Do Precious Metal Prices Help in Forecasting South African Inflation?

Mehmet Balcilar, Nico Katzke () and Rangan Gupta
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Nico Katzke: Department of Economics, Stellenbosch University, South Africa

No 201510, Working Papers from University of Pretoria, Department of Economics

Abstract: In this paper we test whether the key metals prices of gold and platinum significantly improve inflation forecasts for the South African economy. We also test whether controlling for conditional correlations in a dynamic setup, using bivariate Bayesian-Dynamic Conditional Correlation (B-DCC) models, improves inflation forecasts. To achieve this we compare out-of-sample forecast estimates of the B-DCC model to Random Walk, Autoregressive and Bayesian VAR models. We find that for both the BVAR and BDCC models, improving point forecasts of the Autoregressive model of inflation remains an elusive exercise. This, we argue, is of less importance relative to the more informative density forecasts. For this we find improved forecasts of inflation for the B-DCC models at all forecasting horizons tested. We thus conclude that including metals price series as inputs to inflation models leads to improved density forecasts, while controlling for the dynamic relationship between the included price series and inflation similarly leads to significantly improved density forecasts.

Keywords: Bayesian VAR; Dynamic Conditional Correlation; Density forecasting; Random Walk; Autoregressive model (search for similar items in EconPapers)
JEL-codes: C11 C15 E17 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2015-02
New Economics Papers: this item is included in nep-afr, nep-for, nep-mac and nep-mfd
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Related works:
Journal Article: Do precious metal prices help in forecasting South African inflation? (2017)
Working Paper: Do Precious Metal Prices Help in Forecasting South African Inflation? (2015)
Working Paper: Do Precious Metal Prices Help in Forecasting South African Inflation? (2015)
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