An Analysis of In-Migration Patterns for California: A Two-Way Fixed Effects Approach Utilizing a Pooled Sample

Recent policy reports and state briefs continue to highlight the trend of out-migration from California. This outflow has been pronounced over the last three years, revealing a substantial net loss (i.e., net migration) of approximately 740,000 residents. However, there has been comparatively less emphasis on new residents moving to California. Over the past decade, California has attracted substantial in-migration from both domestic and international sources with annual inflows often exceeding 300,000 individuals. As such, studying in-migration is noteworthy as it shapes economic, political, and social landscapes. In-migration can alter the demographic profiles of regions, thereby impacting community dynamics, cultural diversity, and the provision of social services. Using pooled data from the American Community Survey (ACS) from 2021 to 2023 and employing a two-way fixed effects regression framework, I study how temporal changes in racial and ethnic composition, age structure, educational attainment, and economic indicators influence in-migration rates per 1000 residents at the public use microdata level (PUMA). The analysis reveals that higher proportions of Asian and Hispanic populations, as well as an increased share of college-educated residents, are positively associated with in-migration. Notably, higher supplemental poverty rates are also associated with greater in-migration, a counterintuitive finding that may reflect mobility toward affordable housing markets. These findings emphasize the importance of recognizing demographic and intra-regional variability, which can aid policymakers and planners in assessing and delivering public services.