Fiscal Multipliers
Size, Determinants, and Use in Macroeconomic Projections

Fiscal multipliers are important tools for macroeconomic projections and policy design. In many countries, little is known about the size of multipliers, as data availability limits the scope for empirical research. This note provides general guidance on the definition, measurement, and use of fiscal multipliers. It reviews the literature related to their size, persistence and determinants. For countries where no reliable estimate is available, the note proposes a simple method to come up with reasonable values. Finally, the note presents options to incorporate multipliers in macroeconomic forecasts.

Abstract

Fiscal multipliers are important tools for macroeconomic projections and policy design. In many countries, little is known about the size of multipliers, as data availability limits the scope for empirical research. This note provides general guidance on the definition, measurement, and use of fiscal multipliers. It reviews the literature related to their size, persistence and determinants. For countries where no reliable estimate is available, the note proposes a simple method to come up with reasonable values. Finally, the note presents options to incorporate multipliers in macroeconomic forecasts.

I. Introduction

Fiscal multipliers measure the short-term impact of discretionary fiscal policy on output. They are usually defined as the ratio of a change in output to an exogenous change in the fiscal deficit with respect to their respective baselines (Box 1).1

Better estimation and use of multipliers can play a key role in ensuring macroeconomic forecast accuracy. Many countries experienced a dramatic turnaround in their fiscal position during the crisis, shifting from stimulus to consolidation. In this context of large-scale fiscal actions, GDP growth may be primarily driven by fiscal policy. Thus it is essential to measure accurately the relationship between these two variables in order to plan and forecast the effect of policy actions. For example, Blanchard and Leigh (2013) find that the under-estimation of fiscal multipliers early in the crisis contributed significantly to growth forecast errors.

Definitions

Fiscal multipliers can be measured in several ways. Generally, they are defined as the ratio of a change in output (ΔY) to a discretionary change in government spending or tax revenue (ΔG or ΔT) (Spilimbergo and others, 2009). Thus, 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 multipliers are commonly used (focusing on expenditure):

Impactmultiplier=(ΔY(t))/(ΔG(t))multiplierathorizoni=(ΔY(t+i))/(ΔG(t))

where t can be a quarter or a year depending on the frequency of the data that is used in the study.

The “overall” multiplier describes the output response to an unspecified fiscal shock, while the “revenue” (“spending”) multiplier relates output to a discretionary change in revenue (spending).

Multipliers are also important elements to take into consideration in policy advice and design.2 Underestimating multipliers may lead countries to set unachievable fiscal targets, and miscalculate the amount of adjustment necessary to curb their debt ratio (Eyraud and Weber, 2012, 2013). This could affect the credibility of fiscal consolidation programs. In addition, authorities may engage in repeated rounds of tightening in an effort to make fiscal variables (balance, debt) converge to official targets, undermining confidence; and setting off a vicious circle of slow growth, deflation, and further tightening.

Despite their expected benefits, multipliers are not widely used by economists in operational work. The main reason is that their estimation is tricky. In particular, it is difficult to isolate the direct effect of fiscal measures on GDP, because of the two-way relationships between these variables. Spending and taxes typically react automatically to the business cycle through so-called “automatic stabilizers.” They also respond to the cycle in a discretionary way; for instance a countercyclical policy may raise tax rates and cut spending when the output gap increases. Researchers have tried to address this circularity problem by focusing on the subset of exogenous fiscal shocks.3 However, there is no commonly agreed methodology to identify such shocks or to extract the exogenous component from observed fiscal outcomes (Appendix 1). As a result, there is little consensus in the literature on the size of multipliers.

In addition, data availability limits the scope for estimating multipliers. Econometric and model-based methods are demanding in terms of data requirements. For instance, the 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).

For countries where no reliable estimate is available, this note proposes to “guesstimate” multipliers with a method dubbed the “bucket approach.” The general idea is to bunch countries into groups (or “buckets”) that are likely to have similar multiplier values based on their characteristics. Although it is not its primary purpose, this approach can also be used as a useful cross-check in countries where estimates are already available.

The note also presents options to incorporate multipliers in macroeconomic projections. A practical and simple approach is to build a separate excel template to “impact” a baseline growth projection using estimated fiscal shocks and fiscal multiplier estimates.

The note is organized as follows. Section II reviews the literature, proposing specific ranges of multipliers in AEs, EMEs and LICs, and identifying the main determinants. These ranges and determinants are used in Section III to derive multipliers with the bucket approach. Section IV provides guidance on how to incorporate multipliers in macroeconomic projections.

II. What Do We Know About the Size, Persistence, and Determinants of Fiscal Multipliers?

This section summarizes the main findings of the multiplier literature.

A. Size of Fiscal Multipliers

Advanced economies

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 also finds that spending multipliers tend to be larger than revenue multipliers.4 Based on a survey of 41 such studies, Mineshima and others (2014) show that first-year multipliers amount on average to 0.75 for government spending and 0.25 for government revenues in AEs.5 Assuming, in line with recent fiscal adjustment plans in AEs, that two thirds of the adjustment falls on expenditure measures, this would yield an overall “normal times” multiplier of about 0.6.

However, these standard results have been challenged by the more recent literature. First, a number of studies have shown that multipliers can exceed 1 in “abnormal” circumstances—in particular when the economy is in a severe downturn or if the use and/or the transmission of monetary policy are impaired (see Section II.B). Second, some papers, which use a new “narrative” approach to identify exogenous fiscal shocks, find larger tax multipliers than conventional VAR models do. As shown in Tables 1 and 2, these narrative studies do not support the traditional view that spending multipliers are larger than revenue ones.

Table 1.

Narrative Approach: First-Year Tax Multipliers1

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Response of output in percent following an exogenous tax shock of 1 percent of GDP.

Table 2.

Narrative Approach: First-Year Spending Multipliers1

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Reported estimates correspond to the response of output in percent following an exogenous spending shock of 1 percent of GDP. First year multiplier unless otherwise noted.

The narrative approach constitutes a methodological improvement upon the traditional measurement of fiscal shocks. The structural VAR methodology, which employs output elasticities of expenditure and revenue to filter out automatic stabilizers, may fail to capture exogenous policy changes correctly, because, for example, changes in revenues are not only due to output developments and discretionary policy, but also to asset and commodity price movements (IMF, 2010). The narrative approach instead seeks to identify exogenous fiscal shocks directly. On the tax side, the method uses estimates of fiscal measures extracted from budget documents (Romer and Romer, 2010), while excluding the subset of tax measures taken in response to short-term macroeconomic fluctuations (since these would not be exogenous). On the spending side, some studies have used news about future military spending as a measure of exogenous shocks (e.g., Ramey, 2011). The idea is that military spending is determined by wars and foreign policy developments and not by concerns about the state of the economy (Romer, 2011).

Emerging market economies and low-income countries

Little is known about the size of fiscal multipliers in EMEs and LICs. From a theoretical point of view, it is not clear whether multipliers should be expected to be higher or lower than in the AEs (Table 3).

Table 3.

Multipliers in Emes and Lics

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The scarce empirical literature available suggests that multipliers in EMEs and LICs are smaller than in AEs (Estevão and Samake, 2013; Ilzetzki and others, 2013; Ilzetzki, 2011; IMF, 2008; and Kraay, 2012). Some studies even conclude that multipliers are negative, particularly in the longer term (IMF, 2008) and when public debt is high (Ghosh and Rahman, 2008). Appendix 3 provides summary tables reporting estimates from studies on EMEs and LICs.

In terms of fiscal instrument, tax multipliers seem to be broadly similar to expenditure multipliers in EMEs. Ilzetzki (2011) finds that, in EMEs, spending multipliers range from 0.1 to 0.3, while revenue multipliers lie between 0.2 and 0.4 in the short term. The fact that EME spending multipliers are, on average, lower than in AEs could be related to several factors, including expenditure inefficiencies, the difficulty to unwind expenditures (with increases more likely to become permanent),6 or composition effects.7

B. Determinants of the Size of Multipliers

Two types of determinants are identified in the literature: (i) structural country characteristics that influence the economy’s response to fiscal shocks in “normal times;” and (ii) conjunctural/temporary factors (notably cyclical or policy-related phenomena) that make multipliers deviate from “normal” levels.

Structural characteristics

Some structural characteristics influence the economy’s response to fiscal shocks in “normal” times.8 Empirical estimates of fiscal multipliers vary accordingly, although the incremental effect of structural factors on multipliers is, to a large extent, unknown. Key structural characteristics include:

  • Trade openness. Countries with a lower propensity to import (i.e., large countries and/ or countries only partially open to trade) tend to have higher fiscal multipliers because the demand leakage through imports is less pronounced (Barrell and others, 2012; Ilzetzki and others, 2013; IMF, 2008).

  • Labor market rigidity. Countries with more rigid labor markets (i.e., with stronger unions, and/or with stronger labor market regulation) have larger fiscal multipliers if such rigidity implies reduced wage flexibility, since rigid wages tend to amplify the response of output to demand shocks (Cole and Ohanian, 2004; Gorodnichenko and others, 2012).

  • The size of automatic stabilizers. Larger automatic stabilizers reduce fiscal multipliers, since mechanically the automatic response of transfers and taxes offsets part of the initial fiscal shock, thus lowering its effect on GDP (Dolls and others, 2012).

  • The exchange rate regime. Countries with flexible exchange rate regimes tend to have smaller multipliers, because exchange rate movements can offset the impact of discretionary fiscal policy on the economy (Born and others, 2013; Ilzetzki and others, 2013).

  • The debt level. High-debt countries generally have lower multipliers, as fiscal consolidation (resp. stimulus) is likely to have positive (resp. negative) credibility and confidence effects on private demand and the interest rate risk premium (Ilzetzki and others, 2013, Kirchner and others, 2010).

  • Public expenditure management and revenue administration. Multipliers are expected to be smaller when difficulties to collect taxes and expenditure inefficiencies limit the impact of fiscal policy on output.9

Conjunctural factors

Conjunctural (temporary) factors tend to increase or decrease multipliers from their “normal” level.10 The recent literature has identified two main factors:

  • The state of the business cycle. Fiscal multipliers are generally found to be larger in downturns than in expansions (Table 4).11 This is true both for fiscal consolidation and stimulus. A stimulus is less effective in an expansion, because, at full capacity, an increase in public demand crowds out private demand, leaving output unchanged (with higher prices). A consolidation is more costly in terms of output in a downturn, because credit-constrained agents cannot borrow to maintain (smooth) their consumption. Furthermore, Table 4 suggests that a downturn has a stronger effect on multipliers than an upturn. In other words, multipliers increase more in a recession than they decrease in an expansion. One reason could be that the supply constraint is asymmetric: while in a upturn the impact of fiscal policy is limited by the inelastic pool of resources (and eventually nullified when the economy reaches maximum productive and full employment capacity), this constraint does not exist when there is a slack in the economy, and the additional resources provided or extracted by the government have more direct traction on output.

  • Degree of monetary accommodation to fiscal shocks. Expansionary monetary policy and a lowering of interest rates can cushion the impact of fiscal contraction on demand. By contrast, multipliers can potentially be larger, when the use and/or the transmission of monetary policy is impaired—as is the case at the zero interest lower bound (ZLB) (Erceg and Lindé, 2010; Woodford, 2011). Most of the literature focuses on the effect of temporary increases in government purchases and finds that the multiplier at the ZLB exceeds the “normal times” multiplier by a large margin (Table 5).12 This effect is conditional on a number of factors. Erceg and Lindé (2010) show that the size of the shock matters at the ZLB: the larger the discretionary spending increases, the shorter the economy will stay at the ZLB, and therefore the lower the fiscal multiplier. Christiano and others (2011) find that implementation lags reduce the multiplier at the ZLB; for the multiplier to be significantly larger than in “normal times,” it is critical that the ZLB is still present when the spending shock hits the economy.

Table 4.

Fiscal Multipliers Over the Business Cycle

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Using deviation of output from HP trend as measure of business cycle.

Average of all countries in sample (including euro area).

Average of G6 in sample.

Using output gap to define expansions and recessions.

Regimes reflect high and low employment.

Table 5.

Government Spending Multipliers and the Zero Lower Bound

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The composition of fiscal adjustment could also be considered as a conjunctural factor affecting the size of the “overall” multiplier. However, Section II.A finds that recent empirical papers using a narrative approach challenge the common wisdom that short-term multipliers for government consumption and investment are higher than those on taxes.

C. Persistence of Fiscal Multipliers

Understanding the shape and persistence of fiscal multipliers is crucial to compute the effects of fiscal policy on output beyond the first year. The persistence of multipliers should be distinguished, conceptually and empirically, from the persistence of the fiscal shock (which depends on whether the fiscal measure is temporary or permanent). In general, model-based and econometric studies find that the output effect of an exogenous fiscal shock vanishes within five years—even if fiscal measures are permanent. The effect does not decline in a linear way but usually has an inverted U shape, with the maximum impact occurring in the second year (Batini and others, 2012; Baum and others, 2012; Coenen and others, 2012). Based on the literature review by Mineshima and others (2014), the second-year multiplier is, on average, 10–30 percent higher than in the first-year.

However, the duration of these effects varies depending on several factors examined in the following paragraphs: (i) the persistence of the fiscal shock; (ii) the type of fiscal instrument; and (iii) conjunctural factors such as the cyclical position and whether monetary policy responds to the fiscal shock.

Permanent fiscal measures tend to have more persistent output effects than temporary ones. DSGE models clearly differentiate between temporary and permanent fiscal measures.13 In these models, the effect of the temporary fiscal measure does not generally last beyond the duration of the shock itself, because forward-looking agents are not affected by temporary changes in their disposable income, while credit-constrained ones are only affected over the duration of the shock. For instance, Coenen and others (2012) show that GDP returns to its baseline level after two years in the case of a two-year temporary increase in government consumption. By contrast, the effect of a permanent fiscal shock may be more persistent, although it generally does not last more than five years (partly because of the endogenous response of prices and monetary policy).

The persistence of the effect of discretionary fiscal policy on output may to some extent depend on the fiscal instruments used. The model-based literature shows that a permanent discretionary change in indirect taxes, government consumption, and transfers 14 has only short-term output effects, typically vanishing within five years (Anderson and others, 2013; Coenen and others, 2012; European Commission, 2010). In contrast, the effect of a permanent discretionary change in public investment or corporate taxes is longer, and may even be permanent, with multipliers steadily increasing after the first year towards their long-term values (Coenen and others, 2012). This is because corporate income taxes have distortionary effects on investment, leading to a long-run decrease in the capital stock, and hence the productive capacity of the economy. Similarly, cuts in government investment in infrastructure could reduce the productivity of the economy and therefore have durable negative effects on output.

The business cycle also affects the persistence and shape of fiscal multipliers. Fiscal shocks occurring in recessions or when production is below potential may have more persistent effects, because of hysteresis effects (Delong and Summers, 2012; IMF, 2011) or because credit constrained agents cannot offset the reduction in their disposable income by borrowing. The shape of multipliers also depends on the cyclical position: Auerbach and Gorodnichenko (2013) show that multipliers steadily increase if the initial spending shock occurs in a recession, while they steadily decline if the shock happens in an expansion.

Finally, monetary policy is an important determinant of persistence. Persistence is higher if monetary policy does not offset fiscal shocks (i.e., by raising interest rates in response to a fiscal stimulus, or expanding the money supply in response to fiscal tightening). DSGE models show that even if the fiscal shock is temporary, a public consumption-based stimulus lasting for two years can have a positive effect on output of up to five years if there is no response of monetary policy (Coenen and others, 2012). In contrast, if monetary policy offsets the fiscal shock, its effect will not last beyond the duration of the fiscal stimulus.

III. A Back-of-the Envelope Exercise: The Bucket Approach

For countries where fiscal multipliers are not readily available, general findings from the literature on other countries can be used. Specifically, the “bucket approach” bunches countries into three groups that are likely to have similar multiplier values based on their structural characteristics.

The choice of the characteristics and the calculation of their marginal effect on multipliers are mostly based on findings from studies on advanced countries. This simple method hypothesizes that similar factors affect multipliers in EMEs and LICs where empirical and model-based estimates are not widely available.

A. Main Steps

The selection of first-year overall fiscal multipliers can be conducted in three steps.

First, assign scores to the country based on how many structural characteristics associated with “large” multipliers it possesses.

The definition of the characteristics and the thresholds are identical across countries except the “safe” level of public debt, which is assumed to be lower in EMEs/LICs in light of the empirical evidence that AEs can sustain higher debt without jeopardizing market access. Specifically, assign a value of one for each of the following characteristics if the characteristic is present:

  • Low trade openness. The economy is relatively closed, with a ratio of imports to domestic demand below 30 percent on average over the past five years.15

  • High labor market rigidities. The country has strong labor unions and/or its labor market is strongly regulated (indicatively, “strong” means that labor market rigidity measures 0.8–1 in indices of labor market rigidity ranging from 0-weak to 1-strong—as in Botero and others, 2004).

  • Small automatic stabilizers. Automatic stabilizers measured by the ratio of public spending to nominal GDP are “small” (for instance, when the ratio is below 0.40).16

  • Fixed or quasi-fixed exchange rate regime. The exchange rate arrangement of the country is not fully flexible. Countries that have the following exchange rate arrangements in the Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER) could be assigned a score of one: no specific legal tender; currency board; conventional peg; stabilized arrangement; crawling peg; and crawl-like arrangement. Countries within a single currency area would, in general, receive a score of 1 (unless the fiscal shock happens in all countries simultaneously, which would most likely trigger a common exchange rate response).

  • Low/safe public debt level. The country’s gross government debt is below a level that is generally considered “safe” by financial markets (i.e., with a relatively low risk premium). For AEs, this level may be assumed to be 100 percent of GDP, while a threshold of 40 percent can be used for EMEs.17 These thresholds are only indicative. In some cases, the debt ratio does not provide an adequate benchmark for the soundness of public finances, and it should be complemented with other indicators of fiscal space, such as the fiscal balance, the share of debt held by residents, or the status of public bonds as safe haven investment in international currency countries.

  • Effective public expenditure management and revenue administration. On the spending side, the assessment could rely on the Public Expenditure and Financial Accountability (PEFA) performance measurement framework. On the revenue side, calculations of tax productivity (measured by the ratio of actual to potential tax receipts) could provide a first evaluation.

Second, sum the scores to determine the likely level of the first-year multiplier (low, medium, or high) in “normal” times.

Given the limited empirical evidence on the relative importance of the factors determining the level of the multiplier, all structural characteristics receive an equal weight.18 Countries with total scores of 0 to 3 may be assumed to have “low” multipliers; countries with total scores of 3 or 4 have “medium” multipliers; and countries with total scores of 4 to 6 end up in the “large” multiplier category. Because of the overlap, countries with totals of 3 or 4 may end up in multiple categories; this flexibility allows using judgment to take into account country-specific factors and extreme values of structural characteristics.

Table 6 shows a possible distribution of first-year multipliers for each category. Each country group is assigned a multiplier range, rather than a point value, to account for differences among countries in the same grouping, and to allow for judgment when selecting multipliers. The range of medium multipliers (0.4–0.6) is that found in Mineshima and others (2014) for AEs, assuming that the fiscal shock (stimulus or tightening) is equally distributed between spending and revenue measures and that the cyclical conditions are “normal” (the output gap is close to zero and monetary policy is unconstrained). The three buckets are also consistent with the distribution of OECD model-based multipliers, which are found to be roughly equally-distributed into the three categories. Simple theoretical considerations provide further support to the overall range (0.1–1.0).19 Finally, the recent papers using a narrative approach also find first-year multipliers within this range (see Section II.A).

Table 6.

Ranges of First-Year Overall Multipliers (Normal Times)

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Third, scale up or down the range assigned through the scoring method depending on whether the country is undergoing any of the conditions described in the list of “conjunctural” characteristics. More precisely:

  • Adjust the range for the cycle. If the economy is at the lowest point of the cycle (maximum negative output gap based on historical patterns),20 increase both the lower and upper bound of the multipliers range by 60 percent. If on the other hand, the economy is at a peak (maximum positive output gap), decrease both bounds by 40 percent. Scaling up the range this way accounts for empirical findings discussed in Section II.B, including the asymmetry of cyclical effects. When the output gap is zero, no adjustment should be made. For all other cases, interpolate.

  • Adjust the range for the monetary policy stance. If monetary policy is at the effective lower bound and is fully constrained, increase both bounds of the multiplier range by 30 percent.21 If the monetary policy is constrained by other considerations, interpolate between 0 and 30 percent.

As discussed above, we do not introduce adjustments for the fiscal package composition, as recent papers show that spending multipliers are not necessarily higher than revenue multipliers.

A multiplicative formula can be used to account for the combined effect of conjunctural characteristics on the multiplier size. A multiplicative formula implies that these characteristics interact with each other and have cumulative effects. For instance, based on the above calibrations and the formula, the marginal effect of the cycle is stronger if a country is at the ZLB.22

Specifically, adjust the upper and lower bounds of the multiplier range as follows:

M=MNT*(1+Cycle)*(1+Mon)

Where M is the final multiplier estimate, MNT is the “normal times” multiplier derived from step 2, Cycle is the cyclical factor ranging from −0.4 to +0.6, and Mon is the monetary policy stance factor ranging from 0 to 0.3.

As stressed above, the adjustment factors should be interpolated when the conjunctural characteristics are moderate. For example, if the economic cycle is only slightly below potential, the Cycle adjustment factor should be set to a positive but small number, using a full adjustment of 0.6 only when the slack in the economy is substantive.

With the scaling factors, under various combination scenarios, first-year multipliers may vary from about 0 to 2. A first-year multiplier of around 2 may seem elevated. However, such an estimate is not uncommon in the literature taking into account the ZLB or the state of the economy.

Although the calibration of the “bucket approach” is based on AE studies, the methodology can be applied to EMEs and LICs. These countries would generally be placed in the low-multiplier bucket reflecting their structural characteristics (trade openness, flexible labor markets, spending and revenue inefficiencies, and, in some cases, unsafe debt levels). The 0.1–0.3 range of estimates in the low-multiplier category is consistent with the empirical findings of Ilzetzki (2011) for EMEs.

B. Illustration

For illustrative purposes, this section computes a range of first-year multipliers for the United States using the bucket approach. The calculation assumes that the United States has a negative output gap. Tables 7 and 8 describe how the first-year overall multiplier is derived. Although the U.S. public debt is above 100 percent of GDP, we classify its debt as “safe” in light its role as safe haven asset for international investors.

Table 7.

Scoring Based on Structural Characteristics

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Table 8.

Derivation of First-Year Multiplier Using the Bucket Approach

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The total score of 4 leaves room for discretion in the choice of the bucket (medium or high). Based on existing empirical estimates and prior knowledge, we assign the United States to the high bucket. The upper and lower ranges are adjusted by the following factors: +0.3 (moderate negative output gap) and +0.1 (constrained monetary policy).

The results from the bucket approach seem reasonable. By comparison, Auerbach and Gorodnichenko (2012a) estimate a first year expenditure multiplier of about 1.4 in recessions, while Baum and others (2012) find an overall downturn multiplier of 0.9 (under the assumption that half of the adjustment falls on spending), and Batini and others (2012) find a multiplier of 1.2 with the same assumption.

C. Caveats and Extensions

The “bucket approach” only provides rule-of-thumb guidance on the size of fiscal multipliers and should not be applied in a mechanical way. Although fiscal multipliers in EMEs and LICs are likely to be affected by similar factors as in AEs, it is important to keep in mind that the bucket approach was calibrated with studies based on the latter group of countries.

In all cases, judgment should be exercised based on priors and economic theory to modify multipliers appropriately. Examples where further adjustment to the multiplier level could be justified include:

  • When a great proportion of the economy is controlled by the government and the private sector is accordingly small (there is limited scope for crowding-out effect of private demand), the multiplier could be adjusted upwards.

  • In economies with de jure flexible exchange rate regimes, but where monetary policy is constrained by financial stability considerations due to currency mismatches, the multiplier could also be adjusted upwards.

  • In cases where fiscal adjustment is highly credible, the multiplier could be adjusted downwards. It has been argued that confidence effects can alleviate the costs of fiscal consolidation.

Finally, the bucket approach suggests a range of first-year multiplier estimates. To determine the effect of fiscal shocks in subsequent years, the literature on persistence provides some (limited) guidance. Based on these findings reviewed in Section II.C, it seems safe to assume a decline to zero in multiplier size over five years, with possibly a higher multiplier in the second year (by 10 to 30 percent relative to the first-year).

IV. A Simple Method to Incorporate Fiscal Multipliers into Macroeconomic Projections

Once a multiplier (or a range of multipliers) has been selected, it can be used to assess the effect of fiscal shocks on output. This section discusses several ways to do this.

A. Fiscal Shocks and GDP Forecasts

A practical and tractable approach to estimate the growth impact of fiscal measures is to “impact” a baseline output projection using estimated fiscal shocks and fiscal multipliers. For simplicity, this can be done in a separate excel template. The simulation starts with a baseline GDP forecast (which excludes the effect of fiscal shocks), then adds the effect of the planned discretionary fiscal measures, as well as the lagged effect of past measures. Potential output estimates could be used to proxy the baseline, provided that fiscal shocks do not affect potential in the short-term. Planned discretionary fiscal measures can be estimated with the change in the structural primary balance (in percent of potential GDP), although it is preferable to use direct estimates of these measures, as reported in budget documents, if available.

This simple approach, based on fiscal multipliers, is only one of the several methods that exist to estimate the effect of fiscal shocks (Box 2). Compared to other methods, the use of a fiscal multiplier template has several advantages: (i) it is relatively easy to implement in a wide range of countries; (ii) it is transparent and explicitly controls for different shocks; (iii) it can take into account, at low cost, a wide range of country- and time-specific factors, including the composition of adjustment packages, the effect of the cycle, and some structural features; and (iv) it addresses (crudely) the circularity between fiscal and output variables, as the multiplier is a “reduced form” estimate that measures the final effect of the fiscal shock on GDP. Nonetheless, different methods are not mutually exclusive.

Alternative Methods to Assess the Impact of Fiscal Policy on Output

Fiscal multipliers are not the only way to link output and fiscal projections. Other methods include:

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. The effect of fiscal policy on GDP can be estimated from the demand side, where GDP is obtained as the sum of government and private consumption, government and private investment and net exports. In this case, it is necessary to assess the effects of fiscal measures on all the GDP components. Changes in government consumption and investment have a direct “accounting” effect on GDP. The effect on private demand and net export of the fiscal measures should then be estimated to come up with a comprehensive assessment. Overall this approach can provide a more detailed assessment of how fiscal shocks affect the economy than the multiplier approach, but it may lead to incorrect estimates of the overall impact of fiscal measures, as second round effects are difficult to quantify.1

1 Absent second-round effects, the demand-side approach would produce an implicit multiplier of 1 for spending measures (due to the accounting effect), 0 for revenue measures, and between 0 and 1 for a mix.

B. Tips to Design a Fiscal Multiplier Template

As discussed above, a simple excel template can be used to assess the impact of fiscal measures on growth. The template should combine estimates of fiscal multipliers, fiscal shocks and a baseline GDP projection to come up with a projected GDP path that incorporates the effect of the fiscal shocks. It can also be used to assess the consistency of the GDP projections with the assumed fiscal consolidation path.

A well-designed template should incorporate the following features:

  • The template should be sufficiently flexible to simulate alternative scenarios under different sets of parameters. In particular, it should allow easily changing the assumptions on the size and persistence of multipliers.

  • The template should make projections over a reasonably long period of time (say, 5 to 10 years) in order to factor in the persistence of fiscal policy shock effects.

  • To avoid double counting, the baseline GDP should not already include the fiscal shocks’ effects (including the lagged effects of past fiscal shocks)—that is, the baseline GDP estimates should be a “no policy” scenario. Potential output estimates can be used to that end; or alternatively, the potential output series can be calculated with a standard HP filter. Given possible measurement errors of potential GDP, sensitivity analysis to alternative measures should be conducted.

  • To estimate fiscal shocks, direct estimates of fiscal measures should preferably be used if available (possibly taken off-budget). Otherwise, fiscal shocks can be proxied with the change in the cyclically adjusted primary balance. The latter is preferable to the structural balance, which excludes one-off factors (which may also have output effects).23

  • The template should take into account the overlapping effects of past fiscal shocks given the persistence of multiplier effects. For instance, the projected GDP in the second year should incorporate the first-year effect of the second-year fiscal shock, as well as the second-year effect of the first-year shock. This is illustrated in Table 9.

  • The template may allow the multiplier to vary endogenously over the cycle, with higher multipliers in downturns than in expansions. For instance, a fiscal consolidation may increase the size of the multiplier if the economy is pushed into a negative output gap.

  • The risk premium of the interest rate may vary endogenously with the size of the fiscal shock and the evolution of fiscal variables.

  • Hysteresis effects can be incorporated, either by making the rough assumption that multipliers do not decline overtime, or by assuming, like De Long and Summers (2012), that each percentage point of the (lagged) output gap reduces the growth rate of potential GDP.

  • The template may also include the resulting debt dynamics, which are a function of the fiscal shock, the value of the multiplier, and the initial debt level (Eyraud and Weber, 2013).

Table 9.

Effect of Fiscal Tightening on Output Level1 (Relative to Baseline)

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For illustration purposes, we assume a repeated negative fiscal shock of 1 unit in 2015–2018 (e.g. $1 cut in spending) and a maximum multiplier of 1 in year 2 that gradually declines to 0 in year 5.

While the template can be a useful tool, users should interpret its outputs with care. First, adjusting the baseline for the effects of fiscal shocks does not necessarily produce a reliable GDP forecast, unless growth is mainly driven by fiscal shocks. In general other factors will come into play (including financial conditions, monetary policy and global activity). Therefore, the template should be used as a complement to standard projection methods. Second, in light of the difficulties to accurately measure multipliers and the sparse availability of empirical evidence, a sensitivity analysis could be carried out. For a range of estimates, the template could, for instance, produce a fan chart representing the spectrum of possible macro-fiscal outcomes. In this way, macro-fiscal projections would reflect the uncertainty surrounding multiplier estimates.