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Review of the Last Lecture began our discussion of the production of health (section III of the course outline). discussed the production function, HS=HS(HC), the APP & MPP, shift variables, and the intensive and extensive margins

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Review of the Last Lecture

  • began our discussion of the production of health (section III of the course outline).

  • discussed the production function, HS=HS(HC), the APP & MPP, shift variables, and the intensive and extensive margins

  • gave examples of the intensive and extensive margins in HC from Phelps (2003).

  • Today continue our discussion of the production of health


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Can the MPP of HC Be Negative at the Intensive Margin?

YES! Healthcare exerts both positive and negative effects (recall the concept of iatrogenic disease)

For initial quantities of HC applied to an ill segment of the population the positive benefits will outweigh the negative side effects, thus the positive benefits of additional care for this group (intensive margin) will outweigh any negative side effects.

The MPP of HC at the intensive margin will be negative if additional HC yields very little positive benefit for the group and continues to yield the same negative side effects. ///


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Can the MPP of HC at the Extensive Margin be Negative? Yes

The MPP of HC can also be negative at the extensive margin

This may occur if the population, to which a HC procedure is applied, is expanded to include an ever healthier group of people

At the margin, the positive benefits from applying the HC to an ever larger proportion of the population will become less and less until finally the negative side effects of additional HC outweigh the positive health effects and the MPP of HC at the extensive margin becomes negative. ///


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Uncertainty About the MPP of HC At the Two Margins

  • Extensive debate in the literature on the value of HC at the two margins e.g.,

    • correct frequency of preventive care visits to the dentist/optometrist?

    • correct cut-off age for prostate/breast cancer screening?

    • how reliable are diagnostic tests: e.g., PSA test for prostate cancer?

  • This uncertainty has led to variations in medical practice.

  • There are substantial unexplained differences in the frequency with which many medical procedures are performed across geographic areas and across practitioners.

  • Overhead transparency of high to low ratios for various HC procedures performed in 16 large community hospital markets (Phelps, 2003, p. 84).


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Variability in HC Practice and Welfare Loss

  • Variability in HC practice results in a welfare loss, i.e.,

  • Where there is too much HC, cost of the marginal resources used exceeds the value of the marginal benefit generated => MB<MC => suboptimal use of resources.

  • Where there is insufficient HC, there is a chance to generate additional consumer surplus (cost of the additional resources is less than the value of the additional benefit generated, i.e. MB > MC.

  • Illustrate with a diagram. ///


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Output Elasticities

  • Output elasticity:

  • (percentage change in HS)/(percentage change in HC)

  • Show on a production function diagram

  • How is HS measured? Often crudely, e.g.: life expectancy (LE)

  • Can then compute an output elasticity as follows:

  • The percentage change in life expectancy divided by the percentage change in real healthcare expenditures.

  • real healthcare expenditures are expenditures measured at base year prices, eg. 1998 prices. Real HC expenditures can thus only change if the quantity of inputs changes.


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Relevance of an Output Elasticity

  • an output elasticity is a measure of the responsiveness of health status to healthcare inputs

  • the higher the output elasticity the more responsive HS is to changes in healthcare spending

  • the magnitude of the output elasticity gives us some idea where we are on the production function (diagram)


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Estimating Healthcare Output Elasticities

  • although the formula for the output elasticity is:

  • can’t just use raw data to compute its magnitude

  • computing such an elasticity using two raw data points e.g. Canadian data for LE and real HC expenditure for 1970 and 2002 will yield biased results. REASON: other variables that affect LE also change over this time period.

  • must first remove the effects of all other variables on life expectancy over the sample period, HOW? Multiple Regression Analysis! (this technique is discussed in Econ 345, 365)


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Empirical Estimates of Output Elasticities

  • Output elasticity estimates based on different proxies for HS (Text 3rd ed. , p. 108. See overhead transparency, Table 5.2):

  • Proxy for HS: mortality rates (inverse measure of HS):

  • Auster et. al (1969) U.S. statewide data

  • Hadley (1982 and 1988) U.S. county data

  • Proxy for HS: activity/mobility index

  • Sickles and Yazbeck (1998) US data for individuals followed over time

  • Note:

  • HC matters but we are nearly on the “flat of the curve”.

  • The production function shift variables are also important and their effect depends on gender and race (overhead transparency of Table 5.3, Text, 3rd ed., p. 109 from Hadley (1982). ///