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A Large Factor Model for Forecasting Macroeconomic Variables in South Africa

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  • Rangan Gupta
  • Alain Kabundi

Abstract

This paper uses large Factor Models (FMs) which accommodates a large cross-section of macroeconomic time series for forecasting per capita growth rate, inflation, and the nominal short-term interest rate for the South African economy. The FMs used in this study contains 267 quarterly series observed over the period of 1980Q1-2006Q4. The results, based on the RMSEs of one- to four-quarters-ahead out of sample forecasts over 2001Q1 to 2006Q4, indicate that the FMs tend to outperform alternative models such as an unrestricted VAR, Bayesian VARs (BVARs) and a typical New Keynesian Dynamic Stochastic General Equilibrium (NKDSGE) model in forecasting the three variables under consideration, hence, indicating the blessings of dimensionality.

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Bibliographic Info

Paper provided by Economic Research Southern Africa in its series Working Papers with number 137.

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Date of creation: Apr 2009
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Handle: RePEc:rza:wpaper:137

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Keywords: Large Factor Model; VAR; BVAR; NKDSGE Model; Forecast Accuracy;

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Citations

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Cited by:
  1. Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working Papers 200927, University of Pretoria, Department of Economics.
  2. Buss, Ginters, 2010. "A note on GDP now-/forecasting with dynamic versus static factor models along a business cycle," MPRA Paper 22147, University Library of Munich, Germany.
  3. Pilar Poncela & Esther Ruiz, 2012. "More is not always better : back to the Kalman filter in dynamic factor models," Statistics and Econometrics Working Papers ws122317, Universidad Carlos III, Departamento de Estadística y Econometría.
  4. Annari de Waal & Renee van Eyden & Rangan Gupta, 2013. "Do we need a global VAR model to forecast inflation and output in South Africa?," Working Papers 201346, University of Pretoria, Department of Economics.
  5. Ibarra, Raul, 2012. "Do disaggregated CPI data improve the accuracy of inflation forecasts?," Economic Modelling, Elsevier, vol. 29(4), pages 1305-1313.
  6. Ercio Muñoz & Pablo Cruz, 2012. "Uso de un Modelo Favar para Proyectar el Precio del Cobre," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(3), pages 84-95, December.
  7. Costantini, Mauro & Gunter, Ulrich & Kunst, Robert M., 2012. "Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE-VAR System," Economics Series 292, Institute for Advanced Studies.

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