Modelling Inflation Volatility
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Other versions of this item:
- Eric Eisenstat & Rodney W. Strachan, 2014. "Modelling Inflation Volatility," CAMA Working Papers 2014-21, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Eric Eisenstat & Rodney Strachan, 2014. "Modelling Inflation Volatility," Working Paper series 43_14, Rimini Centre for Economic Analysis.
- Eric Eisenstat & Rodney W. Strachan, 2014. "Modelling Inflation Volatility," CAMA Working Papers 2014-68, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
Citations
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Cited by:
- Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
- Joshua C.C. Chan & Angelia L. Grant, 2014. "Issues in Comparing Stochastic Volatility Models Using the Deviance Information Criterion," CAMA Working Papers 2014-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Wenying Zeng & Songbai Song & Yan Kang & Xuan Gao & Rui Ma, 2022. "Response of Runoff to Meteorological Factors Based on Time-Varying Parameter Vector Autoregressive Model with Stochastic Volatility in Arid and Semi-Arid Area of Weihe River Basin," Sustainability, MDPI, vol. 14(12), pages 1-12, June.
- Huber, Florian, 2014.
"Density Forecasting using Bayesian Global Vector Autoregressions with Common Stochastic Volatility,"
Department of Economics Working Paper Series
179, WU Vienna University of Economics and Business.
- Florian Huber, 2014. "Density Forecasting using Bayesian Global Vector Autoregressions with Common Stochastic Volatility," Department of Economics Working Papers wuwp179, Vienna University of Economics and Business, Department of Economics.
- Lenin Arango-Castillo & María José Orraca & Regina Briseño, 2025. "Inflation volatility across advanced and emerging economies during the COVID-19 pandemic," Working Papers 2025-13, Banco de México.
- Nonejad Nima, 2015. "Particle Gibbs with ancestor sampling for stochastic volatility models with: heavy tails, in mean effects, leverage, serial dependence and structural breaks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 561-584, December.
- Legrand, Romain, 2018. "Time-Varying Vector Autoregressions: Efficient Estimation, Random Inertia and Random Mean," MPRA Paper 88925, University Library of Munich, Germany.
- Joshua C. C. Chan, 2018.
"Specification tests for time-varying parameter models with stochastic volatility,"
Econometric Reviews, Taylor & Francis Journals, vol. 37(8), pages 807-823, September.
- Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Charemza, Wojciech & Díaz, Carlos & Makarova, Svetlana, 2019. "Quasi ex-ante inflation forecast uncertainty," International Journal of Forecasting, Elsevier, vol. 35(3), pages 994-1007.
- Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2017.
"Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 110-129, January.
- Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2013. "Macroeconomic factors strike back: A Bayesian change-point model of time-varying risk exposures and premia in the U.S. cross-section," Working Paper 2013/19, Norges Bank.
- Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2015. "Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section," Working Papers 550, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Mohammed Anono ZUBAIR & Samuel Olorunfemi ADAMS & Kosarahchi Sarah ANIAGOLU, 2021. "Economic Impact of Some Determinant Factors of Nigerian Inflation Rate," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 5(2), pages 23-41.
- Bruno Ferreira Frascaroli & Wellington Charles Lacerda Nobrega, 2019. "Inflation Targeting and Inflation Risk in Latin America," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(11), pages 2389-2408, September.
- Joshua C. C. Chan & Angelia L. Grant, 2016. "On the Observed-Data Deviance Information Criterion for Volatility Modeling," Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 772-802.
- Joshua C.C. Chan & Rodney W. Strachan, 2023.
"Bayesian State Space Models In Macroeconometrics,"
Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
- Joshua C.C. Chan & Rodney W. Strachan, 2020. "Bayesian State Space Models in Macroeconometrics," CAMA Working Papers 2020-90, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Joshua C. C. Chan, 2017.
"The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
- Joshua C.C. Chan, 2015. "The Stochastic Volatility in Mean Model with Time-Varying Parameters: An Application to Inflation Modeling," CAMA Working Papers 2015-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2016.
"Does joint modelling of the world economy pay off? Evaluating global forecasts from a Bayesian GVAR,"
Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 86-100.
- Jonas Dovern & Martin Feldkircher & Florian Huber, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR," Working Papers 200, Oesterreichische Nationalbank (Austrian Central Bank).
- Dovern, Jonas & Feldkircher, Martin & Huber , Florian, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR," Working Papers 0590, University of Heidelberg, Department of Economics.
- Fu, Bowen, 2020. "Is the slope of the Phillips curve time-varying? Evidence from unobserved components models," Economic Modelling, Elsevier, vol. 88(C), pages 320-340.
- Roberto Leon‐Gonzalez & Blessings Majoni, 2025. "Exact likelihood for inverse gamma stochastic volatility models," Journal of Time Series Analysis, Wiley Blackwell, vol. 46(4), pages 774-795, July.
- Joshua C. C. Chan & Eric Eisenstat, 2018.
"Bayesian model comparison for time‐varying parameter VARs with stochastic volatility,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 509-532, June.
- Joshua C.C. Chan & Eric Eisenstat, 2015. "Bayesian model comparison for time-varying parameter VARs with stochastic volatility," CAMA Working Papers 2015-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
More about this item
JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
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