  This study explored the variability in Aggregate Personal Income (PI) across
13 major industrial sectors in the US during the COVID-19 pandemic. Utilizing
time-series data from 2010 Q1 to 2019 Q4, we employed Autoregressive Integrated
Moving Average (ARIMA) models to establish baseline trends in Personal Income
(PI) before the pandemic. We then extended these models to forecast PI values
for the subsequent 14 quarters, from 2020 Q1 to 2023 Q2, as if the pandemic had
never happened. This forecasted data was compared with the actual PI data
collected during the pandemic to quantify its impacts. This approach allowed
for the assessment of both immediate and extended effects of COVID-19 on
sector-specific PI. Our study highlighted the resilience of PI in sectors like
Utilities, Retail, Finance, Real Estate, and Healthcare, with Farming showing
an early recovery in PI, despite significant initial setbacks. In contrast, PI
in Accommodation and Food Services experienced delayed recovery, contributing
significantly to the overall impact variance alongside Farming (53.26\% and
33.26\% respectively). Finance and Utilities demonstrated positive deviations,
suggesting a lesser impact or potential benefit in early pandemic stages.
Meanwhile, sectoral PI in Manufacturing, Wholesale and Education showed
moderate recovery, whereas Construction and Government lagged in resilience.
The aggregate economic impact, initially negative at -0.027 in 2020 Q1,
drastically worsened to -1.42 in Q2, but improved by Q4, reflecting a broader
trend of adaptation and resilience across all the sectors during the pandemic.
