首页> 外文期刊>American Journal of Agricultural Economics >Public R&D, private R&D, and U.S. agricultural productivity growth: dynamic and long-run relationships.
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Public R&D, private R&D, and U.S. agricultural productivity growth: dynamic and long-run relationships.

机译:公共研发,私人研发和美国农业生产率的增长:动态和长期的关系。

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This study uses long-term time series data on public and private agricultural R&D spending in the USA to examine their relationship with one another and to agricultural productivity growth. The study finds econometric evidence of complementarity between public and private agricultural research investments, with both sectors responsive to what the other sector is doing (or not doing). Increased spending on public fundamental or applied crop research appears to stimulate an increase in private research on crops, possibly because of new technological opportunities for commercialization opened up by public research. At the same time, public crop research appears to decline following an exogenous increase in private crop research, possibly because the public sector withdraws from areas it sees private companies pursuing. Other results from the study confirm that research affects agricultural productivity only over the long term. Changes in either public or private research expenditure have no significant impact on agricultural TFP growth, but research stocks (accumulation of several years of research expenditures) do. However, due to the high collinearity between public and private agricultural research stocks (even with 40 years of time series data), it remains difficult to estimate the respective impacts of public and private research on productivity.Digital Object Identifier http://dx.doi.org/10.1093/ajae/aat032
机译:这项研究使用有关美国公共和私人农业研发支出的长期时间序列数据来检验它们之间的关系以及与农业生产率增长的关系。该研究发现了公共和私人农业研究投资之间互补性的计量经济学证据,两个部门都对另一部门正在做的(或未做的)做出反应。公共基础研究或应用作物研究的支出增加似乎刺激了私人作物研究的增加,这可能是由于公共研究为商业化提供了新的技术机会。同时,由于私人作物研究的外生增加,公共作物研究似乎下降了,这可能是因为公共部门退出了私人公司追求的领域。该研究的其他结果证实,研究仅长期影响农业生产力。公共或私人研究支出的变化对农业全要素生产率的增长没有显着影响,但是研究存量(几年研究支出的积累)却没有。但是,由于公共和私有农业研究种群之间的高度共线性(即使有40年的时间序列数据),仍然难以估计公共和私有研究对生产率的各自影响。数字对象标识符http:// dx。 doi.org/10.1093/ajae/aat032

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