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While increased access to household assets has been shown to improve older individuals' autonomy and bargaining power at home, the role of gender hierarchy in shaping differential impacts of household assets has received far less attention. This article explores the gender asymmetry in the association of older people's (age 60 years or more) decision-making power at home and survival probability with their ownership of and managerial control over agricultural land in rural India. Using data from the India Human Development Survey, results find that in multi-generational households, landownership at the household level is associated with higher decision-making power and survival probability for older men but not for older women. Among older women, the relationship between household landownership and decision-making power is positive when they have clearly established titles to the land or managerial control but negative when their names are not on the land title. HIGHLIGHTS Landownership is an important source of old age security in India. Agricultural land in India is typically controlled by the patriarch; women rarely own or control household land. The generational power conferred on older men with landownership does not apply to older women to the same degree. It is crucial to register household land under women's names and recognize women as actual landowners. [ABSTRACT FROM AUTHOR]

BACKGROUND: Fertility histories are subject to measurement errors such as incorrect birth dates, incorrect birth orders, incorrect sex, and omissions. These errors can bias demographic estimates such as fertility rates and child mortality rates. OBJECTIVE: We focus on births missing in fertility histories. We estimate the prevalence of such omissions and study their associated factors. METHODS: We leverage a panel survey (the India Human Development Survey) where the same women were interviewed in two waves several years apart. We compare data across waves and identify omitted births. Omissions in the second wave are modeled as a function of several child, mother, household, and survey interviewer variables. Models are fit separately to omissions reported alive or dead in the first wave. RESULTS: We conservatively estimate the prevalence of omissions at 4%. A large majority of omitted births are those of dead children, especially infants, with children in poorer households at greater risk of being omitted. For children alive in wave 1, female children are much more likely to be omitted in wave 2 compared to male children. Interviewers can detect respondent behaviors associated with omissions. CONCLUSIONS Omissions in fertility histories are non-ignorable. They do not randomly occur, and they affect some population subgroups and some interview contexts more than others. CONTRIBUTIONS We investigate the understudied but important phenomenon of omitted births in fertility histories. We bring attention to possible biases in demographic estimates. We shed light on the survey process and propose strategies for minimizing bias through improved survey design. [ABSTRACT FROM AUTHOR]