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Precios de exportación de gas natural para Bolivia: Modelación y pooling de pronósticos
[Bolivian natural gas export prices: Modeling and forecast pooling]

Author

Listed:
  • Aguilar, Ruben
  • Valdivia, Daney

Abstract

The boom of commodity prices was affected by the last economic crisis. The importance of these prices - forecasting – for small and developing countries becomes an important factor in the structure of their balance sheets. In this context, we apply a pooling of different projections methods for fuel prices which are the determinants of natural gas export prices under each contract. The first three forecast methods of these fuels are developed in a short run model where in its dynamic structure is nested the long-term relationship between WTI and fuel prices and the fourth method is a univariate model by its components. The oil path price for the first three projections are also developed under three approaches: i) a GARCH model, ii) WTI future prices and iii) a dynamic GARCH model weighted by the forecast of global oil supply and only with reference purposes we made an ARIMA projection model by components. The pool of projections permits us to evaluate gas export prices ex post. We conclude that the pooling of projections report best statistical properties.

Suggested Citation

  • Aguilar, Ruben & Valdivia, Daney, 2011. "Precios de exportación de gas natural para Bolivia: Modelación y pooling de pronósticos
    [Bolivian natural gas export prices: Modeling and forecast pooling]
    ," MPRA Paper 35485, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:35485
    as

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    File URL: https://mpra.ub.uni-muenchen.de/35485/1/MPRA_paper_35485.pdf
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    References listed on IDEAS

    as
    1. Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Forecasting Irish inflation using ARIMA models," Research Technical Papers 3/RT/98, Central Bank of Ireland.
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    6. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    7. Coulson, N.E. & Robins, R.P., 1989. "Forecast Combination In A Dynamic Setting," Papers 8-88-4, Pennsylvania State - Department of Economics.
    8. Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
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    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    econometrics and statistical methods; energy and macroeconomics;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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