With the deepening of economic globalization, the economic connections among countries around the world are becoming increasingly close. However, there have been challenges, including some random economic events in certain years, particularly in 2020 due to the COVID-19 pandemic, and the short impacts of these events on economic growth in China have not been quantitatively evaluated. Therefore, the quarterly China total gross domestic product (GDP) and province-level data from 2005 to 2022 are used for exploratory analyzing the short-term impact of the random factors via the singular spectrum analysis (SSA) approach. The key point of this study is that the short-term effects of unforeseen events or national economic policies may be reflected in the residual series obtained by removing the long-term trend as well as the annual and semi-annual signals from the overall GDP data. Six unexpected economic shocks, namely, the “2008 American loan crisis”, the “four trillion yuan investment plan”, “supply-side structural reforms”, the “plan to promote foreign trade growth plan”, the “2020 COVID-19 pandemic” and the “Russia-Ukraine conflict/COVID-19 pandemic”, were strongly evaluated during the period from 2005 to 2022. The results show that the short-term China GDP loss from the 2008 American loan crisis event was 1.99 trillion¥GDP, where 1.22 trillion¥was from secondary industry. The “four trillion yuan investment plan” and “plan to promote foreign trade growth” led to an additional GDP increases of 1.65 and 1.74 trillion¥, respectively. In the past two years, the COVID-19 and Russia-Ukraine conflict caused a GDP reduction of -6.49 trillion¥. The province-level data analysis results show that eastern regions, such as Beijing, Shanghai and Guangdong, which have relatively high dependence ratios of foreign trade, are more easily affected by international external influencing factors. In addition, the predicted GDP indicates that China’s GDP is projected to reach 160 trillion¥ in 2025 without considering future potential unforeseen events.