Multivariate Trend‐Cycle‐Seasonal Decompositions with Correlated Innovations
Bibliographic Data
| ID | 21512787 |
|---|---|
| Authors | Jing Tian (0000-0001-7746-7782, Tasmanian School of Business and Economics, Economics University of Tasmania Sand Bay Tasmania Australia), Jan Jacobs (0000-0002-8657-6777, University of Groningen, corresponding author), Jan P A M Jacobs (0000-0002-7994-5175, CAMA Acton Australian Capital Territory Australia, corresponding author), Denise R Osborn (0000-0001-5534-8926, CAMA Acton Australian Capital Territory Australia) |
| Year | 2024 |
| Volume | 86 |
| Issue | 5 |
| Pages | 1260-1289 |
| Publication date | 2024-10-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Oxford Bulletin of Economics and Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0305-9049 • E-ISSN: 1468-0084 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/obes.12602 |
| OpenAlex | W4392167308 |
| Language | EN |
| References cited | 30 |
Multivariate analysis can help to focus on important phenomena, including trend and cyclical movements, but any economic information in seasonality is typically ignored. The present paper aims to more fully exploit time series information through a multivariate unobserved component model for quarterly data that exhibits seasonality together with cross‐variable component correlations. We show that economic restrictions, including common trends, common cycles and common seasonals can aid identification. The approach is illustrated using Italian GDP and consumption data
Econometrics · Economics · Exploit · Multivariate analysis · Multivariate statistics · Seasonal adjustment · Seasonality · Statistics · Univariate · Computer Science · Italy: Economic History and Contemporary Issues · Market Dynamics and Volatility · Mathematics · Monetary Policy and Economic Impact
Time Series Analysis by State Space Methods
Forecasting, Structural Time Series Models and the Kalman Filter
Generalized impulse response analysis in linear multivariate models
Multivariate Seasonal Adjustment, Economic Identities, and Seasonal Taxonomy
Practical Methods for Modeling Weak Varma Processes
Diagnostic Checking of Unobserved-Components Time Series Models
Why Are the Beveridge-Nelson and Unobserved-Components Decompositions of GDP So Different
The Seasonal Cycle and the Business Cycle
| Citation velocity | historical |
|---|---|
| Highly cited | No |