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.
引用
收藏
页码:471 / 493
页数:23
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