Martingale unobserved component models
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Cited by:
- Wen Xu, 2016. "Estimation of Dynamic Panel Data Models with Stochastic Volatility Using Particle Filters," Econometrics, MDPI, vol. 4(4), pages 1-13, October.
- James M. Nason & Gregor W. Smith, 2021.
"Measuring the slowly evolving trend in US inflation with professional forecasts,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 1-17, January.
- James M. Nason & Gregor W. Smith, 2013. "Measuring The Slowly Evolving Trend In Us Inflation With Professional Forecasts," Working Paper 1316, Economics Department, Queen's University.
- James M. Nason & Gregor W. Smith, 2014. "Measuring the Slowly Evolving Trend in US Inflation with Professional Forecasts," CAMA Working Papers 2014-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Hernández, Juan R., 2020.
"Covered Interest Parity: A Stochastic Volatility Approach to Estimate the Neutral Band,"
MPRA Paper
100744, University Library of Munich, Germany.
- Hernández Juan R., 2020. "Covered Interest Parity: A Stochastic Volatility Approach to Estimate the Neutral Band," Working Papers 2020-02, Banco de México.
- Frank Schorfheide & Dongho Song & Amir Yaron, 2018.
"Identifying Long‐Run Risks: A Bayesian Mixed‐Frequency Approach,"
Econometrica, Econometric Society, vol. 86(2), pages 617-654, March.
- Frank Schorfheide & Dongho Song & Amir Yaron, 2013. "Identifying long-run risks: a bayesian mixed-frequency approach," Working Papers 13-39, Federal Reserve Bank of Philadelphia.
- Frank Schorfheide & Dongho Song & Amir Yaron, 2014. "Identifying Long-Run Risks: A Bayesian Mixed-Frequency Approach," NBER Working Papers 20303, National Bureau of Economic Research, Inc.
- Dongho Song & Amir Yaron & Frank Schorfheide, 2013. "Identifying Long-Run Risks: A Bayesian Mixed-Frequency Approach," 2013 Meeting Papers 580, Society for Economic Dynamics.
- Elmar Mertens & James M. Nason, 2020.
"Inflation and professional forecast dynamics: An evaluation of stickiness, persistence, and volatility,"
Quantitative Economics, Econometric Society, vol. 11(4), pages 1485-1520, November.
- Elmar Mertens & James M Nason, 2015. "Inflation and Professional Forecast Dynamics: An Evaluation of Stickiness, Persistence, and Volatility," CAMA Working Papers 2015-06, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Elmar Mertens & James M. Nason, 2018. "Inflation and professional forecast dynamics: an evaluation of stickiness, persistence, and volatility," BIS Working Papers 713, Bank for International Settlements.
- Elmar Mertens & James M. Nason, 2017. "Inflation and professional forecast dynamics: An evaluation of stickiness, persistence, and volatility," CAMA Working Papers 2017-60, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
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Keywords
Auxiliary particle filter; EM algorithm; EWMA; forecasting; Kalman filter; likelihood; martingale unobserved component model; particle filter; stochastic volatility;All these keywords.
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