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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 529-556, April.
    • Handle: RePEc:idn:journl:v:20:y:2018:i:4f:p:529-556
    DOI: https://doi.org/10.21098/bemp.v20i4.905
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    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

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