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The New Economics of Industrial Policy

2024· article· en· W4396566498 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Economics · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIndustrial policyEconomicsSubsidyCorporate governancePolicy analysisWork (physics)DeindustrializationEmpirical evidencePublic economicsSet (abstract data type)Positive economicsPolitical scienceEconomyComputer scienceEngineeringInternational tradeManagementPublic administration

Abstract

fetched live from OpenAlex

We discuss the considerable literature that has developed in recent years providing rigorous evidence on how industrial policies work. This literature is a significant improvement over the earlier generation of empirical work, which was largely correlational and marred by interpretational problems. On the whole, the recent crop of papers offers a more positive take on industrial policy. We review the standard rationales and critiques of industrial policy and provide a broad overview of new empirical approaches to measurement. We discuss how the recent literature, paying close attention to measurement, causal inference, and economic structure, is offering a nuanced and contextual understanding of the effects of industrial policy. We re-evaluate the East Asian experience with industrial policy in light of recent results. Finally, we conclude by reviewing how industrial policy is being reshaped by a new understanding of governance, a richer set of policy instruments beyond subsidies, and the reality of deindustrialization.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.853
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.082
GPT teacher head0.265
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it