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Improving forecasting in an emerging economy, South Africa: Changing trends, long run restrictions and disaggregation

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  • Aron, Janine
  • Muellbauer, John

Abstract

Forecasting inflation is particularly challenging in emerging markets, where trade and monetary policy regimes have shifted and the exchange rate and food prices are highly volatile. This study shows that the information in long-run co-integrated relationships for relative prices in South Africa is helpful in outperforming univariate benchmark models for forecasting inflation. It also investigates gains to the inflation forecast accuracy as a result of aggregating weighted forecasts of the sub-component price indices, versus forecasting the aggregate consumer price index itself. Rich multivariate equilibrium correction models employ general and sectoral information for ten sub-components, including structural breaks and institutional changes. Model selection over the period 1979–2003 generates pseudo out-of-sample forecasts, four quarters ahead, until 2007. The largest gain in forecast accuracy against naïve benchmark models comes from incorporating equilibrium correction into the long-run. For more sophisticated models, aggregating the weighted forecasts of the sub-components outperforms the aggregate forecasts. The analysis also contributes to an improved understanding of sectoral inflationary pressures.

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Bibliographic Info

Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 28 (2012)
Issue (Month): 2 ()
Pages: 456-476

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Handle: RePEc:eee:intfor:v:28:y:2012:i:2:p:456-476

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Web page: http://www.elsevier.com/locate/ijforecast

Related research

Keywords: Sectoral inflation; CPI sub-components; Equilibrium correction models; Evaluating forecasts; Model selection; Multivariate time series; Disaggregation;

References

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Cited by:
  1. 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.
  2. Gabriel Pino & Juan de Dios Tena & Antoni Espasa, 2013. "Forecasting disaggregates by sectors and regions : the case of inflation in the euro area and Spain," Statistics and Econometrics Working Papers ws130807, Universidad Carlos III, Departamento de Estadística y Econometría.

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