A BVAR Model for Forecasting Ukrainian Inflation and GDP
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DOI: 10.26531/vnbu2021.251.02
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- Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2020.
"Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 934-943, September.
- Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019. "Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation," CAMA Working Papers 2019-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Marco Del Negro & Frank Schorfheide, 2004.
"Priors from General Equilibrium Models for VARS,"
International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, May.
- Marco Del Negro & Frank Schorfheide, 2002. "Priors from general equilibrium models for VARs," FRB Atlanta Working Paper 2002-14, Federal Reserve Bank of Atlanta.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015.
"Prior Selection for Vector Autoregressions,"
The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2012. "Prior selection for vector autoregressions," Working Paper Series 1494, European Central Bank.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2012. "Prior Selection for Vector Autoregressions," CEPR Discussion Papers 8755, C.E.P.R. Discussion Papers.
- Domenico Giannone & Michèle Lenza & Giorgio E. Primiceri, 2012. "Prior Selection for Vector Autoregressions," Working Papers ECARES ECARES 2012-002, ULB -- Universite Libre de Bruxelles.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2012. "Prior Selection for Vector Autoregressions," NBER Working Papers 18467, National Bureau of Economic Research, Inc.
- Beechey, Meredith & Österholm, Pär, 2010. "Forecasting inflation in an inflation-targeting regime: A role for informative steady-state priors," International Journal of Forecasting, Elsevier, vol. 26(2), pages 248-264, April.
- Joshua C. C. Chan, 2019. "Large Bayesian vector autoregressions," CAMA Working Papers 2019-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
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More about this item
Keywords
forecasting; inflation; GDP; BVAR; forecast evaluation;All these keywords.
JEL classification:
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
- 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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