IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/35485.html
   My bibliography  Save this paper

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

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/35485/1/MPRA_paper_35485.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    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.
    2. Elkin Castaño & Luis Fernando Melo, 1998. "Métodos de Combinación de Pronósticos: Una Aplicación a la Inflación Colombiana," Borradores de Economia 109, Banco de la Republica de Colombia.
    3. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    4. Deutsch, Melinda & Granger, Clive W. J. & Terasvirta, Timo, 1994. "The combination of forecasts using changing weights," International Journal of Forecasting, Elsevier, vol. 10(1), pages 47-57, June.
    5. Ahumada, Hildegart A. & Garegnani, Maria Lorena, 2012. "Forecasting a monetary aggregate under instability: Argentina after 2001," International Journal of Forecasting, Elsevier, vol. 28(2), pages 412-427.
    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.
    9. Vega, Marco, 2003. "Reportando la distribución de la proyección de inflación," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 10.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Luis Fernando Melo Velandia & Héctor M. Núñez Amortegui, 2004. "Combinación de pronósticos de la inflación en presencia de cambios estructurales," Borradores de Economia 2153, Banco de la Republica.
    2. Bernard, Jean-Thomas & Idoudi, Nadhem & Khalaf, Lynda & Yelou, Clement, 2007. "Finite sample multivariate structural change tests with application to energy demand models," Journal of Econometrics, Elsevier, vol. 141(2), pages 1219-1244, December.
    3. Anne Morrison Piehl & Suzanne J. Cooper & Anthony A. Braga & David M. Kennedy, 2003. "Testing for Structural Breaks in the Evaluation of Programs," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 550-558, August.
    4. Sun, Yanpeng & Song, Yuru & Long, Chi & Qin, Meng & Lobonţ, Oana-Ramona, 2023. "How to improve global environmental governance? Lessons learned from climate risk and climate policy uncertainty," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 1666-1676.
    5. Jan Gottschalk & Ulrich Fritsche, 2005. "The New Keynesian Model and the Long-Run Vertical Phillips Curve: Does It Hold for Germany?," Discussion Papers of DIW Berlin 521, DIW Berlin, German Institute for Economic Research.
    6. Candelon, Bertrand & Lieb, Lenard, 2013. "Fiscal policy in good and bad times," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2679-2694.
    7. Hyeongwoo Kim & Ying Lin, 2018. "Exchange Rate Pass-Through to Consumer Prices and the Role of Energy Prices," Auburn Economics Working Paper Series auwp2018-05, Department of Economics, Auburn University.
    8. González-Rivera, Gloria & Sun, Yingying, 2017. "Density forecast evaluation in unstable environments," International Journal of Forecasting, Elsevier, vol. 33(2), pages 416-432.
    9. Hansen, Bruce E, 1997. "Approximate Asymptotic P Values for Structural-Change Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 60-67, January.
    10. Guntram B. Wolff & Alexander Schulz, 2008. "Sovereign bond market integration: the euro, trading platforms and globalisation," European Economy - Economic Papers 2008 - 2015 332, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    11. Nyakabawo, Wendy & Miller, Stephen M. & Balcilar, Mehmet & Das, Sonali & Gupta, Rangan, 2015. "Temporal causality between house prices and output in the US: A bootstrap rolling-window approach," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 55-73.
    12. Shinhye Chang & Rangan Gupta & Stephen M. Miller, 2018. "Causality Between Per Capita Real GDP and Income Inequality in the U.S.: Evidence from a Wavelet Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 269-289, January.
    13. Benati, Luca, 2007. "Drift and breaks in labor productivity," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2847-2877, August.
    14. Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2014. "Causality and contagion in EMU sovereign debt markets," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 12-27.
    15. Pierre Perron & Yohei Yamamoto, 2022. "Structural change tests under heteroskedasticity: Joint estimation versus two‐steps methods," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 389-411, May.
    16. Rebeca Jiménez-Rodríguez, 2004. "Oil Price Shocks: Testing for Non-linearity," CSEF Working Papers 115, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    17. Luis Fernando Melo Velandia & Martha Alicia Misas Arango, 2004. "Modelos Estructurales de Inflación en Colombia: Estimación a través de Mínimos Cuadrados Flexibles," Borradores de Economia 3244, Banco de la Republica.
    18. Kuikeu, Oscar, 2011. "Arguments contre la zone franc [Against the cfa franc zone]," MPRA Paper 33710, University Library of Munich, Germany.
    19. Giancarlo Bruno & Edoardo Otranto, 2006. "The choice of time interval in seasonal adjustment: A heuristic approach," Statistical Papers, Springer, vol. 47(3), pages 393-417, June.
    20. Youssef Salman & Joseph Ngatchou-Wandji & Zaher Khraibani, 2024. "Testing a Class of Piece-Wise CHARN Models with Application to Change-Point Study," Mathematics, MDPI, vol. 12(13), pages 1-40, July.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:35485. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.