Common Factors, Trends, and Cycles in Large Datasets
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DOI: 10.17016/FEDS.2017.111
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Cited by:
- Francisco Corona & Pilar Poncela & Esther Ruiz, 2020.
"Estimating Non-stationary Common Factors: Implications for Risk Sharing,"
Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 37-60, January.
- Poncela, Pilar & Corona, Francisco & Ruiz Ortega, Esther, 2017. "Estimating non-stationary common factors : Implications for risk sharing," DES - Working Papers. Statistics and Econometrics. WS 24585, Universidad Carlos III de Madrid. Departamento de Estadística.
More about this item
Keywords
EM Algorithm; Gross Domestic Output; Kalman Smoother; Non-stationary Approximate Dynamic Factor Model; Output Gap; Quasi Maximum Likelihood; Trend-Cycle Decomposition;JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
- C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
- E00 - Macroeconomics and Monetary Economics - - General - - - General
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2017-11-26 (Econometrics)
- NEP-ETS-2017-11-26 (Econometric Time Series)
- NEP-MAC-2017-11-26 (Macroeconomics)
Statistics
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