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Despite the widespread use of economic information to anticipate changes in business conditions, innovation metrics are not considered to be leading indicators. We argue that aggregate trademark data reflect firm-level choices that can help predict business cycles. In addition to establishing the conceptual basis for considering trademarks, our statistical evaluations, using turning point analysis and a novel machine learning method, find that trademark filings for product and service offerings in commercial use outperform many of the conventional leading indicators. Our work suggests that including trademark metrics in composite indexes could improve recession forecasting performance.
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Stored only when both papers are in the corpus — 15 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.