Improving Measurement of Productivity in Higher Education (2012) / Chapter Skim
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4 Advancing the Conceptual Framework
4 Advancing the Conceptual Framework
Pages 61-86
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From page 61... ...
Chief among these is the lack of an agreed-upon measure of educational quality. Productivity should be defined as the ratio of quality-adjusted outputs to quality-adjusted inputs, but the needed quality adjustments are not currently possible in higher education and are not likely to become possible any time soon.
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From page 62... ...
· Outputs include credit hour production and degree attainment, both of which have been shown to be important in labor market studies. Most if not all the measures currently in use (e.g., credit hour production alone or graduation rates)
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From page 63... ...
The section also discusses how the model can be computed at the state and single-institution level but, again, we stress that this will be dangerous without a robust quality assurance system. Section 4.4 enhances the base model by differentiating among labor categories.
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From page 64... ...
Our proposed productivity model is based on the methodology for multifactor productivity indices used by BLS, the OECD, and other U.S. and foreign agencies that produce sectoral productivity statistics (Bureau of Labor Statistics, 2007; Schreyer, 2001)
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From page 65... ...
However, because of its widespread use in other applications -- a Törnqvist index is used here for expository purposes. The denominator of our baseline higher education productivity index uses a Törnqvist structure to represent the composite growth rates of labor and capital inputs.
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From page 66... ...
The "sheepskin effect" represents the additional value that credit hours have when they are accumulated and organized into a completed degree. The panel believes that a value equal to a year's worth of credits is a reasonable figure to use as a placeholder for undergraduate degrees.3 Additional research will be needed to determine the sheepskin effect for graduate and first professional programs.
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From page 67... ...
: opportunity cost for the use of physical capital; also called rental value of capital. Expenditures equal the IPEDS book value of capital stock times an estimated national rate of return on assets, where book value of capital stock equals the sum of land, buildings, and equipment.4 Overall, the book value reported in IPEDS is likely too low; however, it does include buildings that may not be specifically allocated to teaching, which offsets the total to an unknown degree.5 These nominal capital values are used in calculating the capital weights.
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From page 68... ...
: For the quantity of capital input, the book value is deflated by the Bureau of Economic Analysis's investment deflator for gross private domestic investment. The deflators for intermediate expenditures and capital are, respectively, the Producer Price Index (PPI)
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From page 69... ...
· IE is expenditures on intermediate inputs; DIE is direct nonlabor ex penditures on instruction; DIS is direct nonlabor expenditures on stu dent services; DIA is direct nonlabor expenditures on administration; EdShDirIE is education share of direct nonlabor expenditures. · Stock is capital stock as shown on institutional balance sheets, ROR is the national rate of return on capital, PPI is the producer price index, and CPDICIPI is the price index for gross private domestic investment (both price indices are suitably normalized)
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From page 70... ...
$261,834 $301,954 $400,791 Total Cost $1,342,913 $1,720,186 $2,214,578 Step 2: Quantity Changes Period 1 Period 1 2 Period 2 3 Output Change Adjusted credit hours 1.000 1.008 1.052 Input Change Labor FTEs 1.000 1.094 1.095 Real intermediate expenditures 1.000 1.497 1.324 Real capital stock 1.000 1.022 1.301 Step 3: Input Index Weights (average) Wages and fringe benefits 53.4% 48.6% Normal intermediate expenditures 28.1% 33.6% Real capital stock 18.5% 17.8% Weighted geometric average 1.180 1.204 Step 4: Multi-Factor Productivity Productivity index 0.854 0.874 Productivity change 2.3% NOTE: FTE = full-time equivalent.
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From page 71... ...
Dividing the output growth by the input growth yields 1.044/1.020 = 1.023, or 2.3 percent, the same as in the table. Put another way, the output index grew 2.3 percent faster than the input index -- which represents productivity improvement (see Box 4.1)
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From page 72... ...
A natural starting point to defining institutional groups is to follow the approach established for the Delta Cost Project, if for no other reason than a considerable amount of experience in working with them has been accumulated. The Delta Cost Project employs six institutional groups: public research, public master's, public community colleges, private nonprofit research, private nonprofit master's, and private nonprofit bachelor's.
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From page 73... ...
Such aggregation is standard practice in sectoral productivity analysis and we see no reason not to use it in higher education. Given that IPEDS reports data for individual institutions, it is almost as easy to do the calculations separately by segment as it is to do them on national aggregates.
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From page 74... ...
More importantly, as we have already emphasized, is the need to deploy robust quality assurance procedures in any situation where high-stakes quantitative productivity measures are used. In the slightly longer term, these quality assurance procedures should be supplemented by improvement-oriented structural models of the kind discussed in Chapter 2.
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From page 75... ...
These considerations suggest the following three-way labor classification scheme based on IPEDS data. · Regular faculty FTEs: approximated from IPEDS data for "Number of full-time Instruction/Research/Public Service staff with faculty status." · Part-time teaching FTEs who are hired on a course-by-course basis: approximated by one-third of the "Number of staff by primary func tion/occupational activity" listed as "Part-time" and "Primarily instruc tion" ("PT/PI")
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From page 76... ...
Only one required data element is unavailable in IPEDS: the ratio of PT/PI salaries per FTE to those of regular faculty. It is possible (though perhaps not cost-effective)
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From page 77... ...
The expenditure figures can be computed as follows: Expenditures for regular faculty = (1+ Fringe benefits rate) × Average salary for FTE instructional staff × Regular faculty FTEs; Expenditures for PT/PI staff = (1+ Fringe benefits rate/2)
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From page 78... ...
As shown in Table 4.4, resulting geometric averages show more variation than did the labor indices in Table 4.2. This produces larger multifactor productivity indices, and also a larger change in the index, as shown at the bottom of the table.
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From page 79... ...
While ignoring differences in the coursetaking profiles, the procedure does allow at least some differentiation among output categories. Aggregation to a single output index is best accomplished by taking a geometric average of the output category indices using their net student revenue shares as weights.
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From page 80... ...
Significant progress on quality assessment has been made, but there is a long way to go before a generally accepted cardinal measure -- one that can be used reliably to adjust weighted credit hours -- can be agreed upon. It is possible, and perhaps even likely, that critics will call for a moratorium on all efforts to measure instructional productivity until a valid and reliable output quality index can be developed.
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From page 81... ...
Progress on the development of quantitative productivity measures may boost the priority for developing a serviceable quality adjustment index.
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From page 82... ...
. As noted in the text, the Törnqvist index is used by the Bureau of Labor Statistics in calculating multi-factor productivity change (cf.
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From page 83... ...
The resulting theorem, Caves Equation (15) reproduced below, shows how one can compute the geometric average of the two input indices using only observable data.
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From page 84... ...
. Furthermore, the two approaches "differ from each other by a factor that reflects the returns to scale of the production structure." Without going into the details, it is intuitively reasonable that a geometric average of the output-based and input-based indices represents a good overall measure of productivity.13 Therefore, the desired productivity index is the ratio of the output-based and input-based Törnqvist indices.
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From page 85... ...
ADVANCING THE CONCEPTUAL FRAMEWORK 85 and elsewhere, whose optimality cannot be proved or that have even been shown to be suboptimal. The question is an open one which calls for additional research.
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