The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Testing and Modeling Multivariate Threshold Models
Abstract
Threshold autoregressive models in which the process is piecewise linear in the threshold space have received much attention in recent years. In this article I use predictive residuals to construct a test statistic for detecting threshold nonlinearity in a vector time series and propose a procedure for building a multivariate threshold model. The thresholds and the model are selected jointly based on the Akaike information criterion. The finite-sample performance of the proposed test is studied by simulation. The modeling procedure is then used to study arbitrage in security markets and results in a threshold cointegration between logarithms of future contracts and spot prices of a security after adjusting for the cost of carrying the contracts. In this particular application, thresholds are determined in part by the transaction costs. I also apply the proposed procedure to U.S. monthly interest rates and two river flow series of Iceland.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Applied Multivariate Statistical Analysis.
Johnson, A. R., & Wichern, D. W. (1988) · Biometrics · doi:10.2307/2531616 · Cited by 11,353
Journal of the Royal Statistical Society.
(1923) · The Economic Journal · doi:10.1093/ej/33.130.269 · Cited by 3,219
Sample Splitting and Threshold Estimation
Hansen, B. E. (2000) · Econometrica · doi:10.1111/1468-0262.00124 · Cited by 2,874
Inference When a Nuisance Parameter Is Not Identified Under the Null Hypothesis
Hansen, B. E. (1996) · Econometrica · doi:10.2307/2171789 · Cited by 2,269
Non-linear time series. A dynamical system approach
Tong, H. (1990) · London School of Economics and Political Science Research Online (London School of Economics and Political Science) · Cited by 1,895
Forecasting and testing in co-integrated systems
Engle, R. F., & Yoo, B. S. (1987) · Journal of Econometrics · doi:10.1016/0304-4076(87)90085-6 · Cited by 1,867
Applied Multivariate Statistical Analysis
Dunn, C. (1989) · Technometrics · doi:10.1080/00401706.1989.10488530 · Cited by 1,608
Chan, K. (1993) · The Annals of Statistics · doi:10.1214/aos/1176349040 · Cited by 1,298
Blake, N. S., & Fomby, T. B. (1997) · International Economic Review · doi:10.2307/2527284 · Cited by 1,040
Testing and Modeling Threshold Autoregressive Processes
Tsay, R. S. (1989) · Journal of the American Statistical Association · doi:10.1080/01621459.1989.10478760 · Cited by 980
Self-citation
Cited by
Computation and analysis of multiple structural change models
Bai, J., & Perron, P. (2003) · Journal of Applied Econometrics · doi:10.1002/jae.659 · Cited by 5,771
Estimation and Inference of Impulse Responses by Local Projections
Jordà, Ò. (2005) · American Economic Review · doi:10.1257/0002828053828518 · Cited by 4,677
Analysis of Financial Time Series
(2006) · Technometrics · doi:10.1198/tech.2006.s405 · Cited by 2,348
Huang, B.-N., Hwang, M. J., & Peng, H.-P. (2005) · Energy Economics · doi:10.1016/j.eneco.2005.03.001 · Cited by 294
Forecast Methods for Time Series Data: A Survey
Liu, Z., Zhu, Z., Gao, J., & Xu, C. (2021) · IEEE Access · doi:10.1109/access.2021.3091162 · Cited by 247
Metadata
- Authors
- Tsay, R. S.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1998-09
- Volume
- 93
- Issue
- 443
- Pages
- 1188-1202
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2110849068
- Cited by
- 677
- References
- 17
- FWCI
- 16.24
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Testing and Modeling Multivariate Threshold Models. https://app.cochat.ai/papers/10.1080/01621459.1998.10473779
- The paper
- Tsay, R. S. (1998). Testing and Modeling Multivariate Threshold Models. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1998.10473779
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
