Degui Li, Yu-Ning Li, Peter C. B. Phillips
arXiv 14 Sep 2025 · Econometrics
arXiv:2509.11060 · PDF · DOI · OpenAlex · Extracted main text
This paper studies high-dimensional curve time series with common stochastic trends. A dual functional factor model structure is adopted with a high-dimensional factor model for the observed curve time series and a low-dimensional factor model for the latent curves with common trends. A functional PCA technique is applied to estimate the common stochastic trends and functional factor loadings. Under some regularity conditions we derive the mean square convergence and limit distribution theory for the developed estimates, allowing the dimension and sample size to jointly diverge to infinity. We propose an easy-to-implement criterion to consistently select the number of common stochastic trends and further discuss model estimation when the nonstationary factors are cointegrated. Extensive Monte-Carlo simulations and two empirical applications to large-scale temperature curves in Australia and log-price curves of S&P 500 stocks are conducted, showing finite-sample performance and providing practical implementations of the new methodology.
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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 | Bai (2004) Estimating cross-section common stochastic trends in nonstationary panel data | 1.000 | 16 | 5 | 100% |
| 2 | Tavakoli, Nisol and Hallin (2023) Factor models for high-dimensional functional time series II: Estimation and forecasting | 1.000 | 11 | 5 | 100% |
| 3 | Bai \ Ng (2002) Determining the number of factors in approximate factor models | 1.000 | 9 | 4 | 100% |
| 4 | Leng et al (2024) Estimating covariance functions for high-dimensional functional time series with dual factor structures | 1.000 | 6 | 4 | 100% |
| 5 | Barigozzi, Lippi \ Luciani (2021) Large-dimensional dynamic factor models: Estimation of impulse-response functions with I(1) cointegrated factors | 1.000 | 5 | 4 | 100% |
| 6 | Bai \ Ng (2004) A PANIC attack on unit roots and cointegration | 1.000 | 5 | 4 | 100% |
| 7 | Tavakoli, Nisol and Hallin (2023) Factor models for high-dimensional functional time series I: Representation results | 0.874 | 6 | 2 | 100% |
| 8 | Cheng \ Phillips (2009) Semiparametric cointegrating rank selection | 0.874 | 5 | 2 | 100% |
| 9 | Guo, Qiao and Wang (2021) Factor modelling for high-dimensional functional time series | 0.874 | 5 | 2 | 100% |
| 10 | Phillips \ Jiang (2025) Cross section curve autoregression: the unit root case | 0.811 | 4 | 2 | 100% |
Showing the top 10 of 54 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | 1cm Inference on common trends in functional time series | 0.405 | 1 | 1 |