Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts
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DOI: 10.1016/j.ijforecast.2020.01.004
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- Bo Zhang & Joshua C.C. Chan & Jamie L. Cross, 2018. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," CAMA Working Papers 2018-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
References listed on IDEAS
- Chib, Siddhartha & Greenberg, Edward, 1994. "Bayes inference in regression models with ARMA (p, q) errors," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 183-206.
- Chan, Joshua C.C., 2013.
"Moving average stochastic volatility models with application to inflation forecast,"
Journal of Econometrics, Elsevier, vol. 176(2), pages 162-172.
- Joshua C C Chan, 2012. "Moving Average Stochastic Volatility Models with Application to Inflation Forecast," ANU Working Papers in Economics and Econometrics 2012-591, Australian National University, College of Business and Economics, School of Economics.
- Joshua C.C. Chan, 2013. "Moving Average Stochastic Volatility Models with Application to Inflation Forecast," CAMA Working Papers 2013-31, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Joshua C. C. Chan & Gary Koop & Simon M. Potter, 2013.
"A New Model of Trend Inflation,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 94-106, January.
- Joshua Chan & Gary Koop & Simon Potter, 2012. "A New Model of Trend Inflation," Working Papers 1202, University of Strathclyde Business School, Department of Economics.
- Chan, Joshua & Koop, Gary & Potter, Simon, 2012. "A New Model Of Trend Inflation," SIRE Discussion Papers 2012-12, Scottish Institute for Research in Economics (SIRE).
- Joshua C C Chan & Gary Koop & Simon M Potter, 2012. "A New Model of Trend Inflation," CAMA Working Papers 2012-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Chan, Joshua & Koop, Gary & Potter, Simon, 2012. "A new model of trend inflation," MPRA Paper 39496, University Library of Munich, Germany.
- Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998.
"Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models,"
The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
- Sangjoon Kim, Neil Shephard & Siddhartha Chib, "undated". "Stochastic volatility: likelihood inference and comparison with ARCH models," Economics Papers W26, revised version of W, Economics Group, Nuffield College, University of Oxford.
- Sangjoon Kim & Neil Shephard, 1994. "Stochastic volatility: likelihood inference and comparison with ARCH models," Economics Papers 3., Economics Group, Nuffield College, University of Oxford.
- Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1996. "Stochastic Volatility: Likelihood Inference And Comparison With Arch Models," Econometrics 9610002, University Library of Munich, Germany.
- Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
- Croushore, Dean & Stark, Tom, 2001.
"A real-time data set for macroeconomists,"
Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
- Dean Croushore & Tom Stark, 1999. "A real-time data set for macroeconomists," Working Papers 99-4, Federal Reserve Bank of Philadelphia.
- Cross, Jamie & Poon, Aubrey, 2016. "Forecasting structural change and fat-tailed events in Australian macroeconomic variables," Economic Modelling, Elsevier, vol. 58(C), pages 34-51.
- Dean Croushore & Tom Stark, 2003.
"A Real-Time Data Set for Macroeconomists: Does the Data Vintage Matter?,"
The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 605-617, August.
- Dean Croushore & Tom Stark, 1999. "A real-time data set for marcoeconomists: does the data vintage matter?," Working Papers 99-21, Federal Reserve Bank of Philadelphia.
- Ang, Andrew & Bekaert, Geert & Wei, Min, 2007.
"Do macro variables, asset markets, or surveys forecast inflation better?,"
Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
- Andrew Ang & Geert Bekaert & Min Wei, 2005. "Do Macro Variables, Asset Markets or Surveys Forecast Inflation Better?," NBER Working Papers 11538, National Bureau of Economic Research, Inc.
- Andrew Ang & Geert Bekaert & Min Wei, 2006. "Do macro variables, asset markets, or surveys forecast inflation better?," Finance and Economics Discussion Series 2006-15, Board of Governors of the Federal Reserve System (U.S.).
- Marcellino, Massimliano, 2004.
"Forecasting EMU macroeconomic variables,"
International Journal of Forecasting, Elsevier, vol. 20(2), pages 359-372.
- Massimiliano Marcellino, "undated". "Forecasting EMU macroeconomic variables," Working Papers 216, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Marcellino, Massimiliano, 2002. "Forecasting EMU Macroeconomic Variables," CEPR Discussion Papers 3529, C.E.P.R. Discussion Papers.
- McCausland, William J. & Miller, Shirley & Pelletier, Denis, 2011. "Simulation smoothing for state-space models: A computational efficiency analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 199-212, January.
- James Mitchell & Donald Robertson & Stephen Wright, 2019.
"R2 Bounds for Predictive Models: What Univariate Properties Tell us About Multivariate Predictability,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 681-695, October.
- Stephen Wright & James Mitchell & Donald Robertson, 2018. "R2 bounds for predictive models: what univariate properties tell us about multivariate predictability," Birkbeck Working Papers in Economics and Finance 1804, Birkbeck, Department of Economics, Mathematics & Statistics.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- James H. Stock & Mark W. Watson, 2007.
"Why Has U.S. Inflation Become Harder to Forecast?,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
- James H. Stock & Mark W. Watson, 2006. "Why Has U.S. Inflation Become Harder to Forecast?," NBER Working Papers 12324, National Bureau of Economic Research, Inc.
- Todd E. Clark & Francesco Ravazzolo, 2015. "Macroeconomic Forecasting Performance under Alternative Specifications of Time‐Varying Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 551-575, June.
- Stock, James H & Watson, Mark W, 1996.
"Evidence on Structural Instability in Macroeconomic Time Series Relations,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
- James H. Stock & Mark W. Watson, 1994. "Evidence on Structural Instability in Macroeconomic Time Series Relations," NBER Technical Working Papers 0164, National Bureau of Economic Research, Inc.
- James H. Stock & Mark W. Watson, 1994. "Evidence on structural instability in macroeconomic times series relations," Working Paper Series, Macroeconomic Issues 94-13, Federal Reserve Bank of Chicago.
- Lloyd B. Thomas, 1999. "Survey Measures of Expected U.S. Inflation," Journal of Economic Perspectives, American Economic Association, vol. 13(4), pages 125-144, Fall.
- Croushore Dean, 2010.
"An Evaluation of Inflation Forecasts from Surveys Using Real-Time Data,"
The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, May.
- Dean Croushore, 2006. "An evaluation of inflation forecasts from surveys using real-time data," Working Papers 06-19, Federal Reserve Bank of Philadelphia.
- Lundbergh, Stefan & Terasvirta, Timo & van Dijk, Dick, 2003.
"Time-Varying Smooth Transition Autoregressive Models,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 104-121, January.
- Lundbergh, Stefan & Teräsvirta, Timo & van Dijk, Dick, 2000. "Time-Varying Smooth Transition Autoregressive Models," SSE/EFI Working Paper Series in Economics and Finance 376, Stockholm School of Economics.
- Faust, Jon & Wright, Jonathan H., 2009.
"Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
- Jon Faust & Jonathan H. Wright, 2007. "Comparing Greenbook and Reduced Form Forecasts using a Large Realtime Dataset," NBER Working Papers 13397, National Bureau of Economic Research, Inc.
- Stephen J. Taylor, 1994. "Modeling Stochastic Volatility: A Review And Comparative Study," Mathematical Finance, Wiley Blackwell, vol. 4(2), pages 183-204, April.
- Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
- Joshua C. C. Chan, 2020.
"Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 68-79, January.
- Joshua C.C. Chan, 2015. "Large Bayesian VARs: A flexible Kronecker error covariance structure," CAMA Working Papers 2015-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Nakatsuma, Teruo, 2000. "Bayesian analysis of ARMA-GARCH models: A Markov chain sampling approach," Journal of Econometrics, Elsevier, vol. 95(1), pages 57-69, March.
- James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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- Del Negro, Marco & Lenza, Michele & Primiceri, Giorgio E. & Tambalotti, Andrea, 2020. "What’s up with the Phillips Curve?," Working Paper Series 2435, European Central Bank.
- William Chen & Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What’s Up with the Phillips Curve?," Liberty Street Economics 20200918a, Federal Reserve Bank of New York.
- Primiceri, Giorgio & Del Negro, Marco & Lenza, Michele & Tambalotti, Andrea, 2020. "What's up with the Phillips Curve?," CEPR Discussion Papers 14583, C.E.P.R. Discussion Papers.
- Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What’s up with the Phillips Curve?," NBER Working Papers 27003, National Bureau of Economic Research, Inc.
- Chenghan Hou & Bao Nguyen & Bo Zhang, 2023. "Real‐time forecasting of the Australian macroeconomy using flexible Bayesian VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 418-451, March.
- Boriss Siliverstovs, 2020.
"Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts,"
Empirical Economics, Springer, vol. 58(1), pages 7-27, January.
- Boriss Siliverstovs, 2019. "Assessing Nowcast Accuracy of US GDP Growth in Real Time: The Role of Booms and Busts," Working Papers 2019/01, Latvijas Banka.
- Arango-Castillo, Lenin & Orraca, María José & Molina, G. Stefano, 2023. "The global component of headline and core inflation in emerging market economies and its ability to improve forecasting performance," Economic Modelling, Elsevier, vol. 120(C).
- Jihyun Park & Andrey Sarantsev, 2024. "The VIX as Stochastic Volatility for Corporate Bonds," Papers 2410.22498, arXiv.org, revised Jan 2025.
- Jamie L. Cross & Chenghan Hou & Gary Koop, 2021. "Macroeconomic Forecasting with Large Stochastic Volatility in Mean VARs," Working Papers No 04/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Yuntong Liu & Yu Wei & Yi Liu & Wenjuan Li, 2020. "Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-12, December.
- Matteo Mogliani & Anna Simoni, 2024. "Bayesian Bi-level Sparse Group Regressions for Macroeconomic Density Forecasting," Papers 2404.02671, arXiv.org, revised Nov 2024.
- Bo Zhang & Jamie Cross & Na Guo, 2020. "Time-Varying Trend Models for Forecasting Inflation in Australia," Working Papers No 09/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Zhang, Bo & Nguyen, Bao H., 2020. "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers 2020-12, University of Tasmania, Tasmanian School of Business and Economics.
- Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023.
"High-dimensional conditionally Gaussian state space models with missing data,"
Journal of Econometrics, Elsevier, vol. 236(1).
- Joshua C. C. Chan & Aubrey Poon & Dan Zhu, 2023. "High-Dimensional Conditionally Gaussian State Space Models with Missing Data," Papers 2302.03172, arXiv.org.
- Na Guo & Bo Zhang & Jamie L. Cross, 2022. "Time‐varying trend models for forecasting inflation in Australia," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 316-330, March.
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More about this item
Keywords
Autoregressive moving average errors; Stochastic volatility; Inflation forecast; State space models; Unobserved components model;All these keywords.
JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
Statistics
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