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衡量科学:一次探索。

Measuring science: an exploration.

作者信息

Adams J, Griliches Z

机构信息

Department of Economics, University of Florida, Gainesville 32611-7140, USA.

出版信息

Proc Natl Acad Sci U S A. 1996 Nov 12;93(23):12664-70. doi: 10.1073/pnas.93.23.12664.

Abstract

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.

摘要

本文考察了美国有关学术研究与开发(R&D)支出、发表论文数量以及这些论文被引用次数的现有数据,将其作为该领域“产出”的可能衡量指标。我们审视了科学与工程领域整体、五个选定主要领域以及各大学学科领域层面的这些数据。《科学与工程指标》中公布的数据表明,若将发表论文作为“产出”衡量指标,学术研发的收益会急剧递减。这些数据存在诸多问题。使用基于“不断扩充”的期刊集以及新发布的经济分析局研发平减指数得出的关于论文和引用的一组更新数据,情况则大为不同,消除了收益递减的表象,但引发了一个问题,即为何学术研发的投入价格上涨速度远快于国内生产总值平减指数或行业隐含研发平减指数。接下来是对各学科领域层面此类数据的生产函数分析。分析表明,“自身”研发存在显著的收益递减,以论文数量为因变量进行估计时,研发系数徘徊在0.5左右,若使用总引用次数作为因变量,该系数约为0.6。当我们用科学家和工程师替代研发作为右侧变量时,论文系数从0.5升至0.8,引用系数从0.6升至0.9,这表明将研发作为科学产出生产的唯一投入存在系统性测量问题。但考虑到各大学学科领域的个体效应,这些系数会大幅降至1以下。由于总体而言,论文数量和引用次数的增长速度与研发速度相同或更快,这一发现可被解释为其他领域、其他大学和其他国家的溢出效应发挥了重大但未被衡量的作用。

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