James D. Hamilton, Xinwei Ma, Jin Xi
arXiv 24 Aug 2026 · Econometrics
arXiv:2608.23732 · PDF · Extracted main text
This paper develops a procedure for uncovering the common cyclical factors that drive a mix of stationary and nonstationary variables. The method does not require knowing which variables are nonstationary or the nature of the nonstationarity. An application to the FRED-MD macroeconomic dataset demonstrates that the approach offers similar benefits to those of traditional principal component analysis with some added advantages.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Hamilton, James D (2018) Why you should never use the Hodrick- Prescott filter self | 1.000 | 9 | 3 | 100% |
| 2 | Onatski, Alexei and Wang, Chen (2021) Spurious Factor Analysis | 1.000 | 7 | 3 | 100% |
| 3 | Stock, James H and Watson, Mark W (2002) Forecasting using principal components from a large number of predictors | 1.000 | 7 | 3 | 100% |
| 4 | Stock, James H and Watson, Mark W (2016) Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics | 0.928 | 4 | 3 | 100% |
| 5 | Bai, Jushan and Ng, Serena (2002) Determining the Number of Factors in Approximate Factor Models | 0.811 | 4 | 2 | 100% |
| 6 | Bai, Jushan and Ng, Serena (2004) A PANIC attack on unit roots and cointegration | 0.737 | 3 | 2 | 100% |
| 7 | McCracken, Michael W and Ng, Serena (2016) FRED- MD: A monthly database for macroeconomic research | 0.693 | 27 | 1 | 100% |
| 8 | Stock, James H and Watson, Mark W (1999) Forecasting inflation | 0.693 | 10 | 1 | 100% |
| 9 | Barigozzi, Matteo and Lippi, Marco and Luciani, Matteo (2021) Large-Dimensional Dynamic Factor Models: Estimation of Impulse–Response Functions with I(1) Cointegrated Factors | 0.585 | 3 | 1 | 100% |
| 10 | Stock, James H and Watson, Mark W (2014) Estimating Turning Points Using Large Data Sets | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 27 scored citations.