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来源与收录范围

汇总期刊目录中的 16 个期刊来源,以及 arXiv 计量经济学与相关统计、金融分类和主题检索中的预印本。期刊题录主要来自 Crossref,可靠摘要保留补充来源;期刊官网链接可在论文检索的说明中核对。

保留计量方法研究、相关统计基础及实质涉及计量方法的应用、教程、比较和综述。待核验、范围外及撤回记录不进入公开简报。基础文献按学习与研究需要单独选编。

自 2026 年 10 月 15 日起,日简报每天北京时间 10:00 发布,连续汇总前一天 10:00(含)至当天 10:00(不含)首次进入公开文献库的论文和新检测到的 arXiv 修订。同一篇在一期只列一次;晚到记录按本站收到的时间进入下一期,不再回填进旧日报。正文保留原站发表与修订日期,延迟收录单独列示;补摘要、引用或 AI 解读不会重复入期。普通采集保留近 45 天的来源更新;批量扩刊仅保留收录当月新文,历史补录仍只留在文献库。尚未抓取成功的来源会提示同步延迟。撤回内容会同步移除;所有历史补录仍可在论文检索中查找。

当前结果:已发表 0 篇 · 待刊 1 篇 · 预印本 4 篇

关键词匹配标题、摘要、作者或 DOI;支持部分字母,多词同时匹配,双引号匹配短语。

新收录期刊、预印本和修订在前,延迟收录单列;组内默认本文引用优先。也可选择作者引用优先或最新收录。

期刊论文在前,预印本在后。组内先看本文引用,再看已有明确关联作者的最高累计引用,最后按当前日期顺序排序。

“作者引用”指已有明确关联作者的最高累计引用,不合计共同作者。目前作者指标只来自有身份关联快照的预印本,普通期刊条目可能没有该项数据;本页 0/5 篇有可核验作者指标。

本文引用采用 OpenAlex 单条关联记录,不合计版本;缺失不记作零。累计引用会随时间积累,可结合近年范围比较;引用数和作者发表经历是阅读线索,不代表论文质量或同行评审状态。

“作者发表记录”展示作者已有论文的可核验发表记录,不证明该预印本已接收或通过同行评审。

正常题录、可靠摘要和引用同步继续;AI 解读依据可靠材料,材料不足时保留待解读状态。

2 个来源同步延迟

本期 5 篇
导出

新收录 · 期刊论文

ON THE RELATION BETWEEN DISCRETE- AND CONTINUOUS-TIME AFFINE OPTION PRICING MODELS

离散时间与连续时间仿射期权定价模型之间的关系

This article studies the weak convergence of discrete-time generalized autoregressive conditional heteroskedasticity (GARCH) and stochastic volatility (SV) option pricing models that allow for fat tails, multi-component volatilities, and non-monotonic pricing kernels. We introduce a general affine framework that enables the simultaneous derivation of new diffusion limits for Gaussian and inverse Gaussian GARCH models based on distributional invariant parametric convergence…

AI 解读阅读原文 ↗BibTeX ↓

延迟收录

Two Gaussians, Too Many: A bootstrap-based approach to assess identifiability in non-Gaussian structural vector autoregressions

Normality pre-tests on reduced-form innovations cannot detect whether two or more underlying structural shocks are Gaussian, and hence cannot detect a failure of identification in non-Gaussian SVARs. We propose a bootstrap-based approach that reveals such a failure. Under the null of valid identification and certain regularity conditions, the conditional bootstrap distribution of the maximum likelihood estimator of the impact matrix is asymptotically normal, so the…

阅读原文 ↗BibTeX ↓

Propensity score with factor loadings: evaluating the effect of the Paris Agreement on the returns of European stocks

Factor models for longitudinal data, where policy adoption is unconfounded with respect to a low-dimensional set of latent factor loadings, have become increasingly popular for causal inference. Most existing approaches, however, rely on a causal finite-sample approach or computationally intensive methods, limiting their applicability and external validity. In this paper, we propose a novel method for panel causal inference within a super-population framework, based on…

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Bootstrap inference in factor-augmented regressions with weak factors

In this paper, we develop bootstrap methods for factor-augmented regressions with potentially weak common components, allowing signal eigenvalues to diverge at heterogeneous rates $N^{α_k}$, where $0<α_k\leq1$, $k=1,\ldots,r$. The regression estimator targets a rotation of the latent parameter vector that may be data dependent, while factor estimation can induce asymptotic bias. The proposed procedure directly constructs the rotation-specific target in the bootstrap world,…

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Beyond Sustainable Development Goal (SDG) Accelerators: Directed Evidence for Adaptive Sustainability Portfolios

Governments and development partners often seek Sustainable Development Goal (SDG) "accelerators" whose progress can propagate gains across human well-being, institutions, resources, and environmental priorities. Such claims require evidence on direction, timing, robustness, and trade-offs, not only network connectivity. We map directed SDG interdependence using a balanced panel of 114 countries observed annually from 2000 to 2024. Because the goal series are persistent,…

阅读原文 ↗BibTeX ↓