跳到正文
收录说明
收录范围
保留计量方法研究、相关统计基础,以及实质涉及计量方法的应用、教程、比较和综述。书评、刊务及明确无关内容不公开;身份或相关性证据不足的记录保留待核,补充可靠材料后可重新判断。
当前期刊来源见下方官网链接及期刊目录。综合经济学与金融期刊逐篇筛查计量方向,证据不足时暂不公开。正刊、在线优先论文和已核实接收稿合并展示;按标题、可靠摘要、目录及身份匹配的出版社 JEL 分类核验相关性;计量类 JEL 与摘要相互印证,无 JEL 不直接排除。历史回补以可取得的注册题录和目录为准,不等于覆盖全部纸本。
日期与排序
默认按最近发表排序:正刊使用刊期,待刊使用上线日期;缺少上线日期时,排序参考登记或首次收录时间,并在卡片注明。更多筛选可选择出版状态和日期口径;卷期依据出版社元数据,不因待刊时间较长而推定已编入正刊。仅有月份或年份时,日期区间相交也会纳入。

日期精度:到日 1 篇 · 到月 2 篇 · 到年 0 篇

分类与引用
领域和方法依据题名、摘要初步分类,可人工修正;分类不代表论文质量。引用数采用 OpenAlex 单条关联记录,不合计版本。
更新与 AI 解读
正常题录、可靠摘要与引用同步继续;日、周、月简报按核实的发表与修订日期汇总,历史补录保留在文献库。AI 解读依据可靠摘要或已核实原文片段,已有解读保留供阅读参考;缺少可靠材料的条目保持待解读,浏览页面不会触发生成。
3 篇论文
导出

Semiparametric Quantile Models for Ascending Auctions With Asymmetric Bidders

非对称竞标者升价拍卖的半参数分位数模型

The article proposes a parsimonious and flexible semiparametric quantile regression specification for asymmetric bidders within the independent private value framework. Asymmetry is parameterized using powers of a parent private value distribution, which is generated by a quantile regression specification. As noted in Cantillon, this covers and extends models used for efficient collusion, joint bidding and mergers among homogeneous bidders. The specification can be estimated…

AI 解读阅读原文 ↗BibTeX ↓

Quantile regression methods for first-price auctions

第一价格拍卖的分位数回归方法

The paper proposes a quantile-regression inference framework for first-price auctions with symmetric risk-neutral bidders under the independent private-value paradigm. It is first shown that a private-value quantile regression generates a quantile regression for the bids. The private-value quantile regression can be easily estimated from the bid quantile regression and its derivative with respect to the quantile level. This also allows to test for various specification or…

AI 解读阅读原文 ↗BibTeX ↓

Nonparametric identification of an interdependent value model with buyer covariates from first-price auction bids

从第一价格拍卖出价非参数识别含买方协变量的相互依赖价值模型

This paper introduces a version of the interdependent value model of Milgrom and Weber (1982), where the signals are given by an index gathering signal shifters observed by the econometrician and private ones specific to each bidders. The model primitives are shown to be nonparametrically identified from first-price auction bids under a testable mild rank condition. Identification holds for all possible signal values. This allows to consider a wide range of counterfactuals…

AI 解读阅读原文 ↗BibTeX ↓