Morten Ørregaard Nielsen, Won-Ki Seo, Dakyung Seong
arXiv 1 Dec 2023 · Econometrics · 1 citations (OpenAlex)
arXiv:2312.00590 · PDF · DOI · OpenAlex · Extracted main text
We study statistical inference on unit roots and cointegration for time series in a Hilbert space. We develop statistical inference on the number of common stochastic trends embedded in the time series, i.e., the dimension of the nonstationary subspace. We also consider tests of hypotheses on the nonstationary and stationary subspaces themselves. The Hilbert space can be of an arbitrarily large dimension, and our methods remain asymptotically valid even when the time series of interest takes values in a subspace of possibly unknown dimension. This has wide applicability in practice; for example, to the case of cointegrated vector time series that are either high-dimensional or of finite dimension, to high-dimensional factor model that includes a finite number of nonstationary factors, to cointegrated curve-valued (or function-valued) time series, and to nonstationary dynamic functional factor models. We include two empirical illustrations to the term structure of interest rates and labor market indices, respectively.
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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 | Degui Li and Peter M. Robinson and Han Lin Shang (2023) Nonstationary fractionally integrated functional time series | 1.000 | 11 | 4 | 100% |
| 2 | Seo, Won-Ki (2024) Functional principal component analysis for cointegrated functional time series self | 1.000 | 5 | 3 | 100% |
| 3 | M. Ø. Nielsen and W.-K. Seo and D. Seong (2023) Inference on the dimension of the nonstationary subspace in functional time series self | 0.912 | 29 | 8 | 76% |
| 4 | Brendan K. Beare and Juwon Seo and Won-Ki Seo (2017) Cointegrated linear processes in Hilbert space self | 0.894 | 7 | 3 | 71% |
| 5 | Yoosoon Chang and Chang Sik Kim and Joon Y. Park (2016) Nonstationarity in time series of state densities | 0.890 | 17 | 7 | 71% |
| 6 | Anna Bykhovskaya and Vadim Gorin (2022) Cointegration in large VARs | 0.811 | 4 | 2 | 100% |
| 7 | Degui Li and Peter M. Robinson and Han Lin Shang (2020) Long-range dependent curve time series | 0.811 | 4 | 2 | 100% |
| 8 | Alexei Onatski and Chen Wang (2018) Alternative asymptotics for cointegration tests in large VARs | 0.811 | 4 | 2 | 100% |
| 9 | Shintani, Mototsugu (2001) A simple cointegrating rank test without vector autoregression | 0.754 | 7 | 3 | 43% |
| 10 | Andrews, D. W. K (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation | 0.737 | 3 | 3 | 67% |
Showing the top 10 of 58 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Functional Regression with Nonstationarity and Error Contamination: Application to the Economic Impact of Climate Change | 0.737 | 3 | 3 |
| 2 | Functional Linear Projection and Impulse Response Analysis | 0.585 | 3 | 1 |
| 3 | Approximate Factor Models for Functional Time Series | 0.405 | 1 | 1 |