Statistical Analysis of Domestic Price Volatility of Sugar in Ethiopia

Anteneh Asmare Godana; Yibeltal Arega Ashebir; Tewodros Getinet Yirtaw

doi:doi:10.11648/j.ajtas.20140306.12

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Statistical Analysis of Domestic Price Volatility of Sugar in Ethiopia

Anteneh Asmare Godana, Yibeltal Arega Ashebir, Tewodros Getinet Yirtaw

Published in American Journal of Theoretical and Applied Statistics (Volume 3, Issue 6)

Received: 26 August 2014 Accepted: 9 September 2014 Published: 30 October 2014

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Abstract

The aim of this study was to model and identify determinants of monthly domestic price volatility of sugar in Ethiopia over the study period from December 2001 to December 2011 GC. The volatility in the domestic price of Sugar has been found to vary over months suggesting the use of GARCH family approach. Thus, family of special characteristics of time series models, namely ARCH, GARCH, TGARCH and EGARCH models with ARIMA mean equations were fitted to the data. The best fitting model among each family of models was selected based on how well the model captures the variation in the data and the optimal lag specification accessed via AIC and SBIC. Comparisons of the symmetric and asymmetric model were carried out based on the significance of asymmetric term in TGARCH and EGARCH models. The analysis showed that: statistically significance asymmetric term and least forecast error from the model established that EGARCH model with Student-t distributional assumptions for residual were superior to the GARCH and TGARCH models. Therefore, ARIMA (0,0,2)-EGARCH(1,3) with Student-t were chosen to be the best fitting models for monthly domestic price volatility of Sugar. Moreover, it was found that from candidate explanatory variables, import price for sugar, fuel oil price, exchange rate (dollar-birr), general inflation, inflation for non food items, inflation for food items, past shock, and volatility on monthly domestic price had statistically significant effect on the current month domestic price volatility on sugar.

Published in	American Journal of Theoretical and Applied Statistics (Volume 3, Issue 6)
DOI	10.11648/j.ajtas.20140306.12
Page(s)	177-183
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2014. Published by Science Publishing Group

Keywords

Price Volatility, Time Series Data, ARIMA, ARCH, GARCH, TGARCH, EGARCH Models

References

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[2]	Engle, R. and Fadng, V. K. (1993). Testing and Measuring the Impact of News on Volatility, Journal of Finance Vol 48, P 1749-1778.
[3]	Engle, R. F. (1982). Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of United Kingdom Inflation, Journal of Econometrics, Vol 50, P 987-1007.
[4]	Swaray, R. (2007). How did the Demise of International Commodity Agreements Affect Volatility of Primary Commodity Prices? Applied Economics, Vol 17, P 2253-2260.
[5]	Ridler, D. and Yandle, C. A. (1972). A Simplified Method for Analyzing the Effect of Exchange Rate on Export of Primary Commodity IMF Staff Paper 19, 559-578.
[6]	Loening, J., Durevall, D. and Birru, Y. A. (2009). Inflation Dynamics and Food Prices in an Agricultural Economy: The Case of Ethiopia. World Bank Policy Research Working Paper Series, No. 4969.
[7]	Gilbert, C. L. (1989). The Impact of Exchange Rates and Developing Country Debt on Commodity Prices. Journal of Economics, Vol 99, P 773–84.
[8]	Chambers, R. G. and Just, R. E. (1984). Effects of Exchange Rate Changes on U.S. Agriculture. Journals of Agricultural Economics, Vol 73, P 33-43.
[9]	Saris, A. and Morisson, J. (2009).“The Evolving Structure of World Agriculture Trade: Implication for Trade Policy and Trade Agreements” Food and Agricultural Organization of United Nations (FAO).
[10]	Baffes, J. (2007). Oil Spills on Other Commodities. World Bank Policy Research Working Paper.
[11]	Shahidur Rashid (2007). Intercommunity Price Transmission and Food price policies, an analysis of Ethiopian Cereal Markets, International food policy Research Institute.
[12]	Harald, G. and Stephan, N. (2005). Agricultural Import Surges in Developing Countries: Exogenous Factors in their Emergence, Humboldt-University of Berlin.

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APA Style

Anteneh Asmare Godana, Yibeltal Arega Ashebir, Tewodros Getinet Yirtaw. (2014). Statistical Analysis of Domestic Price Volatility of Sugar in Ethiopia. American Journal of Theoretical and Applied Statistics, 3(6), 177-183. https://doi.org/10.11648/j.ajtas.20140306.12

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ACS Style

Anteneh Asmare Godana; Yibeltal Arega Ashebir; Tewodros Getinet Yirtaw. Statistical Analysis of Domestic Price Volatility of Sugar in Ethiopia. Am. J. Theor. Appl. Stat. 2014, 3(6), 177-183. doi: 10.11648/j.ajtas.20140306.12

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AMA Style

Anteneh Asmare Godana, Yibeltal Arega Ashebir, Tewodros Getinet Yirtaw. Statistical Analysis of Domestic Price Volatility of Sugar in Ethiopia. Am J Theor Appl Stat. 2014;3(6):177-183. doi: 10.11648/j.ajtas.20140306.12

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@article{10.11648/j.ajtas.20140306.12,
  author = {Anteneh Asmare Godana and Yibeltal Arega Ashebir and Tewodros Getinet Yirtaw},
  title = {Statistical Analysis of Domestic Price Volatility of Sugar in Ethiopia},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {3},
  number = {6},
  pages = {177-183},
  doi = {10.11648/j.ajtas.20140306.12},
  url = {https://doi.org/10.11648/j.ajtas.20140306.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20140306.12},
  abstract = {The aim of this study was to model and identify determinants of monthly domestic price volatility of sugar in Ethiopia over the study period from December 2001 to December 2011 GC. The volatility in the domestic price of Sugar has been found to vary over months suggesting the use of GARCH family approach. Thus, family of special characteristics of time series models, namely ARCH, GARCH, TGARCH and EGARCH models with ARIMA mean equations were fitted to the data. The best fitting model among each family of models was selected based on how well the model captures the variation in the data and the optimal lag specification accessed via AIC and SBIC. Comparisons of the symmetric and asymmetric model were carried out based on the significance of asymmetric term in TGARCH and EGARCH models. The analysis showed that: statistically significance asymmetric term and least forecast error from the model established that EGARCH model with Student-t distributional assumptions for residual were superior to the GARCH and TGARCH models. Therefore, ARIMA (0,0,2)-EGARCH(1,3) with Student-t were chosen to be the best fitting models for monthly domestic price volatility of Sugar. Moreover, it was found that from candidate explanatory variables, import price for sugar, fuel oil price, exchange rate (dollar-birr), general inflation, inflation for non food items, inflation for food items, past shock, and volatility on monthly domestic price had statistically significant effect on the current month domestic price volatility on sugar.},
 year = {2014}
}

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TY  - JOUR
T1  - Statistical Analysis of Domestic Price Volatility of Sugar in Ethiopia
AU  - Anteneh Asmare Godana
AU  - Yibeltal Arega Ashebir
AU  - Tewodros Getinet Yirtaw
Y1  - 2014/10/30
PY  - 2014
N1  - https://doi.org/10.11648/j.ajtas.20140306.12
DO  - 10.11648/j.ajtas.20140306.12
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 177
EP  - 183
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20140306.12
AB  - The aim of this study was to model and identify determinants of monthly domestic price volatility of sugar in Ethiopia over the study period from December 2001 to December 2011 GC. The volatility in the domestic price of Sugar has been found to vary over months suggesting the use of GARCH family approach. Thus, family of special characteristics of time series models, namely ARCH, GARCH, TGARCH and EGARCH models with ARIMA mean equations were fitted to the data. The best fitting model among each family of models was selected based on how well the model captures the variation in the data and the optimal lag specification accessed via AIC and SBIC. Comparisons of the symmetric and asymmetric model were carried out based on the significance of asymmetric term in TGARCH and EGARCH models. The analysis showed that: statistically significance asymmetric term and least forecast error from the model established that EGARCH model with Student-t distributional assumptions for residual were superior to the GARCH and TGARCH models. Therefore, ARIMA (0,0,2)-EGARCH(1,3) with Student-t were chosen to be the best fitting models for monthly domestic price volatility of Sugar. Moreover, it was found that from candidate explanatory variables, import price for sugar, fuel oil price, exchange rate (dollar-birr), general inflation, inflation for non food items, inflation for food items, past shock, and volatility on monthly domestic price had statistically significant effect on the current month domestic price volatility on sugar.
VL  - 3
IS  - 6
ER  -

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Author Information

Anteneh Asmare Godana

University of Gondar, College of Natural and Computational Science, Department of Statistics, Gondar, Ethiopia
Yibeltal Arega Ashebir

University of Gondar, College of Natural and Computational Science, Department of Statistics, Gondar, Ethiopia
Tewodros Getinet Yirtaw

University of Gondar, College of Natural and Computational Science, Department of Statistics, Gondar, Ethiopia

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APA Style

Anteneh Asmare Godana, Yibeltal Arega Ashebir, Tewodros Getinet Yirtaw. (2014). Statistical Analysis of Domestic Price Volatility of Sugar in Ethiopia. American Journal of Theoretical and Applied Statistics, 3(6), 177-183. https://doi.org/10.11648/j.ajtas.20140306.12

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ACS Style

Anteneh Asmare Godana; Yibeltal Arega Ashebir; Tewodros Getinet Yirtaw. Statistical Analysis of Domestic Price Volatility of Sugar in Ethiopia. Am. J. Theor. Appl. Stat. 2014, 3(6), 177-183. doi: 10.11648/j.ajtas.20140306.12

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AMA Style

Anteneh Asmare Godana, Yibeltal Arega Ashebir, Tewodros Getinet Yirtaw. Statistical Analysis of Domestic Price Volatility of Sugar in Ethiopia. Am J Theor Appl Stat. 2014;3(6):177-183. doi: 10.11648/j.ajtas.20140306.12

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@article{10.11648/j.ajtas.20140306.12,
  author = {Anteneh Asmare Godana and Yibeltal Arega Ashebir and Tewodros Getinet Yirtaw},
  title = {Statistical Analysis of Domestic Price Volatility of Sugar in Ethiopia},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {3},
  number = {6},
  pages = {177-183},
  doi = {10.11648/j.ajtas.20140306.12},
  url = {https://doi.org/10.11648/j.ajtas.20140306.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20140306.12},
  abstract = {The aim of this study was to model and identify determinants of monthly domestic price volatility of sugar in Ethiopia over the study period from December 2001 to December 2011 GC. The volatility in the domestic price of Sugar has been found to vary over months suggesting the use of GARCH family approach. Thus, family of special characteristics of time series models, namely ARCH, GARCH, TGARCH and EGARCH models with ARIMA mean equations were fitted to the data. The best fitting model among each family of models was selected based on how well the model captures the variation in the data and the optimal lag specification accessed via AIC and SBIC. Comparisons of the symmetric and asymmetric model were carried out based on the significance of asymmetric term in TGARCH and EGARCH models. The analysis showed that: statistically significance asymmetric term and least forecast error from the model established that EGARCH model with Student-t distributional assumptions for residual were superior to the GARCH and TGARCH models. Therefore, ARIMA (0,0,2)-EGARCH(1,3) with Student-t were chosen to be the best fitting models for monthly domestic price volatility of Sugar. Moreover, it was found that from candidate explanatory variables, import price for sugar, fuel oil price, exchange rate (dollar-birr), general inflation, inflation for non food items, inflation for food items, past shock, and volatility on monthly domestic price had statistically significant effect on the current month domestic price volatility on sugar.},
 year = {2014}
}

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TY  - JOUR
T1  - Statistical Analysis of Domestic Price Volatility of Sugar in Ethiopia
AU  - Anteneh Asmare Godana
AU  - Yibeltal Arega Ashebir
AU  - Tewodros Getinet Yirtaw
Y1  - 2014/10/30
PY  - 2014
N1  - https://doi.org/10.11648/j.ajtas.20140306.12
DO  - 10.11648/j.ajtas.20140306.12
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 177
EP  - 183
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20140306.12
AB  - The aim of this study was to model and identify determinants of monthly domestic price volatility of sugar in Ethiopia over the study period from December 2001 to December 2011 GC. The volatility in the domestic price of Sugar has been found to vary over months suggesting the use of GARCH family approach. Thus, family of special characteristics of time series models, namely ARCH, GARCH, TGARCH and EGARCH models with ARIMA mean equations were fitted to the data. The best fitting model among each family of models was selected based on how well the model captures the variation in the data and the optimal lag specification accessed via AIC and SBIC. Comparisons of the symmetric and asymmetric model were carried out based on the significance of asymmetric term in TGARCH and EGARCH models. The analysis showed that: statistically significance asymmetric term and least forecast error from the model established that EGARCH model with Student-t distributional assumptions for residual were superior to the GARCH and TGARCH models. Therefore, ARIMA (0,0,2)-EGARCH(1,3) with Student-t were chosen to be the best fitting models for monthly domestic price volatility of Sugar. Moreover, it was found that from candidate explanatory variables, import price for sugar, fuel oil price, exchange rate (dollar-birr), general inflation, inflation for non food items, inflation for food items, past shock, and volatility on monthly domestic price had statistically significant effect on the current month domestic price volatility on sugar.
VL  - 3
IS  - 6
ER  -

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