Improving Measurement of Productivity in Higher Education (2012) / Chapter Skim
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2 Defining Productivity for Higher Education
2 Defining Productivity for Higher Education
Pages 19-36
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From page 19... ...
The discussion should begin with a clear understanding of productivity measures and their appropriate application, while recognizing that other related concepts (such as unit cost, efficiency measures, and the like) are also important and inform key policy questions.
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Cost savings can occur as a result of reduction in input prices, so that the same physical quantity of inputs can be purchased at a lower total cost; they are also attainable by reducing the quantity or quality of output produced. But, by focusing on output and input volumes alone, it becomes difficult to distinguish efficiency gains from quality changes.
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From page 21... ...
The construction of productivity measures requires quantitative estimates of the volume of outputs and inputs, excluding the effects of pure price changes while capturing improvements in quality. As a simple illustration, total revenues provide a measure of the value to consumers of an industry's production, and the revenues of the individual types of good or services produced by the industry are deflated by price indexes and weighted together by their shares in total revenues to construct an index of output volume.
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From page 22... ...
are not indicative of the value of the industry's output to society.3 The inputs to education are substantially similar to those of other productive sectors: labor, capital, and purchased inputs. Higher education is distinct, however, in the nature of its outputs and their prices.
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From page 23... ...
As noted above, if the products are sold in open competitive markets, producers will expand output to the point where the marginal revenues of individual products are roughly equal to their marginal costs. Thus, their revenue shares can be used as measures of relative consumer value or weights to combine the various product categories to yield an index of overall output.
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The NCES National Education Longitudinal Study (NELS) repeated the error by not asking about final degree attainment; the Education Longitudinal Study (ELS)
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2.1.2. Inputs Having established that productivity relates the quantity of output to the inputs required to produce it, it is evident that correct measurement requires identifying all inputs and outputs in the production process.
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The price of labor is measured by compensation per hour; hence, labor inputs of different quality are aggregated using as weights their relative wage rates or, alternatively, using the share of each type of labor in total labor compensation. In this respect, the aggregation of the labor input is comparable to the aggregation of individual product lines to arrive at an estimate of total output.
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. Nonetheless, little would be gained for policy purposes by in cluding it in productivity measures.
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From page 28... ...
However, the Internal Revenue Service Form 990 returns filed by nonprofit organizations do contain substantial financial information for these organizations, including data on capital expenditures and depreciation. Energy, Materials, and Other Purchased Inputs Productivity measures require information on intermediate inputs either as one of the inputs to the calculation of multi-factor productivity or as a building block in the measurement of value added.
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On the student side, per-unit instructional costs vary by student level -- undergraduate, taught postgraduate, and research students; mode of attendance -- full- versus part-time students (the cost of student services varies by 13See Webber and Ehrenberg (2010)
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For administrative and other purposes, universities typically track inputs along other dimensions, such as by revenue source. For our purposes, the only reason for classifying inputs according to revenue source is to separate the inputs associated with organized research and public service as described in Chapter 4.
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2.2. PRODUCTIVITY CONTRASTED WITH OTHER MEASUREMENT OBJECTIVES Dozens of metrics have been created to serve as proxies for productivity or as indicators to inform accountability programs and to track costs and outcomes.
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The problem is that simple ratios like cost per student or degree does not take into consideration quality and the multiple outputs produced by higher education institutions. Hence, this approach conveys too little information to be able to attribute productivity differences to differences (over time or between institutions)
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From page 33... ...
data to calculate unit costs, but it is impossible to unpack the unit cost data to obtain productivity measures. The fact that most measurement effort in higher education is aimed at the generation of unit cost data has inhibited the sector's ability to assess and improve its productivity.
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Similarly, studies have usefully shown how tuition and aid policies affect student performance as measured partially by these statistics. The range of performance metrics, including a discussion of the meaning of graduation rates as calculated by the Integrated Postsecondary Education Data System (IPEDS)
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Schools may attempt to artificially boost standardized test scores (Figlio and Winicki, 2005) or even manipulate test scores through outright cheating (Jacob 19See http://www.collegeresults.org/ [June 2012]
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From page 36... ...
in order to look better according to the accountability system; and while value added measures might allow for more apples-to-apples comparisons among institutions, they will not reduce the strategic behavior problem by as much as they might in K-12 education. One example of how higher education institutions respond strategically to the incentives embedded within an evaluation system is observable in relation to the U.S.
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