《Food Productivity Trends from Hybrid Corn: Statistical Analysis of
Patents and Field-test data》
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作者:
Mariam Barry, Giorgio Triulzi, Christopher L. Magee
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最新提交年份:
2017
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英文摘要:
In this research we study productivity trends of hybrid corn - an important subdomain of food production. We estimate the yearly rate of yield improvement of hybrid corn (measured as bushel per acre) by using both information on yields contained in US patent documents for patented hybrid corn varieties and on field-test data of several hybrid corn varieties performed at US State level. We have used a generalization of Moore\'s law to fit productivity trends and obtain the performance improvement rate by analyzing time series of hybrid corn performance for a period covering the last thirty years. The linear regressions results obtained from different data sources indicate that the estimated improvement rates per year are between 1.2 and 2.4 percent. In particular, using yields reported in a sample of patents filed between 1985 and 2010, we estimated an improvement rate of 0.015 (R2 = 0.74, Pvalue = 1.37 x 10^-8). Moreover, we apply two predicting models developed by Benson and Magee (2015) and Triulzi and Magee (2016) that only use patent metadata to estimate the rate of improvement. We compare these predicted values to the rate estimated using US States field-test data. We find that, due to a turning point in patenting practices which begun in 2008, only the predicted rate (rate = 0.015) using patents filed before 2008 is consistent with the empirical rate. Finally, we also investigate at the micro level - on the basis of 70 patents (granted between 1986 and 2015) - whether the number of citations received by a patent is correlated with performance achieved by the patented variety. We find that the relative performance (yield ratio) of the patented seed is positively correlated with the total number of citations received by the patent (until December 2015) but not the citations received within 3 years after the granted year, with the patent application year used as control variable.
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中文摘要:
在本研究中,我们研究了杂交玉米的生产力趋势,这是粮食生产的一个重要子领域。我们通过使用美国专利文件中包含的杂交玉米专利品种的产量信息以及在美国各州进行的几个杂交玉米品种的田间试验数据,估计了杂交玉米的年产量提高率(以每英亩蒲式耳为单位)。我们利用摩尔定律的推广来拟合生产力趋势,并通过分析过去三十年期间杂交玉米的表现时间序列来获得表现改善率。从不同数据来源获得的线性回归结果表明,每年的估计改善率在1.2%到2.4%之间。特别是,使用1985年至2010年间提交的专利样本中报告的产量,我们估计改善率为0.015(R2=0.74,Pvalue=1.37 x 10^-8)。此外,我们应用了Benson和Magee(2015)以及Triulzi和Magee(2016)开发的两个预测模型,它们仅使用专利元数据来估计改进率。我们将这些预测值与使用美国各州现场测试数据估计的速率进行比较。我们发现,由于2008年开始的专利实践的转折点,只有2008年之前申请的专利的预测率(比率=0.015)与经验率一致。最后,我们还以70项专利(1986年至2015年授予)为基础,在微观层面上调查一项专利收到的引文数量是否与该专利品种的绩效相关。我们发现,专利种子的相对性能(产量比)与专利收到的总引文数(截至2015年12月)呈正相关,但与授予年份后3年内收到的引文数无关,以专利申请年份为控制变量。
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分类信息:
一级分类:Quantitative Finance 数量金融学
二级分类:Economics 经济学
分类描述:q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学,包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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