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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.
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.
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