U.S. subsidy effects on production of solar technology research: Using a new measure to assess policy impacts

Eileen Hlavka
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Abstract

Solar technology has advanced substantially in recent years, and policymakers interested in reducing climate change hope these improvements will continue. Nevertheless, only one measure, patent counts, has been widely used to identify the rate of improvement, and scant research has assessed the effectiveness of efforts to increase it. In this paper, the number of articles published on solar energy during each month in 1986-2009 is calculated to create a more detailed supplement to patent counts, and these article counts are used to assess certain relevant subsidies. A combination of counting articles manually and naïve Bayesian classification is used to overcome the difficulties of identifying which articles are relevant. The resulting monthly article counts are modeled as a function of two major subsidy types. The largest U.S. subsidy for renewable energy, the Production Tax Credit, appears to be as much as half as effective at encouraging solar technology research as federal solar research subsidies, despite the fact that the tax credit is given to electricity producers rather than to researchers and goes mostly to non-solar energy sources. This finding may be considered a preliminary example of the use of monthly solar article counts.
美国补贴对太阳能技术生产的影响研究:使用一种新方法来评估政策影响
近年来,太阳能技术取得了长足的进步,对减少气候变化感兴趣的政策制定者希望这些进步能继续下去。然而,只有专利数量这一衡量标准被广泛用于确定技术进步的速度,而且很少有研究评估提高技术进步的有效性。本文通过计算1986-2009年每个月关于太阳能的论文发表数量,对专利数量进行更详细的补充,并使用这些文章数量来评估某些相关补贴。人工计数文章和naïve贝叶斯分类的结合被用来克服识别哪些文章是相关的困难。由此产生的每月文章数被建模为两种主要补贴类型的函数。美国对可再生能源的最大补贴——生产税收抵免——在鼓励太阳能技术研究方面的效果似乎只有联邦太阳能研究补贴的一半,尽管事实上税收抵免是给了电力生产商而不是研究人员,而且主要是给了非太阳能能源。这一发现可被视为使用每月太阳能条目数的初步例子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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