Statistical basis for predicting technological progress.
Statistical basis for predicting technological progress.
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DOI：
10.1371/journal.pone.0052669
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Trancik JE
中科院分区：
文献类型：
--
作者：
Nagy B;Farmer JD;Bui QM;Trancik JE
预测技术进步对工程师、政策制定者和私人投资者都有很大的兴趣。已经提出了几种模型来预测技术进步，但这些模型的表现如何？西奥多赖特（Theodore Wright）在1936年提出的一个早期假设是，成本随着累积生产的幂律而下降。另一种假设是摩尔定律，它可以概括为技术随着时间的推移呈指数级增长。戈达德、辛克莱等人提出了其他替代方案，诺德豪斯这些假设以前没有经过严格的检验。使用一个关于62种不同技术的成本和生产的新数据库，这是同类产品中最广泛的，我们测试了六种不同假设定律预测未来成本的能力。我们的方法涉及后报和开发一个统计模型来排名的假设法律的性能。赖特定律产生了最好的预测，但摩尔定律也不甘落后。我们发现了一个以前没有观察到的规律，即产量往往呈指数级增长。成本的指数下降和产量的指数增长相结合将使摩尔定律和赖特定律难以区分，正如Sahal最初指出的那样。我们第一次表明，在数据中观察到的这种程度，这两个法律的性能几乎是相同的。我们的研究结果表明，技术进步是可预测的，与对数误差的平方根线性增长的预测范围在一个典型的速度为每年2.5%。这些结果对技术变革的理论，以及减缓气候变化的候选技术和政策的评估具有影响。
Forecasting technological progress is of great interest to engineers, policy makers, and private investors. Several models have been proposed for predicting technological improvement, but how well do these models perform? An early hypothesis made by Theodore Wright in 1936 is that cost decreases as a power law of cumulative production. An alternative hypothesis is Moore's law, which can be generalized to say that technologies improve exponentially with time. Other alternatives were proposed by Goddard, Sinclair et al., and Nordhaus. These hypotheses have not previously been rigorously tested. Using a new database on the cost and production of 62 different technologies, which is the most expansive of its kind, we test the ability of six different postulated laws to predict future costs. Our approach involves hindcasting and developing a statistical model to rank the performance of the postulated laws. Wright's law produces the best forecasts, but Moore's law is not far behind. We discover a previously unobserved regularity that production tends to increase exponentially. A combination of an exponential decrease in cost and an exponential increase in production would make Moore's law and Wright's law indistinguishable, as originally pointed out by Sahal. We show for the first time that these regularities are observed in data to such a degree that the performance of these two laws is nearly the same. Our results show that technological progress is forecastable, with the square root of the logarithmic error growing linearly with the forecasting horizon at a typical rate of 2.5% per year. These results have implications for theories of technological change, and assessments of candidate technologies and policies for climate change mitigation.
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DOI：
10.1109/tchmt.1982.1136009
发表时间：
1982-01-01
期刊：
IEEE TRANSACTIONS ON COMPONENTS HYBRIDS AND MANUFACTURING TECHNOLOGY
影响因子：
--
作者：
GODDARD, CT
通讯作者：
GODDARD, CT
DOI：
10.1016/j.techfore.2007.05.007
发表时间：
2008-07-01
影响因子：
12
作者：
Koh, Heebyung;Magee, Christopher L.
通讯作者：
Magee, Christopher L.
DOI：
10.1016/j.techfore.2011.07.006
发表时间：
2011-10-01
影响因子：
12
作者：
Nagy, Bela;Farmer, J. Doyne;Gonzales, John Paul
通讯作者：
Gonzales, John Paul
DOI：
10.1080/05695557908974396
发表时间：
1979-01-01
期刊：
AIIE TRANSACTIONS
影响因子：
--
作者：
SAHAL, D
通讯作者：
SAHAL, D
影响因子：
56.9
作者：
ARGOTE, L;EPPLE, D
通讯作者：
EPPLE, D