Sustainable and Balanced Growth in the Longer Term

International Monetary Fund. Asia and Pacific Dept

doi:10.5089/9798400233517.002.A006

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International Monetary Fund. Asia and Pacific Dept

International Monetary Fund. Asia and Pacific Dept
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Publication Date:: 10 Feb 2023

eISBN:: 9798400233517

ISBN:: 9798400233517

Language:: English

Keywords:: capital share; SOE productivity gap; tertiary sector TFP; TFP level; productivity gain; Productivity; Consumption; Human capital; Global

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China’s potential growth has slowed, and the economy is facing several headwinds expected to further lower potential growth in the medium to long term. Comprehensive structural reforms to lift productivity growth and foster rebalancing towards more sustainable and less investment-driven growth can significantly improve the growth outlook.

Abstract

Sustainable and Balanced Growth in the Longer Term¹

A. Introduction

1. After decades of high growth, the Chinese economy has started slowing and is facing headwinds that are projected to lower potential growth substantially in the longer term. First, with its rapidly aging population, the Chinese economy is expected to have fewer people entering the labor force, which will diminish growth prospects (IMF, 2017). Second, productivity growth has slowed significantly, and as China edges closer to advanced economy status and the technology frontier, its aggregate productivity growth is expected to eventually decline further (Madsen and others, 2010). What is unique in the case of China is the additional pressure from diminishing returns of investment-led growth, as excessive investment—driven by record-high domestic savings—has been channeled towards relatively less productive SOEs, activities such as real estate, which are less growth-enhancing over the longer term, and to further increase China’s already comparatively very large public capital stock. This pattern of investment in China has sped up the decline in aggregate productivity, and hence, potential growth.

2. Structural reforms and rebalancing China’s growth towards a more consumption-based growth path would help transition to “high-quality"—balanced, inclusive, and green— growth. This paper provides updated estimates of China’s potential growth over the medium- to long-term. We establish a baseline scenario of China’s growth prospects and study an illustrative reform scenario and its impact on potential growth that tackles the slowdown in potential growth. Reforms that simultaneously enhance productivity growth, facilitate rebalancing towards consumption against the backdrop of an adjustment of the current zero-COVID strategy (ZCS), and steer against the demographic headwinds are the most promising.

B. Background

3. China’s potential growth decelerated in the decade between the global financial crisis and the pandemic. While China’s high growth rates in the early 2000s were—from the supply-side—largely driven by increases in productivity following the WTO accession and rapid accumulation of capital, they were accompanied by increasing imbalances on the demand side. In the decade before the pandemic, productivity growth slowed, including because of increasingly less productive investment, and domestic demand-side imbalances further increased.

4. Chinese households have an exceptionally high savings rate, also reflected in its low consumption share in GDP. High household savings have been driven by precautionary savings due to gaps in the social protection system and falling job security, in addition to China’s aging population (IMF, 2022; and Zhang and others, 2018). During the pandemic, recurrent COVID outbreaks under the zero-COVID policies have further increased household savings amid high uncertainty, weaker labor markets, and subdued private consumption. This high savings rate is reflected in China’s rising share of investment in GDP over time, coupled with a falling share of consumption.

5. High domestic savings have fueled increasingly unsustainable levels of investment. With increasing per capita income, countries tend to have a lower share of consumption and a higher share of investment in GDP. For China, however, the reduction in the share of consumption and the increase in the share of investment by far exceed the changes implied by the level of its GDP per capita observed elsewhere (Text Figures), leaving China with one of the highest investment-to-GDP ratios and a particularly low consumption-to-GDP share in international comparison. The extraordinarily high amount of savings has been channeled into investments that helped support high growth rates, especially in the 2000s. Later, however, a substantial amount of investment went to relatively less productive sectors which, beyond the short-term effect on GDP, provided diminishing support to China’s growth potential over the long run.

6. Following the Global Financial Crisis (GFC), China’s growth has become increasingly dependent on investment in infrastructure and housing. To maintain high growth rates in the wake of the global recession, the authorities ramped up infrastructure investment. In addition, households channeled their high savings increasingly towards housing, including for speculative motives, and real estate investment became one of the main drivers of growth, with the real estate sector accounting for around 20 percent of China’s GDP. This was made possible by high savings and excessive credit growth (Text Figure) accompanied by sharply rising debt levels across the economy, particularly in the real estate sector and the government, with the augmented government debt-to-GDP ratio reaching more than 100 percent in recent years.²

7. China’s investment-led growth strategy has been facing rapidly diminishing returns. Vulnerabilities have risen—as shown by the ongoing crisis in the real estate sector—and strong investment in infrastructure and housing has been associated with falling returns to capital (Brandt and others, 2020). The marginal product of capital, in aggregate, has been falling (Text Figure). While China’s capital stock is still considerably below that of advanced economies, this suggests resource misallocation and build-up of excess capacity in some parts of the economy.

8. Productivity growth in China’s manufacturing sector has been falling amid a large SOE presence. Compared to infrastructure and real estate investment, manufacturing investment has grown more slowly in the previous decade with less evidence of excessiveness. Yet several studies show that China’s manufacturing productivity growth slowed considerably following the global financial crisis (Brandt and others, 2020; and Cerdeiro and Ruane, 2022), linked to declining business dynamism and a significant presence of less-productive state-owned enterprises (SOEs). Detailed analysis using manufacturing firm-level data indicates that the responsiveness of capital growth to the marginal product of capital has declined in recent years, and that large productivity gaps between SOEs and private firms persist (Jurzyk and Ruane, 2021; and Cerdeiro and Ruane, 2022).

C. Approach and Historical Decomposition

9. We rely on a standard supply-side production function approach to estimate potential growth. Standard growth accounting frameworks decompose output into contributions from physical capital, labor, human capital (i.e., the skill-level of the labor force) and total factor productivity (TFP). TFP measures an economies’ efficiency, i.e., the output produced for a given level of inputs. Our potential growth estimates are based on a standard Cobb-Douglas production function:

Y_{t} = A_{t} K_{t}^{α} {(L_{t} h_{t})}^{1 - α}

with Y = real GDP, A = TFP, K = capital stock (derived from investment I and depreciation rate δ via the perpetual inventory method), L = labor, h = human capital, α = elasticity of output to capital, 1– α = elasticity of output to labor, and t = years. In the historical decomposition, TFP is derived as the residual of the production function (see Annex I). Historical data is described in Annex II.

10. One adjustment to the standard approach is a sectoral decomposition to capture the impact of sectoral rebalancing. We incorporate sectoral factor reallocation between the primary, secondary and tertiary sectors, and split total TFP into within-sector productivity and productivity gains from sectoral reallocation (see Annex I).³ Data constraints do not allow us modelling the real estate sector separately. Instead, the sector is incorporated as part of the secondary sector.

11. We make the simplifying assumption that parameter a remains constant. The elasticity of output to input factors is oftentimes approximated by their shares in incomes, as this is the case when firms are profit-maximizing under perfect competition and the production function has constant returns to scale. However, given labor and capital misallocations in China (see e.g., Hsieh and Klenow, 2009), factor prices might not adequately represent their marginal productivities. In line with the literature (see Albert and others, 2015), we thus use conventional coefficients α = 0.4 and 1 - α = 0.6.

12. When decomposing historical output, we use Chen and Kang’s (2018) estimates of sustainable GDP growth—i.e., growth without excessive credit expansion—rather than actual GDP growth. Sustainable output is the level of GDP that an economy can sustainably produce over the medium term in the absence of imbalances. Post-GFC, Chinese GDP and investment growth were supported by excessive credit growth, with the nonfinancial private sector credit-to-GDP ratio increasing by 45 percentage points during 2012-2016. Without excessive credit growth and the private sector credit gap, Chen and Kang (2018) estimate that nonfinancial private sector credit-to- GDP would have increased by around 10 percentage points over the same period. They note that credit efficiency—the amount of credit needed for a unit increase in nominal GDP—deteriorated sharply during the post-GFC period, pointing to growing resource misallocation as capital increasingly grew in relatively less productive sectors, such as real estate. When deriving sustainable GDP, Chen and Kang (2018) use counterfactual credit efficiency, assuming it remains in line with the previous trend, thus deteriorating less than the actual. We extend their analysis until 2018, when China’s credit gap was largely closed according to BIS estimates. Following these adjustments, we find that average sustainable real GDP growth for 2012-18 would have been 5.3 percent rather than actual GDP growth of 7.2 percent.

13. TFP growth fell sharply over the last decade. We derive historical TFP growth as the residual of the production function based on the estimated sustainable level of GDP growth. The decomposition shows that aggregate TFP growth sharply fell from 3.7 percent in the 2000s to 1.9 percent from 2010-19. While these numbers diverge from other estimates of TFP growth (see Text Figure), all point to a significant slowdown in the last decade.

14. Within-sector TFP growth rates have also fallen across all sectors since the 2000s, similar to aggregate TFP growth rates. Our sectoral decomposition shows that within-sector TFP growth fell from averages of around 3-4 percent in the 2000s to 1 percent or less in the 2010s (see Text Figure). TFP levels are highest in the secondary sector, though the level of TFP in the tertiary sector is starting to catch up to that in the secondary sector thanks to slightly higher TFP growth rates in the tertiary sector in recent years. Finally, as more resources have moved out of the primary sector and into the more productive secondary and tertiary sectors, factor reallocation across sectors is contributing toward aggregate TFP growth, so that aggregate TFP growth exceeds within-sector TFP growth rates.

15. Overall, we find that China’s potential growth has fallen from a peak of around 10 percent to less than 5 percent. The historical decomposition shows China’s potential growth peaked in 2005-06 and has fallen since in line with weaker productivity growth, less productive capital, and a shrinking workforce. For 2021, we estimate potential growth of 4.7 percent, with weaker TFP growth explaining the largest part of the drop from its peak.

D. Forecast Scenarios

16. We provide estimates of China’s potential growth over the medium- to long-term under a baseline and an upside scenario. With our upside scenario, we aim to illustrate one possible path of China’s potential growth under a set of simultaneous reforms—a best-case scenario. We use a bottom-up approach to forecast each of the factors in our production function. Forecast scenarios are derived by projecting and changing assumptions of the input factors to the production function.

Baseline scenario

17. In our baseline scenario, we assume no significant structural reforms, but a return to pre-pandemic trends following the lifting of the zero-COVID strategy in 2023. The baseline assumes the following developments (see Text Table):

Labor evolves in line with the UN’s medium fertility growth scenario. This implicitly assumes that the average retirement age of 54 will remain constant. In the absence of significant rebalancing, sectoral labor shares converge to advanced economy shares only by 2050.
Human capital will continue growing at its current rate, i.e., assumes no lasting scarring from ZCS.

Investment: In the absence of significant reforms towards rebalancing, investment is assumed to remain a large share of GDP, even as it grows less than before. In line with trends in the household savings rate and demographics, we assume the investment-to-GDP ratio will fall by about 1 percentage point in the long term from its current level. Slow factor reallocation implies capital stock shares converge to current advanced economy shares only by 2050.
TFP: Within-sector TFP growth is assumed to remain constant at its current level, which—as discussed above—is at the higher end of different available estimates. Additionally, sectoral reallocation will continue in line with the assumptions on labor and capital shares, with the reallocation share in total TFP gradually falling over time.

18. Our baseline scenario suggests that potential growth is going to slow considerably over the medium- to long-term. We find that potential GDP growth rates could drop to about 4 percent on average between 2023-27 and 3 percent on average over 2028-37, implying per capita growth rates of similar magnitude over the same horizon. This compares to averages of around 6 percent sustainable GDP growth, 7 percent actual GDP growth, and 6 percent real per capita GDP growth over the last 10 years.

Scenario Assumptions in the Production Function

	Baseline	Upside
K	Investment-to-GDP ratio falls in line with savings rate by about 1 percent until 2050 (based on demographics & income).	Investment-to-GDP ratio falls to advanced economy (AE) average of 22 percent over 15 years.
K_i	Convergence to shares in AEs by 2050.	Convergence to AE shares within 15 years.
L	Total workforce in line with UN population projections, medium fertility scenario.	Retirement age gradually moves by 10 years (from 55 to 65) for females and by 5 years (from 60 to 65) for males over long-run.
L_i	Return to pre-pandemic trends; by 2050 convergence towards AE sectoral employment shares.	Reallocation towards services and AE shares over reform horizon of 15 years.
h	Continues to grow at current rate.	Human capital converges to current AE level within 15 years.
A_i	Stays constant at pre-pandemic growth rate.	No change for primary sector; secondary sector TFP lifted by 6 percent over 15 years on top of baseline to close SOE productivity gap plus 1ppt higher growth over 15 years from higher market dynamism; tertiary sector TFP improves with labor reallocation by 0.05ppt per 1ppt higher labor share.

Scenario Assumptions in the Production Function

	Baseline	Upside
K	Investment-to-GDP ratio falls in line with savings rate by about 1 percent until 2050 (based on demographics & income).	Investment-to-GDP ratio falls to advanced economy (AE) average of 22 percent over 15 years.
K_i	Convergence to shares in AEs by 2050.	Convergence to AE shares within 15 years.
L	Total workforce in line with UN population projections, medium fertility scenario.	Retirement age gradually moves by 10 years (from 55 to 65) for females and by 5 years (from 60 to 65) for males over long-run.
L_i	Return to pre-pandemic trends; by 2050 convergence towards AE sectoral employment shares.	Reallocation towards services and AE shares over reform horizon of 15 years.
h	Continues to grow at current rate.	Human capital converges to current AE level within 15 years.
A_i	Stays constant at pre-pandemic growth rate.	No change for primary sector; secondary sector TFP lifted by 6 percent over 15 years on top of baseline to close SOE productivity gap plus 1ppt higher growth over 15 years from higher market dynamism; tertiary sector TFP improves with labor reallocation by 0.05ppt per 1ppt higher labor share.

Upside scenario

19. To illustrate the scope for reform, the upside scenario assumes several growth-enhancing reforms compared to the baseline. Reforms are phased in linearly over 15 years starting in 2023. The main assumptions are the following (see Text Table for the production function assumptions):

SOE reforms: Implementation of SOE reforms help close the SOE-POE productivity gap in the manufacturing sector by improving resource allocation and deleveraging among SOEs. Jurzyk and Ruane (2021) estimate the counterfactual productivity gap to be around 6 percent. We assume this gap to extend to the entire secondary sector and to be closed by year 2038. We make the simplifying assumption that productivity reform alone will not have an impact on rebalancing.
Market dynamism: Pro-market reforms improve business dynamism, with higher firm entry and exit boosting productivity. In line with findings in Brandt and others (2020), we assume these reforms would boost productivity in the secondary sector by 1 percentage point over the reform horizon.
Demand-side rebalancing: A budget-neutral re-composition of fiscal expenditures toward households, including strengthening the social protection system (IMF, 2022), supports a reduction of the excessively high household savings rate and rebalancing toward consumption, triggering an expansion of services and consumer industries and associated investment. Consequently, the investment -to-GDP share is assumed to fall by around 18 percentage points over the reform horizon as it converges to current advanced economy ratios, implying an improvement in the ratio of private consumption of a similar magnitude. Sectoral reallocation of labor and capital will occur faster than under the baseline scenario as higher consumption implies more demand for services, increasing factor demand in the sector relative to the other sectors.⁴ Reallocation of resources from less productive to more productive sectors is assumed to boost tertiary sector TFP by 0.05 percentage points per additional percentage point of higher labor share (see Nabar and N’Diaye, 2013) on the back of higher investments and within-sector reallocation over the reform horizon.
Retirement age reform: To address changing demographics, labor market reforms gradually lift the retirement age from 60 (male) and 55 (female) to 65 over the long run, thus enlarging the potential workforce. This is in line with suggestions in IMF (2022).
Education reform: Reforms that further improve access to and enhance the quality of education boost human capital, with human capital converging to current advanced economy levels over the reform horizon.

We find that potential growth would be significantly higher under our upside scenario than the baseline over the reform period. The scenario implies average GDP growth rates of about 4.5 percent between 2023-37 and a similar per capita growth rate. The reforms are estimated to lift the level of real GDP by around 2.5 percent by 2027 compared to the baseline scenario, and by around 18 percent by 2037, with the bulk of the benefits stemming from productivity-enhancing reforms (Text Figure). Combined with a re-orientation of fiscal resources toward household support, domestic consumption would increase significantly, with the higher consumption share of GDP by around 18 percentage points in 2037 translating to an improvement in consumption of 75 percent over the same time period.

20. These reform policies would also ensure growth benefits are shared more broadly and offer faster progress towards China’s climate goals. In particular, China would not only narrow the gap to advanced economies in terms of per capita GDP (Text Figure) but—thanks to the lower energy intensity of a more balanced GDP growth—make faster progress towards its climate goals, with the direct effect on CO2 emissions a reduction of about 15 percent by 2037 (Chateau and others, 2022). Productivity enhancing SOE reforms could also support decarbonization goals, especially since estimates suggest that SOEs generate about half of the country’s total GHG emission (Clark and Benoit, 2022), while typically having easier access to credit.

21. Finally, growth would also be less risky. Under the same path for fiscal policy, higher growth would reduce augmented public debt by 2037 from 173 percent of GDP under the baseline to 146 percent of GDP in the upside scenario. This would create additional fiscal space the authorities could build as a buffer. The corporate debt burden would also fall, mainly because of higher growth. The reduction in saving rates would also make the economy less prone to asset bubbles and provide a sustainable driver for non-real estate investment.

E. Conclusion

22. China’s potential growth has started falling and several headwinds suggest it will continue to slow, showing the need for comprehensive reforms of China’s growth model. With an ageing population, slowing aggregate productivity, as well as record-high investment rates that have pushed investment into less productive sectors, potential growth under a baseline medium- to long-term scenario is expected to fall. Without reform efforts, aging and declining productivity would likely continue to suppress growth over the long term, beyond our forecast horizon. These pressing factors suggest the need to rebalance away from the investment-led, carbon-intensive, growth model towards more sustainable growth drivers, in particular consumption. Such a demand-side transformation could be an important step on China’s path to an advanced economy. Additional downside risks, such as a prolonged adherence to zero-COVID policies, geoeconomic fragmentation and reduced technology knowledge exchange amid technological decoupling, could further dampen short- to medium-term prospects.

23. Under a comprehensive reform scenario, steps to lift productivity growth and foster rebalancing towards sustainable, less investment-driven growth can significantly raise China’s growth potential. A return to market-based structural reforms addressing productivity issues could lift aggregate TFP. In addition, reallocating capital between SOEs and POEs and from infrastructure and real estate into more productive manufacturing or services sectors would help lift overall productivity. SOE reforms to enhance productivity in the use of carbon-intensive inputs, while stimulating innovation in renewables, could also support growth. Furthermore, to shift reliance towards more sustainable demand drivers, moving to more consumption-based growth would expand the services sector and rebalance away from excessive, low-productivity investment. These policies would not only raise growth and output levels, but reduce risks, raise welfare, and make growth more sustainable, balanced, and green.

Annex I. Methodology

We rely on a standard Cobb-Douglas production function describing the supply side of output:

Y_{t} = A_{t} K_{t}^{α} {(L_{t} h_{t})}^{β} (1)

with Y = real GDP, A = total factor productivity (TFP), K = capital stock (derived from investment I and depreciation rate δ via the perpetual inventory method), L = labor, h = human capital, α = elasticity of output to capital, β = elasticity of output to labor, and t = years.

By log-linearizing and taking first differences, we can express equation (1) in growth rates, with $\hat{X}$ denoting the growth rate of variable X:

{\hat{Y}}_{t} = {\hat{A}}_{t} + α {\hat{K}}_{t} + (1 - α) {\hat{L}}_{t} + (1 - α) {\hat{h}}_{t} (2)

Potential growth ${\hat{\tilde{Y}}}_{t}$ is thus defined by the following equation, taking into account the trend $\tilde{X}$ of each variable X (derived through a Hodrick-Prescott filter) to abstract from the business cycle:

{\hat{\tilde{Y}}}_{t} = {\hat{\tilde{A}}}_{t} + α {\hat{\tilde{K}}}_{t} + (1 - α) {\hat{\tilde{L}}}_{t} + (1 - α) {\hat{\tilde{h}}}_{t} (3)

In the historical decomposition, TFP is derived as the residual of the production function:

{\hat{A}}_{t} = {\hat{Y}}_{t} - α {\hat{K}}_{t} - (1 - α) {\hat{L}}_{t} - (1 - α) {\hat{h}}_{t} (4)

We adjust equation (3) by also taking into account a sectoral decomposition, in which each sector i = primary, secondary, tertiary sector is described by a Cobb-Douglas production function analogous to the economy-wide function:

Y_{i, t} = A_{i,}_{t} K_{i, t}^{α} {(L_{i, t} h_{i, t})}^{(1 - α)} (5)

With $Y_{t} = \sum_{i = 1}^{3} Y_{i, t} and {\hat{Y}}_{i, t} = {\hat{A}}_{i, t} + α {\hat{K}}_{i, t} + (1 - α) {\hat{L}}_{i, t} + (1 - α) {\hat{h}}_{i, t}$ , assuming α the same across all sectors and human capital $\hat{h_{i, t}} = \hat{h_{t}}$ , we can decompose overall TFP from equation (4) into a within-sector TFP growth component and a reallocation factor:

{\hat{A}}_{t} = \underset{Within-sector TFP growth}{\underset{︸}{\sum_{i = 1}^{3} (\frac{Y_{i}}{Y}) {\hat{A}}_{i}}} + α \underset{Factor reallocation across sectors}{\underset{︸}{\sum_{i - 1}^{3} (\frac{Y_{i}}{Y} - \frac{K_{i}}{K}) \hat{K_{i}} + (1 - α) \sum_{i = 1}^{3} (\frac{Y_{i}}{Y} - \frac{L_{i}}{L}) \hat{L_{i}}}} (6)

And can thus express potential growth as:

\hat{\tilde{Y_{t}}} = A_{t}^{\hat{\tilde{w i t h i n}}} + A_{t}^{r e a l \hat{\tilde{l o c a t i}} o n} + a {\hat{\tilde{K}}}_{t} + (1 - α) {\hat{\tilde{L}}}_{t} + (1 - α) {\hat{\tilde{h}}}_{t} . (7)

Annex II. Data

CI. Real GDP (from NBS); sectoral GDP shares based on nominal GDP shares.

CII. Capital stock sourced from Herd (2020), extended by the perpetual inventory method using real gross fixed capital formation (staff estimates based on NBS data) and depreciation rates from Herd (2020). Sectoral capital stock based on Wu (2016) for the initial period and subsequent investment shares based on sectoral shares in fixed asset investment. This data is based on urban investment and thus likely underestimates investment in the primary sector.

CIII. Labor is proxied by the working age population (15-59 for males, 15-54 for females); sectoral labor is based on employment shares by sector, sourced from NBS.

CIV. Human capital is based on an index from Penn World Tables 10.0, based on average years of schooling and returns to education.

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Prepared by Anne Oeking, Natalija Novta, and Fan Zhang.

Augmented debt is comprised of official general government debt (central and explicit local government debt, including general and special local government bonds and other recognized off-budget liabilities incurred by end-2014) and off-budget liabilities estimated by staff (debt of local government financing vehicles, government-guided funds, and special construction funds).

We will refer to the main sectors of China’s economy as the primary, secondary, and tertiary sectors. The primary sector encompasses agriculture, forestry, animal husbandry and fishery industries, the secondary sector includes not only manufacturing, but also construction, mining and quarrying, and production and supply of utilities. The tertiary sector encompasses all other industries.

The rise of the tertiary sector and the decline or leveling-off of the secondary sector need not hinder economy-wide productivity growth even as aggregate productivity in the secondary sector is higher. Market-based service subsectors, such as finance and telecommunications, have labor productivity growth as high or higher than the manufacturing sector in a cross section of countries (IMF, 2018). In China’s case, Zhu and others (2019) show how sectoral transitions within the manufacturing and services sector based on significant variation in productivity within those sectors could be an important buffer to moderate a productivity slowdown. In addition, resolving resource misallocation would help outweigh downward pressures.

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People’s Republic of China: Selected Issues

Author:

International Monetary Fund. Asia and Pacific Dept

Volume/Issue:: Volume 2023: Issue 081

Publisher:: International Monetary Fund

ISBN:: 9798400233517

ISSN:: 1934-7685

Pages:: 96

DOI:: https://doi.org/10.5089/9798400233517.002

Keywords
Sustainable and Balanced Growth in the Longer Term1
Annex I. Methodology
Annex II. Data
References

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Investment and Private Consumption

(In percent of GDP)

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Consumption Across Countries vs. China Over Time

(In percent)

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Investment Across Countries vs. China Over Time

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Credit to GDP Gap

(In percent of GDP)

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Marginal Product of Capital

(Marginal product of capital = ratio of change in output to change in capital stock)

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Average Growth Rate of Sectoral Investment

(In percent)

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Estimated Aggregate TFP Growth

(In percent, detrended)

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TFP Growth Estimates

(In percent)

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Sectoral TFP Growth Estimates

(In percent, detrended)

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Potential Growth

(In percent)

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Estimated Workforce

(In hundred thousand people)

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Potential Growth Estimate, Baseline

(In percent)

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Potential Growth Estimate, Upside

(In percent)

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Gains Over the Reform Period in Upside Scenario

(In percent)

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Potential Growth in the Cross-Section

(In percent)

Foresee

Scenario Assumptions in the Production Function

	Baseline	Upside
K	Investment-to-GDP ratio falls in line with savings rate by about 1 percent until 2050 (based on demographics & income).	Investment-to-GDP ratio falls to advanced economy (AE) average of 22 percent over 15 years.
K_i	Convergence to shares in AEs by 2050.	Convergence to AE shares within 15 years.
L	Total workforce in line with UN population projections, medium fertility scenario.	Retirement age gradually moves by 10 years (from 55 to 65) for females and by 5 years (from 60 to 65) for males over long-run.
L_i	Return to pre-pandemic trends; by 2050 convergence towards AE sectoral employment shares.	Reallocation towards services and AE shares over reform horizon of 15 years.
h	Continues to grow at current rate.	Human capital converges to current AE level within 15 years.
A_i	Stays constant at pre-pandemic growth rate.	No change for primary sector; secondary sector TFP lifted by 6 percent over 15 years on top of baseline to close SOE productivity gap plus 1ppt higher growth over 15 years from higher market dynamism; tertiary sector TFP improves with labor reallocation by 0.05ppt per 1ppt higher labor share.

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Abstract

Sustainable and Balanced Growth in the Longer Term1

A. Introduction

B. Background

C. Approach and Historical Decomposition

D. Forecast Scenarios

Baseline scenario

Upside scenario

E. Conclusion

Annex I. Methodology

Annex II. Data

References

Other IMF Content

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Asian Development Bank

Inter-American Development Bank

International Labour Organization

Nordic Council of Ministers

The World Bank

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Sustainable and Balanced Growth in the Longer Term¹