Wednesday, October 16, 2013
Productivity is the ratio of output produced per unit of input. In the classic economics hypothetical of labor used to produce widgets, productivity can be stated as the number of widgets produced per work hour. For example, in time period one, a firm might produce 5 widgets per hour of labor. Then, in time period two, with use of improved technology, the firm might produce 8 widgets per hour of labor. The firm's productivity has increased from period one to period two.
The widget example shows how productivity is important to an economy. Technology allowed the same worker to produce more widgets per hour. This increased production generates additional sales and revenue, which allows the employer to pay higher wages. Increased productivity, then, can result in increased income and standard of living.
To compute productivity in higher education, we must identify the applicable units of output and input. That is, we must answer the questions, What outputs are produced by a college or university?, and What inputs are used to produce those outputs? Further, to measure productivity, we must be able to quantify these variables. The difficulty in this analysis is summarized quite well in the following passage from a panel report of the National Research Council entitled Improving Measurement of Productivity in Higher Education:
A number of complexities characterize higher education production processes. These reflect the presence of (1) joint production—colleges and universities generate a number of outputs (such as educated and credentialed citizens, research findings, athletic events, hospital services), and the labor and other inputs involved cannot always be neatly allocated to them; (2) high variability in the quality and characteristics of inputs, such as teachers and students, and outputs, such as degrees; and (3) outputs (and inputs) of the production process that are nonmarket in nature. As is the case with other sectors of the economy, particularly services, productivity measurement for higher education is very much a work in progress in terms of its capacity to handle these complexities. Because no single metric can incorporate everything that is important, decision makers must appeal to a range of statistics or indicators when assessing policy options—but surely a well-conceived productivity measure is one of these.
In the next post on this topic, I will discuss the outputs and inputs to higher education.