Search

Removing racial differences when examining asset ownership reduced wealth inequality significantly, with whites buying more high-return, high-risk assets than blacks. Most of the remaining difference can be accounted for by racial differences in educational attainment.

Abstract The intergenerational transfer of assets helps create and maintain wealth inequality over time, and cohort differences in these wealth transfers provide unique insights into the changing mechanisms that lead to inequality. We examine cohort differences in asset transfers in two ways. First, we explore whether there are general cohort differences. Second, we examine how transfers have changed across four specific U.S. birth cohorts. We draw on ideas from research on cohort succession processes to document differences across cohorts in financial resources, and we draw on work on bequest behavior to address how resource differences might lead to cohort differences in transfers. Using the Survey of Consumer Finances, we find that members of younger cohorts are less likely than members of older cohorts to receive any transfer but that younger recipients receive larger transfers. We also find that members of younger cohorts are less likely to receive inheritances and trusts, more likely to receive inter vivos gifts, and less likely to inherit at any age than members of older cohorts. Our findings underscore the importance of birth cohorts in studies of inequality and suggest that wealth inequality may worsen over time given that a smaller number of people are receiving large transfers. [ABSTRACT FROM AUTHOR]

Growing inequality has heightened awareness of those at the top of the income and wealth distributions, and researchers are beginning to acknowledge the need for a way to identify top households that simultaneously accounts for their income and net worth. We contribute to the literatures on top income and wealth households by introducing a measure of top status that includes a larger number of affluent households and that explicitly accounts for the interrelationship between income and wealth. Our innovation is to start with both income and wealth holders and to divide the top into three groups: those who are top income only, those who are top net worth only, and those who are at the top of both distributions (the double one percent). Our results show that the top three groups are unique financially and demographically in ways that inform understanding of inequality and the processes that lead to membership in top income and wealth positions. Perhaps most importantly, our results identify those who are merely elite and those who occupy even more exclusive, or super elite, positions at the top of both the income and wealth distributions. [ABSTRACT FROM AUTHOR]

The article presents information on changes in firm labor practices and policies and discuss how these are likely to impact the nature of social stratification in China. The study emphasizes differences between state-owned enterprises (SOE) and non-SOEs in order to highlight the role that firm ownership structure is likely to play in defining future stratification systems. The article further draws on recently-collected longitudinal (1994-1999) quantitative survey data on 800 Chinese SOEs and non-SOEs, including 433 SOEs and 367 firms with other ownership structures. In the next section, I provide a brief synopsis of the nature of enterprises prior to reform and describe the way labor reform affected firms. An overview of the survey is then presented by discussing how information from this survey informs understanding of the relationship between changing labor practices and stratification. The article also explores current labor conditions in Chinese firms, characteristics of workers, and the nature of current hiring and termination practices. The objective of the author is to provide a snapshot of the nature of labor conditions in China at the turn of the millennium and to discuss the potential for these conditions to shape the future of social stratification in that country.

This study broadens the traditional focus on income as the primary measure of economic deprivation by providing the first analysis of wealth deprivation, or net worth poverty (NWP), and adult health. Net worth poverty—having wealth (assets minus debts) less than one-fourth of the federal poverty line—likely exacerbates the negative effects of income poverty (IP). In 2019, one-third of US households were net worth poor, with substantially higher rates among Black (60%) relative to White (25%) households. We estimate longitudinal growth curve (i.e., linear mixed effects) models to test how NWP, IP, and the interaction of the two predict a diverse set of health measures. We also consider whether NWP resulting from either low assets or high debts is more predictive of health outcomes and test for heterogeneous associations by race. Data come from Panel Study of Income Dynamics on 8,962 individuals ages 25 to 64, observed between 2011 and 2019 (n = 26,776). Adjusting for income poverty, net worth poverty, relative to no poverty, was associated with a one-quarter to one-third increase in the likelihood of reporting poor self-rated health, psychological distress, and work limitations. Simultaneously experiencing both NWP and IP was associated with the largest deficits. Both asset-driven (low asset) and debt-driven (high debt) NWP reduced health, but asset-driven NWP had stronger associations (e.g., a 5-percentage point increase of being in poor health, twice that of debt-driven). White, relative to Black, adults exhibited statistically larger associations for psychological distress (4.3 vs 1.1 percentage points) and work limitations (3.7 vs. 1.5 percentage points). White and Black adults who were jointly net worth and income poor exhibited the most disadvantage. Findings underscore how wealth is a critical component of financial deprivation and that wealth deprivation, particularly the lack of assets, merits attention in socioeconomic studies of health inequalities. • Net worth poverty-wealth less than 1/4 of poverty line-negatively predicts health. • Net worth poverty related to poor health, psychological distress, and work limits. • Being both net worth and income poor put Black and White adults at the most risk. • Lack of assets may be more consequential for poor health than high debt. [ABSTRACT FROM AUTHOR]