DGSE Model-Based Forecasting of Modeled and Non-Modeled Inflation Variables in South Africa
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- Rangan Gupta & Patrick T. kanda & Mampho P. Modise & Alessia Paccagnini, 2013. "DSGE Model-Based Forecasting of Modeled and Non-Modeled Inflation Variables in South Africa," Working Papers 201374, University of Pretoria, Department of Economics.
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- Franz Ruch & Mehmet Balcilar & Rangan Gupta & Mampho P. Modise, 2020.
"Forecasting core inflation: the case of South Africa,"
Applied Economics, Taylor & Francis Journals, vol. 52(28), pages 3004-3022, June.
- Franz Ruch & Mehmet Balcilar & Mampho P. Modise & Rangan Gupta, 2015. "Forecasting Core Inflation: The Case of South Africa," Working Papers 201543, University of Pretoria, Department of Economics.
- Franz Ruch & Mehmet Balcilar Author-Name-First Mehmet & Mampho P. Modise & Rangan Gupta, 2015. "Forecasting Core Inflation: The Case of South Africa," Working Papers 15-08, Eastern Mediterranean University, Department of Economics.
- Byron J. Idrovo-Aguirre & Javier E. Contreras-Reyes, 2019. "Backcasting cement production and characterizing cement’s economic cycles for Chile 1991–2015," Empirical Economics, Springer, vol. 57(5), pages 1829-1852, November.
- Gupta, Rangan & Kotzé, Kevin, 2017.
"The role of oil prices in the forecasts of South African interest rates: A Bayesian approach,"
Energy Economics, Elsevier, vol. 61(C), pages 270-278.
- Rangan Gupta & Kevin Kotze, 2015. "The Role of Oil Prices in the Forecasts of South African Interest Rates: A Bayesian Approach," Working Papers 201531, University of Pretoria, Department of Economics.
- Rangan Gupta & Kevin Kotze, 2016. "The Role of Oil Prices in the Forecasts of South African Interest Rates: A Bayesian Approach," School of Economics Macroeconomic Discussion Paper Series 2016-01, School of Economics, University of Cape Town.
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- Idrovo Aguirre, Byron & Contreras, Javier, 2015. "Back-splicing of cement production and characterization of its economic cycle: The case of Chile (1991-2015)," MPRA Paper 67387, University Library of Munich, Germany, revised 20 Sep 2015.
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More about this item
Keywords
DSGE model; in ation; core variables; non-core variables;All these keywords.
JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
- E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
NEP fields
This paper has been announced in the following NEP Reports:- NEP-AFR-2013-12-06 (Africa)
- NEP-DGE-2013-12-06 (Dynamic General Equilibrium)
- NEP-FOR-2013-12-06 (Forecasting)
- NEP-MAC-2013-12-06 (Macroeconomics)
- NEP-MON-2013-12-06 (Monetary Economics)
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