The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Estimating Potential Output as a Latent Variable
Abstract
This article proposes a new method for estimating potential output in which potential real gross domestic product (GDP) is modeled as an unobserved stochastic trend, and deviations of GDP from potential affect inflation through an aggregate supply relationship. The output and inflation equations together form a bivariate unobserved-components model which is estimated via maximum likelihood through the use of the Kalman-filter algorithm. The procedure yields a measure of potential output and its standard error and an estimate of the quantitative response of inflation to real growth and the output gap.
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Citations
Cites
Forecasting, Structural Time Series Models and the Kalman Filter
Harvey, A. C. (1990) · doi:10.1017/cbo9781107049994 · Cited by 4,195
Cited by
Whither Monetary and Financial Stability? The Implications of Evolving Policy Regimes
Borio, C. E. V., & White, W. R. (2004) · SSRN Electronic Journal · doi:10.2139/ssrn.901387 · Cited by 368
Metadata
- Authors
- Kuttner, K. N.
- Venue
- Journal of Business & Economic Statistics
- Publisher
- Informa UK Limited
- Published
- 1994-07
- Volume
- 12
- Issue
- 3
- Pages
- 361-368
- ISSN
- 0735-0015 (ISSN-L)
- 1537-2707
- OpenAlex
- W2045251164
- Cited by
- 452
- References
- 1
- FWCI
- 9.20
- Type
- journal article
- Language
- en
- Open access
- closed
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- Kuttner, K. N. (1994). Estimating Potential Output as a Latent Variable. Journal of Business & Economic Statistics. https://doi.org/10.1080/07350015.1994.10524551
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.
