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Alexander Al-Haschimi
Tajda Spital
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The evolution of China's growth model: challenges and long-term growth prospects

Prepared by Alexander Al-Haschimi and Tajda Spital

Published as part of the ECB Economic Bulletin, Issue 5/2024.

1 Introduction

China’s rapid economic transformation to become the world’s second-largest economy is inextricably linked to its investment-led growth model. This investment has been financed by high levels of domestic savings resulting from a number of government policies.[1] These savings have been channelled into a financial system that has provided highly-subsidised lending for infrastructure, manufacturing and real estate investment. As a result, China has achieved high rates of economic growth by ramping up its level of investment faster than most other countries at a similar level of development (Chart 1, panel a).[2]

Nevertheless, this investment-led growth model is coming under increasing pressure. First, diminishing rates of return imply that it is becoming more difficult to generate growth from one additional unit of investment, and some observers believe that China has long passed the point at which it can productively absorb these high rates of investment. Second, a policy-driven severe downturn in China’s property sector, which accounted for about 30% of GDP before the real estate downturn in 2021, is set to sustainably diminish this major pillar of domestic demand. Third, external demand is also shrinking, as trade tensions are increasing and a rising number of trading partners are unwilling to further accommodate higher trade deficits with China. More generally, structural challenges, including an ageing population and low productivity growth, are adding to the headwinds faced by China’s economy.

In response to these challenges, China’s government is redoubling its efforts to spur growth through investment-centric policies. This additional push to boost investment appears to be driven almost exclusively by the state-owned sector, whereas fixed asset investment by the private sector has stalled since the onset of the housing crisis in 2021 (Chart 1, panel b). Government policies to expand output in the face of slowing demand have potential implications for China’s trading partners. A supply-driven expansion of production could materially affect trade prices and hence inflation in their economies. The shift towards manufacturing previously-imported advanced goods is designed to enhance China’s self-reliance, thereby reducing the import intensity of its growth while shifting competitiveness and trade balances in relation to its trading partners.

Against this background, this article will briefly summarise China’s investment-led growth model and assess supply-demand imbalances in its manufacturing sector. It will then evaluate the potential spillover effects for China’s trading partners and review the policy implications for key advanced economies.

Chart 1

China’s investment-led growth model

a) Investment by stage of development

b) China’s investment by source

(x-axis: GDP per capita in US dollars based on 2017 purchasing power parities; y-axis: total investment as a percentage of GDP)

(index, 2019=100; 12-month moving average)

Source: World Bank, Penn World Tables, National Bureau of Statistics of China and ECB staff calculations.
Notes: GDP per capita from 2020 to 2022 is extrapolated based on World Bank data. The starting point for investment shares is GDP of USD 2,000 or above. The latest observations are for 2022 (panel a) and April 2024 (panel b).

2 The evolution of China’s economic growth drivers

Investment remains a major growth driver in China. In the 30 years leading up to 2010, the share of investment in China’s GDP gradually rose from 35% to 47% (Chart 2). By comparison, the typical investment-to-GDP ratio for developed economies is about 20%, whereas post-Soviet countries averaged about 30% in the first ten years after their transition to a market economy. Over the same 30-year period, the share of final consumption fell steadily from about 65% to below 50% in 2010. By comparison, the contribution of net trade to annual growth ranks significantly below that of investment and consumption. The net trade contribution to annual real GDP averaged 0.9 percentage points in the 1990s and since 2000 has averaged 0 percentage points. While integration into global value chains was instrumental in its technological development, China continued to have a high rate of imports, partly due to imports of intermediate goods processed for manufacturing exports but also imports of investment goods, such as machinery, to upgrade its productive capacities. For many decades, high investment rates provided the necessary upgrades to infrastructure and modernised China’s production technology, helping the country to become a global manufacturing powerhouse.

However, over time, high rates of investment face diminishing rates of return. Despite already high rates of investment, China’s government proceeded with two further investment waves after the global financial crisis. The first was a response to the Great Recession, which saw the Chinese government implement a large-scale stimulus programme focusing on infrastructure and real estate, bringing annual state-financed fixed asset investment growth rates in 2008 and 2009 to 36% and 60% respectively. Once the stimulus policies came to an end, however, significant overcapacity had built up in a number of sectors. By 2015 the government reacted with supply-side reforms, which among other things aimed to reduce excess industrial capacity in specific industries, resolve unprofitable firms and reduce the stock of unsold housing.[3] The second investment wave started in 2020 as a response to the coronavirus (COVID-19) pandemic, when the Chinese government targeted its support programmes at firms with the aim of increasing growth across all manufacturing sectors, including those previously subjected to capacity reduction efforts in 2015. As a result, productive capacity built up again owing to supply-driven factors, outpacing demand, which was more subdued as a result of the zero-COVID policy.

Chart 2

Long-term trend in China’s output components

a) Total investment as a share of GDP

b) Final consumption as a share of GDP

(percentage share of GDP)

(percentage share of GDP)

Source: OECD and ECB staff calculations.
Note: The latest observations are for 2022.

Structural and cyclical factors are increasingly weighing on demand

Since the global financial crisis, GDP growth has been on a secular decline in China, partly due to structural headwinds. Total factor productivity (TFP) began to decline as additional infrastructure spending enhanced productivity less over time. While aggregate annual TFP growth was 2.8% in the ten years leading up to the Great Recession, it slowed to 0.7% over the period 2009-18. In addition, China’s working age population started to decline in 2011. According to UN estimates, by 2050 it will have declined by nearly a quarter. These headwinds are already depressing China’s potential growth rate and this downward trend is likely to persist (see Box 1 for a model-based analysis).

In addition, cyclical demand factors became negative during the pandemic. Consumer demand fell sharply during the pandemic, as uncertainty amid pandemic restrictions led to a rise in precautionary savings (Chart 3). This was sustained by the housing crisis, which started in 2021 and further depressed consumer demand, given that the dominant share of household wealth in China is linked to the property sector.

Chart 3

Consumer confidence and real estate sector developments

(standardised index and index, 2019=100)

Source: National Bureau of Statistics of China and ECB staff calculations.
Notes: The latest observations are for April 2024 for consumer confidence and May 2024 for the real estate climate index. The real estate climate index summarises a set of indicators for real estate investment, capital, area and sales.

The current housing crisis is likely to make future investment less inward facing

The housing crisis severely impaired one of the three main pillars of investment growth. Total fixed asset investment in China consisted predominantly of three categories in roughly equal parts: infrastructure, real estate and manufacturing. The rapidly growing housing sector increasingly coincided with rising levels of leverage among developers, while the stock of housing began to outstrip demand in a growing number of regions. The Chinese authorities took steps in 2020 to rebalance and derisk the sector. With new restrictions on leverage, the derisking policies are also designed to achieve a long-term reduction in the overall size of the sector in terms of share of GDP. The resizing of the sector, amid a liquidity crisis among developers, led real estate investment growth to turn negative in late-2021 (Chart 4). In the absence of the real estate investment pillar, the investment-led growth model now relies more heavily on infrastructure and manufacturing investment to support economic growth.

Chart 4

Fixed asset investment by sector

(year-to-date year-on-year growth)

Source: National Bureau of Statistics of China.
Note: The latest observation is for April 2024.

Infrastructure and manufacturing investment are more likely than housing investment to be export oriented. China’s push to become self-reliant and further develop its high technology sector implies that its infrastructure spending is changing. There will be less emphasis on building roads and bridges and more on building new infrastructure aimed at developing sectors, such as telecommunications networks, high-speed rail networks, and research and development facilities, which support advanced manufacturing. The most recent announcements made by China’s government to build “new productive forces” to shore up growth targeted these sectors. Specifically, the government aims to support new technology sectors such as electric vehicles (EVs), microchip technology and new materials. Given the subdued outlook for domestic demand as a result of the ongoing housing sector weakness, this additional capacity will materialise over the next few years to a significant extent in the export sector, which will have potentially important implications for China’s trading partners.

Box 1
China’s long-term growth prospects

Prepared by Sergiu Dinu and Seng Guan Toh

The recent decade has seen a slowdown in China’s growth trajectory, particularly after the global financial crisis. As income levels in China approach those in more advanced economies, a further slowdown is expected, mirroring the convergence experienced in other fast-growing East Asian economies. Demographics would also suggest lower potential growth, as China’s population is declining and it is faced with growing external constraints (e.g. tariffs and export controls imposed by advanced economies) that may hinder its attempts to catch up with the technological frontier.

This box summarises the findings of a model-based analysis of China’s longer-term growth prospects to quantify several structural drivers that are pertinent to its growth model.[4] The model is based on an extension of the neoclassical growth framework entailing a total factor productivity (TFP) catch-up process which describes how China catches up with the world technology frontier (represented by the United States).[5] This model uses Penn World Table data covering 1995-2019 and is calibrated to match historical data on labour developments, capital and TFP. The findings of the analysis point to the importance of both demographics and productivity as structural determinants to understand and address China’s growth-related challenges.

A baseline scenario evaluates potential long-term economic growth based on the following assumptions: a stable labour force participation rate, demographic developments based on UN medium-fertility forecasts and a continuation of historical TFP trends.[6] Baseline projections indicate that ageing and the downward trend in productivity growth would lead to a decline in the annual GDP growth rate from 5.3% in 2025 to 3.7% in 2035.[7] In other words, these two structural factors would reduce the annual growth rate by 1.6 percentage points over the decade to 2035. The baseline projections are necessarily subject to high uncertainty. To assess the impact of variations in the baseline, these projections are then compared with two alternative scenarios which quantify the impact of more adverse structural developments on the GDP growth rate. They are: (i) less benign demographic developments reflecting a stronger fall in the fertility rate; and (ii) a more adverse TFP growth slowdown scenario based on an Asian Development Bank paper, further compounded by additional foreign direct investment (FDI) outflows assumed to be the result of global value chain (GVC) fragmentation.[8]

China’s fast demographic shift to a declining population threatens to limit the labour supply. The repercussions of China’s now defunct one-child policy exacerbate the current issues of decreasing fertility and gender imbalance, which contributed to a fall in the population in 2022 for the first time since 1960. In the medium term, less optimistic demographic developments in the form of lower population growth are expected to cut the aggregate GDP growth rate per annum in 10 years’ time by more than 0.2 percentage points relative to the baseline (Table A).

China’s ability to deepen its domestic technological base faces risks from further fragmentation of GVC. Moreover, increasing uncertainty relating to regulatory and geopolitical risks coincides with rising outflows of FDI. A rise in GVC fragmentation could lead to further FDI outflows and accelerate the slowdown in TFP growth. This in turn could lower the 10-year-ahead baseline GDP growth rate by 0.6 percentage points.

Table A

Long-term structural growth of China

(percentages)

Year

Baseline

Demographics – Lower fertility

TFP slowdown –
FDI outflows 2021-26

2030

4.4%

4.2% (-0.2pp)

3.7% (-0.7pp)

2035

3.7%

3.5% (-0.2pp)

3.1% (-0.6pp)

2040

3.2%

2.9% (-0.3pp)

2.6% (-0.6pp)

2050

2.2%

1.9% (-0.3pp)

1.8% (-0.4pp)

Sources: Penn World Table 10.01, UN, OECD, Peschel and Liu, op. cit., State Administration of Foreign Exchange of China, ECB staff calculations.
Note: The numbers in brackets correspond to the percentage point (pp) deviations of the scenarios’ projections from the baseline projections.

3 China’s development of manufacturing capacity

The build-up of manufacturing capacity in China is historically unparalleled. China’s share of gross global manufacturing production rose from 5% to 35% over the course of 1995-2023, and it currently has a higher manufacturing output than that of the next nine largest manufacturing countries combined (Chart 5). This unprecedented rise in productive capacity did not just serve China’s large and growing domestic market but coincided with a rapidly rising share of world manufacturing exports, which grew from 3% in 1995 to 20% by 2020. If China is now aiming to invest further in productive capacities, this raises the question of whether the additional capacity will be absorbed domestically or externally.

Chart 5

Shares in global manufacturing value added by country or area

(percentage share)

Source: World Bank.
Note: The latest observations are 2021 for the United States and 2022 for the others.

There are signs that the recent rise in manufacturing output is creating distortions in the Chinese market. The supply of Chinese industrial firms outpaced demand, resulting in a build-up of inventories and a decline in prices, ultimately reducing firms’ profitability. The number of loss-making firms has doubled to 28% since 2018 in tandem with a considerable increase in the inventory-to-sales ratio (Chart 6).

Chart 6

Loss-making firms and inventories

(percentage share and ratio, 12-month moving average)

Sources: National Bureau of Statistics of China and ECB staff calculations.
Notes: The inventory-to-sales ratio refers to the ratio between the end-of-month inventories and monthly operating income of Chinese industrial companies. The latest observation is for April 2024.

China’s trading partners have been increasingly vocal about their level-playing-field concerns, as production surpluses are often linked to extensive government support. China’s industrial policy measures account for a much larger share of GDP relative to other economies (Chart 7). While direct subsidies account for only a small share of all measures, indirect subsidies, such as preferential access to lending, lower financing costs and land allocation are much more common.[9] These policies are predominantly accessible to public firms and government-linked private firms, while private and foreign firms do not have the same preferential access.[10]

Chart 7

Industrial policy comparison across countries

State subsidies as a share of GDP

(percentage share and percentage point contributions)

Source: Center for Strategic and International Studies.
Note: The estimates refer to 2019. For more details, see DiPippo, G. et al., “Red ink: estimating Chinese industrial policy spending in comparative perspective”, Center for Strategic and International Studies, May 2022.

Tracing excess capacity in China’s manufacturing sectors

Signs of rising overcapacity can materialise in different forms across sectors. The building of excess capacity can be defined as a level of production that cannot be absorbed by demand at current prices. An increase in output would thereby increase inventories, be sold at lower prices, or a combination of both. We provide three types of evidence for the existence of overcapacities in China, namely an overview of Chinese inventories and profits by sector, the latest business survey data of European companies in China, and a structural Bayesian VAR analysis of Chinese exports. First, we find that in a wide range of sectors, which together represent the majority of China’s manufacturing sector, the inventory-to-sales ratio has increased, highlighting that Chinese domestic output is currently expanding faster than sales (Chart 8). This is particularly evident for sectors linked to real estate, which faced a sudden and severe decline in domestic demand (especially in the cement, steel and metal products industries). Second, recent survey evidence confirms the existence of overcapacities and their disinflationary effects. In a recent survey by the European Union Chamber of Commerce in China, over one-third of respondents among European companies in China observed overcapacity in their industry in the past year and cited overinvestment as the main reason.[11] Moreover, in the sectors where overcapacities were observed, prices tended to decline. Overall, it emerges that where domestic demand cannot absorb the additional output, producers will aim to direct this excess capacity to export markets, often by lowering prices.

Chart 8

Overcapacity in Chinese sectors

Change in inventories-to-sales ratios and profit growth rates

(change and percentage point change between 2023 and 2015-19)

Sources: National Bureau of Statistics of China and ECB staff calculations.
Notes: The red columns refer to industries classified as “advanced manufacturing”, while the green columns refer to industries closely linked to the real estate sector. The remaining industries are shown in blue.

The rise in Chinese output is predominantly supply driven. As a third piece of evidence for the existence of overcapacities, a structural Bayesian VAR analysis is carried out to disentangle demand and supply factors in Chinese export growth.[12] It shows that in real estate-related industries, such as steel and other metals, exports over the past year have been almost entirely driven by supply factors, while foreign demand remained broadly neutral or negative (Chart 9, panel a). The same dynamics can be observed for motor vehicle exports (Chart 9, panel b). More generally, when comparing the share of supply factors in exports by sector, we find that over the past year, supply factors have become a growing driver of exports across a range of sectors compared with the 2017-19 period (Chart 9, panel c). The results show that the share of foreign demand in the exports of sectors related to the real estate and advanced manufacturing sectors in particular appear to be falling.

Chart 9

BVAR historical shock decomposition of Chinese exports

a) Foreign demand and Chinese domestic supply factors in steel and other metal exports

b) Foreign demand and Chinese domestic supply factors in motor vehicle exports

(percentage deviation from the mean and percentage point contributions, year on year)

(percentage deviation from the mean and percentage point contributions, year on year)


c) Change in domestic supply contribution by sector

(percentage share of domestic supply shocks in total deviations from the mean)

Sources: National Bureau of Statistics of China and ECB staff calculations.
Notes: Panels a) and b) show the median posterior distribution of the historical decomposition of Chinese exports in deviation from its initial condition. All variables are measured in log levels, while the chart shows the decomposition in year-on-year growth rates. In panel c), the x-axis measures the share of domestic supply shocks in total deviation from the mean between 2017 and 2019 based on a BVAR historical shock decomposition. The y-axis shows the average share between the second quarter of 2023 and the first quarter of 2024. For sectors above the diagonal line, it could be implied that domestic supply factors are behind the increase in exports, and thus more likely to have built up overcapacity. The latest observations are for March 2024.

4 Global implications of China’s investment policies

China’s efforts to further invest in the productive capacities of highly subsidised industries has global implications for its trading partners. To the extent that additional output cannot be entirely absorbed domestically and external demand remains broadly constant, a rise in China’s exports necessitates a further increase in its global share of manufacturing exports. Given recent tariff action against China, a further expansion of its export market share may not go unchallenged in global markets. Moreover, by lowering prices or increasing exports of heavily-subsidised products, a rise in exports could lead to international spillovers of disinflationary pressures. These could be further exacerbated if trading partners’ domestic firms in turn lower their prices to remain competitive with Chinese exports. Finally, with China’s development of its advanced manufacturing capacities, particularly in green technology sectors, the relatively larger size of state subsidies in China could also affect the competitiveness of trade partners in these relatively new and growing advanced manufacturing sectors.

Impact on euro area prices by sector

A static exercise modelling a further decline in Chinese export prices in sectors with overcapacity would have a downward impact on euro area consumer prices, which could be amplified through a subsequent decline in euro area producer prices. To quantify the potential impact, we perform a sectoral bottom-up analysis based on the elasticities of international production networks captured in input-output tables.[13] We first assume a 30% drop in Chinese export prices in sectors identified as having overcapacities in our BVAR analysis.[14] The decrease in price is calibrated by considering past price movements in the solar panel industry, as this industry can serve as a case study for potential developments in other green technology industries.[15] The simulation results find that the decline in Chinese export prices would lead to a 0.3 percentage point fall in euro area consumer price inflation. This result consists of a smaller direct impact through consumption of Chinese final products, and a larger indirect impact through intermediate input linkages, reflecting the rich interdependencies of euro area and Chinese production networks. Second, we look at how this change is amplified if euro area producers lower their prices in response to cheaper Chinese products. We consider a 7% decrease in the prices of euro area producers. This is calibrated by considering the differential in government subsidies between China and Germany, as German subsidies account for about one-quarter of those of Chinese producers.[16] The price reduction by euro area producers in affected sectors results in an additional 0.6 percentage point drop in euro area consumer price inflation (Chart 10). While the imposition of tariffs could mitigate this impact, it could vary across different products and producers and potentially lead to retaliatory measures.

Chart 10

Impact of declining Chinese trade prices on euro area prices by sector

a) Cumulative impact and contribution of individual sectors

(percentage point changes)


b) Impact on individual sectors and contribution of direct and indirect spillovers

(percentage point changes)

Sources: Trade in Value Added (TiVA) input-output tables and ECB staff calculations.
Notes: The chart shows analysis based on the elasticities of international production networks captured in input-output tables. The chart shows the cumulative impact of declining prices on euro area consumer prices in Chinese sectors previously identified as having overcapacity (panel a) (see BVAR analysis above). It also shows the contribution of individual sectors (panel b). The positive technology shock is standardised to produce a 30% decrease in Chinese export prices in each sector and a reciprocal 7% decrease in euro area producer prices. The blue and red bars show the direct impact that changes in Chinese export prices have on final consumption in the euro area, while the yellow and green bars show the indirect impact, accounting also for intermediate input interlinkages. The latest observation is for 2020.

Impact on China’s competitiveness

China’s share of global exports has been consistently increasing, particularly in the advanced manufacturing and green technology sectors. These gains in market share can be observed across the board, including in industries where we find traces of overcapacity (Chart 11).[17] Rapid expansion is particularly evident in the new green technology industries, where China’s growing share of the solar panel industry serves as a cautionary tale for other emerging green industries (Chart 12). To assess the potential scenario where the electric vehicle industry follows a similar trajectory to the solar panel industry, Box 2 attempts to quantify the potential impact a 50% decrease in EV prices would have on prices and market shares in the euro area and other countries.

Chart 11

Increase in China’s competitiveness

Changes in Chinese export share

(percentage share of total exports)

Sources: Trade Data Monitor, UNCTAD and ECB staff calculations.
Notes: The chart shows changes in China’s export share in total exports by sector. The latest observations are for 2023 and 2022.

Chart 12

Changes in market share in green technology industries for China, the euro area and the United States

(percentage share of total exports)

a) Solar panels

b) Electric batteries

c) Electric vehicles

Sources: Trade Data Monitor and ECB staff calculations.
Notes: The chart shows exports as a share of total exports in different green technology sectors. The data refers to trade flows in US dollars. Exports from the euro area exclude trade between euro area countries. The latest observation is for April 2024.

China has increased its competitiveness in sectors traditionally dominated by advanced economies. Along with rising market share, China’s value added in global value chains has also been growing.[18] This increase in value added is enhancing China’s competitiveness and exposing advanced economies to competition in a greater number of sectors, as China gradually develops a comparative advantage in sectors in which the latter specialise. In the last 20 years in particular, China has become increasingly competitive in sectors previously dominated by other advanced economies (Chart 13). Of these advanced economies, Italy appears to be most exposed because China has become competitive in 60 sectors where Italy holds a comparative advantage. On the other hand, Germany has seen the largest surge in exposure to Chinese competitiveness, which has increased from 20 sectors in 2000 to 50 in 2022.

China’s aim of boosting its self-reliance will impact its demand for imports and its competitiveness in third-country markets. It has been aiming to reduce its reliance on global trading partners by importing less and by vertically integrating its value chains.[19] As it gradually replaces imported goods with domestically-produced ones, China’s demand for imported industrial goods will decline. A surge in the domestic production of industrial goods will also increase competition from China in third-country export markets. Both phenomena will put downward pressure on the trade balance of industrial goods exporters, such as the euro area. At the same time, the change in the trade balance is likely to affect the renminbi exchange rate, which will offset part of the gain in China’s price competitiveness.

Chart 13

China’s increased competitiveness

Countries exposed to China’s increased competitiveness

(number of product categories with comparative advantage)

Sources: UN trade and development and ECB staff calculations.
Notes: The chart shows comparative advantage, referring to the revealed comparative advantage indicator, measuring the ratio between the share of a country’s exports in a particular product category in its total exports and the same share for the world as a whole. A country has comparative advantage if the value of this ratio is over 1. The latest observation is for 2022.

Impact on competitors’ prices

China’s competition will also give rise to further disinflationary pressures through second-round effects emerging as a result of competitors being forced to lower the prices of their products. While Chinese production surpluses in some sectors may not affect the market shares of firms in advanced economies directly, they could lead to the reallocation of production from third markets to China, leading to overall lower prices for these products. At the same time, competitive Chinese prices could force producers in advanced economies to also reduce their prices. Both cases could potentially trigger second-round effects on consumer prices in advanced economies.

Box 2
A model-based assessment of the spillovers of Chinese subsidies to electric vehicles

Prepared by Maria-Grazia Attinasi, Lukas Boeckelmann, Bernardo de Castro Martins and Baptiste Meunier

China increasingly subsidises electric vehicle producers, mirroring what happened in the solar panel industry where it has become a global leader thanks to massive state aid. Overall, industrial subsidies in China are estimated to be three to nine times higher than those in advanced economies, with conservative estimates showing subsidies amounting to €221 billion (2% of China’s GDP). There has recently been a huge increase in subsidies to Chinese green tech companies, notably to producers of electric vehicles.[20] This approach mirrors how China has become a world leader in the solar panel industry, increasing its global market share from 5% in 2000 to 50% in 2024 through massive government subsidies.[21]

Global spillovers are quantified using a state-of-the-art, multi-country, multi-sector model run on a newly-developed granular input-output table. We use the Baqaee and Farhi (2024) model, which accounts for amplification effects of shocks through global production networks and substitution effects via international trade.[22] The model makes it possible to simulate the propagation of shocks both downstream to consumers and upstream to suppliers, and to derive the non-linear effects of shocks across countries and sectors. By enhancing the granularity of available input-output tables in the calibration of the model to isolate green sectors, such as EVs, our methodology enables us to simulate shocks targeted only at green sectors and to recover the sectoral impact on the industries of interest. [23] We simulate a hypothetical and stylised scenario where the relative price of Chinese EVs and electric batteries drops by 50% following government subsidies, in line with estimates of the price differential between Chinese and EU producers.[24]

Massive Chinese subsidies would lower the price of EVs for consumers across the globe but would also severely downsize their domestic production in the rest of the world. Heavily-subsidised Chinese EVs are estimated to lower the price consumers pay for EVs by 30% globally and 15% in the EU (Chart A, panel a). This leads to a 6% increase in the global production of EVs, as consumers substitute thermal vehicles for cheaper EVs, but EU domestic production would decline by 70% (Chart A, panel a) as consumers switch to cheaper Chinese products. As a result, China substantially increases its global market share in EVs by 60 percentage points, notably at the expense of EU producers, whose share shrinks by 30 percentage points (Chart A, panel b), of which 18 percentage points relate to German producers. This scenario closely resembles what happened in the solar panel industry, where Chinese subsidies made products cheaper and enabled China to gain a dominant market share while producers in the rest of the world were forced to scale back production. Finally, even though the sectoral impact on the EV industry is sizeable, the global impact is limited: total consumer prices decline by only 0.2% and overall EU production falls by a mere 0.1% owing to the small size of the EV industry.

The estimates presented in this box should be considered an upper bound for losses in market shares for the euro area as the model abstracts from potential mitigating effects. First, EU producers may react endogenously to Chinese subsidies by lowering their prices or by bridging the price competitiveness gap through more innovation and digitalisation.[25] The EU could also impose countervailing duties, such as the new tariffs announced in June 2024 and not accounted for in the box.[26] The scenario considered in the box instead illustrates, other things being equal, the risks related to sizeable Chinese subsidies. Second, consumer preferences for EVs might be less price sensitive than assumed in our scenario. While we account for this in the Baqaee-Farhi model by setting a product-specific elasticity of substitution, estimates in the literature relate to all vehicles and not specifically to EVs.[27] Should price sensitivities for EVs be lower than for other vehicles, this could lead to an over-estimation of the substitution effects towards Chinese EVs.

Chart A

Global sectoral spillovers of Chinese subsidies to electric vehicles

a) Consumer prices and real production of EVs

b) Changes in global market share of EVs

(deviation from steady state, percentages)

(percentage points)

Sources: Baqaee and Farhi, op. cit., OECD, International Energy Agency, Fally, T. and Sayre, J., “Commodity Trade Matters”, Working paper, No 24965, National Bureau of Economic Research, August 2018 and ECB staff calculations.
Notes: The non-linear impact is simulated through 25 iterations of the log-linearised model. The granular input-output tables isolating electric vehicles are obtained following the methodology of Attinasi, M-G.et al., op.cit.

5 Conclusion

China’s recent policy approach to address economic weakness by doubling down on its investment-driven growth model and identifying new productive sources is widely expected to increase already existing overcapacities. Given diminishing marginal returns to investment, the continued emphasis on the supply side of the economy is leading to rising inventories, lower profitability and growing supply-demand imbalances in a number of sectors and industries. Against a background of subdued domestic demand, efforts to direct additional productive capacities to export markets is fuelling tensions in global trade relations.

Trade policies vis-à-vis China are changing rapidly. The United States recently introduced a sharp increase in tariffs on Chinese imports, notably raising tariffs on Chinese EVs from 25% to 100%. Moreover, other countries are also increasing tariff and non-tariff barriers to Chinese imports (Chart 14). In the EU, several trade policy instruments were introduced that address level playing field considerations in public procurements and also review dumping practices. The changing trade policy dynamics are also increasingly visible in trade flows. Since 2017-18, China’s share of imports has been on a declining path in the United States and Japan, albeit briefly interrupted by the pandemic, when demand initially focused temporarily on medical products and then on manufacturing goods made in China. By contrast, China’s share continued to rise in the EU, currently standing above pre-pandemic levels (Chart 15).

Chart 14

Trade measures introduced on Chinese products

(number of trade measures)

Sources: Global Trade Alert and ECB staff calculations.
Notes: The chart shows new trade measures introduced on Chinese products with HS 6-digit detail since 2008. The latest observation is for December 2023.

Given these shifting trade policy dynamics, the role of the EU as an export market for China could potentially become more central. In the event that non-EU countries further close their markets to Chinese products, China could redouble its efforts to export to the EU, thereby exacerbating the impact on Europe in terms of rising disinflationary pressures, a loss of competitiveness in advanced manufacturing sectors and a declining share in both manufacturing output and exports. Given the potentially significant effects on output, inflation and labour markets, the European policy response needs to be carefully calibrated to ensure level playing field conditions.[28]

Chart 15

Share of imports originating from China

(change since 2015; 12-month moving average)

Sources: IMF and ECB staff calculations.
Note: The latest observation is for January 2024.

  1. The one-child policy introduced in the late 1970s reduced the amount of old-age support from dependants, thereby raising retirement savings. The shift from a centrally-planned economy towards a greater role for markets in the 1990s reduced the social safety net, driving up precautionary savings, and the switch from employer-provided housing to private property ownership required higher savings for down payments and mortgage payments. See Zhang, L, Brooks, R., Ding, D., Ding, H., He, H., Lu, J. and Mano, R., “China’s High Savings: Drivers, Prospects, and Policies,” IMF Working Paper, No 277, International Monetary Fund, December 2018.

  2. See also Dorrucci, E., Pula, G. and Santabárbara, D., “China’s economic growth and rebalancing”, Occasional Paper Series, No 142, ECB, February 2013; and Dieppe, A., Gilhooly, R., Han, J., Korhonen, I. and Lodge, D. (editors), “The transition of China to sustainable growth – implications for the global economy and the euro area”, Occasional Paper Series, No 206, ECB, January 2018.

  3. The industries targeted included steel, coal, cement, glass, real estate and agriculture. See Boulter, J., “China’s supply-side structural reform”, Bulletin, Reserve Bank of Australia, December 2018.

  4. See Dinu, S. and Toh, S.G., “China’s structural growth prospects - scenario analysis with demographics and productivity”, Working Paper Series, European Central Bank, forthcoming.

  5. See Fernández-Villaverde, J., Ohanian, L. E. and Yao, W., “The Neoclassical Growth of China”, Working Paper Series, No 31351, National Bureau of Economic Research, June 2023. This model allows the construction of scenarios that can quantify the impact of structural and secular issues on China’s GDP growth rate.

  6. The most recent World Population Prospects report, which presents demographic trends and projections, was published by the United Nations in 2022.

  7. Note that the projected growth rate measures underlying structural potential long-term growth and hence does not include the unique effects of the COVID-19 pandemic nor recent cyclical drivers, such as the real estate downturn or policy stimulus.

  8. See Peschel, D. and Liu, W., “The Long-Term Growth Prospects of the People’s Republic of China”, Working Paper Series, No 54, Asian Development Bank, December 2022. Their TFP projections for China incorporate additional information about challenges in technological advancements.

  9. Chinese government policies promoting firms in strategic industries largely fall under two initiatives: the “Made in China 2025” initiative aimed at promoting high-tech industries, and the “10,000 Little Giants” initiative targeted at small and medium-sized enterprises.

  10. For more details, see García-Herrero, A. and Schindowski, R., “Unpacking China’s industrial policy and its implications for Europe”, Working Paper, Issue 11, Bruegel, 13 May 2024.

  11. Business confidence survey 2024, European Union Chamber of Commerce in China, May 2024.

  12. The Bayesian VAR analysis decomposes supply and demand shocks in Chinese export growth. Structural shocks are identified using sign restrictions, estimated using monthly samples ranging from January 2012 to March 2024. In particular, aggregate foreign demand shocks are identified by assuming that real exports and export prices move in the same direction, while aggregate domestic supply shocks assume they move in opposite directions.

  13. The production network framework assumes a positive technology shock affecting Chinese sectors with overcapacities, propagating forward to export prices and accounting for input interdependence in the supply chains. The framework also assumes nominal rigidities, namely that there exists some wedge between the final price and marginal cost, which softens the overall impact on euro area prices.

  14. The sectors identified are pharmaceuticals, electrical machinery, chemicals, basic metals, motor vehicles, non-metallic minerals, and timber and wood.

  15. As Chinese solar panel prices fell on average by about 30% each year between 2007 and 2011 (from 5.5 USD/kW to 1 USD/kW), our simulation considers a similar magnitude, to gauge the largest potential impact on euro area consumer prices. For more insight into the solar panels industry, see Wen, D., Gao, W., Qian, F., Gu, Q. and Ren, J., “Development of solar photovoltaic industry and market in China, Germany, Japan and the United States of America using incentive policies”, Energy Exploration & Exploitation, Vol.39, Issue 5, pp.1381-1836, September 2021.

  16. See also di Sano, M., Pongetti, G., Schuler, T. and Toh, S.G., “Spillovers to the euro area from recent negative inflation in China”, Economic Bulletin, Issue 7, ECB, 2023; see also the box by Dieppe, A., Frankovic, I. and Liu, M., “Could China export disinflation?”, Eurosystem staff macroeconomic projections for the euro area, ECB, June 2024.

  17. Analysis by Jean, S. et al., “Dominance on World Markets: the China Conundrum”, Policy Brief, No 44, CEPII Research Center, December 2023. This Policy Brief shows that, at a more detailed level of harmonised trade classification, China’s export market share surpassed 50% for more than 600 products. In comparison, the United States had 100 dominant products while the EU had 300.

  18. Value added in Chinese exports to the EU is growing. This is particularly evident in industries reliant on Chinese inputs within international supply chains, such as basic metals, chemicals and electrical equipment. For more details see Vandermeeren, F., “Understanding EU-China economic exposure”, Single Market Economics Briefs, No 4, European Commission, 17 January 2024.

  19. China owns entire value chains, ranging from raw material mines to final production processes in specific technologies, such as drones and electric vehicles. For more details, see Arjona, R. et al.,“An enhanced methodology to monitor the EU’s strategic dependencies and vulnerabilities”, Single Market Economics Papers, No14, European Commission, 18 April 2023.

  20. See Bickenbach, F., Dohse, D., Langhammer, R. J., and Liu, W-H. (2024), “Foul Play? On the Scale and Scope of Industrial Subsidies in China”, Kiel Policy Brief, No 173. For example, direct subsidies to the car maker BYD increased from about €0.2 billion in 2020 to €2.1 billion in 2022.

  21. See Gang, C., “China's Solar PV Manufacturing and Subsidies from the Perspective of State Capitalism”, The Copenhagen Journal of Asian Studies, Vol. 33, Issue 1, pp. 90-106, June 2015.

  22. Baqaee, D. and Farhi, E., “Networks, Barriers, and Trade”, Econometrica, Vol. 92, Issue 2. pp. 505-541, March 2024.

  23. While input-output tables feature sectoral granularity (e.g. 45 sectors in OECD TiVA tables), they are not granular enough to isolate specific green products. For example, electric vehicles are merged with thermal vehicles in the motor vehicles sector in the OECD TiVA tables. The construction of granular input-output tables relies on product-level trade data to decompose each broad sector in an initial input-output table into green and non-green products following the methodology of Borin, A., Conteduca, F. P., di Stefano, E., Gunnella, V., Mancini, M. and Panon, L., “Trade decoupling from Russia”, International Economics, Vol. 175, pp.25-44, October 2023. We refine the methodology to capture specific sectoral interlinkages in Attinasi, M-G., Boeckelmann, L., Borin, A., de Castro Martins, B., Mancini, M. and Meunier, B., “Climate change and trade fragmentation”, unpublished manuscript, European Central Bank, 2024.

  24. For example, Rhodium Group estimates the price differential between German and Chinese EVs to be around 50%. The Baqaee-Farhi model does not include a fiscal block that would simulate the financing mode of subsidies.

  25. See also de Santis, R.A., Neves, P., di Nino, V., Furbach, N. and Neumann, U., “Will the euro area car sector recover?”, Economic Bulletin, Issue 4, ECB, 2024.

  26. As a result of the anti-subsidy investigation launched by the European Commission in October 2023 on imports of battery electric vehicles for passengers originating in China, in June 2024 the Commission announced new tariffs on Chinese EV producers ranging from 17.4% to 37.6% on top of a 10% duty that was already in place for all electric cars imported from China.

  27. Trade elasticities are based on Fontagné, L., Guimbard, H. and Orefice, G., “Tariff-based product-level trade elasticities”, Journal of International Economics, Vol. 137, July 2022, as well as on Boehm, C.E., Levchenko, A.A. and Pandalai-Nayar, N., “The Long and Short (Run) of Trade Elasticities”, American Economic Review, Vol. 113, No 4, pp. 861-905, April 2023.

  28. A report by the European Commission highlights how China is the main source of the EU’s dependencies, accounting for about one-third of all products identified as Single Origin Dependencies. For more details, see Arjona, R. et al., “An enhanced methodology to monitor the EU’s strategic dependencies and vulnerabilities”, Single Market Economics Papers, No 14, European Commission, 18 April 2023.