs:
  - 0.75 weight on government spending and 0.25 weight on government revenues.
- Assuming two thirds of the adjustment falls on expenditure measures, overall “normal times” multiplier ≈ 0.6.
- Model- and econometric-based typical first-year multiplier ranges (normal times):
  - Low multiplier: 0.1–0.3
  - Medium multiplier: 0.4–0.6
  - High multiplier: 0.7–1.0
- Literature-average second-year multiplier is, on average, 10–30 percent higher than the first-year multiplier.
- Output effects of exogenous fiscal shocks generally vanish within five years even for permanent measures; maximum typically in the second year.

### Narrative approach — selected first-year multipliers (response of output in percent following an exogenous 1 percent of GDP tax or spending shock)
- Selected narrative first-year tax multipliers:
  - Cloyne (2013), United Kingdom: 0.6 (Maximum multiplier reached after 10 quarters (about 2.5))
  - Favero and Giavazzi (2012), United States: 0.7 (Maximum multiplier reached after 9 quarters (just below 1))
  - Guajardo and others (2014), Panel of OECD Countries: 1 (After two years, multiplier reaches about 3.)
  - Hayo and Uhl (2014), Germany: 1 (Maximum multiplier after 8 quarters (about 2.4).)
  - Mertens and Ravn (2013), United States: 1 (Maximum multiplier reached after 8 quarters (about 2))
  - Romer and Romer (2010), United States: 1.2 (Maximum multiplier reached after 10 quarters (around 3))
- Selected narrative first-year spending multipliers:
  - Barro and Redlick (2011): 0.4–0.6 (U.S. defense spending news; 1917–2006; lower multiplier for temporary spending changes, higher end for permanent)
  - Guajardo and others (2014): 0.3 (Overall spending shock. After two years, multiplier reaches about 1.)
  - Hall (2009): 0.6 (U.S. defense spending news; 1930–2008)
  - Owyang, Ramey, Zubairy (2013): United States: 0.8; Canada: 0.4–1.6 (U.S. defense spending news; two-year multipliers; Canada range reflects low and high unemployment regimes)
  - Ramey (2011): 1.1–1.2 (U.S. defense spending news; 1939–2008; peak multiplier after 6 quarters)

### Multipliers in EMEs and LICs
- Empirical literature suggests multipliers in EMEs and LICs are smaller than in AEs.
- Some studies find negative multipliers in the longer term or when public debt is high.
- Ilzetzki (2011) EME short-term ranges:
  - Spending multipliers: 0.1 to 0.3
  - Revenue multipliers: 0.2 to 0.4
- Factors potentially increasing multipliers in EMEs/LICs:
  - Less consumption smoothing when liquidity constraints exist; agents less forward looking.
  - Lower automatic stabilizers.
  - Lower government debt (more room for credibility/confidence effects).
- Factors potentially decreasing multipliers in EMEs/LICs:
  - Monetary policy response less effective.
  - Inefficiencies in public expenditure management and revenue administration.
  - Supply constraints that sustain positive output gaps.
  - Economies are smaller and more open (higher leakage).

### Determinants of multiplier size
- Structural characteristics (affect “normal times” multipliers):
  - Trade openness: Lower propensity to import → higher multiplier.
  - Labor market rigidity: More rigid labor markets → larger multiplier if reduced wage flexibility amplifies output response.
  - Size of automatic stabilizers: Larger stabilizers → smaller multiplier.
  - Exchange rate regime: Flexible regimes → smaller multipliers.
  - Debt level: High-debt countries → lower multipliers.
  - Public expenditure management and revenue administration: Inefficiencies → smaller multipliers.
- Conjunctural factors:
  - State of the business cycle: Multipliers larger in downturns than in expansions.
  - Degree of monetary accommodation: At the zero lower bound (ZLB) spending multipliers can be substantially larger. Examples:
    - Christiano and others (2011): No ZLB 1.1; ZLB 3.7 (impact multiplier for temporary increase in spending in the United States)
    - Eggertson (2010): No ZLB 0.5; ZLB 2.3
    - Erceg and Linde (2010): No ZLB 1; ZLB 4 (ZLB multiplier of 4 based on temporary spending increase of 1 percent of GDP and ZLB duration of 8 quarters)

### Persistence and dynamics
- Persistence depends on:
  - Persistence of the fiscal shock (temporary vs permanent).
  - Type of fiscal instrument: permanent public investment or corporate tax changes can have longer-lasting or permanent effects; indirect taxes, government consumption, and transfers typically vanish within five years.
  - Cyclical position: shocks in recessions may have more persistent effects due to hysteresis or credit constraints.
  - Monetary policy response: multipliers more persistent if monetary policy does not offset fiscal shocks.

### The bucket approach — rule-of-thumb first-year multiplier estimates
- Core idea: group countries into three buckets based on structural characteristics; score value 1 if characteristic present.
- Scoring criteria (assign value 1 if characteristic present):
  - Low trade openness: imports/domestic demand < 30 percent (average over past five years).
  - High labor market rigidities: labor market rigidity measures 0.8–1 in indices from 0-weak to 1-strong.
  - Small automatic stabilizers: public spending/nominal GDP below 0.40.
  - Fixed or quasi-fixed exchange rate regime.
  - Low/safe public debt level: threshold for AEs = 100 percent of GDP; for EMEs = 40 percent of GDP.
  - Effective public expenditure management and revenue administration.
- Bucket assignment by total score:
  - Total scores 0 to 3: Low multipliers (0.1–0.3)
  - Total scores 3 or 4: Medium multipliers (0.4–0.6)
  - Total scores 4 to 6: High multipliers (0.7–1.0)
  - Countries with totals of 3 or 4 can be flexibly assigned using judgment.
- Conjunctural scaling adjustments (multiplicative):
  - Cycle adjustment (Cycle): range from −0.4 to +0.6
    - If economy at lowest historical point, increase both bounds by 60 percent (+0.6).
    - If at peak, decrease both bounds by 40 percent (−0.4).
  - Monetary policy stance adjustment (Mon): range from 0 to 0.3
    - If monetary policy at effective lower bound and fully constrained, increase both bounds by 30 percent (+0.3).
  - Multiplicative formula: M = MNT * (1+Cycle) * (1+Mon)
    - M = final multiplier estimate
    - MNT = “normal times” multiplier from bucket
    - Cycle ranges from −0.4 to +0.6
    - Mon ranges from 0 to 0.3
- Under combined scenarios, first-year multipliers may vary from about 0 to 2.

### Bucket illustration — United States (example)
- Structural characteristic scores:
  - Relatively Closed: 1
  - Rigid Labor Markets: 0
  - Small Automatic Stabilizers: 1
  - Fixed Exchange Rate Regime: 0
  - Safe Government Debt: 1
  - Effective Expenditure/Revenue Management: 1
  - Total Score: 4
- Bucket-derived ranges and scaled results (assumes negative output gap; adjustments +0.3 cycle and +0.1 monetary):
  - Medium (0.4–0.6) → after scaling: 0.6–0.9
  - High (0.7–1.0) → after scaling: 1.0–1.4

### Practical implementation: incorporating multipliers into macro projections
- Practical approach: build a separate excel template to “impact” a baseline growth projection using estimated fiscal shocks and fiscal multiplier estimates.
- Implementation guidance:
  - Impact baseline GDP projection (which excludes fiscal shocks) by adding effects of planned discretionary fiscal measures and lagged effects of past measures.
  - Planned discretionary measures can be proxied by change in structural primary balance (percent of potential GDP) or, preferably, direct estimates from budget documents.
- Advantages of multiplier-based template:
  - Relatively easy to implement across countries.
  - Transparent and controls explicitly for different shocks.
  - Can incorporate composition of adjustment packages, cyclical effects, and structural features.
  - Addresses circularity between fiscal and output variables by using reduced-form multiplier estimates.
- Caveat: multiplier-based approach is one of several methods and can be used alongside other approaches.

### Box 2 — Alternative methods to assess the impact of fiscal policy on output
- Full-fledged model:
  - Macroeconomic models require large resources and data, rarely available in many countries.
- Demand-side approach:
  - GDP = government and private consumption + government and private investment + net exports.
  - Direct “accounting” effect of changes in government consumption and investment; effects on private demand and net exports must be estimated for completeness.
  - Absent second-round effects, implicit multipliers: 1 for spending measures, 0 for revenue measures, and between 0 and 1 for a mix.
- Empirical (SVAR, narrative) vs model-based (DSGE, GIMF):
  - SVAR shortcomings: may not capture purely exogenous fiscal shocks; generally linear; state-contingent multipliers may be missed.
  - Narrative approaches identify exogenous shocks directly from budget documents or news; can be combined with SVARs.
  - DSGE challenges: parameter sensitivity; many models linearized; no generally accepted fiscal rule analogous to Taylor rule.
- Practical template design tips:
  - Flexibility to simulate scenarios; project 5 to 10 years to capture persistence.
  - Baseline GDP should be a “no policy” scenario.
  - Prefer direct estimates of fiscal measures; otherwise proxy with change in cyclically adjusted primary balance.
  - Account for overlapping effects of past shocks; allow multipliers to vary over the cycle; incorporate risk-premium and hysteresis effects; include debt dynamics.
  - Use sensitivity analysis and fan charts to reflect uncertainty.

### Illustration and evidence by instrument and country (select entries)
- Model-implied hierarchy (short-term multipliers):
  - On spending side: investment highest short-term multiplier > government wages > government purchases > untargeted transfers (lowest).
  - On revenue side: corporate income taxes and personal income taxes have the most negative effects on GDP; consumption taxes perform relatively better.
  - Property taxes appear most growth-friendly (OECD 2009; OECD 2010; EC 2010).
- Select empirical/model-based short-term (impact/first-year) evidence:
  - Mertens and Ravn (2013), USA: PIT 1; CIT 1.4; VAT 1.8; GC 0.4; GI 0.6; Impact 3–4 quarters.
  - Perotti (2004), multiple countries: PIT 1.4; CIT 0.8; VAT 0.6; GC 0.6; GI 0.6.
  - Ilzetzki and others (2013), panel: Advanced G 0.4; Developing G 0.
  - China (Wang and Wen (2013)): GT 1.7/2.8.
  - MENAP (IMF (2014)): GT 1.1/0.9 (Oil Importers/Exporters).
  - Malaysia (Rafiq and Zeufack (2012)): GT *2.7 / 2 ; 0.1/0.2 (Peak multiplier; downturn/upturn).
  - Panel LICs (Kraay (2012)): G 0.5 (public investment only; not statistically significant).
  - Panel EMs (Ilzetzki (2011)): G 0.2 (panel, 17 EMs).
  - Model-based (examples): Bangladesh: G 0.4; T 0.8; G*T 0.1. China: G 0.3; G*T 1.6; T 0.4. Mexico: G 0.7; T 0.2. Poland: G 0.6; T 0.2. Emerging Asia (GIMF): G 1.0; T 0.5.

*Source: Technical Notes and Manuals 14/04 (2014), International Monetary Fund.*

### Box 1. Definitions

### Box 1. Definitions

### Definitions and measurement
- Fiscal multipliers are defined as the ratio of a change in output (ΔY) to a discretionary change in government spending or tax revenue (ΔG or ΔT).
- The fiscal multiplier measures the effect of a $1 change in spending or a $1 change in tax revenue on the level of GDP.
- Two commonly used expenditure-focused multipliers:
  - Impact multiplier = (ΔY(t))/(ΔG(t))
  - Multiplier at horizon i = (ΔY(t+i))/(ΔG(t))
  - Note: t can be a quarter or a year depending on the frequency of the data used in the study.

### Types of multipliers
- “Overall” multiplier: output response to an unspecified fiscal shock.
- “Revenue” (“spending”) multiplier: output response to a discretionary change in revenue (spending).

### Data and estimation constraints
- Econometric and model-based methods (for example, SVAR and DSGE) are demanding in terms of data requirements.
- Estimation of structural vector autoregressive models (SVAR) necessitates high-frequency data and sufficiently long time series.
- Long quarterly series do not exist in many advanced economies (AEs), as well as in most emerging market economies (EMEs) and low-income countries (LICs).

### Bucket approach for countries lacking reliable estimates
- For countries where no reliable estimate is available, the note proposes a “guesstimate” method called the “bucket approach.”
- Core idea: group (or “bucket”) countries likely to have similar multiplier values based on their characteristics.
- Secondary use: serve as a cross-check in countries where estimates are already available.

### Incorporating multipliers in macroeconomic projections
- A practical and simple approach: build a separate excel template to “impact” a baseline growth projection using estimated fiscal shocks and fiscal multiplier estimates.

### Organization of the note (as presented)
- Section II: literature review, proposing specific ranges of multipliers in AEs, EMEs and LICs, and identifying the main determinants.
- Section III: derive multipliers with the bucket approach using the ranges and determinants from Section II.
- Section IV: guidance on how to incorporate multipliers in macroeconomic projections.

### Empirical finding cited
- DSGE simulations and SVAR models, developed since the early 1990s, suggest that first-year multipliers generally lie between 0 and 1 in “normal times.”
- This literature finds that spending multipliers tend to be larger than revenue multipliers.
- Based on a survey of 41 such studies, Mineshima and others (2014) show that first-year multipliers amount on average to

*Source: Box 1. Definitions — Technical Notes and Manuals 14/04 | 2014*

### 0.75 for government spending and 0.25 for government revenues in AEs.

### 0.75 for government spending and 0.25 for government revenues in AEs.

### Summary of key empirical findings
- Baseline “normal times” composition assumption: 0.75 weight on government spending and 0.25 weight on government revenues in AEs.
- Assuming two thirds of the adjustment falls on expenditure measures, overall “normal times” multiplier ≈ 0.6.
- Narrative studies challenge standard results: some find tax multipliers as large as, or larger than, spending multipliers.
- Model- and econometric-based typical first-year multiplier ranges (normal times, Table 6):
  - Low multiplier: 0.1–0.3
  - Medium multiplier: 0.4–0.6
  - High multiplier: 0.7–1.0
- Literature-average second-year multiplier is, on average, 10–30 percent higher than the first-year multiplier.

### Narrative vs. traditional (VAR/DSGE) approaches
- Structural VAR may misidentify exogenous fiscal shocks because revenues also respond to asset and commodity price movements.
- Narrative approach: identifies exogenous fiscal shocks directly from budget documents (tax side) or news about future military spending (spending side).
- Selected narrative first-year tax multipliers (response of output in percent following an exogenous tax shock of 1 percent of GDP):
  - Cloyne (2013), United Kingdom: 0.6 (Maximum multiplier reached after 10 quarters (about 2.5))
  - Favero and Giavazzi (2012), United States: 0.7 (Maximum multiplier reached after 9 quarters (just below 1))
  - Guajardo and others (2014), Panel of OECD Countries: 1 (After two years, multiplier reaches about 3.)
  - Hayo and Uhl (2014), Germany: 1 (Maximum multiplier after 8 quarters (about 2.4).)
  - Mertens and Ravn (2013), United States: 1 (Maximum multiplier reached after 8 quarters (about 2))
  - Romer and Romer (2010), United States: 1.2 (Maximum multiplier reached after 10 quarters (around 3))
- Selected narrative first-year spending multipliers (response of output in percent following an exogenous spending shock of 1 percent of GDP):
  - Barro and Redlick (2011): 0.4–0.6 (U.S. defense spending news; 1917–2006; lower multiplier for temporary spending changes, higher end for permanent)
  - Guajardo and others (2014): 0.3 (Overall spending shock. After two years, multiplier reaches about 1.)
  - Hall (2009): 0.6 (U.S. defense spending news; 1930–2008)
  - Owyang, Ramey, Zubairy (2013): United States: 0.8; Canada: 0.4–1.6 (U.S. defense spending news; two-year multipliers; Canada range reflects low and high unemployment regimes)
  - Ramey (2011): 1.1–1.2 (U.S. defense spending news; 1939–2008; peak multiplier after 6 quarters)

### Multipliers in EMEs and LICs
- Empirical literature suggests multipliers in EMEs and LICs are smaller than in AEs (Estevão and Samake, 2013; Ilzetzki and others, 2013; Ilzetzki, 2011; IMF, 2008; Kraay, 2012).
- Some studies find negative multipliers in the longer term or when public debt is high.
- Ilzetzki (2011) EME short-term ranges:
  - Spending multipliers: 0.1 to 0.3
  - Revenue multipliers: 0.2 to 0.4
- Factors potentially increasing multipliers in EMEs/LICs:
  - Less consumption smoothing when liquidity constraints are present and agents are less forward looking.
  - Lower automatic stabilizers.
  - Lower government debt (more room for credibility/confidence effects).
- Factors potentially decreasing multipliers in EMEs/LICs:
  - Monetary policy response less effective.
  - Inefficiencies in public expenditure management and revenue administration.
  - Supply constraints that sustain positive output gaps.
  - Economies are smaller and more open (higher leakage).

### Determinants of multiplier size
- Structural characteristics that shape “normal times” multipliers:
  - Trade openness: Lower propensity to import → higher multiplier.
  - Labor market rigidity: More rigid labor markets → larger multiplier if reduced wage flexibility amplifies output response.
  - Size of automatic stabilizers: Larger stabilizers → smaller multiplier.
  - Exchange rate regime: Flexible regimes → smaller multipliers.
  - Debt level: High-debt countries → lower multipliers (credibility/confidence effects).
  - Public expenditure management and revenue administration: Inefficiencies → smaller multipliers.
- Conjunctural (temporary) factors:
  - State of the business cycle: Multipliers larger in downturns than in expansions; downturns increase multipliers more than upturns reduce them.
  - Degree of monetary accommodation: At the zero lower bound (ZLB) multipliers for government spending can be substantially larger than in normal times (Table 5 examples):
    - Christiano and others (2011): No ZLB 1.1; ZLB 3.7 (impact multiplier for temporary increase in spending in the United States)
    - Eggertson (2010): No ZLB 0.5; ZLB 2.3
    - Erceg and Linde (2010): No ZLB 1; ZLB 4 (ZLB multiplier of 4 based on temporary spending increase of 1 percent of GDP and ZLB duration of 8 quarters; larger shocks shorten ZLB duration and lower multiplier)

### Persistence and dynamics of multipliers
- Output effects of exogenous fiscal shocks generally vanish within five years even for permanent measures; effects have an inverted U shape with maximum typically in the second year.
- Second-year multipliers typically 10–30 percent higher than first-year multipliers (Mineshima and others (2014) literature review).
- Persistence depends on:
  - Persistence of the fiscal shock (temporary vs permanent).
  - Type of fiscal instrument: permanent changes in public investment or corporate taxes can have longer-lasting or permanent effects; changes in indirect taxes, government consumption, and transfers typically vanish within five years.
  - Cyclical position: shocks in recessions may have more persistent effects due to hysteresis or credit constraints.
  - Monetary policy response: multipliers more persistent if monetary policy does not offset fiscal shocks.

### The bucket approach (back-of-the-envelope)
- Purpose: provide rule-of-thumb first-year multiplier estimates for countries without direct estimates by grouping countries into three buckets based on structural characteristics.
- Scoring (assign value 1 if characteristic present):
  - Low trade openness: imports/domestic demand < 30 percent (average over past five years).
  - High labor market rigidities: labor market rigidity measures 0.8–1 in indices from 0-weak to 1-strong.
  - Small automatic stabilizers: public spending/nominal GDP below 0.40.
  - Fixed or quasi-fixed exchange rate regime.
  - Low/safe public debt level: threshold for AEs = 100 percent of GDP; for EMEs = 40 percent of GDP.
  - Effective public expenditure management and revenue administration.
- Bucket assignment by total score:
  - Total scores 0 to 3: Low multipliers (0.1–0.3)
  - Total scores 3 or 4: Medium multipliers (0.4–0.6)
  - Total scores 4 to 6: High multipliers (0.7–1.0)
  - Countries with totals of 3 or 4 can be flexibly assigned using judgment.
- Conjunctural scaling adjustments (multiplicative):
  - Cycle adjustment (Cycle): range from −0.4 to +0.6
    - If economy at lowest historical point, increase both bounds by 60 percent (+0.6).
    - If at peak, decrease both bounds by 40 percent (−0.4).
  - Monetary policy stance adjustment (Mon): range from 0 to 0.3
    - If monetary policy at effective lower bound and fully constrained, increase both bounds by 30 percent (+0.3).
  - Multiplicative formula: M = MNT * (1+Cycle) * (1+Mon)
    - M = final multiplier estimate
    - MNT = “normal times” multiplier from bucket
    - Cycle ranges from −0.4 to +0.6
    - Mon ranges from 0 to 0.3
- Under combined scenarios, first-year multipliers may vary from about 0 to 2.
- Illustration for the United States (example scoring and scaling):
  - Structural characteristic scores:
    - Relatively Closed: 1
    - Rigid Labor Markets: 0
    - Small Automatic Stabilizers: 1
    - Fixed Exchange Rate Regime: 0
    - Safe Government Debt: 1
    - Effective Expenditure/Revenue Management: 1
    - Total Score: 4
  - Bucket-derived ranges and scaled results (assumes negative output gap; adjustments +0.3 cycle and +0.1 monetary):
    - Medium (0.4–0.6) → after scaling: 0.6–0.9
    - High (0.7–1.0) → after scaling: 1.0–1.4

### Practical implementation: incorporating multipliers into macro projections
- Practical approach: “impact” a baseline GDP projection (which excludes fiscal shocks) by adding effects of planned discretionary fiscal measures and lagged effects of past measures.
- Planned discretionary measures can be proxied by change in structural primary balance (percent of potential GDP) or, preferably, direct estimates from budget documents.
- Advantages of multiplier-based template:
  - Relatively easy to implement across countries.
  - Transparent and controls explicitly for different shocks.
  - Can incorporate composition of adjustment packages, cyclical effects, and structural features.
  - Addresses circularity between fiscal and output variables by using reduced-form multiplier estimates.
- Caveat: multiplier-based approach is one of several methods and can be used alongside other approaches.

*Source: Technical Notes and Manuals 14/04 (2014), International Monetary Fund.*

### Box 2: Alternative Methods to Assess the Impact of Fiscal Policy on Output

### Box 2: Alternative Methods to Assess the Impact of Fiscal Policy on Output

### Alternative methods to link fiscal policy and output
- Full-fledged model
  - Macroeconomic models can be used to analyze the effects of fiscal and other policies on output.
  - This approach requires a large amount of resources and data, rarely available in many countries.
- Demand-side approach
  - GDP = government and private consumption + government and private investment + net exports.
  - Requires assessment of the effects of fiscal measures on all GDP components.
  - Changes in government consumption and investment have a direct “accounting” effect on GDP.
  - Effects on private demand and net exports must be estimated to provide a comprehensive assessment.
  - Can provide a more detailed assessment than multipliers but may give incorrect overall estimates because second-round effects are difficult to quantify.
  - Absent second-round effects, the demand-side approach would produce an implicit multiplier of 1 for spending measures, 0 for revenue measures, and between 0 and 1 for a mix.

### Tips to design a fiscal multiplier template
- Purpose
  - Combine estimates of fiscal multipliers, fiscal shocks and a baseline GDP projection to produce a projected GDP path incorporating fiscal shocks.
  - Assess consistency of GDP projections with assumed fiscal consolidation path.
- Desirable features
  - Flexibility to simulate alternative scenarios and easily change assumptions on the size and persistence of multipliers.
  - Projections over a reasonably long period (say, 5 to 10 years) to factor in persistence of fiscal shock effects.
  - Baseline GDP should be a “no policy” scenario (not already include fiscal shocks, including lagged effects). Potential output estimates or an HP filter can be used; sensitivity analysis to alternative measures is recommended.
  - Fiscal shocks: direct estimates of fiscal measures preferred (possibly off-budget). Otherwise, proxy with the change in the cyclically adjusted primary balance. The cyclically adjusted primary balance is preferable to the structural balance, which excludes one-off factors that may also have output effects.
  - Account for overlapping effects of past fiscal shocks given persistence of multiplier effects (projected GDP in year t should include lagged effects from prior-year shocks and first-year effects of current-year shocks).
  - Allow multiplier to vary endogenously over the cycle, with higher multipliers in downturns than in expansions.
  - Allow the risk premium of the interest rate to vary endogenously with the size of the fiscal shock and the evolution of fiscal variables.
  - Incorporate hysteresis effects either by assuming multipliers do not decline over time or by assuming each percentage point of the (lagged) output gap reduces the growth rate of potential GDP (De Long and Summers (2012) approach).
  - Include resulting debt dynamics as a function of the fiscal shock, the multiplier, and the initial debt level (Eyraud and Weber, 2013).
- Use and limitations
  - Adjusting the baseline for fiscal shocks does not necessarily produce a reliable GDP forecast unless growth is mainly driven by fiscal shocks; other factors (financial conditions, monetary policy, global activity) also matter.
  - Template should complement standard projection methods.
  - Perform sensitivity analysis and produce a fan chart across a range of multiplier estimates to reflect uncertainty.

### Illustration: overlapping effects (Table 9)
- Assumption for illustration
  - Repeated negative fiscal shock of 1 unit in 2015–2018 (e.g., $1 cut in spending).
  - Maximum multiplier of 1 in year 2 that gradually declines to 0 in year 5.
- Effect on output level (relative to baseline) by year (as shown in Table 9)
  - Row "Effect on output level 2015": 2015 -0.8 -1 -0.6 -0.3 ......... (shows negative impacts starting in 2015)
  - Row "Effect on output level 2016": 2016 ... -0.8 -1 -0.6 -0.3 ...... 
  - Row "Effect on output level 2017": 2017 ...... -0.8 -1 -0.6 -0.3...
  - Row "Effect on output level 2018": 2018 ......... -0.8 -1 -0.6 -0.3
  - Total Impact on Output (relative to baseline) by year: -0.8 -1.8 -2.4 -2.7 -1.9 -0.9 -0.3

### Empirical versus model-based multiplier estimation
- Empirical estimations (SVAR, narrative)
  - SVAR models use structural identification to extract fiscal shocks and estimate impacts on GDP.
  - Shortcomings of SVARs:
    - May fail to capture purely exogenous fiscal shocks (e.g., do not filter out asset and commodity price movements).
    - Provide average responses based on past information; may not be accurate if the economy underwent major structural change.
    - Generally linear and may not capture state-contingent multipliers.
  - Narrative (action-based) approaches use direct estimates of fiscal measures from government documents to identify exogenous shocks; can be combined with SVARs.
  - Non-linear SVARs have been used to examine state dependence (Auerbach and Gorodnichenko, 2012a and 2012b; Batini and others, 2012; Baum and others, 2012).
- Model-based estimations (DSGE, GIMF)
  - DSGE models analyze the economy’s microeconomic interactions and can reflect unusual conditions (e.g., zero lower bound, many credit-constrained agents).
  - Challenges of DSGE models:
    - No generally accepted fiscal rule analogous to the Taylor rule for monetary policy.
    - Many DSGE models are linearized, ruling out state-dependent multipliers.
    - Results sensitive to parameter choices (degree of price and wage rigidities, habit persistence, investment adjustment cost, proportion of liquidity-constrained agents).
    - Calibration choices influence dispersion; using same model across countries yields less dispersion than empirical studies.
- Rule of thumb for choosing estimates
  - Empirical studies (long-period estimations) useful for “average” or “normal” circumstances (small output gap, interest rates not at zero lower bound), with narrative approaches often higher-quality.
  - If current circumstances differ from historical estimation periods, model-based multipliers may be more useful.

### Practical difficulties with the narrative approach
- Fiscal measures assessed against "unchanged policy" benchmark which is not always clearly defined (e.g., freezing wages may be tightening or expansionary depending on context).
- Measures announced for the future and then reversed can result in registering two or zero measures depending on baseline inclusion.
- Methodology to quantify effects may lack transparency and can be incorrect; influenced by data availability and political decisions; yield of administrative measures is hard to assess.
- Conflicting evidence from official sources may require a “consensus estimate” of fiscal shock sizes.

### Multipliers by instrument and evidence on expansionary consolidations
- Model-implied hierarchy (DSGE, Commission, Forni and others)
  - On spending side: investment highest short-term multiplier > government wages > government purchases > untargeted transfers (lowest).
  - On revenue side: corporate income taxes and personal income taxes have the most negative effects on GDP; consumption taxes perform relatively better.
  - Note: Property taxes seem to be the most growth-friendly instrument (OECD 2009; OECD 2010; EC 2010).
- Empirical evidence differences
  - Some empirical studies suggest labor income taxes may have larger multipliers than corporate income taxes.
  - Increases in consumption taxes associated with sizeable short-term output losses in some studies.
  - No clear evidence that government investment yields larger multipliers than government consumption in advanced economies (Perotti, 2004).
  - In emerging economies, Ilzetzki and others (2013) find government investment associated with positive multipliers, while discretionary changes in government consumption may not have significant effects.
- Can fiscal consolidations be expansionary?
  - Earlier literature argued that expenditure-based consolidations could be expansionary via confidence effects (Giavazzi and Pagano, 1990; Alesina and Perotti, 1996; Alesina and Ardagna, 1998, 2010).
  - Recent research finds earlier findings sensitive to the definition of fiscal consolidation (Jordà and Taylor, 2013; Guajardo and others, 2014).
  - Famous expansionary episodes in Europe in the 1980s and 1990s were likely driven by external demand rather than internal private demand from confidence (Perotti, 2012).
  - Evidence does not indicate confidence effects played a major role in the Great Recession and its aftermath.

### Select empirical and model-based multiplier evidence (short-term / first-year / impact multipliers)
- Empirical studies (short-run multipliers by instrument; selected entries from Table A.2.1 and A.3.1)
  - Mertens and Ravn (2013), USA: PIT 1; CIT 1.4; VAT 1.8; GC 0.4; GI 0.6; Impact 3–4 quarters; Impact of 1 percentage point cut in average tax rate on real GDP per capita.
  - Riera-Chrichton and others (2012), panel of 14 industrial countries: VAT 1; Impact 3 quarters.
  - Perotti (2004), USA/DEU/GBR/CAN/AUS and Advanced/Developing: various values including PIT 1.4; CIT 0.8; VAT 0.6; GC 0.6; GI 0.6; Details shown as 4 quarters in multiple entries.
  - Ilzetzki and others (2013), panel of countries: Advanced/Developing: G 0.4 for Advanced; G 0 for Developing; Overall panel values reported include 0.4, 0.6; SVAR; panel; quarterly data; unbalanced panel of 44 countries.
- Short-term multipliers in EMEs/LICs (selected entries from Table A.3.1)
  - China (Wang and Wen (2013)): GT 1.7/2.8 (N/A Consumption multiplier)
  - MENAP (IMF (2014)): GT 1.1/0.9 (N/A Oil Importers/Exporters)
  - Malaysia (Rafiq and Zeufack (2012)): GT *2.7 / 2 ; 0.1/0.2 (Peak multiplier; downturn/upturn)
  - Panel LICs (Kraay (2012)): G 0.5 (N/A Public investment only; 29 aid-dependent low-income countries. Multiplier not statistically significant.)
  - Panel EMs (Ilzetzki (2011)): G 0.2 (panel, 17 Ems)
- Model-based short-term (impact) multipliers in EMEs and LICs (selected entries from Table A.3.2)
  - OECD (2009) / GIMF / IMF internal calculations and others report impact-year multipliers such as:
    - Bangladesh: G 0.4; T 0.8; G*T 0.1
    - China: G 0.3; G*T 1.6; T 0.4
    - Mexico: G 0.7; T 0.2
    - Poland: G 0.6; T 0.2
    - Emerging Asia (Freedman and others (2009) based on GIMF): G 1.0; T 0.5
  - Note: Short-term refers to impact multipliers, which in DSGE models typically correspond to the first year.

*Source: Box 2, Technical Notes and Manuals 14/04 | 2014.*

### References

### References

### Fiscal multipliers and fiscal policy (overview and measurement)
- Alesina, A., and R. Perotti, 1996, “Fiscal Adjustments in OECD Countries: Composition and Macroeconomic Effects,” NBER Working Papers 5730 (Cambridge: National Bureau of Economic Research).
- Alesina, A., and S. Ardagna, 1998, “Tales of Fiscal Adjustment,” Economic Policy, Vol. 13, No. 27, pp. 487–545.
- Alesina, A., and S. Ardagna, 2010, “Large Changes in Fiscal Policy: Taxes Versus Spending,” Tax Policy and the Economy, Vol. 24, pp. 35–68.
- Auerbach, A.J., and Y. Gorodnichenko, 2012a, “Measuring the Output Responses to Fiscal Policy,” American Economic Journal: Economic Policy, Vol. 4, pp. 1–27.
- Auerbach, A.J., and Y. Gorodnichenko, 2012b, “Fiscal Multipliers in Recession and Expansion,” in Fiscal Policy after the Financial Crisis, ed. by A. Alesina and F. Giavazzi (Chigago: University of Chicago Press).
- Auerbach, A.J., and Y. Gorodnichenko, 2013, “Output Spillovers from Fiscal Policy,” American Economic Review, Vol. 103, No. 3, pp. 141–6.
- Auerbach, A.J., and Y. Gorodnichenko, 2014, “Fiscal Multipliers in Japan,” NBER Working Paper w19911 (Cambridge: National Bureau of Economic Research).
- Barrell, R., D. Holland, and I. Hurst, 2012, “Fiscal Consolidation: Part 2. Fiscal Multipliers and Fiscal Consolidations,” OECD Economics Department Working Paper No. 933 (Paris: Organisation for Economic Co-operation and Development).
- Batini, N., G. Callegari, and G. Melina, 2012, “Successful Austerity in the United States, Europe and Japan,” IMF Working Paper 12/190 (Washington: International Monetary Fund).
- Batini, N., L. Eyraud, and A. Weber, 2014, “A Simple Method to Compute Fiscal Multipliers,” IMF Working Paper 14/93 (Washington: International Monetary Fund).
- Baum, A., M. Poplawski-Ribeiro and A. Weber, 2012, “Fiscal Multipliers and the State of the Economy,” IMF Working Paper 12/286 (Washington: International Monetary Fund).
- Blanchard, O., and R. Perotti, 2002, “An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output,” Quarterly Journal of Economics, Vol. 117, pp. 1329–68.
- Blanchard, O., and D. Leigh, 2013, “Growth Forecast Errors and Fiscal Multipliers,” American Economic Review, Vol. 103, No. 3, pp. 117–20.
- Christiano, L., M. Eichenbaum, and S. Rebelo, 2011, “When is the Government Spending-Multiplier Large?” Journal of Political Economy, Vol. 119, No. 1, pp. 78–121.
- Coenen, G., et al., 2012, “Effects of Fiscal Stimulus in Structural Models,” American Economic Journal: Macroeconomics, Vol. 4, No. 1, pp. 22–68.
- Corsetti, G., A. Meier, and G.J. Müller, 2012, “What Determines Government Spending Multipliers?” IMF Working Paper 12/150 (Washington: International Monetary Fund).
- Ilzetzki E., E. G. Mendoza, and C. A. Vegh, 2013, “How Big (Small?) Are Fiscal Multipliers?” Journal of Monetary Economics, Vol. 60, pp. 239–54.
- Spilimbergo, A., S. Symansky, and M. Schindler, 2009, “Fiscal Multipliers,” IMF Staff Position Note 09/11 (Washington: International Monetary Fund).
- Woodford, M., 2011, “Simple Analytics of the Government Expenditure Multiplier,” American Economic Journal: Macroeconomics, Vol. 3, No. 1, pp.1–35.

### Narrative, identification, and econometric approaches to fiscal shocks
- Favero, C., and F. Giavazzi, 2012, “Measuring Tax Multipliers: The Narrative Method in Fiscal VARs,” American Economic Journal: Economic Policy, Vol. 4, No. 2, pp. 69–94.
- Cloyne, J., 2013, “Discretionary Tax Changes and the Macroeconomy: New Narrative Evidence from the United Kingdom,” American Economic Review, Vol. 103, No. 4, pp. 1507–28.
- Ramey, V., 2011, “Identifying Government Spending Shocks: It’s All in The Timing,” Quarterly Journal of Economics, Vol. 126, No. 1, pp. 1–50.
- Mertens, R. and M. O Ravn, 2012, A Reconciliation of SVAR and Narrative Estimates of Tax Multipliers, CEPR Discussion Paper 8973 (London: Center for Economic Policy Research).
- Mertens, R. and M. O Ravn, 2013, “The Dynamic Effects of Personal and Corporate Income Taxes in the United States,” American Economic Review, Vol. 103, pp. 1212–47.
- Riera-Crichton, R., C. Veigh, and G. Vultein, 2012, “Tax Multipliers: Pitfall in Measurement and Identification,” NBER Working Paper No. 18497 (Cambridge: National Bureau of Economic Research).
- Romer, C.D., and D.H. Romer, 2010, “The Macroeconomic Effects of Tax Changes: Estimates Based on a New Measure of Fiscal Shocks,” American Economic Review, Vol. 100, pp. 763–801.
- Romer, C.D., 2011, “What Do We Know About the Effects of Fiscal Policy? Separating Evidence From Ideology,” Hamilton College, November 7, 2011.
- Barro, R. J., and C.J. Redlick, 2011, “Macroeconomic Effects from Government Purchases and Taxes,” Quarterly Journal of Economics, Vol. 126, pp. 51–102.

### Models, simulations, and structural analysis
- Anderson, D., B. Hunt, M. Kortelainen, M. Kumhof, D. Laxton, D. Muir, S. Mursula, and S. Snudden, 2013, “Getting to Know GIMF: The Simulation Properties of the Global Integrated Monetary and Fiscal Model,” IMF Working Paper 13/55 (Washington: International Monetary Fund).
- Canzoneri, M., F. Collard, H. Dellas, and B. Diba, 2012, “Fiscal Multipliers in Recessions,” Discussion Papers, Department of Economics 12-04 (Bern: Universität Bern).
- Christiano, L., M. Eichenbaum, and S. Rebelo, 2011, “When is the Government Spending-Multiplier Large?” Journal of Political Economy, Vol. 119, No. 1, pp. 78–121.
- Forni, L., L. Monteforte, and L. Sessa, 2009, “The General Equilibrium Effects of Fiscal Policy: Estimates for the Euro Area,” Journal of Public Economics, Vol. 93 No. 3–4, pp.559–85.
- Erceg, C. J., and J. Lindé, 2010, “Is There a Free Lunch in a Liquidity Trap?” International Finance Discussion Papers 1003 (Washington: U.S. Federal Reserve System).
- Conway, P. and Orr, A., 2002, “The GIRM: A Global Interest Rate Model,” Westpac Institutional Bank Occasional Paper (Wellington: Westpac Institutional Bank).

### Country studies and regional analyses
- Anós-Casero, P., D. Cardero, and R. Trezzi, 2010, “Estimating the Fiscal Multiplier in Argentina,” World Bank Policy Research Working Paper 5220 (Washington: World Bank).
- Espinoza, R., and A. Senhadji, 2011, “How Strong are Fiscal Multipliers in the GCC? An Empirical Investigation,” IMF Working Paper 11/61 (Washington: International Monetary Fund).
- Gonzales-Garcia, J., A. Lemus, and M. Mrkaic, 2013, “Fiscal Multipliers in the ECCU,” IMF Working Paper 13/117 (Washington: International Monetary Fund).
- Muir, D., and A. Weber, 2013, “Fiscal Multipliers in Bulgaria: Low But Still Relevant,” IMF Working Paper 13/49 (Washington: International Monetary Fund).
- Jooste, C., 2012, “Analyzing the Effects of Fiscal Policy Shocks in the South African Economy,” Department of Economics Working Paper 2012-06 (Pretoria: University of Pretoria).
- Hernández de Cos, P., and Moral-Benito, E., 2013, “Fiscal Multipliers in Turbulent Times: The Case of Spain,” Bank of Spain Working Paper 1309 (Madrid: Bank of Spain).
- Stoian, A., 2012, “The Macroeconomic Effects of Fiscal Policy in Romania,” Presentation. www.finsys.rau.ro/docs/Stoian%20Anca.pdf.
- Tang, H. C., P. Liu, and E. C. Cheung, 2010, “Changing Impact of Fiscal Policy on Selected ASEAN Countries,” ADB Working Paper 70 (Washington: Asian Development Bank).
- Wang, X., and Y. Wen, 2013, “Is Government Spending a Free Lunch? — Evidence from China," Federal Reserve Bank of St. Louis Working Paper Series, Working Paper 2013-013A (St. Louis: U.S. Federal Reserve Bank).
- Rafiq, S., and A. Zeufack, 2012, “Fiscal Multipliers over the Growth Cycle: Evidence from Malaysia,” World Bank Policy Research Working Paper 5982 (Washington: World Bank).
- Ducanes, G., M.A. Cagas, D. Qin, P. Quising, and M.A. Razaque, 2006, “Macroeconomic Effects of Fiscal Policy: Empirical Evidence from Bangladesh, China, Indonesia, and the Philippines,” Queen Mary, University of London Working Paper 564 (London: University of London).

### Automatic stabilizers, debt dynamics, and fiscal consolidation
- Baunsgaard, T. and S. A. Symansky, 2009, “Automatic Stabilizers: How Can They be Enhanced Without Increasing the Size of Government,” IMF Staff Position Note 09/23 (Washington: International Monetary Fund).
- Eyraud, L., and A. Weber, 2012, “Debt Reduction during Fiscal Consolidations: The Role of Fiscal Multipliers,” unpublished paper presented at the IMF surveillance meeting seminar of April 10, 2012.
- Eyraud, L., and A. Weber, 2013, “The Challenge of Debt Reduction During Fiscal Consolidation,” IMF Working Paper 13/67 (Washington: International Monetary Fund).
- Estevão, M and I. Samake, 2013, “The Economic Effects of Fiscal Consolidation with Debt Feedback,” IMF Working Paper 13/136 (Washington: International Monetary Fund).
- Belhocine, N., and S. Dell’Erba, 2013, “The Impact of Debt Sustainability and the Level of Debt on Emerging Markets Spreads,” IMF Working Paper 13/93 (Washington: International Monetary Fund).
- Freedman, C., M. Kumhof, D. Laxton, and J. Lee, 2009, “The Case for Global Fiscal Stimulus,” IMF Staff Position Note 09/03 (Washington: International Monetary Fund).
- Giavazzi, F., and M. Pagano, 1990, “Can Severe Fiscal Contractions Be Expansionary? Tales of Two Small European Countries,” NBER Macroeconomics Annual 1990, Volume 5, pp. 75–122.
- Guajardo J., D. Leigh, and A. Pescatori, 2014, “Expansionary Austerity: International Evidence,” Journal of the European Economic Association (forthcoming).

### Complementary theoretical and empirical contributions
- DeLong, B.J., and L.H. Summers, 2012, “Fiscal Policy in a Depressed Economy,” presented to Brookings Papers on Economic Activity, March 2012.
- Hall, R. E., 2009, “By How Much Does GDP Rise If the Government Buys More Output?” Brookings Papers on Economic Activity, pp. 183–231.
- Mehra, Y., 2001, “The Wealth Effect in Empirical Life-Cycle Aggregate Consumption Equations,” FRB Richmond Economic Quarterly, Vol. 87, No. 2, pp. 45–68.
- Woodford, M., 2011, “Simple Analytics of the Government Expenditure Multiplier,” American Economic Journal: Macroeconomics, Vol. 3, No. 1, pp.1–35.
- Ilzetzki, E., 2011, “Fiscal Policy and Debt Dynamics in Developing Countries,” Policy Research Working Paper Series 5666 (Washington: The World Bank).
- Banerji, R. (Note: entry not present in this references list; included here only if present in the source.)
- Additional contributions on labor regulation, tax changes, exchange rate regimes, and historical episodes are included across the listed works (for example, Botero et al., 2004; Mertens and Ravn; Born, Juessen, and Mueller, 2013; Gorodnichenko, Mendoza, and Tesar, 2012; and others).

*Source: _tnm1404 - References*

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