An economic analysis of unilateral refusals to license intellectual property

The intellectual property laws in the United States provide the owners of intellectual property with discretion to license the right to use that property or to make or sell products that embody the intellectual property. However, the antitrust laws constrain the use of property, including intellectual property, by a firm with market power and may place limitations on the licensing of intellectual property. This paper focuses on one aspect of antitrust law, the so-called “essential facilities doctrine,” which may impose a duty upon firms controlling an “essential facility” to make that facility available to their rivals. In the intellectual property context, an obligation to make property available is equivalent to a requirement for compulsory licensing. Compulsory licensing may embrace the requirement that the owner of software permit access to the underlying code so that others can develop compatible application programs. Compulsory licensing may undermine incentives for research and development by reducing the value of an innovation to the inventor. This paper shows that compulsory licensing also may reduce economic efficiency in the short run by facilitating the entry of inefficient producers and by promoting licensing arrangements that result in higher prices.

Measuring science: An exploration

This paper examines the available United States data on academic research and development (R&D) expenditures and the number of papers published and the number of citations to these papers as possible measures of “output” of this enterprise. We look at these numbers for science and engineering as a whole, for five selected major fields, and at the individual university field level. The published data in Science and Engineering Indicators imply sharply diminishing returns to academic R&D using published papers as an “output” measure. These data are quite problematic. Using a newer set of data on papers and citations, based on an “expanding” set of journals and the newly released Bureau of Economic Analysis R&D deflators, changes the picture drastically, eliminating the appearance of diminishing returns but raising the question of why the input prices of academic R&D are rising so much faster than either the gross domestic product deflator or the implicit R&D deflator in industry. A production function analysis of such data at the individual field level follows. It indicates significant diminishing returns to “own” R&D, with the R&D coefficients hovering around 0.5 for estimates with paper numbers as the dependent variable and around 0.6 if total citations are used as the dependent variable. When we substitute scientists and engineers in place of R&D as the right-hand side variables, the coefficient on papers rises from 0.5 to 0.8, and the coefficient on citations rises from 0.6 to 0.9, indicating systematic measurement problems with R&D as the sole input into the production of scientific output. But allowing for individual university field effects drives these numbers down significantly below unity. Because in the aggregate both paper numbers and citations are growing as fast or faster than R&D, this finding can be interpreted as leaving a major, yet unmeasured, role for the contribution of spillovers from other fields, other universities, and other countries.