Abstract
Fiscal policy is an essential tool for Chinese policymakers, not only as an instrument to manage macroeconomic demand but also as an element of the larger quest to rebalance China’s economy. This paper finds that means-tested transfers to households have a significantly higher short-term stabilization impact than other fiscal policy measures while contributing to securing high-quality, balanced growth.
Short-Term Fiscal Multipliers in China1
Fiscal policy is an essential tool for Chinese policymakers, not only as an instrument to manage macroeconomic demand but also as an element of the larger quest to rebalance China’s economy. This paper finds that means-tested transfers to households have a significantly higher short-term stabilization impact than other fiscal policy measures while contributing to securing high-quality, balanced growth.
A. Fiscal Multipliers
1. China has traditionally relied heavily on increasing public investment to offset exogenous shocks to demand. In response to the Global Financial Crisis, the government turned to investment to support demand. Following the pandemic, the authorities have also relied disproportionately on investment to boost growth. This raises the question whether relying on public investment to boost short-term demand is the best use of fiscal resources.
2. Fiscal multipliers measure the impact of a discretionary changes in government spending or tax revenue (i.e., fiscal shocks) on output. Good estimates of fiscal multipliers are essential for fiscal policy to play an effective role in supporting economic stabilization and fiscal policy credibility as well as for more accurate macroeconomic forecasting. Overestimating multipliers could result in a government providing insufficient stimulus to offset a negative shock to the economy. Underestimating multipliers may lead countries to miscalculate the amount of adjustment necessary to curb their debt ratio.
3. Estimation of fiscal multipliers is challenging. Changes in the government balance and its revenue and expenditure components affect aggregate demand and changes in aggregate demand, in turn, affect the government balance and its components. This dynamic endogeneity complicates empirical estimates of multipliers from observed changes in fiscal aggregates and output. For example, a discretionary increase in income tax rates, aimed at lowering a fiscal deficit, reduces aggregate disposable income. The drop in income will reduce aggregate consumption—especially if many households lack access to credit or savings to smooth the negative shock—inducing layoffs and a fall in aggregate taxable income. The smaller income tax base translates, in turn, into lower tax revenue which can offset some or all of the initial effort to increase tax revenue.2
4. Estimated multipliers vary with a country’s structural characteristics and the conjunctural setting. Izquierdo and others (2019) offer a succinct review of the academic literature on how the government spending multiplier depends on:
the state of the economy, with multipliers being larger in recessions than in expansions (e.g., Auerbach and Gorodnichenko, 2012 and 2013; Riera-Crichton, Vegh, and Vuletin, 2015);
the exchange rate regime, with multipliers being larger under fixed regimes (e.g., Ilzetzki, Mendoza, and Vegh, 2013);
the degree of indebtedness, with multipliers being larger when debt is low (e.g., Ilzetzki, Mendoza, and Vegh, 2013; Huidrom et al., 2019);
the degree of accommodation of monetary policy, with multipliers being larger when monetary policy is loose and/or close to the zero lower bound (Christiano, Eichenbaum, and Rebelo, 2011; Coenen, Straub, and Trabandt, 2013); and
the degree of openness of the economy, with multipliers being smaller in economies more open to trade (e.g., Ilzetzki, Mendoza, and Vegh, 2013; Gonzalez-Garcia, Lemus, and Mrkaic, 2013). Moreover, studies indicate that the output effect of public investment falls when efficiency is low (Leeper, Walker, and Yang, 2010; Cavallo and Daude, 2011; Furceri and Li, 2017).
5. Against this backdrop, it is perhaps not surprising that estimates of the size of multipliers for China cover a wide range. Estimates of short-term spending multipliers in China range between 0.3 – 1.7 (Text Table). While these differences may reflect differences in sample periods, techniques used to identify fiscal shocks, and estimation approaches, they point to the difficulty in arriving at point estimates for multipliers, particularly in emerging markets such as China.
6. This paper employs two methodologies to further explore the size of short-term multipliers in China. First, we apply the “bucket” approach developed by Batini, Eyraud, and Weber (2014) to derive an indicative range for the overall fiscal multiplier. The “bucket” approach yields a range for the average multiplier. Second, we model multipliers for various fiscal instruments in responses to recessionary shocks using an estimated New Keynesian model with detailed fiscal specifications and accounting for fiscal and monetary policy interaction.
China: Estimates of Fiscal Multipliers: China and Emerging Markets
China: Estimates of Fiscal Multipliers: China and Emerging Markets
| Country | Term | G | T | Notes | Source |
|---|---|---|---|---|---|
| Empirical Estimates of Multipliers | |||||
| China | ST | 1.7 | Consumption multiplier | Wang and Wen (2013) | |
| China | LT | 1.6/1.0 | Economic upturn/downturn | Zhang, Zhang, Zheng, and Zhang (2019) | |
| China | ST | 0.5/0.6 | Depending on sample period | Jeong, Kang, and Kim (2017) | |
| China | ST | 0.6 | Based on annual data from China's prefectures | Guo, Liu, and Ma (2016) | |
| EMs | ST | 0.2 | 0.3 | Panel, 17 EMs | Ilzetzki (2011) |
| Model-based Estimates of Short-Term Multipliers | |||||
| China | ST | 0.3/1.1 | 0.4 | G Increase/Decrease | Ducanes and others (2006) |
| Emerging Asia | ST | 1 | 0.5 | Averages of expenditures (ex.transfers) and tax instruments | Freedman and others (2009) based on GIMF |
China: Estimates of Fiscal Multipliers: China and Emerging Markets
| Country | Term | G | T | Notes | Source |
|---|---|---|---|---|---|
| Empirical Estimates of Multipliers | |||||
| China | ST | 1.7 | Consumption multiplier | Wang and Wen (2013) | |
| China | LT | 1.6/1.0 | Economic upturn/downturn | Zhang, Zhang, Zheng, and Zhang (2019) | |
| China | ST | 0.5/0.6 | Depending on sample period | Jeong, Kang, and Kim (2017) | |
| China | ST | 0.6 | Based on annual data from China's prefectures | Guo, Liu, and Ma (2016) | |
| EMs | ST | 0.2 | 0.3 | Panel, 17 EMs | Ilzetzki (2011) |
| Model-based Estimates of Short-Term Multipliers | |||||
| China | ST | 0.3/1.1 | 0.4 | G Increase/Decrease | Ducanes and others (2006) |
| Emerging Asia | ST | 1 | 0.5 | Averages of expenditures (ex.transfers) and tax instruments | Freedman and others (2009) based on GIMF |
B. The “Bucket” Approach to Estimating the Overall Multiplier
7. The “bucket” approach provides a framework for thinking about the likely impact of discretionary fiscal policy on output. It synthesizes the extensive literature on fiscal multipliers into a granular approach to develop a range estimate of a country’s overall multiplier—that is, the output response to a change in the fiscal balance generated by a discretionary fiscal policy choice. The range estimate is indicative and a starting point for quantifying the impact of fiscal shocks on activity. The “bucket” approach employs a three-step process.
Step one: Assess China’s Structural Characteristics that Influence Level of Multiplier
8. China’s structural characteristics influence how its economy responds to fiscal shocks. Based on the literature, Batini, Eyraud, and Weber (2014), identify six structural factors that either enhance or reduce the magnitude of a country’s overall fiscal multiplier compared to “normal” times.3
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. China’s imports over the five-year period from 2015-19 averaged about 18 percent of domestic demand. This is lower than the weighted-average value for G20 emerging market economies over the same period of 22 percent.
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. China’s labor market is rigidity is not high. For example, Botero and others (2004) assess China to have an index value of about 0.5 on a scale of from 0 – 1. An index value greater than 0.8 is indicative of high labor market rigidity.
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. China’s automatic stabilizers fall below the threshold of 40 percent, above which stabilizers are considered large under the “bucket” approach. China’s public expenditure relative to nominal GDP over the five-year period from 2015-19 averaged about 33 percent, similar to the weighted-average value for G20 emerging market economies over the same period of 31 percent. In addition, direct taxes, particularly the personal income tax, are low, averaging about 1.1 percent over the last several years.
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. The IMF’s 2020 Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER) classifies China’s de facto exchange rate regime as “other managed”arrangement, effective March 3, 2022 (see China: 2022 Article IV Consultation – Informational Annex. A not less-than-fully-flexible exchange rate tend to enhance the magnitude of fiscal multipliers compared to a fully flexible one.
Debt level. High-debt countries generally have lower multipliers, as fiscal stimulus (consolidation) undertaken when debt is high is likely to have negative (positive) credibility and confidence effects on private demand and the interest rate risk premium. China’s overall level of general government debt stands at around 110 percent of GDP.4 This significantly exceeds the average debt-to-GDP ratio for emerging markets, excluding China, of 59 percent of GDP in 2021. However, the impact of the high debt ratio on interest rate premium in China is somewhat muted by a largely closed capital account, which limits investment opportunities for domestic savers.
Public expenditure management and revenue administration. Multipliers are expected to be smaller when difficulties to collect taxes and expenditure inefficiencies, including coordination of expenditure among different levels of government, undermine the transmission of fiscal policy on output. To our knowledge, there is no objective measure of the effectiveness of China’s public financial management (PFM) system. One possible source for assessing its effectiveness is the Public Expenditure and Financial Accountability (PEFA) performance measurement framework. However, China’s PFM system has not been assessed through PEFA.
Step two: Assign China to a Short-Term Multiplier Bucket
9. Overall, China’s structural characteristics suggest multiplier of low to medium size. Text Table summarizes the analysis (above) of China’s structural characteristics relative to the threshold values for each characteristic. If the characteristic is above the relevant threshold China received a score of “1.” If not, its score is zero. All structural characteristics receive an equal weight given the limited empirical evidence on the relative importance of the factors determining the level of the multiplier. China’s total score of “3” reflects its relatively low trade openness, small automatic stabilizers, and crawl-like exchange rate regime, all of which tend to enhance the magnitude of its overall fiscal multiplier.
China: “Score” Under the “Bucket” Approach
China: “Score” Under the “Bucket” Approach
| Structural characteristics | Metric | China | Score |
|---|---|---|---|
| Low trade openness | Imports < 30 percent of domestic demand | 17.5 | 1 |
| High labor market rigidity | Index > 0.8 (Botero and others, 2004) | 0.51 | 0 |
| Small automatic stabilizers | Spending < 40 percent of GDP | 33 | 1 |
| Fixed/Quasi FX regime | AREAER classification | Crawl-like | 1 |
| Low public debt level | Debt < 70 percent of GDP | 110 | 0 |
| Strong PFM/Revenue admin | PEFA/ Revenue “gaps” | N/A | 0 |
| Total | 3 |
China: “Score” Under the “Bucket” Approach
| Structural characteristics | Metric | China | Score |
|---|---|---|---|
| Low trade openness | Imports < 30 percent of domestic demand | 17.5 | 1 |
| High labor market rigidity | Index > 0.8 (Botero and others, 2004) | 0.51 | 0 |
| Small automatic stabilizers | Spending < 40 percent of GDP | 33 | 1 |
| Fixed/Quasi FX regime | AREAER classification | Crawl-like | 1 |
| Low public debt level | Debt < 70 percent of GDP | 110 | 0 |
| Strong PFM/Revenue admin | PEFA/ Revenue “gaps” | N/A | 0 |
| Total | 3 |
10. Based on China’s structural characteristics, fiscal multipliers are neither unusually high nor low during normal times. Batini, Eyraud, and Weber (2014) developed a schematic for placing countries in low, medium, and high short-term multiplier buckets based on their scores (Text Table). With a score of 3, China falls in either the low or medium multiplier bucket. We place China in the low multiplier bucket, which is broadly in line with other emerging markets (Ilzetzki, Mendoza, and Vegh 2013).
China: First-year Overall Multipliers
China: First-year Overall Multipliers
| (Normal times) | ||
|---|---|---|
| Country category | Structural score | Multiplier ranges |
| Low multiplier | 0 - 3 | 0.1 - 0.3 |
| Medium multiplier | 3 - 4 | 0.4 - 0.6 |
| High multiplier | 4 - 6 | 0.7 - 1.0 |
China: First-year Overall Multipliers
| (Normal times) | ||
|---|---|---|
| Country category | Structural score | Multiplier ranges |
| Low multiplier | 0 - 3 | 0.1 - 0.3 |
| Medium multiplier | 3 - 4 | 0.4 - 0.6 |
| High multiplier | 4 - 6 | 0.7 - 1.0 |
Step three: Adjust “Normal Times” Multiplier for Conjunctural Situation
11. The stage of the business cycle effects the size of fiscal multipliers. Discretionary fiscal stimulus is less effective during an expansion than a contraction, particularly when the output gap is positive. In this case, the increase in output is likely to be marginal as there are few underutilized labor and capital resources to employ to increase supply. Conversely, a fiscal consolidation is more costly in terms of output in a downturn than an upturn because credit-constrained agents cannot borrow to maintain or smooth their consumption. To account for the impact of the business cycle on fiscal multipliers, under the “bucket” approach the “normal times” multiplier is decreased by up to 40 percent if the economy is at its cyclical peak and increased by up to 60 percent if an economy is at a cyclical trough.
12. Monetary policy also influences the magnitude of a fiscal multiplier. Expansionary monetary policy enhances the output response to a discretionary fiscal stimulus, such as an increase in spending on goods and services, by offsetting upward pressure on interest rates due to the fiscally induced boost in aggregate demand (i.e., there is no crowding out of private sector demand due to higher interest rates). Similarly, when fiscal policy is tightened through, for example, a cut in public investment, a tighter monetary policy offsets any tendency for interest rates to fall in response to the decrease in public-sector demand. The “bucket” approach accounts for the monetary policy stance by adjusting the “normal times” multiplier by up to 30 percent depending on the degree to which monetary policy is constrained by other considerations. For example, if monetary policy is at the zero-lower bound the overall multiplier would be increased by 30 percent.
13. A simple equation summarizes the impact of conjunctural factors on the “normal times” multiplier:
M = MNT * (1+Cycle)*(1+Mon)
where:
M = final overall multiplier estimate
MNT = “Normal times” multiplier (Step 2)
Cycle = cyclical adjustment
Mon = monetary policy stance factor
14. China’s economy is estimated to be operating below potential and monetary policy is somewhat accommodative during 2022-23. These conjunctural factors suggest that the impact of an expansionary fiscal policy on economic activity would be enhanced. China’s “normal times” overall multiplier (MNT) range is between 0.0 – 0.3. With a negative output gap exceeding two percent of potential GDP, there is slack in the economy. This suggests the cyclical adjustment factor (Cycle) should be about 40 percent (0.4). Monetary policy is somewhat accommodative but could be more so. With this in mind, a reasonable value for the monetary stance factor (Mon) is about 20 percent (0.2). Bringing the structural and conjunctural factors together, the “bucket” approach provides a potential range for China’s short-term overall multiplier of 0.2 – 0.5, at the current juncture (Text Table).
China: “Bucket” approach: Final range estimate for the short-term overall multiplier
China: “Bucket” approach: Final range estimate for the short-term overall multiplier
| Step 1 | Step 2 | Step 3 | Estimate | ||
|---|---|---|---|---|---|
| Score | Multiplier range | Cycle adjustment | Monetary factor | Final range | |
| China | 3 | Low (0.1 - 0.3) | 0.4 | 0.2 | (0.2 - 0.5) |
China: “Bucket” approach: Final range estimate for the short-term overall multiplier
| Step 1 | Step 2 | Step 3 | Estimate | ||
|---|---|---|---|---|---|
| Score | Multiplier range | Cycle adjustment | Monetary factor | Final range | |
| China | 3 | Low (0.1 - 0.3) | 0.4 | 0.2 | (0.2 - 0.5) |
15. Other factors can introduce variation in the multiplier around the average value identified through the “bucket” approach.
Policy uncertainty. Other policies that can induce a high degree of uncertainty into daily economic life such as the potential for repeated lockdowns under China’s zero-COVID strategy likely lower fiscal multipliers as mobility is restricted and economic agents are likely to increase savings to offset the potential for income losses.
Public investment vs consumption. For example, the use of different fiscal instruments can amplify or detract from the average multiplier. A meta-analysis of the literature on fiscal multipliers points to average estimates for public spending on goods and services (government purchases) of about 1, with that for public investment slightly higher than that for public consumption, although there is a large degree of variability (April 2020 WEO). For China, we applied a DSGE model to simulate how the multiplier may vary with the use of different fiscal instruments (see next section).
Green investment. “Green” investment may have higher multipliers than other types of investment.
16. Public support for households may be a particularly effectful policy instrument. A significant portion of China’s households face liquidity constraints. Public spending through means-tested transfers to households with higher marginal propensities to consume generates higher fiscal multipliers than transfers to other households (Jappelli and Pistaferri 2014; McKay and Reis 2016). A discretionary policy that targets cash transfers to these households is likely to have an outsized impact on output. The following section follows up on these considerations.
C. A Model Simulation of China’s Fiscal Multipliers by Fiscal Instrument
17. We apply a DSGE model to further study the relative implications of various discretionary fiscal policy shocks (measures) on output under the current cyclical position for China. We focus on the short-term implication of the fiscal expansion as a stabilization instrument. Three policy scenarios are analyzed to understand the differences between the public investment and household support measures, in terms of stabilizing output and their effects on supporting a more balanced recovery. The model estimates complement the “bucket” approach which does not consider potential differences in multipliers among fiscal instruments.
18. The model is an extension of Traum and Yang (2015) and Leeper, Plante, and Traum (2010):
The model features two types of households: liquidity-constrained (also known as “non-savers” representing low-income households) and unconstrained (aka. savers representing high-income households). The liquidity-constrained households do not have access to financial or capital markets and consume all their disposable income each period. The liquidity-unconstrained households are forward-looking with access to complete asset and capital markets.
The model includes an extensive set of fiscal instruments including transfers, public investment, differentiated labor income taxes, capital income taxes, and consumption tax. Debt is stabilized by adjusting non-distortionary lump-sum taxes to the higher income households.
The inclusion of liquidity-constrained households, who have a higher marginal propensity to consume, allows stronger short-run demand effects following expansionary fiscal policy than in models with a representative non-constrained household.
The model features a central bank that sets policy interest rate based on a Taylor rule specification. In addition, we also model the implicit interest rate the government pays on its debt, which depends on the average maturity structure of sovereign debt as in line with Veld et al. (2012).
Model Calibration
19. Our parameter choices reflect data availability and the standards of the literature.
On the structure of the economy, the share of government consumption, investment, and transfer to households relative to GDP is estimated based on official data for the period between 2016 and 2019 to avoid the disruptions caused by the pandemic.
While the share of capital in the Cobb-Douglas production function is not readily available, a wide range of estimates is available in the literature, from a low of 0.36 estimated by Ge and others (2022), to a high of 0.45 estimated by Zhang, Liu, and Huang (2019). The literature gravitates toward the view that China’s capital share is higher than the 0.3 commonly used for other countries. In our simulation, the share of capital is assumed to be 0.4, in which the share of public and private capital in the production function is about 0.14 and 0.26, respectively.
For the household sector, the effective labor income tax rate, which includes personal income tax and social security contributions, for liquidity unconstrained households is estimated to be between 10 and 20 percent and around 10 percent for constrained households, based on the current tax statutes.
The data for the proportion of liquidity constrained households is not available and difficult to estimate. The share ranges from 25 to 40 percent for advanced economies and is much higher for emerging economies according to estimates by Barrail (2020). For China, Xie and Jin (2015) show that the poorest half held 8 percent of total national wealth. However, most of the wealth is concentrated in illiquid assets, e.g., land and houses, which provide relatively limited buffers for smoothing consumption. In our analysis, the share of liquidity constrained households in China is assumed to be around 50 percent.5
Model Results
20. To best depict the current state of the Chinese economy, a number of fiscal policy scenarios are layered on top of large negative demand shocks (i.e., preferences shocks and investment-specific technology shocks) which lower output, consumption, and private investment. As a result, the pre-policy level of output is three percent below potential output. The public debt to GDP ratio is calibrated to 81.6 percent, the level in 20196.
21. We analyze three fiscal policy scenarios: 1) an increase in the means-tested transfer to lower income households, 2) an increase in the untargeted transfer to all households, and 3) an increase in public investment.7 In each case, the fiscal expansion is normalized to one percent of GDP in the first year, and then gradually phases out.8 In the meantime, monetary policy remains broadly unresponsive. The fiscal expansion is assumed to be in the form of public investment and transfers to all households or to liquidity constrained households only. We then estimate the respective fiscal multipliers as the cumulative change of output or consumption for each yuan spent in the fiscal package over the same horizon.
22. All three fiscal spending measures raise output, but the size of the multipliers varies significantly. As a fiscal response to stabilize economy in the short term, means-tested government transfers to households with liquidity constraints, who have a higher marginal propensity to consume, are the most effective in closing the output gap, particularly when interest rates remain largely unchanged, therefore limiting the crowding-out effects of government support, which is typically the case in a recession. The short-term multiplier estimate derived from the model for means-tested transfers is 1.5. For the same fiscal cost, the untargeted transfer result in a multiplier below 1, reflecting the fast that unconstrainted households save part of the transfers. Finally, a public investment-driven fiscal expansion would generate a short-run output multiplier of 1.9 While public investment, if deployed efficiently, eventually increases the stock of future public capital, this takes time. The impact of public investment—operating indirectly through income effects—is significantly lower than the impact of direct transfers to the households, especially when the latter are means-tested and targeted.
Fiscal Multipliers
Citation: IMF Staff Country Reports 2023, 081; 10.5089/9798400233517.002.A002
Source: IMF staff estimates.Fiscal Multipliers
Citation: IMF Staff Country Reports 2023, 081; 10.5089/9798400233517.002.A002
Source: IMF staff estimates.Fiscal Multipliers
Citation: IMF Staff Country Reports 2023, 081; 10.5089/9798400233517.002.A002
Source: IMF staff estimates.23. The estimate on means-tested transfers is within the range of estimates for government spending multipliers for China found in the academic literature.10 While the estimate for the cash transfer is significantly higher than the top range of 0.5 for the overall multiplier from the “bucket” approach, the divergence is not necessarily surprising. The overall multiplier represents an average across fiscal instruments and the multiplier on some revenue and expenditure instruments can be quite low.
D. Conclusion
24. A focus of fiscal measures on targeted, means-tested household support promises a higher growth impact and will help the economy rebalance. The authorities should reprioritize spending away from infrastructure investment and towards spending that boosts private consumption—for example, means-tested direct income support to vulnerable households who have a higher propensity to consume—which would lower high household savings, help rebalance the recovery, and help close the negative output gap.
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Prepared by Anh Nguyen (FAD), John Ralyea (FAD) and Fan Zhang (RES).
The aggregate change in tax revenue depends on the tax multiplier, the elasticity of tax revenue to output, and capacity to administer taxes.
In “normal” times, a country’s output gap is close to zero and its monetary policy is unconstrained (e.g., not at the zero-lower bound). Since the onset of the COVID-19 pandemic, China’s actual output has fallen short of its potential output (i.e., it has a negative output gap) as in many emerging markets, but its monetary policy has remained unconstrained.
Estimated debt level based on the augmented debt concept, which reflects the fiscal stance and the government’s role in the economy. A reconciliation of the augmented concept figures with the authorities’ figures, can be found in the published China Article IV reports.
Our calibration is in line with the GIMF model for emerging Asia (Kumhof et al., 2010), which is smaller than the 70 percent assumed in Cosa, Pisani, and Rebucci (2011).
Augmented debt level published in Article IV staff reports.
Investment spending efficiency is assumed to be 0.75.
The fiscal impulses are assumed to phase out following an AR(1) process.
These multipliers are in line with IMF (2020, Fiscal Monitor October).
The multipliers are in line with estimates of government spending multipliers when monetary policy is constrained in other studies (e.g., Christiano, Eichenbaum, and Rebelo 2011; Klein and Winkler 2021).
