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摘要翻译：
我们考虑独立私有价值第一价格拍卖模型的非参数辨识，其中分析员只观察中标。我们的基准模型假设一个外生的投标人数量$N$。我们证明，如果投标者观察到$N$，中标密度的不连续性可以用来识别$N$的分布。可以在第二步骤中识别私有值分布。第二类模型考虑由于保留价格或进入成本而内生确定的$N$.如果投标人遵守$N$，这些模型也可以通过中标不连续来识别。但是，如果投标人不能观察到$N$，除非分析员观察到一个影响保留价或进入成本的工具，否则识别是不可能的。最后，我们得到了一些可检验的限制条件，即竞标者是否观察竞争者的数量，内生参与是由于保留价格还是进入成本。对USFS木材拍卖数据的应用说明了我们的理论结果对竞争分析的有用性，表明近三分之一的投标可能是非竞争性的。它还表明，由错误衡量的竞争造成的风险规避偏差可能很大。
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英文标题：
《Nonparametric Identification of First-Price Auction with Unobserved
Competition: A Density Discontinuity Framework》
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作者：
Emmanuel Guerre and Yao Luo
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最新提交年份：
2019
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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：
We consider nonparametric identification of independent private value first-price auction models, in which the analyst only observes winning bids. Our benchmark model assumes an exogenous number of bidders $N$. We show that, if the bidders observe $N$, the resulting discontinuities in the winning bid density can be used to identify the distribution of $N$. The private value distribution can be identified in a second step. A second class of models considers endogenously-determined $N$, due to a reserve price or an entry cost. If bidders observe $N$, these models are also identifiable using winning bid discontinuities. If bidders cannot observe $N$, however, identification is not possible unless the analyst observes an instrument which affects the reserve price or entry cost. Lastly, we derive some testable restrictions for whether bidders observe the number of competitors and whether endogenous participation is due to a reserve price or entry cost. An application to USFS timber auction data illustrates the usefulness of our theoretical results for competition analysis, showing that nearly one bid out of three can be non competitive. It also suggests that the risk aversion bias caused by a mismeasured competition can be large.
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PDF链接：
https://arxiv.org/pdf/1908.05476
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