Health expenditure dynamics and years of U.S. residence: analyzing spending disparities among Latinos by citizenship/nativity status.

According to the Centers for Medicare and Medicaid Services the United States spent U.S.$2.5 trillion on health care in 2009, or approximately U.S.$8,086 per resident (Center for Medicare and Medicaid Services 2010). The previous literature on health-spending disparities demonstrates a clear gap among non-Latino whites (whites, subsequently), African American, and Latinos (Escarce and Kapur 2003; McGuire et al. 2006; Stanton 2006; Cook, McGuire, and Miranda 2007; DiMassa and Escarce 2007). The magnitude of disparities varies across age, health status, and income cohorts (Le Cook, McGuire, and Zuvekas 2009). Differences in health expenditures diminish in the upper levels of the health expenditure distribution; however, health spending for African Americans and Latinos remains significantly low compared with whites (Cook and Manning 2009). A recent multiyear study that analyzes trends on health expenditure disparities between African Americans and Latinos finds that while African American—white disparities have remained constant, Latino–white disparities have widened between 1996–1997 and 2004–2005 (Le Cook, McGuire, and Zuvekas 2009). One possible explanation of these diverging trends on health expenditure could be the disproportionate share of foreign-born residents and immigrants across ethnic/racial groups. In the United States, certain ethnic/racial groups have a higher share of foreign-born individuals. For example, Latinos (38.1 percent) are more likely to be foreign-born compared with African Americans (7.7 percent) and whites (3.9 percent) (PEW Hispanic Center 2009; U.S. Census 2009). The uneven share of foreign-born individuals complicates comparisons across ethnic/racial groups due to immigrant self-selection. Immigrants can be either positively or negatively self-selected, depending on their socioeconomic and demographic characteristics (Borjas 2003; Chiswick, Lee, and Miller 2005). Controlling for citizenship/nativity status is not enough, because the previous literature shows how unobserved characteristics are correlated with foreign-born status (Card 2001). Research on health care and expenditure disparities should address immigrant self-selection by estimating the share of disparities that is due to observed and unobserved characteristics. The outcomes of this analysis are increasingly relevant as Latinos currently represent 15.5 percent of U.S. residents, constituting the largest ethnic minority group in the country (PEW Hispanic Center 2008). According to recent Census estimates, Latinos are likely to represent a quarter of the U.S. population by 2050 (Passel and Cohn 2008). If present trends continue, increasing Latino–white disparities could contribute to raising health-spending inequality. Foreign-born individuals are less likely to spend on health care according to the recent literature (Mohanty et al. 2005; Ku 2009a, b). We thus investigate the dynamics of health expenditure disparities between Latinos and whites analyzing spending by time of U.S. residence and citizenship/nativity status. We later assess whether outcome differences are due to observed or unobserved characteristics. Our first research hypothesis is that increasing Latino–white disparities are partly due to lower spending among foreign-born Latinos who are less likely to spend on health care compared with whites. Our second research hypothesis is that health-spending disparities are likely to decrease the longer Latino residents and immigrants live in the country. Our third hypothesis is that lower spending among foreign-born Latinos could be mostly explained by immigrant self-selection, pictured on different sociodemographic characteristics. To test these hypotheses, we use two-part models to first estimate the probability of reporting any health expenditures and any out-of-pocket (OOP) health spending between Latinos and whites, distinguishing among Latinos by time of U.S. residence and citizenship/nativity status. A subsequent multivariate analysis compares disparities by the amount of total health spending and by the OOP share of health expenditure among individuals who report any spending. A stratified analysis by insurance status is implemented to check for the results' robustness. A second stage of the analyses uses Blinder–Oaxaca decomposition methods to test the proposed hypotheses and to identify specific factors explaining different health expenditure rates.