Slow Magic: Agricultural Versus Industrial R&D Lag Models

被引:8
|
作者
Alston, Julian M. [1 ]
Pardey, Philip G. [2 ]
Serfas, Devin [1 ]
Wang, Shanchao [3 ]
机构
[1] Univ Calif Davis, Dept Agr & Resource Econ, Davis, CA 95616 USA
[2] Univ Minnesota, Dept Appl Econ, St Paul, MN USA
[3] Meta, Seattle, WA USA
关键词
knowledge stocks and flows; industrial and agricultural sectors; R&D; adoption; technological change; innovation; PRODUCTIVITY GROWTH; HYBRID CORN; RESEARCH EXPENDITURES; RETURNS; US; INNOVATION; KNOWLEDGE; ECONOMICS; OUTPUT; COSTS;
D O I
10.1146/annurev-resource-111820-034312
中图分类号
F3 [农业经济];
学科分类号
0202 ; 020205 ; 1203 ;
摘要
R&D is slow magic. It takes many years before research investments begin to affect productivity, but then they can affect productivity for a long time. Many economists get this wrong. Here, we revisit the conceptual foundations for R&D lag models used to represent the temporal links between research investments and impact, review prevalent practice, and document and discuss a range of evidence on R&D lags in agriculture and other industries. Our theory and evidence consistently support the use of longer lags with a different overall lag profile than is typically imposed in studies of industrial R&D and government compilations of R&D knowledge stocks. Many studies systematically fail to recognize the many years of investment and effort typically required to create a new technology and bring it to market and the subsequent years as the technology is diffused and adopted. Consequential distortions in the measures and economic understanding are implied.
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页码:471 / 493
页数:23
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