Forecasting inflation with thick models and neural networks
Working paper by Paul McNelis, Peter McAdam, published by the European Central Bank. A staff paper is its authors’ text. Dated 2004-04.
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- Forecasting inflation with thick models and neural networks European Central Bank · published 2004-04 · Retrieved for the candidate pack on 2026-11-04 (SHA-256 4252bd524ee1f3ccc3a2a90541ff30556c5f75ed77c2244c78e56cfdb0e32dce). Retrieved again at admission on 2026-11-06 (same file). PDF of ECB Working Paper No. 352 (April 2004) as served by the ECB
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- AI can improve nowcasting and policy analysisECB Working Paper No. 352 of April 2004, by Paul McNelis and Peter McAdam, reports that “thick” models combining several neural-network models outperform the best-performing linear models in real-time and bootstrap inflation forecasts for euro-area service-price indices, and do as well or sometimes better for consumer and producer price indices across several countries.2004-04 · publication · Stated in source · Supported Inspect claim & evidence ↗AI can improve nowcasting and policy analysis: propositions page →
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