Recent research has documented the decline in residential mobility rates in the United States over the past several decades, accelerating over the Great Recession. In particular, interstate migration dropped by about 50 percent since 1991 (Kaplan and Schuhofer-Wohl, 2013). Such patterns vary by age, gender, education, race/ethnicity, family structure, and nativity. (Molloy et al 2011). Immigrant populations have been historically more mobile than native born populations in pursuit of economic opportunities and because of less strong ties to particular places. After the recession, Painter and Yu (2014) found that the mobility of immigrants in established gateways fell to the rate of native born populations in those places.  This could be due to reduced economic opportunities (Liu and Edwards, 2014), but could also be due to changes in the composition of the immigrant population in those areas as some may have left the area due to disproportionate job losses in those areas (Painter and Calnan, 2013).

This research will systematically examine the overall mobility patterns of the immigrants and native-born populations over three decades from 1990 to 2010 (specifically, 1990, 2000, 2005, and 2010 to better characterize changes over the economic cycle). The study will first determine whether the mobility rates of immigrants declined at a similar rate as did the native born population.  Second, we will focus on what have been the primary drivers of this change in mobility.  Age-cohort and regression analysis will be conducted to assess the relative importance of age cohorts, arrival cohorts, as well as other individual socio-demographic characteristics including skills, race/ethnicity, and national origin in immigrants’ mobility choices.  Distinction will be made among inter-state, inter-MSA, and inter-county moves to understand mobility across various geographic scales.

We will use Decennial Census Microdata from 1990 and 2000 and American Community Survey Microdata for 2005 and 2008-2012 combined samples (for 2010) for the empirical analysis. We will focus on a series of mobility variables on the individual’s mobility status as well as mobility origins and destinations (same or different state, MSA, Public Use Microdata Area, and county).