Health care costs represent a nearly 18% of U.S. gross domestic product and 20% of government spending. While there is detailed information on where these health care dollars are spent, there is much less evidence on how this spending affects health. The research in Measuring and Modeling Health Care Costs seeks to connect our knowledge of expenditures with what we are able to measure of results, probing questions of methodology, changes in the pharmaceutical industry, and the shifting landscape of physician practice. The research in this volume investigates, for example, obesity's effect on health care spending, the effect of generic pharmaceutical releases on the market, and the disparity between disease-based and population-based spending measures. This vast and varied volume applies a range of economic tools to the analysis of health care and health outcomes. Practical and descriptive, this new volume in the Studies in Income and Wealth series is full of insights relevant to health policy students and specialists alike.

Price indexes provide a way to summarize changes in prices of individual goods and services using an aggregate statistic. An important use of these indexes is to decompose changes in spending into price and quantity components. This is the role that price indexes play in the National Income and Product Accounts to obtain measures of real output and productivity. Price indexes are also used in the National Health Expenditure Accounts to provide information on the drivers of spending growth in the nation's health care sector. More broadly, health economists have used similar decompositions to inform policy debates about which levers may be used to contain cost growth (Merlis 2000).

Dale Jorgenson's Presidential address to the American Economic Association (2001) makes a convincing case that accelerated technological change in the production of semiconductors, microprocessors in particular, has driven the recent increased productivity growth in the U.S. economy. But, while semiconductors now gure prominently in accounts of economic growth, Jorgenson points out that there is not a fully satisfactory economic model of the industry that produces them. This paper is our attempt to rise to Jorgenson's challenge.

This note uses scanner data for over 60 segments of consumer information technology (IT) and electronic goods to construct matched-model indexes. Virtually all of the segment-level indexes constructed with these data show price declines that reflect quality increases-a typical exception is floppy disks, a category that shows price declines that reflect falling average prices. Our first pass at these data show that in all but nine of the categories, unweighted geometric mean price indexes falls faster than weighted superlative indexes (Fisher and Tornquist). Part of the reason for this appears to be that, within each segment, goods with relatively low market shares tend to show faster price declines than those with high market shares. Although it would be interesting to explore whether life-cycle effects over the life of each good also contribute to this result, the time-series dimension of our data is short and precludes an analysis of pricing over the product cycle.

In this paper, we explore the importance of shifts in treatments for explaining increases in the cost of health care services. Using a large database of health insurance claims for sample patients, we find that there have been shifts in treatment intensity that have an important effect on costs and that, on average, those treatment shifts served to lower the cost of treating disease. These costs savings appear to be numerically important and pervasive. Our results lend support to earlier work that found these effects for a set of important conditions: heart attacks, cataract, and depression.