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摘要翻译：
本文给出了一种求解平均产品质量的数值方法，该方法将实际市场份额等同于由离散选择模型预测的市场份额。该方法涵盖了一般的离散选择模型，包括Berry and Pakes(2007)的纯特征模型和Berry et al.(1995)的随机系数logit模型（以下简称BLP）。该方法将原来的市场份额反演问题转化为无约束凸极小化问题，使得任何凸规划算法都可以用来求解反演问题。此外，这些结果也意味着反演一个需求模型的计算复杂度不应超过凸规划问题的计算复杂度。仿真实例表明，该方法优于BLP中的压缩映射算法。我还发现，在市场份额接近零的纯特征模型中，该方法仍然是稳健的。
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英文标题：
《A General Method for Demand Inversion》
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作者：
Lixiong Li
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最新提交年份：
2018
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分类信息：
一级分类：Economics 经济学
二级分类：Econometrics 计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
This paper describes a numerical method to solve for mean product qualities which equates the real market share to the market share predicted by a discrete choice model. The method covers a general class of discrete choice model, including the pure characteristics model in Berry and Pakes(2007) and the random coefficient logit model in Berry et al.(1995) (hereafter BLP). The method transforms the original market share inversion problem to an unconstrained convex minimization problem, so that any convex programming algorithm can be used to solve the inversion. Moreover, such results also imply that the computational complexity of inverting a demand model should be no more than that of a convex programming problem. In simulation examples, I show the method outperforms the contraction mapping algorithm in BLP. I also find the method remains robust in pure characteristics models with near-zero market shares.
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PDF链接：
https://arxiv.org/pdf/1802.04444
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