Forecasting of US GDP using Two Different Methods
DOI:
https://doi.org/10.54097/01tzhh17Keywords:
GDP growth forecasting, series, non-linear regression.Abstract
In the rapid development of society and economy today, Gross Domestic Product (GDP) is regarded as a significant indicator to measure a country’s economic development and residents’ income. In this study, the author introduced several methods used by many scholars in the history, included BP neural network and ARIMA model. Then the author gave two different methods (Series and non-linear regression), next the author used past US GDP data predicted the US GDP tendency in next 2 years. By using first method author figured out the GDP value in 2024 and 2025 is 29.112226k and 30.931449k. And the GDP value in 2024 and 2025 which are predicted by regression is 29.57k and 31.598k. These different results illustrate the difference in prediction between the two different methods. The author explained the different results, and mentioned the advantages and disadvantages of these two methods. At the end future research direction and application were discussed.
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