Author

Louis Agyekum

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Preprint Oct 2026

Does the AI Productivity Dividend Diminish? Does the AI Productivity Dividend Diminish? A Validated Framework for Identifying the Shape of Firm-Level Returns to Artificial Intelligence

Forecasts of the productivity dividend from artificial intelligence (AI) differ by an order of magnitude, partly because they extrapolate average gains observed among early, highly exposed adopters. Whether those gains scale linearly, flatten, or are competed away is an empirical question about the shape of the return...

Louis Agyekum · 0 citations

Preprint Aug 2026

Forecasting in the Fog: Real-Time versus Revised-Data Evidence on Machine Learning's Edge over the Phillips Curve

Whether the ML advantage over the Phillips curve documented in Agyekum (2026) survives when models are trained and evaluated on real-time (ALFRED) vintages rather than revised series, and whether SHAP feature-importance rankings are an artifact of in-sample estimation.

Louis Agyekum, Obed Obese · 0 citations

Preprint Jul 2026

Forecasting and Explaining the Phillips Curve: A SHAP-Based Comparison of Machine Learning and Traditional Time-Series Models for Canadian Unemployment and Inflation

Analysis of the top-performing XGBoost model indicates that lagged inflation is more influential than unemployment, which only becomes significantly impactful during the pandemic tail, and clarify when machine learning methods can surpass traditional benchmarks.

Louis Agyekum · 0 citations