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How well do experience curves predict technological progress? A method for making distributional forecasts

机译:经验曲线如何很好地预测技术进步?进行分布预测的方法

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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.
机译:经验曲线被广泛用于预测增加技术部署的成本收益。但是这样的预测有多好?可以先验地预测其准确性吗?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。我们使用包含51种产品和技术的成本和经验代理的数据集测试了我们的方法,并证明了它的合理性。我们开发的框架有助于弄清为什么经验曲线方法经常给出与简单地假设成本呈指数下降的相似结果。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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