Graduate Thesis Or Dissertation

Money and nonmoney incomes of elderly families and individuals : analysis and distribution

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  • Resource distribution and adequacy, of elderly individuals and families, was measured by determining an annual dollar value of money and nonmoney economic resources. The nonmoney economic resources were identified as fringe benfits, household production, durable assets, interfamily grants, and community provided goods and services. The data were collected by interviewing 75 residents, 70 years or older, in Bernalillo County (Albuquerque) ,New Mexico, during 1980. The Gini Coefficient changed from .344 (money income) to .186 with all incomes. When household production and community provided goods and services were omitted, due to the method of valuation (based on prior research), the Gini Coefficient was .616, indicating greater inequality. An analysis of variance was computed to determine if differences (p<.05) existed between dollar amounts of the nonmoney resources available to families categorized into four different levels of living. There was no difference in the dollar amount of fringe benefits or interfamily grants. The dollar amount of durable assets among elderly families was significant (p<.05). The Cochran Q test was used to determine whether changes took place in the number of families below poverty as nonmoney resources were included. The poverty line was adjusted with the inclusion of each resource. Based on money income, 15 families were defined as in poverty. With all nonmoney resources in the measure, no family was defined as in poverty; the change was significant (p.05). When household production and community provided goods and services were omitted, nine families remained in poverty. Six families were no longer defined as in poverty after interfamily grants were included. The change was significant (p<.05). Multiple regression models were developed. The predictor variables in the money income model were: number of sources of money income and whether the participant's primary occupation had been management/professional (explaining 24 percent of the variation). No selected predictor variables met the criterion for explaining fringe benefits. Homeownership and number of cars were included in the model explaining durable assets (explaining 54 percent of the variation). Number of events and whether there were children, were included in the model for interfamily grants (explaining 25 percent of the variation).
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