The Growing Allocative Inefficiency of the U.S. Higher Education Sector

This paper presents new evidence on research and teaching productivity in universities using a panel of 102 top U.S. schools during 1981-1999. Faculty employment grows at 0.6 percent per year, compared with growth of 4.9 percent in industrial researchers. Productivity growth per researcher is 1.4-6.7 percent and is higher in private universities. Productivity growth per teacher is 0.8-1.1 percent and is higher in public universities. Growth in research productivity within universities exceeds overall growth, because the research share grows in universities where productivity growth is less. This finding suggests that allocative efficiency of U.S. higher education declined during the late 20th century. R&D stock, endowment, and post-docs increase research productivity in universities, the effect of nonfederal R&D is less, and the returns to research are diminishing. Since the nonfederal R&D share grows and is higher in public schools, this may explain the rising inefficiency. Decreasing returns in research but not teaching suggest that most differences in university size are due to teaching.

The Growing Allocative Inefficiency of the U.S. Higher Education Sector

This paper presents new evidence on research and teaching productivity in universities. The findings are based on a panel that covers 1981-1999 and includes 102 top U.S. universities. Faculty size grows at 0.6 percent per year, compared with growth of 4.9 percent in the industrial science and engineering workforce. Measured by papers and citations per researcher, productivity grows at 1.4-6.7 percent per year and productivity and its rate of growth are higher in private than public universities. Measured by baccalaureate and graduate degrees per teacher, teaching productivity grows at 0.8-1.1 percent per year and growth is faster in public than private universities. A decomposition analysis shows that growth in research productivity within universities exceeds overall growth. This is because research shares grow more rapidly in universities whose productivity grows less rapidly. Likewise the research share of public universities increases even though productivity grows less rapidly in public universities. Together these findings suggest that allocative efficiency of U.S. higher education declined during the late 20th century. Regression analysis of individual universities finds that R&D stock, endowment, and postdoctoral students increase research productivity, that the effect of nonfederal R&D stock is less, and that research is subject to decreasing returns. Since the nonfederal R&D share grows and is much higher in public universities, this could account for some of the rising allocative inefficiency. The evidence for decreasing returns in research, which are greater than in teaching, suggests limits on the ability of more efficient institutions to expand and implies that differences in the scale of the teaching function are the primary reason for differences in university size. Besides all this the data strongly hint at growing financial pressures on U.S. public universities.

Science and Industry: Tracing the Flow of Basic Research through Manufacturing and Trade

This paper describes flows of basic research through the U.S. economy and explores their implications for scientific output at the industry and field level. The time period is the late 20th century. This paper differs from others in its use of measures of science rather than technology. Together its results provide a more complete picture of the structure of basic research flows than was previously available. Basic research flows are high within petrochemicals and drugs and within a second cluster composed of software and communications. Flows of chemistry, physics, and engineering are common throughout industry; biology and medicine are almost confined to petrochemicals and drugs, and computer science is nearly as limited to software and communications. In general, basic research flows are more concentrated within scientific fields than within industries. The paper also compares effects of different types of basic research on scientific output. The main finding is that the academic spillover effect significantly exceeds that of industrial spillovers or industry basic research. Finally, within field effects exceed between field effects, while the within- and between industry effects are equal. Therefore, scientific fields limit basic research flows more than industries.

Standing on Academic Shoulders: Measuring Scientific Influence in Universities

This article measures scientific influence by means of citations to academic papers. The data source is the Institute for Scientific Information (ISI); the scientific institutions included are the top 110 U.S. research universities; the 12 main fields that classify the data cover nearly all of science; and the time period is 1981-1999. Altogether the database includes 2.4 million papers and 18.8 million citations. Thus the evidence underlying our findings accounts for much of the basic research conducted in the United States during the last quarter of the 20th century. This research in turn contributes a significant part of knowledge production in the U.S. during the same period. The citation measure used is the citation probability, which equals actual citations divided by potential citations, and captures average utilization of cited literature by individual citing articles. The mean citation probability within fields is on the order of 10-5. Cross-field citation probabilities are one-tenth to one-hundredth as large, or 10-6 to 10-7. Citations between pairs of citing and cited fields are significant in less than one-fourth of the possible cases. It follows that citations are largely bounded by field, with corresponding implications for the limits of scientific influence. Cross-field citation probabilities appear to be symmetric for mutually citing fields. Scientific influence is asymmetric within fields, and occurs primarily from top institutions to those less highly ranked. Still, there is significant reverse influence on higher-ranked schools. We also find that top institutions are more often cited by peer institutions than lower-ranked institutions are cited by their peers. Overall the results suggest that knowledge spillovers in basic science research are important, but are circumscribed by field and by intrinsic relevance. Perhaps the most important implication of the results are the limits that they seem to impose on the returns to scale in the knowledge production function for basic research, namely the proportion of available knowledge that spills over from one scientist to another.

The Role of Search in University Productivity: Inside, Outside, and Interdisciplinary Dimensions

Due to improving information technology, the growing complexity of research problems, and policies designed to foster interdisciplinary research, the practice of science in the United States has undergone significant structural change. Using a sample of 110 top U.S. universities observed during the late 20th century we find that knowledge flows, both in total and in their major components, are a significant and positive determinant of research output. Outside knowledge-flows from other universities have increased at a faster rate than inside flows from the same university. Over time, the importance of outside flows for research output has risen, and it has done so at a faster rate than the importance of inside flows has decreased. Thus the overall contribution of knowledge-flows has increased and has shifted towards outside flows. Turning to knowledge-flows by field, we find that interdisciplinary knowledge-flows have increased only slightly relative to same field flows, despite policy initiatives that favor interdisciplinary research. Moreover, the importance of interdisciplinary flows for research output, while positive and statistically highly significant, has stayed about the same, even as same field flows have become more important, probably because of growth in cyber infrastructure. Although a final verdict is yet to be reached, one interpretation is that interdisciplinary research is still in its early stages. While interdisciplinary flows have begun to increase, the resulting discoveries, and their influence on subsequent research, may still lie in the future.

The NBER-Rensselaer Scientific Papers Database: Form, Nature, and Function

This article is a guide to the NBER-Rensselaer Scientific Papers Database, which includes more than 2.5 million scientific publications and over 21 million citations to those papers. The data cover an important sample of 110 top U.S. universities and 200 top U.S.-based R&D-performing firms during the period 1981-1999. This article describes the file system which comprises the database, explains the variables included in the files, and discusses the functions of the various files. It includes numerous descriptive tables, as well as graphs of the data in the time series dimension. In addition, it discusses limitations and strengths of the data as well as some questions that the data might be used to address.

The Origins of Industrial Scientific Discoveries

This paper estimates science production functions for R&D-performing firms in the United States using scientific papers as the measure of output, by analogy with patents. The underlying evidence covers 200 top U.S. R&D firms during 1981-1999 as well as 110 top U.S. universities. We find that industrial science builds on past scientific research inside and outside the firm, with most of the returns to scale in production deriving from outside knowledge. In turn, the largest outside contribution derives from universities rather than firms; this is especially true when papers are weighted by citations received, a measure of their importance. Consistent with the role assigned to knowledge spillovers in growth theory, the importance of outside knowledge, especially that of universities, increases from the firm to the industry level. The findings survive the inclusion of fixed effects, interactions among the effects, variations in sample and specification, and efforts to control for endogeneity.

Scientific Teams and Institutional Collaborations: Evidence from U.S. Universities, 1981-1999

This paper explores recent trends in the size of scientific teams and in institutional collaborations. The data derive from 2.4 million scientific papers written in 110 top U.S. research universities over the period 1981–1999. The top 110 account for a large share of published basic research conducted in the U.S. during this time. We measure team size by the number of authors on a scientific paper. Using this measure we find that team size increases by 50% over the 19-year period. We supplement team size with measures of domestic and foreign institutional collaborations, which capture the geographic dispersion of team workers. The time series evidence suggests that the trend towards more geographically dispersed scientific teams accelerates beginning with papers published at the start of the 1990s. This acceleration suggests a sharp decline in the cost of collaboration. Our hypothesis is that the decline is due to the deployment of the National Science Foundation’s NSFNET and its connection to networks in Europe and Japan after 1987. Using a panel of top university departments we also find that private universities and departments whose scientists have earned prestigious awards participate in larger teams, as do departments that have larger amounts of federal funding. Placement of former graduate students is a key determinant of institutional collaborations, especially collaborations with firms and with foreign scientific institutions. Finally, the evidence suggests that scientific output and influence increase with team size and that influence rises along with institutional collaborations. Since increasing team size implies an increase in the division of labor, these results suggest that scientific productivity increases with the scientific division of labor. Keywords: Science; Research and development; Collaboration; Team