Abstract

Empirically, the real GDP growth rates and the unemployment rates are typically negatively correlated. From the post-COVID-19 era, countries around the world have not fully recovered from the pandemic. In this case, forecasts of GDP growth and unemployment rate are a vital reference for governments to recover economies in the future. This study collected the real GDP and unemployment rate data of the United States from 1948 to 2023, studied their relationship through linear and nonlinear regression, and predicted their future trends, respectively, with the ARIMA model. By comparing linear regression and nonlinear regression (locally estimated scatterplot smoothing) between the GDP growth rate and change in the unemployment rate, this study found that nonlinear regression can more accurately express the relationship between these two factors. The forecasts of GDP growth rates and unemployment rates provided by the ARIMA model show a relatively optimistic future with healthy GDP growth and low unemployment. However, wide ranges of confidence intervals also pointed to the danger of low GDP growth and widespread unemployment. The relationship between GDP and unemployment and their projections in this study serve as valuable references for future economic planning and incentive policies in the U.S. government. It may also be applicable to other countries that have similar economic conditions.

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