This paper re-examines the Rouwenhorst method of approximating first-order autoregressive processes. This method is appealing because it can match the conditional and unconditional mean, the conditional and unconditional variance and the first-order autocorrelation of any AR(1) process. This paper provides the first formal proof of this and other results. When comparing to five other methods, the Rouwenhorst method has the best performance in approximating the business cycle moments generated by the stochastic growth model. It is shown that, equipped with the Rouwenhorst method, an alternative approach to generating these moments has a higher degree of accuracy than the simulation method.
We consider a life-cycle model with idiosyncratic risk in labor earnings, out-of-pocket medical and nursing home expenses, and survival. Partial insurance is available through welfare, Medicaid, and social security. Calibrating the model to the U.S., we find that nursing home expenses play an important role in the savings of the wealthy. In our policy analysis, we find that elimination of out-of-pocket expenses through public health care would reduce the capital stock by 12 percent, Medicaid and old-age welfare programs crowd out 44 percent of savings and greatly increase wealth inequality, and social security effects are influenced by out-of-pocket health expenses.
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 2 to 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.
