Abstract
The Chinese authorities welcomed the spillover analysis, noting that their policies have important global spillover effects. The note also discusses China’s evolving role in global trade, impact of rebalancing on the supply chain, estimating China’s spillovers, elasticities approach, factor pricing, overcapacity, and sustainability risks. It elaborates on the impact of competition from Brazil and Mexico, China’s closed capital account and capital flows to emerging markets, the impact of China’s saving on global financial conditions, and potential impact on global bond markets of reallocating reserves.
IV. FACTOR PRICING, OVERCAPACITY, AND SUSTAINABILITY RISKS1
This chapter examines the argument that distortions in factor markets effectively subsidize China’s tradables investment. It finds that distortions in capital costs are substantial and have increased over time. Moreover, the export-oriented growth model looks increasingly unsustainable. Delays in reform pose the risk of significant spillovers in the interim.
A. Factor Pricing
1. Factor costs. In addition to an undervalued exchange rate, China’s export-oriented growth model has relied on a combination of distorted factor prices. Distortions to capital, labor, land, energy, and environmental prices have been suggested in the literature (e.g. Huang, 2010). Huang and Kunyu (2010) suggest the estimated extent of aggregate distortions have declined from a peak of around 12 percent of GDP in 2006 to around 9½ percent in 2009. More directly, the extent of the potential distortion can be seen from the gap between Chinese interest rates and growth, and the relatively low price of gasoline.
Real Lending Rate less GDP Growth, 2004 - 2008
(in percent)
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
Source: International Financial Statistics, IMF.Real Lending Rate less GDP Growth, 2004 - 2008
(in percent)
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
Source: International Financial Statistics, IMF.Real Lending Rate less GDP Growth, 2004 - 2008
(in percent)
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
Source: International Financial Statistics, IMF.
International Comparison Retail Price of Gas
(U.S. Dollar per Litre)
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
International Comparison Retail Price of Gas
(U.S. Dollar per Litre)
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
International Comparison Retail Price of Gas
(U.S. Dollar per Litre)
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
2. Aggregate estimate. A measure of the aggregate factor cost distortions can be constructed from aggregate production and income data.2 Applying the methodology of Aziz (2006) to China, the implied tax on capital is significantly negative over much of the period since 1990 and has become more negative over the past decade, suggesting distortions amounting to substantial subsidies to capital over this period. Many other countries effectively tax capital or have smaller implicit subsidies, particularly since 2000. Given the undervalued exchange rate and the capital intensity of the tradables sector, new investment spending has been largely concentrated in tradables.
Imputed Tax/Subsidy on Capital Costs
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
1/ Includes Indonesia, Korea, Singapore, and Taiwan Province of China.Imputed Tax/Subsidy on Capital Costs
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
1/ Includes Indonesia, Korea, Singapore, and Taiwan Province of China.Imputed Tax/Subsidy on Capital Costs
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
1/ Includes Indonesia, Korea, Singapore, and Taiwan Province of China.
Sectoral Fixed Asset Investment
(In percent of Fixed Asset Investment Spending)
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
Sectoral Fixed Asset Investment
(In percent of Fixed Asset Investment Spending)
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
Sectoral Fixed Asset Investment
(In percent of Fixed Asset Investment Spending)
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
B. Sustainability and Competitiveness
3. Unsustainable? China’s current growth pattern, without rebalancing, would require continued gains in market share in the global market. Absent substantial productivity growth or further subsidies with undesirable distortions, large price cuts (and an associated squeeze of profit margins) could be unavoidable to gain the required market share.
Market Shares of Selected Economies since Growth Take-off
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
Market Shares of Selected Economies since Growth Take-off
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
Market Shares of Selected Economies since Growth Take-off
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
4. Illustration. An illustrative scenario in Guo and N’Diaye (2010) suggests that key industries could see their profit margins evaporate in a few years in order to gain the required market shares, particularly those with thin profit margins and large capacities (e.g., steel). The mismatch between the buildup of tradable manufacturing capacity in China and the lack of strong external demand could have significant implications for the balance sheets of the corporate and banking sectors.
5. Spillovers. Based on the estimates from a global vector autoregression (GVAR, see Chapter VI), a deterioration in the quality of non-financial corporate and financial balance sheets in China would have substantial negative effects on the rest of the world, particularly on the regional supply chain and commodity exporters.
Corporates. An increase in Chinese corporate default probabilities (a measure of balance sheet deterioration) by 10 percentage points could lower industrial output in other economies by as much as 3⅓ percent among emerging Asian economies and 2 percent of GDP in commodity exporters.
Banks. A similar deterioration in bank balance sheets would have somewhat larger impacts. An increase in Chinese banks’ default probability by 10 percentage points could lower industrial output in Japan and emerging Asia by about 3⅓ percent. U.K. industrial output would also be lower by about 5 percent. Many other economies, such as in the Euro Area, could also experience some decline in industrial production.
Caveat The measure of financial stress is indicative of problems in balance sheets that would affect real activity, at least until policies are implemented to either resolve the problems directly or to transfer them out of the banks’ balance sheets and, as some expect, onto the balance sheet of the public sector.
6. Historical default rates. Historical evidence from China and the U.S. suggest that a significant hike in the default probability could occur following the booms, particularly investment driven ones. The default probability of the Chinese banking sector increased by more than 200 bps following the credit boom in the early 2000’s. In the U.S., corporate default rates also increased by a similar magnitude during the 1990–1991 recession and after the crash of the dot-com bubble (Maurer, Nguyen, Sarkar and Wei, 2008). Historically, the U.S. has experienced even higher (double-digit) corporate default rates after large booms, e.g. 13 percent in the Great Depression, and 36 percent after the bursting of the railroad investment bubble (Giesecke, Longstaff, Schaefer and Strebulaev, 2010).
China:Credit Growth (y/y) and Banks 1-Year Ahead Default Probability
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
China:Credit Growth (y/y) and Banks 1-Year Ahead Default Probability
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
China:Credit Growth (y/y) and Banks 1-Year Ahead Default Probability
Citation: IMF Staff Country Reports 2011, 193; 10.5089/9781462342570.002.A005
References
Aziz, Jahangir, 2006, “Rebalancing China’s Economy: What Does Growth Theory Tell Us?,” IMF Working Paper 06/291.
Huang, Yiping, 2010, “China’s Great Ascendency and Structural Risks: Consequences of Asymmetric Market Liberalization,” Asian-Pacific Economic Literature, Vol. 24, pp. 65–85.
Huang, Yiping and Tao Kunyu, 2010, “Causes and Remedies of China’s External Imbalances,” China Center for Economic Research Working Paper 2010–02.
Giesecke, Kay, Francis Longstaff, Stephen Schaefer and Ilya Strebulaev, 2010, “Corporate Bond Default Risk: A 150-Year Perspective,” NBER working paper 15848.
Guo, Kai and Papa N’Diaye, 2009, “Is China’s Export-Oriented Growth Sustainable?,” IMF Working Papers 09/172.
Maurer, Samuel, Luu Nguyen, Asani Sarkar, and Chenyang Wei, 2008, “Financial innovation and corporate default rates,” Proceedings of the IFC Conference, BIS.
Xiang, Tang, “Solving the “China Price” Puzzle: An Input-Output Analysis,” Peking University School of Economics Working Paper C-2010-09-009.
Illustrative Conditions to Sustain China’s Growth Strategy
end of period.
Average 2005–2007.
Illustrative Conditions to Sustain China’s Growth Strategy
| 2007 | Baseline 2011–2020 | |||||
|---|---|---|---|---|---|---|
| Production volume | ||||||
| Steel (in percent of world production) | 35.5 | 53.6 1/ | ||||
| Ship building | 18.4 | 61.7 1/ | ||||
| Machine tools | 15.0 | 30.2 | ||||
| Excess capacity utilization rate (in percent) | ||||||
| Steel | 18.5 | -84.2 | ||||
| Ship building | ||||||
| Machine tools | ||||||
| Annual investment growth | ||||||
| Steel | 12.3 2/ | 9.4 | ||||
| Ship building | 8.5 | |||||
| Machine tools | 34.7 | 15.0 | ||||
| Annual average profit margin | ||||||
| Steel | 5.5 | |||||
| Ship building | 9.6 | |||||
| Machine tools | 6.4 | |||||
| Scenario: Annual average export growth | ||||||
| Steel | 66.6 2/ | 18.3 | ||||
| Of which: | ||||||
| Annual average world demand | 14.0 | |||||
| Cumulative required price change | -24.4 | |||||
| Ship building | 31.5 | 18.3 | ||||
| Of which: | ||||||
| Annual average world demand | 17.8 | |||||
| Cumulative required price change | -12.8 | |||||
| Machinery | 14.7 | 18.3 | ||||
| Of which: | ||||||
| Annual average world demand | 15.8 | |||||
| Cumulative required price change | -14.5 | |||||
end of period.
Average 2005–2007.
Illustrative Conditions to Sustain China’s Growth Strategy
| 2007 | Baseline 2011–2020 | |||||
|---|---|---|---|---|---|---|
| Production volume | ||||||
| Steel (in percent of world production) | 35.5 | 53.6 1/ | ||||
| Ship building | 18.4 | 61.7 1/ | ||||
| Machine tools | 15.0 | 30.2 | ||||
| Excess capacity utilization rate (in percent) | ||||||
| Steel | 18.5 | -84.2 | ||||
| Ship building | ||||||
| Machine tools | ||||||
| Annual investment growth | ||||||
| Steel | 12.3 2/ | 9.4 | ||||
| Ship building | 8.5 | |||||
| Machine tools | 34.7 | 15.0 | ||||
| Annual average profit margin | ||||||
| Steel | 5.5 | |||||
| Ship building | 9.6 | |||||
| Machine tools | 6.4 | |||||
| Scenario: Annual average export growth | ||||||
| Steel | 66.6 2/ | 18.3 | ||||
| Of which: | ||||||
| Annual average world demand | 14.0 | |||||
| Cumulative required price change | -24.4 | |||||
| Ship building | 31.5 | 18.3 | ||||
| Of which: | ||||||
| Annual average world demand | 17.8 | |||||
| Cumulative required price change | -12.8 | |||||
| Machinery | 14.7 | 18.3 | ||||
| Of which: | ||||||
| Annual average world demand | 15.8 | |||||
| Cumulative required price change | -14.5 | |||||
end of period.
Average 2005–2007.
Prepared by Kai Guo (SPR) and Nathan Porter (SPR) with helpful inputs from Papa N’Diaye (APD).
Aziz (2006) uses growth accounting to calculate the implicit tax (or subsidy, if negative) on investment such that aggregate productivity, factor use, and consumption are consistent with a model-based benchmark. Since this essentially measures the distortion in the cost of capital required to account for the difference between economic behavior described in the aggregate data and a distortion-free benchmark, it provides a single measure of all distortions. In particular, it can be used to track changes in aggregate distortions over time.
