The effects of double-counting and expensing on the measured returns to r&d
The effects of double-counting and expensing on the measured returns to r&d
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重复计算和费用化对 r 测得回报的影响
DOI：
10.2307/1924367
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发表时间：
1981
期刊：
影响因子：
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通讯作者：
Mark A. Schankerman
中科院分区：
文献类型：
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作者：
Mark A. Schankerman
本文主要研究重复计算和费用化对R&D计量收益的影响。研究与开发对经济增长的贡献一般用两种方法来衡量。第一种是在增长核算框架中计算全要素生产率，并将这种“剩余”增长归因于研发。普遍的看法是，在存在重复计算的情况下，研究与发展的计量贡献代表了高于传统资本正常报酬的回报。作者证明了这种超额收益解释（ERI）在增长核算框架中基本上是正确的，并且由此产生的R&D对增长贡献的测量偏差很大。在战后的美国制造业中，测量的残差向下偏差高达30%。在这种情况下，费用化偏差是向下的，并加强了超额收益偏差，总偏差很大。在增长核算和计量经济学的背景下，偏差的大小可能会随着样本和时间的推移而变化。没有任何东西可以替代正确测量的变量。
This article focuses on the effects of double-counting and expensing on the measured returns to R&D. The contribution of research and development (R&D) to economic growth has been measured in two general ways. The first is to compute total factor productivity in a growth accounting framework and to attribute this "residual" growth to R&D. The prevailing view is that, in the presence of double-counting, the measured contribution of R&D represents the return above and beyond the normal remuneration to traditional capital. Author demonstrate that this excess returns interpretation (ERI) is essentially correct in the growth accounting framework and that the resulting bias in the measured contribution of R&D to growth is large. In postwar U.S. manufacturing the measured residual is biased downward by as much as 30%. The expensing bias is downward and reinforces the excess returns bias in this case, and the total bias is large. In both the growth accounting and econometric contexts, the magnitude of the biases may vary across samples and over time. There is simply no substitute for properly measured variables.