IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/86180.html
   My bibliography  Save this paper

Comparison between Static and Dynamic Forecast in Autoregressive Integrated Moving Average for Seasonally Adjusted Headline Consumer Price Index

Author

Listed:
  • Jackson, Emerson Abraham

Abstract

This empirical study has provided interpretive outcome from a univariate forecast using Box-Jenkins ARIMA methodology. The HCPI_SA seasonally adjusted data for Sierra Leone shows a robust model outcome with three months ahead prediction based on the STATIC method result. Test results like Autocorrelation and also comparative values for MAPE and the Inverted Root values have indicated that the model is a good fit. Despite better choice of outcome from the STATIC result in comparison to DYNAMIC forecast, the conclusion a cautious means of advice when using results for policy outcomes and with comparative forecasts highly recommended a way forward in guiding policy makers’ decision.

Suggested Citation

  • Jackson, Emerson Abraham, 2018. "Comparison between Static and Dynamic Forecast in Autoregressive Integrated Moving Average for Seasonally Adjusted Headline Consumer Price Index," MPRA Paper 86180, University Library of Munich, Germany, revised 12 Apr 2018.
    • Handle: RePEc:pra:mprapa:86180
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/86180/1/MPRA_paper_86180.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Emerson Abraham Jackson & Edmond Tamuke & Abdulai Sillah, 2018. "Modelling Monthly Headline Consumer Price Index (HCPI) through Seasonal Box-Jenkins Methodology," International Journal of Sciences, Office ijSciences, vol. 7(01), pages 51-56, January.
    2. Ericsson, Neil R., 2017. "Economic forecasting in theory and practice: An interview with David F. Hendry," International Journal of Forecasting, Elsevier, vol. 33(2), pages 523-542.
    3. Raffaella Giacomini, 2015. "Economic theory and forecasting: lessons from the literature," Econometrics Journal, Royal Economic Society, vol. 18(2), pages 22-41, June.
    4. Hubrich, Kirstin, 2005. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," International Journal of Forecasting, Elsevier, vol. 21(1), pages 119-136.
    5. Ikechukwu Kelikume & Adedoyin Salami, 2014. "Time Series Modeling and Forecasting Information: Evidence from Nigeria," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 8(2), pages 41-51.
    6. Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Bayesian VAR Models for Forecasting Irish Inflation," MPRA Paper 11360, University Library of Munich, Germany.
    7. James W. Taylor, 2008. "A Comparison of Univariate Time Series Methods for Forecasting Intraday Arrivals at a Call Center," Management Science, INFORMS, vol. 54(2), pages 253-265, February.
    8. J W Taylor, 2003. "Short-term electricity demand forecasting using double seasonal exponential smoothing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(8), pages 799-805, August.
    9. Bianchi, Lisa & Jarrett, Jeffrey & Choudary Hanumara, R., 1998. "Improving forecasting for telemarketing centers by ARIMA modeling with intervention," International Journal of Forecasting, Elsevier, vol. 14(4), pages 497-504, December.
    10. Ette Harrison Etuk & Imoh Udo Moffat & Benjamin Ele Chims, 2013. "Modelling Monthly Rainfall Data of Port Harcourt, Nigeria by Seasonal Box-Jenkins Methods," International Journal of Sciences, Office ijSciences, vol. 2(07), pages 60-67, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jackson Emerson Abraham, 2017. "Theoretical and Methodological Context of (Post)-Modern Econometrics and Competing Philosophical Discourses for Policy Prescription," Journal of Heterodox Economics, Sciendo, vol. 4(2), pages 119-129, December.
    2. Jackson, Emerson Abraham & Tamuke, Edmund, 2019. "Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model," MPRA Paper 96845, University Library of Munich, Germany, revised 23 Dec 2019.
    3. Emerson Abraham JACKSON & Mohamed JABBİE & Edmund TAMUKE & Augustine NGOMBU, 2020. "Adoption of Inflation Targeting in Sierra Leone: An Empirical Discourse," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 7(2), pages 21-50, July.
    4. Jackson, Emerson Abraham & Tamuke, Edmund, 2018. "Probability Forecast Using Fan Chart Analysis: A case of the Sierra Leone Economy," MPRA Paper 88853, University Library of Munich, Germany, revised 04 Sep 2018.
    5. Jackson, Emerson Abraham, 2020. "Understanding SLL / US$ exchange rate dynamics in Sierra Leone using Box-Jenkins ARIMA approach," MPRA Paper 97965, University Library of Munich, Germany, revised 03 Jan 2020.
    6. JACKSON Emerson Abraham & TAMUKE Edmund & JABBIE Mohamed, 2019. "Disaggregated Short-Term Inflation Forecast (Stif) For Monetary Policy Decision In Sierra Leone," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 71(3), pages 31-53, November.
    7. Emerson Abraham Jackson, 2021. "Forecasting COVID-19 Daily Contraction in Sierra Leone with Implications for Policy Formulation," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 8(1), pages 29-43, January.

    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. Jackson, Emerson Abraham & Tamuke, Edmund, 2019. "Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model," MPRA Paper 96845, University Library of Munich, Germany, revised 23 Dec 2019.
    2. Barrow, Devon K., 2016. "Forecasting intraday call arrivals using the seasonal moving average method," Journal of Business Research, Elsevier, vol. 69(12), pages 6088-6096.
    3. Theresa Maria Rausch & Tobias Albrecht & Daniel Baier, 2022. "Beyond the beaten paths of forecasting call center arrivals: on the use of dynamic harmonic regression with predictor variables," Journal of Business Economics, Springer, vol. 92(4), pages 675-706, May.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Jackson, Emerson Abraham, 2018. "On the question of the relevance of Economics as a science: Postmodern filosofia critique," EconStor Preprints 177393, ZBW - Leibniz Information Centre for Economics.
    6. Ibrahim, Rouba & Ye, Han & L’Ecuyer, Pierre & Shen, Haipeng, 2016. "Modeling and forecasting call center arrivals: A literature survey and a case study," International Journal of Forecasting, Elsevier, vol. 32(3), pages 865-874.
    7. Rouba Ibrahim & Pierre L'Ecuyer, 2013. "Forecasting Call Center Arrivals: Fixed-Effects, Mixed-Effects, and Bivariate Models," Manufacturing & Service Operations Management, INFORMS, vol. 15(1), pages 72-85, May.
    8. Jackson, Emerson Abraham & Tamuke, Edmund, 2018. "Probability Forecast Using Fan Chart Analysis: A case of the Sierra Leone Economy," MPRA Paper 88853, University Library of Munich, Germany, revised 04 Sep 2018.
    9. Jackson, Emerson Abraham & Tamuke, Edmund & Jabbie, Mohamed, 2019. "Disaggregated Short-Term Inflation Forecast (STIF) for Monetary Policy Decision in Sierra Leone," MPRA Paper 96735, University Library of Munich, Germany, revised 26 Nov 2019.
    10. Mauro Bernardi & Lea Petrella, 2015. "Multiple seasonal cycles forecasting model: the Italian electricity demand," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(4), pages 671-695, November.
    11. Andrea BASTIANIN & Marzio GALEOTTI & Matteo MANERA, 2011. "Forecast evaluation in call centers: combined forecasts, flexible loss functions and economic criteria," Departmental Working Papers 2011-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    12. Kim, Myung Suk, 2013. "Modeling special-day effects for forecasting intraday electricity demand," European Journal of Operational Research, Elsevier, vol. 230(1), pages 170-180.
    13. JACKSON Emerson Abraham & TAMUKE Edmund & JABBIE Mohamed, 2019. "Disaggregated Short-Term Inflation Forecast (Stif) For Monetary Policy Decision In Sierra Leone," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 71(3), pages 31-53, November.
    14. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2019. "Statistical and economic evaluation of time series models for forecasting arrivals at call centers," Empirical Economics, Springer, vol. 57(3), pages 923-955, September.
    15. Barrow, Devon & Kourentzes, Nikolaos, 2018. "The impact of special days in call arrivals forecasting: A neural network approach to modelling special days," European Journal of Operational Research, Elsevier, vol. 264(3), pages 967-977.
    16. James W. Taylor, 2012. "Density Forecasting of Intraday Call Center Arrivals Using Models Based on Exponential Smoothing," Management Science, INFORMS, vol. 58(3), pages 534-549, March.
    17. Diogo de Prince & Emerson Fernandes Marçal & Pedro L. Valls Pereira, 2022. "Forecasting Industrial Production Using Its Aggregated and Disaggregated Series or a Combination of Both: Evidence from One Emerging Market Economy," Econometrics, MDPI, vol. 10(2), pages 1-34, June.
    18. Taylor, James W., 2010. "Triple seasonal methods for short-term electricity demand forecasting," European Journal of Operational Research, Elsevier, vol. 204(1), pages 139-152, July.
    19. Haipeng Shen & Jianhua Z. Huang, 2008. "Interday Forecasting and Intraday Updating of Call Center Arrivals," Manufacturing & Service Operations Management, INFORMS, vol. 10(3), pages 391-410, July.
    20. James W. Taylor, 2008. "A Comparison of Univariate Time Series Methods for Forecasting Intraday Arrivals at a Call Center," Management Science, INFORMS, vol. 54(2), pages 253-265, February.

    More about this item

    Keywords

    ARIMA; Forecast; Headline Consumer Price Index [HCPI]; Sierra Leone;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    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:86180. 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.