The objectives of this paper are 1) to assess the impact of medical and nursing home expenses on life-cycle savings and wealth inequality in the U.S., and 2) to quantitatively evaluate the effects of alternative old-age social insurance policies in a general equilibrium framework. We consider a life-cycle model where individuals face uninsurable labor earnings risk, out-of-pocket medical and nursing home expense risk and survival risk. Partial insurance is available through three social insurance programs: welfare, Medicaid and a pay-as-you-go social security system. We find that out-of-pocket health expenses amplify precautionary savings against survival risk and that nursing home expenses drive the savings behavior of wealthier individuals. The dominant role played by nursing home expenses is primarily due to differences in the degree of social insurance available for medical versus nursing home expense risk. We find that elimination of private medical and nursing home expenses through public health care would reduce the capital stock by 20 percent. We also find that while the welfare program for workers has little effect on savings behavior in the presence of large out-of-pocket expenses, Medicaid and old-age welfare programs crowd out over 60 percent of life-cycle savings and dramatically increase wealth inequality. Furthermore, we find that social security amplifies the effect of OOP health expenses on wealth accumulation. Overall, we conclude that out-of-pocket health expenses play an important role in wealth accumulation on aggregate and across the permanent income distribution.
The welfare gain to consumers from the introduction of personal computers is estimated here. A simple model of consumer demand is formulated that uses a slightly modified version of standard preferences. The modification permits marginal utility, and hence total utility, to be finite when the consumption of computers is zero. This implies that the good won't be consumed at a high enough price. It also bounds the consumer surplus derived from the product. The model is calibrated/estimated using standard national income and product account data. The welfare gain from the introduction of personal computers is about 4 percent of consumption expenditure.
Macro models are developed to explore the impact of technological progress on the household. Chapter 1 focuses on the impact of technological progress in transportation on suburbanization. In Chapter 2, a model with leisure production and endogenous retirement is used to explain the declining labor-force participation rates of elderly males. Finally, in Chapter 3, the welfare gain from technological progress in personal computer production is measured by constructing a simple model of computer demand.
A
model with leisure production and endogenous retirement
is used to explain the declining labor-force participation
rates of elderly males. Using the Health and Retirement
Study, the model is calibrated to cross-sectional
data on the labor-force participation rates of
elderly US males by age and their average drop
in market consumption in the year 2000. Running
the calibrated model for the period 1850 to 2000,
a prediction of the evolution of the cross-section
is obtained and compared with data. The model
is able to predict both the increase in retirement
since 1850 and the observed drop in market consumption
at the moment of retirement. The increase in retirement
is driven by rising real wages and a falling price
of leisure goods over time.
Suburbanization in the U.S. between 1910 and 1970 was concurrent with the rapid diffusion of the automobile. A circular city model is developed in order to access quantitatively the contribution of automobiles and rising incomes to suburbanization. The model incorporates a number of driving forces of suburbanization and car adoption, including falling automobile prices, rising real incomes, changing costs of traveling by car and with public transportation, and urban population growth. According to the model, 60 percent of postwar (1940-1970) suburbanization can be explained by these factors. Rising real incomes and falling automobile prices are shown to be the key drivers of suburbanization.
