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Long-Term GDP Forecasts and the Prospects for Growth

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  • MODIS, THEODORE

Abstract

The growth of GDP is considered as a natural-growth process amenable to description by the logistic-growth equation. The S-shaped logistic pattern provides good descriptions and forecasts for both nominal and real GDP per capita in the US over the last 80 years. This enables the calculation of a long-term forecast for inflation, which is to enter a declining trend not so far in the future. The two logistics are well advanced, more so for nominal GDP. The assumption for logistic growth works even better for Japan whose nominal GDP per capita has already completed tracing out an entire logistic trajectory. The economic woes of industrialized countries could be attributed to the saturation of growth there, as if a niche in nature had been filled to capacity. In contrast, GDP growth in China and India is in the very early stages of logistic growth still indistinguishable from exponential patterns. The ceiling of these logistics can be anywhere between 7 and 15 times today’s levels.

Suggested Citation

  • Modis, Theodore, 2013. "Long-Term GDP Forecasts and the Prospects for Growth," OSF Preprints aqcht, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:aqcht
    DOI: 10.31219/osf.io/aqcht
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    1. Modis, Theodore, 1994. "Determination of the Uncertainties in S-Curve Logistic Fits," OSF Preprints n53pd, Center for Open Science.
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    Cited by:

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    4. Sokolov-Mladenović, Svetlana & Milovančević, Milos & Mladenović, Igor, 2017. "Evaluation of trade influence on economic growth rate by computational intelligence approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 358-362.
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    6. Marković, Dušan & Petković, Dalibor & Nikolić, Vlastimir & Milovančević, Miloš & Petković, Biljana, 2017. "Soft computing prediction of economic growth based in science and technology factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 217-220.
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    12. Igor Mladenović & Miloš Milovančević & Svetlana Sokolov-Mladenović, 2017. "RETRACTED ARTICLE: Analyzing of innovations influence on economic growth by fuzzy system," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1297-1304, May.
    13. Maksimović, Goran & Jović, Srđan & Jovanović, Radomir, 2017. "Economic growth rate management by soft computing approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 520-524.
    14. Kordanuli, Bojana & Barjaktarović, Lidija & Jeremić, Ljiljana & Alizamir, Meysam, 2017. "Appraisal of artificial neural network for forecasting of economic parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 515-519.

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