亚开行-浮力还是下沉？亚洲发展中国家的税收表现和前景（英）-2022.5-24页_718kb

报告摘要

Summary of "Buoyant or Sinking? Tax Revenue Performance and Prospects in Developing Asia"

Core Content

This working paper by Samuel Hill, Yothin Jinjarak, and Donghyun Park analyzes the performance and future outlook of tax revenue in developing Asian economies before and during the COVID-19 pandemic. The study uses empirical methods to estimate short-run and long-run tax buoyancy, which measures how tax revenues respond to changes in GDP. It also examines the impact of the pandemic and fiscal measures on tax revenue and projects the tax-to-GDP ratio for 2030.

Main Viewpoints

Tax buoyancy is a key indicator of fiscal sustainability and the effectiveness of tax systems as automatic stabilizers.
Before the pandemic, short-run and long-run tax buoyancy coefficients were close to one, suggesting that tax revenues were growing in line with GDP, supporting fiscal sustainability.
The pandemic had a negative impact on tax revenues, with a GDP-weighted excess tax revenue loss of about 0.5 percentage points of 2019 GDP.
Fiscal stimulus measures, including tax relief, were implemented in many economies, and their impact on tax buoyancy is analyzed.
Tax-to-GDP ratios are projected to improve in most developing Asian economies by 2030, assuming constant other factors.

Key Information

I. Tax Revenue Performance

Tax buoyancy is defined as the responsiveness of tax revenue to changes in GDP.
Short-run buoyancy reflects the immediate impact of economic activity on tax revenues.
Long-run buoyancy indicates the structural relationship between GDP and tax revenues over time.
A buoyancy coefficient greater than one suggests tax revenues grow faster than GDP, indicating fiscal sustainability.
A buoyancy coefficient less than one suggests tax revenues fall behind GDP, potentially threatening fiscal sustainability.

II. Impact of the Pandemic

The pandemic caused a decline in tax revenues beyond what was expected due to the GDP downturn.
The average GDP-weighted excess tax revenue loss in 2020 was 0.5% of 2019 GDP.
The model predicted tax revenues were used to compare against actual tax revenues and quantify the excess loss.
The dummy variable for 2020 showed a statistically significant negative impact on tax revenue growth, indicating the pandemic’s adverse effect.

III. Fiscal Measures and Tax Buoyancy

Many economies implemented large-scale tax relief as part of their pandemic fiscal response.
These measures may have temporarily reduced tax revenues, but if extended, could lower the long-term tax-to-GDP ratio.
The study suggests that tax buoyancy is affected by discretionary fiscal policies, including tax relief, and that these changes are important for understanding revenue trends.

IV. Empirical Strategy and Findings

The study uses error correction models (ECMs) and panel data analysis to estimate tax buoyancy.
The mean-group estimator was applied to panel data from 25 developing Asian economies (1998–2020), yielding short-run and long-run coefficients.
The ARDL model was used to assess individual economy-level buoyancy, allowing for cointegration analysis.
The bounds test was employed to determine the cointegrating relationship between tax revenue and GDP.
The results show that in most economies, the long-run tax buoyancy is above one, indicating fiscal sustainability.

V. Projection to 2030

The tax-to-GDP ratio is projected to rise in most developing Asian economies by 2030.
The projection is sensitive to growth forecasts and model specifications, but overall, the estimates are consistent across different models.
Some economies show insignificant results, possibly due to high variability or short time series.
The study highlights the importance of tax collection efficiency and fiscal policy design in shaping future revenue trends.

Methodology

Data Sources: IMF, OECD, and ADB databases.
Time Period: 1998–2020 for the panel analysis.
Model Used: Error correction model (ECM) and autoregressive distributed lag (ARDL) model.
Variables: Tax revenue, GDP, dummy variable for 2020, and control variables such as inflation and policy variables.
Unit Root Tests: Confirmed stationarity of the data in log differences.

Policy Implications

The pandemic significantly reduced tax revenues, emphasizing the need for fiscal resilience.
Tax buoyancy is a critical metric for assessing the capacity of tax systems to support government spending.
Fiscal stimulus can temporarily lower tax buoyancy, but long-term implications depend on the sustainability of these measures.
Improving tax-to-GDP ratios is essential for fiscal sustainability and achieving development goals.

Conclusion

Developing Asian economies showed relatively stable tax buoyancy before the pandemic.
The pandemic caused an unexpected drop in tax revenues, with significant excess losses.
The impact of fiscal measures on tax buoyancy is important for understanding revenue recovery.
Tax-to-GDP ratios are expected to improve by 2030, provided growth and policy remain stable.

Appendices and References

Appendix A1 provides the distribution of the tax-to-GDP ratio across economies.
Appendix A2 includes correlations between tax growth, GDP growth, inflation, and debt-to-GDP.
References include studies by Jalles (2021), Lagravinese et al. (2020), and others, highlighting the literature on tax buoyancy and fiscal policy.

Tables and Figures

Table 1: Pooled Mean-Group Estimator results showing short-run and long-run buoyancy coefficients.
Figure 1: Long-run tax buoyancy coefficients across 25 economies.
Figure 2: Excess tax losses in 2020 as a percentage of 2019 GDP.

Summary of Key Findings

Before the pandemic, tax buoyancy was close to one, indicating fiscal sustainability.
During the pandemic, tax revenues fell more than expected, with an average excess loss of 0.5% of GDP.
Fiscal stimulus (especially tax relief) affected tax buoyancy, potentially lowering long-term revenue capacity.
By 2030, tax-to-GDP ratios are projected to improve in most economies, but results vary depending on model specification and growth assumptions.