Nonparametric identification of random coefficients in aggregate demand models for differentiated products
Nonparametric identification of random coefficients in aggregate demand models for differentiated products
复制标题
差异化产品总需求模型中随机系数的非参数辨识
DOI：
10.1093/ectj/utad002
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Kaido, Hiroaki
中科院分区：
文献类型：
--
作者：
Dunker, Fabian;Hoderlein, Stefan;Kaido, Hiroaki
研究了具有异质消费者的差异化产品市场层次需求模型中的非参数辨识问题。我们考虑了一类一般的模型，它允许个体特有的系数在整个群体中连续变化，并给出了识别这些系数的密度的条件，从而也给出了识别泛函的条件，例如从反事实干预中受益的个体的分数。
This paper studies nonparametric identification in market-level demand models for differentiated products with heterogeneous consumers. We consider a general class of models that allows for the individual-specific coefficients to vary continuously across the population and give conditions under which the density of these coefficients, and hence also functionals such as the fractions of individuals who benefit from a counterfactual intervention, is identified.