Modelling the Density of Inflation Using Autoregressive Conditional Heteroscedasticity, Skewness, and Kurtosis Models
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References listed on IDEAS
- 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.
- Laurence Ball & N. Gregory Mankiw, 1995.
"Relative-Price Changes as Aggregate Supply Shocks,"
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- Laurence Ball & N. Gregory Mankiw, 1992. "Relative-Price Changes as Aggregate Supply Shocks," NBER Working Papers 4168, National Bureau of Economic Research, Inc.
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- Michael F. Bryan & Stephen G. Cecchetti, 1999. "Inflation And The Distribution Of Price Changes," The Review of Economics and Statistics, MIT Press, vol. 81(2), pages 188-196, May.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Doaa Akl Ahmed & Mamdouh M. Abdelsalam, 2015. "Modelling the Density of Egyptian Quarterly CPI Inflation," Working Papers 936, Economic Research Forum, revised Aug 2015.
- Durán-Vázquez, Rocio & Lorenzo-Valdes, Arturo & Ruiz-Porras, Antonio, 2012.
"Un modelo GARCH con asimetría condicional autorregresiva para modelar series de tiempo: Una aplicación para el Indice de Precios y Cotizaciones
[A GARCH model with autorregresive conditional asymme," MPRA Paper 42548, University Library of Munich, Germany.
More about this item
Keywordsinflation targeting; conditional volatility; skewness and kurtosis; modelling uncertainty of inflation;
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
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