Forecasting Using Principal Components from a Large Number of Predictors.¶
Stock, J. H., & Watson, M. W. (2002). Forecasting Using Principal Components from a Large Number of Predictors. Journal of the American Statistical Association, 1167-1179.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Cross-Dimensional Leakage
- Macroeconometrics: a common shock (oil prices, monetary policy) contaminates apparent cross-sectoral or cross-country relations; factor models partition out the common component.
This sourceDevelops dynamic-factor methods that partition out a common component (common shock) from many economic series via principal components.
Supported in partVerified against the work's full text
Supports the factor-model mechanism for extracting a common component from many series, not the claim that common shocks contaminate apparent relations.
“This high-dimensional problem is simplified by modeling the covariability of the series in terms of a relatively few number of unobserved latent factors.”
- Macroeconometrics: a common shock (oil prices, monetary policy) contaminates apparent cross-sectoral or cross-country relations; factor models partition out the common component.
Verification¶
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Registry ID ref:e86cc6d23c12 · see in the full table