Leading Indicators of Heating Coal Pricing in Turkey: A Coal Pricing Model (2003-2009)
Mehmet Mithat Mithat Uner, Nezir Kose, Soner Gokten
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DOI: 10.4236/nr.2011.22014   PDF    HTML     4,396 Downloads   8,997 Views  

Abstract

In this study, a coal pricing model for Turkey is developed employing Granger causality and cointegration analysis by using monthly data between January 2003 and April 2009. Empirical results based on Granger causality tests indicate that foreign coal futures prices and domestic consumer price index for energy sector can be used as the leading indica- tors for domestic coal prices for Turkey. An error correction model for Turkish coal pricing is specified by taking into account the results of Granger causality. The forecast of the coal prices based on error correction model is giving very successful results. It is observed that the coal prices and forecasted coal prices values are almost moving together or very close to each other.

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M. Uner, N. Kose and S. Gokten, "Leading Indicators of Heating Coal Pricing in Turkey: A Coal Pricing Model (2003-2009)," Natural Resources, Vol. 2 No. 2, 2011, pp. 102-106. doi: 10.4236/nr.2011.22014.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] M. M. Uner, N. Kose, S. Gokten, and P. Okan, “Financial and Economic Factors Affecting the Lignite Prices in Turkey: An Analysis of Soma and Can Lignites,” Resources Policy, Vol. 33, No. 4, 2008, pp. 230-239. doi:10.1016/j.resourpol.2008.08.007
[2] C. W. J. Granger, “Investigating Causal Relations by Econometric Models: Cross Spectral Methods,” Econometrica, Vol. 37, No. 3, 1969, pp. 424–438. doi:10.2307/1912791
[3] J. R. McCrorie and M. J. Chambers, “Granger Causality and the Sampling of Economic Processes,” Journal of Econometrics, Vol. 132, No. 2, 2006, pp. 311-336. doi:10.1016/j.jeconom.2005.02.002
[4] D. Tj?stheim, “Granger-causality in multiple time series,” Journal of Econometrics, Vol. 17, No. 2, 1981, pp. 157-176. doi:10.1016/0304-4076(81)90024-5
[5] G. S. Maddala and M. Kim, “Unit Roots, Cointegration and Structural Change,” Cambridge University Press, 2002.
[6] J. Y. Park and P. C. B. Philips, “Statistical Inference in Regressions with Integrated Process: Part 2,” Econometric Theory, Vol. 5, 1989, pp. 95-132. doi:10.1017/S0266466600012287
[7] C. A. Sims, J. H. Stock and M. W. Watson, “Inference in Linear Time Series Models With Some Unit Roots,” Econometrica, Vol. 58, 1990, pp. 113-144. doi:10.2307/2938337
[8] H. Y. Toda and P. C. B. Phillips, “Vector Autoregression and Causality,” Econometrica, Vol. 59, 1993, pp. 229-255. doi:10.1016/0304-4076(93)90024-Y
[9] H. Toda and T. Yamamato, “Statistical Inference in Vector Autoregressions with Possibly Integrated Processes,” Journal of Econometrics, Vol. 66, 1995, pp. 225-250. doi:10.1016/0304-4076(94)01616-8
[10] D. A. Dickey and W. A. Fuller, “Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root,” Econometrica, Vol. 49, 1981, pp. 1057-1072. doi:10.2307/1912517
[11] P. Perron, “The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis,” Econometrica, Vol. 57, 1989, pp. 1361-1401. doi:10.2307/1913712
[12] E. Zivot and D. Andrews, “Further Evidence on the Great Crash, the Oil-Price Shocks, and the Unit Root hy- pothesis,” Journal of Business and Economic Statistics, Vol. 10, 1992, pp. 251-272. doi:10.2307/1391541
[13] P. Perron, “Further Evidence on Breaking Trend Functions in Macroeconomic Variables,” Journal of Econometrics, Vol. 80, 1997, pp. 355-385. doi:10.1016/S0304-4076(97)00049-3
[14] S. Johansen and K. Juselius, “Maximum Likelihood Estimation and Inference on Cointegration with Applications to the Demand for Money,” Oxford Bulletin of Economics and Statistics, Vol. 52, 1990, pp. 169-210. doi:10.1111/j.1468-0084.1990.mp52002003.x
[15] H. Lütkepohl and M. M. Burda, “Modified Wald Tests under Nonregular Conditions,” Journal of Econometrics, Vol. 78, No. 1, 1997, pp. 315-332. doi:10.1016/S0304-4076(97)80015-2

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