Author(s) :

Sean Ting.

Volume/Issue :

Abstract :

This study explores long-term unemployment trends in California across two geographic scales: county and state levels. While state-wide unemployment rates are often used as an indicator for economic health, this research paper highlights how such indicators can hide local and regional variations. Using California labor force and unemployment data from 1990 to 2025, this paper critiques the limitations of linear models that assume uniform trends across different geographical scales. The findings reveal that several counties were not representative of the state’s averages, deviating significantly from state-wide averages. Counties, such as Imperial County and Colusa County, significantly deviated from California state-wide averages with Imperial County having the most significant deviation, with a mean deviation of 15.59 percentage points throughout the period of 35 years. The study also found that simplistic models like linear regression models were not accurate at predictions for both the state and county levels, with R-squared values of less than 0.14. The findings highlight the importance of economic policies that account for local conditions to ensure more equitable regional support. The results also show that simplistic models can risk misinformed economic decision-making.