英文标题：
《How well do experience curves predict technological progress? A method
for making distributional forecasts》
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作者：
Fran\\c{c}ois Lafond, Aimee Gotway Bailey, Jan David Bakker, Dylan
Rebois, Rubina Zadourian, Patrick McSharry, and J. Doyne Farmer
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最新提交年份：
2017
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英文摘要：
Experience curves are widely used to predict the cost benefits of increasing the deployment of a technology. But how good are such forecasts? Can one predict their accuracy a priori? In this paper we answer these questions by developing a method to make distributional forecasts for experience curves. We test our method using a dataset with proxies for cost and experience for 51 products and technologies and show that it works reasonably well. The framework that we develop helps clarify why the experience curve method often gives similar results to simply assuming that costs decrease exponentially. To illustrate our method we make a distributional forecast for prices of solar photovoltaic modules.
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中文摘要：
经验曲线被广泛用于预测增加技术部署的成本效益。但这样的预测有多好？人们能先验地预测它们的准确性吗？在本文中，我们通过开发一种对经验曲线进行分布预测的方法来回答这些问题。我们使用51种产品和技术的成本和经验代理数据集对我们的方法进行了测试，结果表明它运行得相当好。我们开发的框架有助于澄清为什么经验曲线法通常给出与简单假设成本呈指数下降类似的结果。为了说明我们的方法，我们对太阳能光伏组件的价格进行了分布预测。
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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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