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This paper relies on a novel dataset of more than 31,000 industrial policies in around 150 economies over the period 2009–2022 to codify and examine the stated objectives and design characteristics of these policies. Using large‐scale machine learning methods applied to policy texts, we systematically classify policy objectives at a global level and document several new stylised facts. We find that industrial policies increasingly pursue multiple objectives, often ones that may be hard to reconcile. In a two‐way fixed effects framework, we show that industrial policies with environmental objectives are more common in Western economies while secure supply objectives are more common in economies geopolitically aligned with China. The majority of industrial policies exhibit features that may make them prone to capture by special interests: they discriminate against foreigners, are firm‐specific and lack ‘sunset clauses’. Industrial policies which reduce firms' costs (such as subsidies, as opposed to taxes) have become more common over time, in particular in rival geopolitical blocs. These features of industrial policies highlight the importance and challenges of evaluating their value‐for‐money, which, in turn, requires clear identification of the primary objective of each policy.
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Kóczán et al. (2026) studied this question.
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