This article provides a broad overview of the measurement techniques used in estimating GDP and the national accounts in the United States. In the United States, the GDP and the national accounts estimates are fundamentally based on detailed economic census data and other information that is available only once every five years. The challenge lies in developing a framework and methods that take these economic census data and combine them using a mosaic of monthly, quarterly, and annual economic indicators to produce quarterly and annual GDP estimates. One problem is that the other economic indicators that are used to extrapolate GDP in between the five-year economic census data -- such as retail sales, housing starts, and manufacturers shipments of capital goods -- are often collected for purposes other than estimating GDP and may embody definitions that differ from those used in the national accounts. Another problem is some data are simply not available for the earlier estimates in the reporting process. For the initial monthly estimates of GDP, data on about 25 percent of GDP -- especially in the service sector -- are not available, and so these sectors of the economy are estimated based on past trends and whatever related data are available. The initial monthly GDP estimates based on these extrapolations are revised as more complete data become available In producing the national accounts estimates, the Bureau of Economic Analysis attempts to strike a balance between accuracy and timeliness so that the estimates can be used to monitor real overall economic growth and inflation, as well as major sectors of interest.

Human capital estimates of the economic value of life have been routinely used in the past to perform cost-benefit analyses of health programs. Recently, however, serious questions have been raised concerning the conceptual basis for valuing human life by applying these estimates. Most economists writing on these issues tend to agree that a more conceptually correct method to value risks to human life in costbenefit analyses would be based on individuals' "willingness to pay" for small changes in their probability of survival. Attempts to implement the willingness-topay approach using survey responses or revealedpreference estimates have produced a confusing array of values fraught with statistical problems and measurement difficulties. As a result, economists have searched for a link between willingness to pay and standard human capital estimates and have found that for most individuals a lower bound for valuing risks to life can be based on their willingness to pay to avoid the expected economic losses associated with death. However, while these studies provide support for using individual's private valuation of forgone income in valuing risks to life, it is also clear that standard human capital estimates cannot be used for this purpose without reformulation. After reviewing the major approaches to valuing risks to life, this paper concludes that estimates based on the human capital approach-reformulated using a willingness-to-pay criterion-produce the only clear, consistent, and objective values for use in cost-benefit analyses of policies affecting risks to life. The paper presents the first empirical estimates of such adjusted willingness-topay/human capital values.

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U.S. mortality rates (total, infant and disease-specific) across 117 standard metropolitan statisical areas in 1960 and 1961are investigated in an attempt to estimate their association with measures of air poll ution. Multivariate regression analysis is utilized to control for some of the important factors affecting mortality with the underlying hypothesis that air pollution will exhibit a significant association with mortality in the presence of other relevant factors. Taken as a whole, the analysis demonstrates a close association between air pollution and mortality and the estimated magnitude of the relationship is. substantial.