IDEAS home Printed from https://ideas.repec.org/a/idn/journl/v20y2018i4p1-28.html
   My bibliography  Save this article

Disaggregation And Forecasting Of The Monthly Indonesian Gross Domestic Product (Gdp)

Author

Listed:
  • Profita Sumunar Luthfiana

    (Statistic Indonesia Government Office)

  • Nasrudin

    (Sekolah Tinggi Ilmu Statistik (STIS) Jakarta)

Abstract

Gross Domestic Product (GDP) is considered as the the best measure of economic performance. However, in Indonesia, the GDP is presented in quarterly aggregate value. As a result, the monthly economic outlook is known, and analysis with other monthly economic variables become limited. Therefore, this study will disaggregate quarterly GDP into monthly GDP and its forecasting by using one of the coincident indicators which are monthly Production Index of Large and Medium Manufacturing (industrial production index). Disaggregation is done on National GDP data of Indonesia period 2000/I to 2016/IV, whereas forecasting is made on monthly and quarterly GDP 2017. This study uses combination of the simple linear regression model and ARIMA model with some modifications. The disaggregation result indicates that the monthly GDP moves volatile and has a different pattern between quarter. Also,the monthly GDP disaggregation and forecasting are proven that can be used by industrial production index that becomes a coincident indicator. GDP 2017 shows that the highest quarterly GDP will have occurred in the third quarter, whereas the highest monthly GDP will have occurred in June (second quarter). The result of disaggregation can be used further to the study of economic outlook will be more comprehensive.

Suggested Citation

  • Profita Sumunar Luthfiana & Nasrudin, 2018. "Disaggregation And Forecasting Of The Monthly Indonesian Gross Domestic Product (Gdp)," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 20(4), pages 1-28, April.
    • Handle: RePEc:idn:journl:v:20:y:2018:i:4:p:1-28
    DOI: https://doi.org/10.21098/bemp.v20i4.905
    as

    Download full text from publisher

    File URL: https://www.bmeb-bi.org/index.php/BEMP/article/download/905/701
    Download Restriction: no
    File URL: https://libkey.io/https://doi.org/10.21098/bemp.v20i4.905?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
    ---><---

    Citations

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


    Cited by:

    1. Berry A. Harahap & Pakasa Bary & Anggita Cinditya M. Kusuma, 2020. "The Determinants of Indonesia’s Business Cycle," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 9(special i), pages 215-235.

    More about this item

    Keywords

    Disaggregation; Monthly GDP; Coincident Indicator; Industrial Production Index; ARIMA;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:idn:journl:v:20:y:2018:i:4:p:1-28. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Lutzardo Tobing or Jimmy Kathon (email available below). General contact details of provider: https://edirc.repec.org/data/bigovid.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.