The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Characterizing nonlinearities in business cycles using smooth transition autoregressive models
Abstract
During the past few years investigators have found evidence indicating that various time-series representing business cycles, such as production and unemployment, may be nonlinear. In this paper it is assumed that if the time-series is nonlinear, then it can be adequately described by a smooth transition autoregressive (STAR) model. The paper describes the application of these models to quarterly logarithmic production indices for 13 countries and ‘Europe’. Tests reject linearity for most of these series, and estimated STAR models indicate that the nonlinearity is needed mainly to describe the responses of production to large negative shocks such as oil price shocks.
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Citations
Cites
Engle, R. F. (1982) · Econometrica · doi:10.2307/1912773 · Cited by 20,795
Metadata
- Authors
- Terasvirta, T., & Anderson, H. M.
- Venue
- Journal of Applied Econometrics
- Publisher
- Wiley
- Published
- 1992-12
- Volume
- 7
- Issue
- S1
- Pages
- S119-S136
- ISSN
- 0883-7252 (ISSN-L)
- 1099-1255
- OpenAlex
- W2132978003
- Cited by
- 890
- References
- 1
- FWCI
- 24.69
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Characterizing nonlinearities in business cycles using smooth transition autoregressive models. https://app.cochat.ai/papers/10.1002/jae.3950070509
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- Terasvirta, T., & Anderson, H. M. (1992). Characterizing nonlinearities in business cycles using smooth transition autoregressive models. Journal of Applied Econometrics. https://doi.org/10.1002/jae.3950070509
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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.
