IDEAS home Printed from https://ideas.repec.org/a/jbl/ref000/v8y2024i1id1158.html

Application of a single-equation SARIMA model for short-term conditional forecast (projection) of CPI price dynamics in Poland

Author

Listed:
  • Patryk Kołbyko

    (Maria Curie-Sklodowska University, Lublin, Poland)

Abstract

The aim of the article is to construct an optimal SARIMA model for short-term conditional forecasting (projection) of the dynamics of prices expressed by the Consumer Price Index (CPI), as understood within the extended Box-Jenkins procedure. The construction of such a forecast aims to influence, through the expectations channel, the institutional trust of society in monetary authorities and assess the effectiveness of achieving the monetary policy goal within the framework of the democratic responsibility of the decision-making body of the National Bank of Poland – the Monetary Policy Council. The selection of the optimal SARIMA model was carried out using an iterative method within the Box-Jenkins procedure, with the goal of reducing the systematic bias of estimators – coherence with empirical data. The analysis was conducted on compiled secondary data of the monthly Consumer Price Index for goods and services from the Central Statistical Office for the years 2010-2023 (on a monthly basis). Results show that the short-term forecast demonstrated accuracy within a specified confidence interval. The application of the SARIMA model serves as a useful methodological tool for constructing elaborate DSGE models (for example, the NECMOD model) using procedures such as SEM (System for Averaging Models) from Norges Bank.

Suggested Citation

  • Patryk Kołbyko, 2024. "Application of a single-equation SARIMA model for short-term conditional forecast (projection) of CPI price dynamics in Poland," Research Papers in Economics and Finance, Poznań University of Economics and Business, vol. 8(1), June.
    • Handle: RePEc:jbl:ref000:v:8:y:2024:i:1:id:1158
    DOI: 10.18559/ref.2024.1.1158
    as

    Download full text from publisher

    File URL: https://journals.ue.poznan.pl/REF/article/view/1158
    File Function: Abstract page
    Download Restriction: no
    File URL: https://journals.ue.poznan.pl/REF/article/download/1158/936
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.18559/ref.2024.1.1158?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    2. Frederic Mishkin & Klaus Schmidt-Hebbel, 2002. "A Decade of Inflation Targeting in the World: What Do We Know and What Do We Need to Know?," Central Banking, Analysis, and Economic Policies Book Series, in: Norman Loayza & Raimundo Soto & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series Editor) (ed.),Inflation Targeting: Desing, Performance, Challenges, edition 1, volume 5, chapter 4, pages 171-220, Central Bank of Chile.
    3. Naoko Hara & Hibiki Ichiue & Satoko Kojima & Koji Nakamura & Toyoichiro Shirota, 2009. "Practical Use of Macroeconomic Models at Central Banks," Bank of Japan Review Series 09-E-1, Bank of Japan.
    4. Alan G. White, 1999. "Measurement Biases in Consumer Price Indexes," International Statistical Review, International Statistical Institute, vol. 67(3), pages 301-325, December.
    5. Marek Gruszczyński, 2022. "Accounting and Econometrics: From Paweł Ciompa to Contemporary Research," JRFM, MDPI, vol. 15(11), pages 1-10, November.
    6. Jacek Białek, 2014. "Pomiar obciążenia wskaźnika cen towarów i usług konsumpcyjnych," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 63-80.
    7. Thijs ten Raa, 2009. "Monopoly, Pareto and Ramsey Mark-ups," Journal of Industry, Competition and Trade, Springer, vol. 9(1), pages 57-63, March.
    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. Garrod Brian & Almeida António & Machado Luiz, 2023. "Modelling of nonlinear asymmetric effects of changes in tourism on economic growth in an autonomous small-island economy," European Journal of Tourism, Hospitality and Recreation, Paradigm, vol. 13(2), pages 154-172, December.
    2. Kenneth N Kuttner, 2004. "A Snapshot of Inflation Targeting in its Adolescence," RBA Annual Conference Volume (Discontinued), in: Christopher Kent & Simon Guttmann (ed.),The Future of Inflation Targeting, Reserve Bank of Australia.
    3. A. Phiri, 2019. "Asymmetries in the revenue–expenditure nexus: new evidence from South Africa," Empirical Economics, Springer, vol. 56(5), pages 1515-1547, May.
    4. Chambers, Marcus J. & Ercolani, Joanne S. & Taylor, A.M. Robert, 2014. "Testing for seasonal unit roots by frequency domain regression," Journal of Econometrics, Elsevier, vol. 178(P2), pages 243-258.
    5. Stephen G Cecchetti & Alfonso Flores-Lagunes & Stefan Krause, 2005. "Assessing the Sources of Changes in the Volatility of Real Growth," RBA Annual Conference Volume (Discontinued), in: Christopher Kent & David Norman (ed.),The Changing Nature of the Business Cycle, Reserve Bank of Australia.
    6. Luis Gil-Alana, 2001. "Seasonal long memory in the US monthly monetary aggregate," Applied Economics Letters, Taylor & Francis Journals, vol. 8(9), pages 573-575.
    7. Pulapre Balakrishnan & M Parameswaran, 2019. "Modeling the Dynamics of Inflation in India," Working Papers 16, Ashoka University, Department of Economics.
    8. Isaac Abunyuwah, 2020. "Modeling Market Integration and Asymmetric Price Transmission Dynamics of Yam Markets in Ghana," Journal of Economics and Behavioral Studies, AMH International, vol. 12(3), pages 23-31.
    9. Alpanda, Sami & Honig, Adam, 2014. "The impact of central bank independence on the performance of inflation targeting regimes," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 118-135.
    10. Gyula Dörgő & Viktor Sebestyén & János Abonyi, 2018. "Evaluating the Interconnectedness of the Sustainable Development Goals Based on the Causality Analysis of Sustainability Indicators," Sustainability, MDPI, vol. 10(10), pages 1-26, October.
    11. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2005. "Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study," Trinity Economics Papers tep20021, Trinity College Dublin, Department of Economics.
    12. Jacek Kotlowski, 2005. "Money and prices in the Polish economy. Seasonal cointegration approach," Working Papers 20, Department of Applied Econometrics, Warsaw School of Economics.
    13. Jimeno, Juan F. & Bentolila, Samuel, 1998. "Regional unemployment persistence (Spain, 1976-1994)," Labour Economics, Elsevier, vol. 5(1), pages 25-51, March.
    14. Jacobson, Tor & Ohlsson, Henry, 1994. "Long-Run Relations between Private and Public Sector Wages in Sweden," Empirical Economics, Springer, vol. 19(3), pages 343-360.
    15. Moosa, Imad A. & Choe, Chongwoo, 1998. "Is the Korean economy export-driven?," Economic Modelling, Elsevier, vol. 15(2), pages 237-255, April.
    16. Ozlem Goktas & Aycan Hepsag, 2011. "Do stock returns lead real economic activity? Evidence from seasonal cointegration analysis," Economics Bulletin, AccessEcon, vol. 31(3), pages 2117-2127.
    17. Koop, Gary & Dijk, Herman K. Van, 2000. "Testing for integration using evolving trend and seasonals models: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 97(2), pages 261-291, August.
    18. Brannlund, Runar & Nordstrom, Jonas, 2004. "Carbon tax simulations using a household demand model," European Economic Review, Elsevier, vol. 48(1), pages 211-233, February.
    19. Shin, Dong Wan & Oh, Man-Suk, 2000. "Semiparametric tests for seasonal unit roots based on a semiparametric feasible GLSE," Statistics & Probability Letters, Elsevier, vol. 50(3), pages 207-218, November.
    20. Paulo Rodrigues & Philip Hans Franses, 2005. "A sequential approach to testing seasonal unit roots in high frequency data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(6), pages 555-569.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:jbl:ref000:v:8:y:2024:i:1:id:1158. 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: Anna Bogajewska-Szymańska (email available below). General contact details of provider: https://journals.ue.poznan.pl/REF .

    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.