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 0 篇 · 到月 3 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

Interest rate volatility, the yield curve, and the macroeconomy

利率波动率、收益率曲线与宏观经济

This paper provides theory and evidence that a low-dimensional term structure model can simultaneously price bonds and related options. It shows that a component of volatility risk largely unrelated to the shape of the yield curve is a determinant of expected excess returns for holding long maturity bonds. It also finds evidence for this return relationship both in the model and directly in the data through regression analysis. The paper also identifies a link between…

AI 解读阅读原文 ↗BibTeX ↓

Why Gaussian macro-finance term structure models are (nearly) unconstrained factor-VARs

为何高斯宏观金融期限结构模型几乎是不受约束的因子VAR

This paper explores the implications of filtering and no-arbitrage for the maximum likelihood estimates of the entire conditional distribution of the risk factors and bond yields in Gaussian macro-finance term structure model (MTSM) when all yields are priced imperfectly. For typical yield curves and macro-variables studied in this literature, the estimated joint distribution within a canonical MTSM is nearly identical to the estimate from an economic-model-free factor…

AI 解读阅读原文 ↗BibTeX ↓

AN EQUIVALENCE RESULT FOR VC CLASSES OF SETS

集合 VC 类的一个等价性结果

Let and Θ be infinite sets and let × Θ. We show that the class of projections of A onto is a Vapnik–Chervonenkis ( VC ) class of sets if and only if the class of projections of A onto Θ is a VC class. We illustrate the result in the context of semiparametric estimation of a transformation model. In this application, the VC property is hard to establish for the projection class of interest but easy to establish for the other projection class.

AI 解读阅读原文 ↗BibTeX ↓