American Journal of Theoretical and Applied Statistics

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Ethiopian Economic Features and Changing Persistence: A Time Series Analysis

Received: 15 October 2019    Accepted: 15 April 2020    Published: 28 April 2020
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Abstract

Ethiopia was one of the countries least developed and it is among the countries in the bottom in the rank of GDP’s that UN lists. However, nowadays Ethiopia is one of the fastest growing economies in the world. In Ethiopia much effort has been made to build the national economy. Ethiopia has made significant strides towards becoming a middle income country by 2025. This paper provides an overview of Box-Jenkins model for temporal data. In this research we used time series analysis of some of Ethiopian economic features such as GDP, GDP growth rate and inflation rate. Box-Jenkins model was used to analyze 35-year data (1981-2015). GDP, GDP growth rate, and inflation rate were variables under the study to describe persistence change and to forecast future behaviors. We tried to find best model for description and predictive model for these series using different model selection tools. We compared different orders of Autoregressive Integrated Moving Average (ARIMA) using AIC, BIC and MSE to fit the observed data. The best from compared was ARIMA (2, 2, 2) for GDP, ARIMA (2, 1, 2) for GDP growth rate and ARIMA (1, 1, 1) for inflation rate. Since forecasting is important for many purposes, we forecast the series from best ARIMA models. Five year forecast showing that GDP is an increasing trend and the average forecast of GDP rates is showing an average of 10.028.

DOI 10.11648/j.ajtas.20200903.12
Published in American Journal of Theoretical and Applied Statistics (Volume 9, Issue 3, May 2020)
Page(s) 37-46
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), 2024. Published by Science Publishing Group

Keywords

ACF, PACF, ARIMA, ARMA, Inflation, GDP, Forecast, Box-Jenkins, Box-Ljung

References
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[6] Sources of Inflation and Economic Growth in Ethiopia Part II By Teshome A. (PhD) 01 September 2011.
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[10] Tewodros Gebru, 2015: Determinants of economic growth in Ethiopia, A time series analysis, Msc thesis, Addis Ababa University.
[11] Javer Contreras et. al 2003: ARIMA models to predict next day electricity price, IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 18, NO. 3.
[12] Burdekin, R. C. K. and P. L. Siklos (1999): ”Exchange rate regimes and shifts in inflation persistence: does nothing else matter Journal of Money, Credit and Banking 31, 235–247.
[13] Mankiw, N. G., J. A. Miron, and D. N. Weil (1987): ”The adjustment of expectations to changek in regime: a study of the founding of the federal reserve.” American Economic Review 77,
[14] Hakkio, C. S. and M. Rush (1991): ”Is the budget deficit too large?” Economic Inquiry.
[15] Wayne A. Fuller 1996: Introduction to statistical time series, second Edition, Wiley Series in probability and statistics.
[16] Alexander Aue, 2010: Applied Time series analysis, Lecture notes, University of California, Davis.
[17] Robert Yaffee with Monnie McGee; 1999: Introduction to time series analysis and forecasting with application of SAS and SPSS.
[18] W. N. Venables, D. M. smith and the R-core team, 2016: An introduction to R.
[19] Alemayehu Geda, Addis yimer, 2014: Growth, Poverity and Inquality in Ethiopia, 2000-2013: Amacroeconomic Appraisal, Department of Economics Addis Ababa university.
[20] Chinoso Michael, Oluchukuwu Chukuwuemeka, Charity Uchena, Nnaemeka Martin Eze, Chukwunenya Ifeanyi Okonkwo. On the Fourier Residual Modification of Arima Models in Modeling Malaria Incidence Rates among Pregnant Women. American Journal of Theoretical and Applied Statistics Vol. 9, No. 1, 2020, pp. 1-7. doi: 10.11648/j.ajtas.20200901.11
[21] Admasu Shiferaw, 2017: Productive capacity and Economic growth in Ethiopia. Department of Economic and social affairs. CDP Background Paper No. 34.
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[23] Adisie Melak 2018: The Contribution of Foreign Direct Investment for Economic growth of Ethiopia: Time Series Analysis DebreTabor University, Ethiopia
Author Information
  • Department of Statistics, Werabe University, Werabe, Ethiopia

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    Tofik Mussa Reshid. (2020). Ethiopian Economic Features and Changing Persistence: A Time Series Analysis. American Journal of Theoretical and Applied Statistics, 9(3), 37-46. https://doi.org/10.11648/j.ajtas.20200903.12

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    Tofik Mussa Reshid. Ethiopian Economic Features and Changing Persistence: A Time Series Analysis. Am. J. Theor. Appl. Stat. 2020, 9(3), 37-46. doi: 10.11648/j.ajtas.20200903.12

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    AMA Style

    Tofik Mussa Reshid. Ethiopian Economic Features and Changing Persistence: A Time Series Analysis. Am J Theor Appl Stat. 2020;9(3):37-46. doi: 10.11648/j.ajtas.20200903.12

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  • @article{10.11648/j.ajtas.20200903.12,
      author = {Tofik Mussa Reshid},
      title = {Ethiopian Economic Features and Changing Persistence: A Time Series Analysis},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {9},
      number = {3},
      pages = {37-46},
      doi = {10.11648/j.ajtas.20200903.12},
      url = {https://doi.org/10.11648/j.ajtas.20200903.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajtas.20200903.12},
      abstract = {Ethiopia was one of the countries least developed and it is among the countries in the bottom in the rank of GDP’s that UN lists. However, nowadays Ethiopia is one of the fastest growing economies in the world. In Ethiopia much effort has been made to build the national economy. Ethiopia has made significant strides towards becoming a middle income country by 2025. This paper provides an overview of Box-Jenkins model for temporal data. In this research we used time series analysis of some of Ethiopian economic features such as GDP, GDP growth rate and inflation rate. Box-Jenkins model was used to analyze 35-year data (1981-2015). GDP, GDP growth rate, and inflation rate were variables under the study to describe persistence change and to forecast future behaviors. We tried to find best model for description and predictive model for these series using different model selection tools. We compared different orders of Autoregressive Integrated Moving Average (ARIMA) using AIC, BIC and MSE to fit the observed data. The best from compared was ARIMA (2, 2, 2) for GDP, ARIMA (2, 1, 2) for GDP growth rate and ARIMA (1, 1, 1) for inflation rate. Since forecasting is important for many purposes, we forecast the series from best ARIMA models. Five year forecast showing that GDP is an increasing trend and the average forecast of GDP rates is showing an average of 10.028.},
     year = {2020}
    }
    

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    AU  - Tofik Mussa Reshid
    Y1  - 2020/04/28
    PY  - 2020
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    T2  - American Journal of Theoretical and Applied Statistics
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    JO  - American Journal of Theoretical and Applied Statistics
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    AB  - Ethiopia was one of the countries least developed and it is among the countries in the bottom in the rank of GDP’s that UN lists. However, nowadays Ethiopia is one of the fastest growing economies in the world. In Ethiopia much effort has been made to build the national economy. Ethiopia has made significant strides towards becoming a middle income country by 2025. This paper provides an overview of Box-Jenkins model for temporal data. In this research we used time series analysis of some of Ethiopian economic features such as GDP, GDP growth rate and inflation rate. Box-Jenkins model was used to analyze 35-year data (1981-2015). GDP, GDP growth rate, and inflation rate were variables under the study to describe persistence change and to forecast future behaviors. We tried to find best model for description and predictive model for these series using different model selection tools. We compared different orders of Autoregressive Integrated Moving Average (ARIMA) using AIC, BIC and MSE to fit the observed data. The best from compared was ARIMA (2, 2, 2) for GDP, ARIMA (2, 1, 2) for GDP growth rate and ARIMA (1, 1, 1) for inflation rate. Since forecasting is important for many purposes, we forecast the series from best ARIMA models. Five year forecast showing that GDP is an increasing trend and the average forecast of GDP rates is showing an average of 10.028.
    VL  - 9
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