How China’s Costly Industrial Policy Is Undermining Efficiency, IMF Analysis Shows

The International Monetary Fund’s Asia and Pacific Department, drawing on data from the Ministry of Natural Resources, the Real Estate Registration Center, and the Bureau Van Dijk’s Orbis database, has released an in-depth working paper that dissects the magnitude and consequences of China’s industrial policy. Authored by Daniel Garcia-Macia, Siddharth Kothari, Yutong Li, and Yifan Tao, the study quantifies the fiscal scale of key policy instruments and measures their effect on resource allocation efficiency. It finds that annual support through cash subsidies, tax benefits, subsidized credit, and discounted land totals about 4.4 percent of GDP, far higher than in major advanced economies, and that these measures depress total factor productivity (TFP) by over one percent.

Unpacking the Scale of Support

The empirical analysis spans more than 5,000 listed firms from 2010 to 2023 and a registry of 1.6 million land sales. Cash subsidies account for the largest share at around 2.0 percent of GDP in 2023, followed by tax benefits at 1.5 percent, land subsidies at 0.5 percent, and subsidized credit at 0.4 percent. While the total size of support has stayed relatively constant, its composition has shifted in recent years. Pandemic-driven tax relief programs swelled the share of tax benefits, while cash subsidies and preferential credit declined modestly. Contrary to the popular perception that state-owned enterprises are the main beneficiaries, the findings reveal a more nuanced picture. Private firms frequently enjoy larger tax benefits, whereas SOEs obtain cheaper credit and higher cash subsidy rates once sector differences are taken into account. Manufacturing consistently emerges as the most favored sector, receiving both cheaper loans and heavily discounted industrial land, prices roughly two-thirds lower than comparable non-manufacturing parcels. The land discount widened during China’s real estate boom and persisted until the property market downturn.

The Mechanics of Misallocation

To gauge the efficiency costs of this support, the authors employ the Hsieh and Klenow (2009) model of misallocation, which uses differences in total factor productivity in revenues (TFPR) as a signal of distortions in capital and labor allocation. They integrate this model with “industrial policy counts” from the Global Trade Alert database, as compiled by Juhasz et al. (2025), covering the number and type of policy measures across sectors from 2009 to 2018. Merging this policy data with firm-level productivity records from Orbis and sectoral statistics from the KLEMS database allows for a detailed mapping of policy intensity to TFPR outcomes. The results are clear: subsidies, both cash and credit, encourage firms to produce above the efficiency benchmark, lowering TFPR, while trade and regulatory barriers restrict output, raising TFPR by shielding incumbents. These opposing effects explain why the overall picture of distortions is complex but unmistakably significant.

Where the Distortions Lie

The numbers reveal that industrial policy accounts for about 24 percent of the dispersion in TFPR between sectors, compared with only 4 percent of the dispersion within sectors. This means most of the inefficiency stems from shifting resources across sectors in ways that do not align with productivity fundamentals, rather than from unequal treatment of firms in the same sector, though such within-sector effects remain notable. Running these dispersion measures through the model suggests that policy-induced misallocation lowers China’s aggregate TFP by roughly 1.2 percent. Of this, about one percentage point comes from between-sector distortions and 0.2 points from within-sector distortions. Factoring in how capital might adjust, the GDP level could be up to 2 percent lower as a result.

When set against an international backdrop, China’s industrial policy stands out starkly. In G7 economies with robust firm-level data, France, Germany, Italy, Japan, and the UK, there is no statistically significant link between policy intensity and misallocation, reflecting both smaller policy scale and less distortionary targeting during the period studied. European Union state aid, for example, averaged about 1.5 percent of GDP in 2022, with the biggest manufacturing economies only slightly above this figure.

Winners, Losers, and Policy Lessons

The analysis of firm-level productivity reveals no significant association between the average TFP of a sector and its level of industrial policy support, even when looking at changes over a decade. This suggests that potential gains from innovation incentives or economies of scale are being offset by reduced competition or incentives that keep weaker firms afloat. The “industrial champion” story is more complicated than its rhetoric: sector leaders do tend to post higher TFP than the average firm, but they often have lower TFPR, a sign they are producing at levels above the efficiency point because of policy support. This is especially true for state-owned sector leaders, likely aided by subsidies and implicit credit guarantees from the government.

From a policy perspective, the findings align closely with IMF recommendations. The authors argue for greater transparency on industrial policy, particularly at the local government level, where data gaps are largest. They call for narrowing the scope of interventions to cases of clearly defined market failures and for favoring direct budgetary tools over credit quotas or regulatory privileges, as the former are generally more transparent and less distortionary. While the paper notes that China has already begun moving in this direction by reducing reliance on opaque credit and regulatory measures, it maintains that significant fiscal and efficiency gains remain untapped. The study also stresses the need for more comprehensive data to assess the full picture, including instruments not captured in their estimates, such as government-guided investment funds.

Even with these caveats, the message is unequivocal: China’s industrial policy machine is large, costly, and in need of sharper focus if it is to avoid undermining the productivity it aims to promote. The combination of vast fiscal outlays and measurable efficiency losses sets a high bar for justifying such interventions, making transparency, restraint, and precision not just economic virtues, but practical necessities for sustaining growth.