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The Role of Asset Prices in Forecasting Inflation and Output in South Africa

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Author Info

  • Rangan Gupta

    (Rangan Gupta, Professor, University of Pretoria, Department of Economics, Pretoria 0002, South Africa. E-mail: Rangan.Gupta@up.ac.za)

  • Faaiqa Hartley

    (Faaiqa Hartley, Graduate Student, Department of Economics, University of Pretoria, Pretoria 0002, South Africa. E-mail: faaiqasalie@gmail.com)

Abstract

This article assesses the predictive ability of asset prices relative to other variables in forecasting inflation and real GDP growth in South Africa. A total of 42 asset and non-asset predictor variables are considered. Forecasts of inflation and real GDP growth are computed using both individual predictor autoregressive distributed lag (ARDL) models, forecast combination approaches, as well as large scale models. The large scale data models considered include Bayesian vector autoregressive models and classical and Bayesian univariate and multivariate factor augmented vector autoregressive models. The models are estimated for an in-sample of 1980:Q2 to 1999:Q4, and then one- to eight-step-ahead forecasts for inflation and real GDP growth are evaluated over the 2000:Q1 to 2010:Q2 out-of-sample period. Principle Component forecast combination models are found to produce the most accurate out-of-sample forecasts of inflation and real GDP growth relative to the other combination and more sophisticated models considered. Asset prices are found to contain particularly useful information for forecasting inflation and real GDP growth at certain horizons. Asset prices are however found to be stronger predictors of inflation, particularly in the long run.JEL Classification: C11, C32, R53

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Bibliographic Info

Article provided by Institute for Financial Management and Research in its journal Journal of Emerging Market Finance.

Volume (Year): 12 (2013)
Issue (Month): 3 (December)
Pages: 239-291

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Handle: RePEc:sae:emffin:v:12:y:2013:i:3:p:239-291

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Web page: http://www.ifmr.ac.in

Related research

Keywords: Asset prices; combination forecasts; BVAR; FAVAR;

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Cited by:
  1. Plakandaras, Vasilios & Gupta, Rangan & Papadimitriou, Theophilos & Gogas, Periklis, 2014. "Forecasting the U.S. Real House Price Index," DUTH Research Papers in Economics, Democritus University of Thrace, Department of Economics 10-2014, Democritus University of Thrace, Department of Economics.
  2. Rangan Gupta & Mampho P. Modise & Josine Uwilingiye, 2011. "Out-of-Sample Equity Premium Predictability in South Africa: Evidence from a Large Number of Predictors," Working Papers 201122, University of Pretoria, Department of Economics.
  3. Goodness C. Aye & Mehmet Balcilar & Rangan Gupta & Charl Jooste & Stephen M. Miller & Zeynel A. Ozdemir, 2012. "Fiscal Policy Shocks and the Dynamics of Asset Prices: The South African Experience," Working Papers 201228, University of Pretoria, Department of Economics.
  4. Pejman Bahramian & Mehmet Balcilar & Rangan Gupta & Patrick T. kanda, 2014. "Forecasting South African Inflation Using Non-Linear Models: A Weighted Loss-Based Evaluation," Working Papers 201416, University of Pretoria, Department of Economics.
  5. Rangan Gupta, 2012. "Forecasting House Prices for the Four Census Regions and the Aggregate US Economy: The Role of a Data-Rich Environment," Working Papers 201214, University of Pretoria, Department of Economics.
  6. Luis A. Gil-Alana & Goodness C. Aye & Rangan Gupta, 2012. "Testing for Persistence with Breaks and Outliers in South African House Prices," Working Papers 201233, University of Pretoria, Department of Economics.

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