Since the outbreak of the COVID-19 pandemic in 2020, the issue of unemployment has garnered widespread attention from the government, the public, employers and various other stakeholders. In this context, accurate prediction of the unemployment rate has become particularly crucial. This study builds upon previous research and focuses on the unemployment rate data in Texas from January 1976 to September 2023. Firstly, the data undergoes first-order differencing to transform it into a stable time series. Subsequently, the author constructs ARIMA models with different parameters and select appropriate evaluation metrics to obtain more accurate forecasting results. Finally, in conjunction with the realities of the COVID-19 pandemic, a comprehensive analysis is conducted on both the predictive outcomes and the original data. Analysis of the raw data shows that the impact of the COVID-19 pandemic on the unemployment rate is undeniable. The forecasting results indicate an upward trend in the unemployment rate for the state of Texas. Based on these analyses, this paper presents some policy recommendations to the government in addressing the unemployment issue.
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Xiuyuan ShangGuan (2024) studied this question.
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