Detecting common breaks in the means of high dimensional cross-dependent panels
| Autor: | Gregory Rice, Zhenya Liu, Lajos Horváth, Yuqian Zhao |
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| Přispěvatelé: | Centre d'Études et de Recherche en Gestion d'Aix-Marseille (CERGAM), Aix Marseille Université (AMU)-Université de Toulon (UTLN) |
| Rok vydání: | 2021 |
| Předmět: |
Economics and Econometrics
Series (mathematics) 05 social sciences Monte Carlo method CUSUM Type (model theory) [SHS.ECO]Humanities and Social Sciences/Economics and Finance HG 01 natural sciences Data set 010104 statistics & probability Sampling distribution 0502 economics and business Applied mathematics 0101 mathematics Statistic 050205 econometrics Mathematics Statistical hypothesis testing |
| Zdroj: | Econometrics Journal Econometrics Journal, Wiley-Blackwell: No OnlineOpen, 2021, ⟨10.1093/ectj/utab028⟩ |
| ISSN: | 1368-423X 1368-4221 |
| Popis: | Summary The problem of detecting change points in the mean of high dimensional panel data with potentially strong cross-sectional dependence is considered. Under the assumption that the cross-sectional dependence is captured by an unknown number of common factors, a new CUSUM-type statistic is proposed. We derive its asymptotic properties under three scenarios depending on to what extent the common factors are asymptotically dominant. With panel data consisting of N cross sectional time series of length T, the asymptotic results hold under the mild assumption that $\min \lbrace N,T\rbrace \rightarrow \infty$, with an otherwise arbitrary relationship between N and T, allowing the results to apply to most panel data examples. Bootstrap procedures are proposed to approximate the sampling distribution of the test statistics. A Monte Carlo simulation study showed that our test outperforms several other existing tests in finite samples in a number of cases, particularly when N is much larger than T. The practical application of the proposed results are demonstrated with real data applications to detecting and estimating change points in the high dimensional FRED-MD macroeconomic data set. |
| Databáze: | OpenAIRE |
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