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Bayesian Methods Of Forecasting Inventory Investment

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  • Rangan Gupta

Abstract

This paper develops a Bayesian Vector Error Correction Model (BVECM) for forecasting inventory investment. The model is estimated using South African quarterly data on actual sales, production, unfilled orders, price level and interest rate, for the period 1978 to 2000. The out‐of‐sample‐forecast accuracy obtained from the BVECM over the forecasting horizon of 2001:1 to 2003:4, is compared with those generated from the classical variant of the Vector Autoregresssive (VAR) model and the VECM, the Bayesian VAR, and the recently developed ECM by Smith et al., for the South African economy. The BVECM with the most‐tight prior outperforms all the other models, except for a relatively tight BVAR which also correctly predicts the direction of change of inventory investment over the period of 2004:1 to 2006:3.

Suggested Citation

  • Rangan Gupta, 2009. "Bayesian Methods Of Forecasting Inventory Investment," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 113-126, March.
  • Handle: RePEc:bla:sajeco:v:77:y:2009:i:1:p:113-126
    DOI: 10.1111/j.1813-6982.2009.01199.x
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    Cited by:

    1. Mirriam Chitalu Chama-Chiliba & Rangan Gupta & Nonophile Nkambule & Naomi Tlotlego, 2011. "Forecasting Key Macroeconomic Variables of the South African Economy Using Bayesian Variable Selection," Working Papers 201132, University of Pretoria, Department of Economics.
    2. Rangan Gupta & Sonali Das, 2010. "Predicting Downturns in the US Housing Market: A Bayesian Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 41(3), pages 294-319, October.
    3. Das, Sonali & Gupta, Rangan & Kabundi, Alain, 2009. "Could we have predicted the recent downturn in the South African housing market?," Journal of Housing Economics, Elsevier, vol. 18(4), pages 325-335, December.
    4. Rangan Gupta & Alain Kabundi, 2010. "Forecasting macroeconomic variables in a small open economy: a comparison between small- and large-scale models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 168-185.

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