Industrial policies, defined as policies aimed at changing the sectoral structure of the economy, have become more prevalent around the world in recent years (Millot and Rawdanowicz 2024, Juhász et al. 2023). In China, industrial policies have long been a centrepiece of the policy toolkit, with the government deploying an array of policy tools to promote strategically important economic sectors. These include cash subsidies, tax benefits, subsidised credit, subsidised land, trade and regulatory barriers, and industry coordination.
These policies have had a material impact on the economy, helping to develop specific industries and technologies. However, they also generate costs which often go unreported, such as fiscal outlays and economic efficiency losses, including because of duplication of efforts across local governments competing to subsidise the same national priority sectors (Fang and others, 2025). Our new paper (Garcia-Macia et al. 2025) sheds light on these costs by quantifying the main industrial policy instruments in China and analysing their impact on domestic factor misallocation and aggregate productivity.
What is the size of industrial policy in China?
Given the lack of official data on Chinese industrial policies, we use financial statements of listed firms and land transaction data to calculate the equivalent fiscal cost of four key industrial policy instruments in China over the 2010–2023 period:
- Cash subsidies: Cash subsidies are directly reported in the income statements of listed firms. We find that the subsidy rate by sector, defined as aggregate cash subsidies as a share of value added, is highest in sectors identified as priorities by the authorities, including semiconductors, high-tech manufacturing, and automobiles. The least favoured sectors include consumer goods, services, real estate, and energy. Aggregate subsidy rates have declined over the last decade, from 2.4% in 2013 to 2.0% in 2023, but the sectoral ranking has been stable.
- Tax benefits: Favoured sectors, such as high-tech, are also supported via lower tax rates. We measure tax benefits at the sector level as the gap between the top statutory corporate income tax rate (25%) and the effective corporate income tax rate reported by listed firms in the sector. Aggregate tax benefit rates rose from 4.4% of profits in 2013 to 6.3% in 2023, and the sectoral ranking is very similar to the one for cash subsidies.
- Credit subsidies: Credit allocation is another important industrial policy tool. For example, the People’s Bank of China encourages banks to provide low-cost loans to high-tech and green technology sectors. Credit subsidies are measured as differences in average effective interest rates reported by listed firms across sectors, controlling for financial determinants. We find that manufacturing firms benefit from effective interest rates that are on average 0.4 percentage points below those of other sectors.
- Land subsidies: Local governments also provide discounted land-use rights to support certain sectors and firms. We estimate land subsidies using data from the land registry, which includes all land transactions in China. Subsidies are measured as systematic differences in the unit price of land sold to manufacturing firms versus non-manufacturing firms in the same year and within one kilometre of distance. Manufacturing land prices have been roughly stable and slightly above 200 RMB per square meter, while prices in other sectors have been consistently above 600 RMB per square meter, implying a price discount of at least two thirds for manufacturing firms (Figure 1).
Figure 1 Unit prices of land by sector (real RMB per square meter; median and interquartile range)
Source: Garcia-Macia et al. (2025).
Adding up the four instruments, industrial policy support is estimated to be about 4% of GDP as of 2023 (Figure 2). For comparison, state aid provided by EU countries amounted to about 1.5% of GDP in 2022 according to the European Commission.
Figure 2 Industrial policy support by instrument over time (percent of GDP)
Source: Garcia-Macia et al. (2025).
Note: Results for listed firms are extrapolated to all firms, correcting for the disproportionate share of tax revenue contributed by listed firms.
As an important caveat, our aggregate estimates extrapolate the cash, credit, and tax benefits observed for listed firms to non-listed ones. These estimates may overstate the size of industrial policy to the extent that non-listed firms receive proportionally less support. On the other hand, our study excludes other instruments for which sectoral data is not accessible, such as tax benefits beyond corporate income taxes or subsidised equity funding through Government Guided Funds, which would add to the tally.
How does industrial policy affect productivity?
In addition to generating fiscal costs, industrial policy may lower aggregate productivity by diverting production factors from their most productive uses. Such factor misallocation is measured as differences in the total factor productivity in revenues (TFPR) across sectors and firms (following Hsieh and Klenow 2009), with TFPR defined as revenues per unit of inputs. TFPR differences reflect misallocation because in the absence of distortions, profit-maximising firms would reallocate production factors to chase any excess returns per unit of inputs, thus equalizing TFPR.
To capture the impact of industrial policies on factor allocation, we correlate a measure of industrial policy counts at the sector level from Juhasz et al. (2025) with estimated TFPR levels of more than 300,000 firms in China. The results in Figure 3 reveal that subsidies tend to decrease the average TFPR of a sector, as they encourage firms to utilise an excessive amount of inputs per unit of revenue and sell the larger than optimal output at lower prices. In contrast, trade and regulatory barriers tend to increase TFPR, possibly as they protect incumbent firms from competition, allowing them to charge higher prices while restricting inputs.
We also find that, in general, sectors with more industrial policy measures feature wider dispersion in TFPR across firms within the sector, suggesting that not all firms in a sector benefit equally from industrial policy. Finally, industrial policy does not appear to have significant effects on firm-level physical productivity (what is referred to as TFPQ in the literature).
Figure 3 Impact of industrial policy on sector TFPR by measure, 2009-18
Source: Garcia-Macia et al. (2025).
Notes: The coefficients show the elasticity of TFPR to industrial policy counts in each category, based on a sector-level regression at NACE 4-digit level, with NACE 2-digit sector fixed effects, using 2018 firm-level data for China and policies over 2009-18. Whiskers indicate 90-percent confidence intervals.
Combining the between- and within-sector estimates above, we find that misallocation generated by industrial policies explains a non-negligible share of overall misallocation in China. Figure 4 shows that about a quarter of total misallocation between sectors and 4% of misallocation within sectors is related to differences in industrial policy intensity. To provide a benchmark, Figure 4 also replicates the exercise for G7 countries. Notably, no statistically significant relationship between industrial policy and misallocation is found in that case. G7 countries tend to have less overall misallocation than China, and part of that gap may be explained by industrial policy induced misallocation in China.
Figure 4 Between-sector (left) and within-sector (right) TFPR dispersion, 2018 (log TFPR, standard deviation)
Source: Garcia-Macia et al. (2025).
Notes: The G7 average includes countries with sufficiently large samples in Orbis: France, Germany, Italy, Japan, and the United Kingdom.
The estimated contribution of industrial policies to misallocation can be filtered through the Hsieh and Klenow (2009) model to calculate the associated loss in aggregate productivity. Relative to a ‘no industrial policy’ baseline, factor misallocation generated by industrial policies is estimated to reduce the domestic aggregate TFP level by about 1.2%. In turn, this could reduce the GDP level by up to 2% after accounting for the associated decline in capital accumulation.
The case for scaling back industrial policy
Our findings underscore the need to scale back the size of industrial policy in China to reduce fiscal costs and factor misallocation, and lift productivity. Industrial policy should be pursued cautiously and only to tackle well-defined market failures. To the extent that it is implemented, industrial policy should use budgetary tools, which tend to be more transparent and less distortionary than indirect measures. More transparency around industrial policy measures would also help to improve policymaking and alleviate concerns of trading partners.
Authors’ note: The views expressed in this column are those of the authors and should not be attributed to the IMF, its Executive Board, or its management.
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