跳到正文
简报说明

来源与收录范围

汇总期刊目录中的 10 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。

本站收录时间统一使用北京时间。“本期动态”汇总期刊新收录与 arXiv 首次发布、修订;“近期发表”按已知发表/首次提交日期匹配。按已知发表日期范围匹配,包含仅到月或年的记录。可确定在本期内的论文优先排列;日期范围仅部分相交的论文单独计数,可能在多个周期出现,不表示当日新增。未知发表日期与明确未来日期不计入。撤回内容会同步移除;发表日期依原文版本和已知日期精度确定。

当前结果:已发表 31 篇 · 待刊 9 篇 · 预印本 12 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。

按发表日期的简报默认保留各组原有日期顺序。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。

“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 0/24 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。

52 篇论文
导出

Metropolis–Hastings with Scalable Subsampling

采用可扩展子采样的 Metropolis–Hastings 算法

The Metropolis–Hastings (MH) algorithm is one of the most widely used Markov Chain Monte Carlo schemes for generating samples from Bayesian posterior distributions. The algorithm is asymptotically exact, flexible and easy to implement. However, in the context of Bayesian inference for large datasets, evaluating the likelihood on the full data for thousands of iterations until convergence can be prohibitively expensive. This paper introduces a new subsample MH algorithm that…

AI 解读阅读原文 ↗BibTeX ↓

BAP: Bayesian Biomarker-Assisted Platform Design for Dose Ranging in Multi-Agent Multi-Dose Trials

BAP:多药物多剂量试验的贝叶斯生物标志物辅助平台设计

Assessing the long-term benefits of new treatments can be expensive and time-consuming, particularly in disease areas with unmet medical needs. While platform trials enable the evaluation of multiple interventions simultaneously, they currently cannot assess studies involving multiple agents and doses or utilize longitudinal biomarkers in decision-making. We propose a Bayesian biomarker-assisted platform design that offers a unified framework for evaluating multiple…

AI 解读阅读原文 ↗BibTeX ↓

Safe, Always-Valid Alpha-Investing Rules For Doubly Sequential Online Inference

双重序贯在线推断中的安全且随时有效的Alpha投资规则

Dynamic decision-making in rapidly evolving research domains, including marketing, finance, and pharmaceutical development, presents a significant challenge. Researchers frequently confront the need for real-time action within a doubly sequential framework characterized by the continuous influx of high-volume data streams and the intermittent arrival of novel tasks. This calls for the development and implementation of new online inference protocols capable of handling both…

AI 解读阅读原文 ↗BibTeX ↓

Kernel-based Adaptive Huber Mean Regression with Heavy Tails and Contamination

重尾与污染下基于核的自适应Huber均值回归

We consider robust conditional mean learning in the mathematical framework of reproducing kernel Hilbert spaces, assuming the errors can be heavy-tailed and at the same time some responses are subject to arbitrary contamination. Simultaneous robustness to both heavy tails and contamination are of interest. When there is no contamination, we establish rates when the (1+θ)-moment ( θ>0) of the error exists, which matches the minimax rate for the least squares regression as…

AI 解读阅读原文 ↗BibTeX ↓

Structured Mixture of Continuation-Ratio Logits Models for Ordinal Regression

用于有序回归的延续比Logit结构化混合模型

We develop a nonparametric Bayesian modeling approach to ordinal regression based on priors placed directly on the discrete distribution of the ordinal responses. The prior probability models are built from a structured mixture of multinomial distributions. We leverage the continuation-ratio logits representation to formulate the mixture kernel, with mixture weights defined through the logit stick-breaking process that incorporates the covariates through a linear function.…

AI 解读阅读原文 ↗BibTeX ↓

Fairness-Aware Gaussian Graphical Regression Models with Application to Brain Co-Expression QTL Studies

公平性感知的高斯图回归及脑共表达QTL研究应用

Glioblastoma multiforme (GBM) is a highly aggressive brain cancer with largely ineffective treatment. It is imperative to explore more effective therapies, such as gene-based treatments. For co-expression QTL studies of GBM, we develop fairness-aware Gaussian graphical regression models (Fair RegGGMs), which can determine how genetic variants modulate subject-level gene networks, and recover both population-level and subject-level gene graphs, while ensuring that the…

AI 解读阅读原文 ↗BibTeX ↓

Encompassing and Progression Testing in High-Dimensions

高维环境中的涵盖检验与递进检验

This paper introduces the Subseries-based Cauchy Combination Test (SCT), a novel procedure for testing encompassing relationships or model validity using identification conditions formulated as multiple moment restrictions. SCT applies to weakly or short-range-dependent data and eliminates the need to estimate high-dimensional covariance matrices. Unlike Wald- or J-type tests, it remains reliable in both low- and high-dimensional settings. The test is asymptotically unbiased…

AI 解读阅读原文 ↗BibTeX ↓

Panel Stochastic Frontier Models with Latent Group Structures

具有潜在分组结构的面板随机前沿模型

Stochastic frontier models have attracted considerable attention due to the incorporation of an inefficiency term in addition to the conventional error term. In this paper, we propose a general estimation framework for panel stochastic frontier models that accommodates potential heterogeneity through latent group structures. The framework is tailored to the distinctive features of stochastic frontier models and is paired with a practical hybrid estimation procedure that…

AI 解读阅读原文 ↗BibTeX ↓

ON THE POWER PROPERTIES OF INFERENCE FOR PARAMETERS WITH INTERVAL IDENTIFIED SETS

区间识别集参数推断的功效性质

This article studies the power properties of confidence intervals (CIs) for a partially-identified parameter of interest with an interval identified set. We assume that the researcher has bounds estimators needed to construct the CIs proposed by Imbens and Manski (2004), Stoye (2009), and Stoye (2020), denoted by C I α 1 $CI_{\alpha }^{1}$ upper C upper I Subscript alpha Superscript 1 , C I α 2 $CI_{\alpha }^{2}$ upper C upper I Subscript alpha Superscript 2 , C I α 3 $CI_{\alpha }^{3}$…

AI 解读阅读原文 ↗BibTeX ↓

Locally Robust Semiparametrically Efficient Bayesian Inference

局部稳健且半参数有效的贝叶斯推断

We propose a framework for making Bayesian parametric models robust to local misspecification. Suppose in a baseline parametric model, a parameter of interest has an interpretation in an encompassing semiparametric model. Bayesian and maximum likelihood estimators are generally biased under local misspecification. We propose to augment the baseline likelihood by a multiplicative factor that involves scores for the baseline model, the efficient scores for the encompassing…

AI 解读阅读原文 ↗BibTeX ↓

Causal Inference for Spatial Treatments

空间处理的因果推断

Many events and policies (treatments) occur at specific spatial locations, with researchers interested in their effects on nearby units. I approach the spatial treatment setting from an experimental perspective: What ideal experiment would we design to estimate the causal effects of spatial treatments? This perspective motivates a comparison between units near realized treatment locations and units near counterfactual (unrealized) candidate locations, which differs from…

AI 解读阅读原文 ↗BibTeX ↓

Double Robustness of Local Projections and Some Unpleasant VARithmetic

局部投影的双重稳健性与 VAR 推断的隐患

We consider impulse response inference in a locally misspecified vector autoregression (VAR) model. The conventional local projection (LP) confidence interval has correct coverage even when the misspecification is so large that it can be detected with probability approaching 1. This result follows from a “double robustness” property analogous to that of popular partially linear regression estimators. By contrast, the conventional VAR confidence interval with…

AI 解读阅读原文 ↗BibTeX ↓

Economic Growth and the Rise of Large Firms

经济增长与大型企业的崛起

I document that the right tail of the firm size distribution systematically thickens with economic development. To rationalize this fact, I develop a parsimonious idea search model in which both aggregate growth and the firm size distribution are endogenously determined. The model features an asymptotic balanced growth path along which Gibrat's law holds at each date, and the right tail of the firm size distribution thickens monotonically toward Zipf's law. The model also…

AI 解读阅读原文 ↗BibTeX ↓

Mechanism Design for Personalized Policy: A Field Experiment Incentivizing Exercise

个性化政策的机制设计:激励运动的实地实验

Personalizing policies can theoretically increase their effectiveness. However, personalization is difficult when individual types are unobservable and the preferences of policymakers and individuals are not aligned, which could cause individuals to misreport their type. Mechanism design offers a strategy to overcome this issue: offer an “incentive‐compatible” menu of policy choices designed to induce participants to select the variant intended for their type. Using a field…

AI 解读阅读原文 ↗BibTeX ↓

Continuity of the Distribution Function of the argmax of a Gaussian Process

高斯过程最大值位置分布函数的连续性

Certain extremum estimators have asymptotic distributions that are non‐Gaussian, yet characterizable as the distribution of the arg max of a Gaussian process. This paper presents high‐level sufficient conditions under which such asymptotic distributions admit a continuous distribution function. The plausibility of the sufficient conditions is demonstrated by verifying them in three examples, namely, maximum score estimation, empirical risk minimization, and threshold…

AI 解读阅读原文 ↗BibTeX ↓

Communicating Scientific Uncertainty via Approximate Posteriors

通过近似后验传达科学不确定性

We cast the problem of communicating scientific uncertainty as one of reporting a posterior distribution on an unknown parameter to an audience of Bayesian decision‐makers. We establish novel bounds on the audience's regret when the analyst reports an approximation to a posterior that the audience treats as exact. Under a palatable restriction on the audience's decision problems, the bounds take an especially convenient form. Under a further restriction on the audience's…

AI 解读阅读原文 ↗BibTeX ↓

Rural Migrants and Urban Informality: Evidence From Brazil

农村移民与城市非正规就业:来自巴西的证据

This paper studies the economic effects of rural‐urban migration on Brazilian cities. Using a shift‐share IV design, we show that, over a decade, drought‐induced immigration reduces informality, has no effect on unemployment, and increases the number of formal firms and jobs. Downward formal wage adjustments play a key role, as these long‐run effects are weaker in regions with stronger wage rigidity. In the short run, when wage rigidity is strongest, we replicate the…

AI 解读阅读原文 ↗BibTeX ↓

Empirical Bayes When Estimation Precision Predicts Parameters

估计精度能够预测参数时的经验贝叶斯方法

Gaussian empirical Bayes methods usually maintain a precision independence assumption: The unknown parameters of interest are independent from the known standard errors of the estimates. This assumption is often theoretically questionable and empirically rejected. This paper proposes to model the conditional distribution of the parameter given the standard errors as a flexibly parameterized location‐scale family of distributions, leading to a family of methods that we call…

AI 解读阅读原文 ↗BibTeX ↓

Optimally‐Transported Generalized Method of Moments

基于最优传输的广义矩估计

We propose a novel optimal transport‐based version of the Generalized Method of Moment (GMM). Instead of handling overidentification by reweighting the data to satisfy the moment conditions (as in Generalized Empirical Likelihood methods), this method proceeds by allowing for errors in the variables of the least mean‐square magnitude necessary to simultaneously satisfy all moment conditions. This approach, based on the notions of optimal transport and Wasserstein metric,…

AI 解读阅读原文 ↗BibTeX ↓

Optimal Shrinkage Estimation of Fixed Effects in Linear Panel Data Models

线性面板模型中固定效应的最优收缩估计

Shrinkage methods are frequently used to improve the precision of least squares estimators of fixed effects. However, widely used shrinkage estimators guarantee improved precision only under strong distributional assumptions. I develop an estimator for the fixed effects that obtains the best possible mean squared error within a class of shrinkage estimators. This class includes conventional shrinkage estimators and the optimality does not require distributional assumptions.…

AI 解读阅读原文 ↗BibTeX ↓

An Experimental Evaluation of Deferred Acceptance: Evidence From Over 100 Army Officer Labor Markets

延迟接受算法的实验评估:来自逾百个军官劳动力市场的证据

Internal labor markets are increasingly important for matching workers to jobs within organizations. We present evidence from a randomized trial that compares matching workers to jobs using the deferred acceptance (DA) algorithm to the traditional manager‐directed matching process. Our setting is the U.S. Army's internal labor market, which matches over 14,000 officers to units annually. We find that DA reduces administrative burden and increases match quality as measured by…

AI 解读阅读原文 ↗BibTeX ↓

Spatial Economics for Granular Settings

细粒度情境中的空间经济学

We examine the application of quantitative spatial models to the growing body of fine spatial data used to study local economic outcomes. In granular settings in which people choose from a large set of potential residence‐workplace pairs, observed outcomes in part reflect idiosyncratic choices. Using analytical examples, Monte Carlo simulations, and event studies of neighborhood employment booms, we demonstrate that calibration procedures that equate observed shares and…

AI 解读阅读原文 ↗BibTeX ↓

Multidimensional Screening With Precise Seller Information

卖方信息精确时的多维筛选

A multi‐product monopolist faces a buyer who is privately informed about his valuations for the goods. As is well known, optimal mechanisms are in general complicated, while simple mechanisms—such as pure bundling or separate sales—can be far from optimal and do not admit clear‐cut comparisons. We show that this changes if the monopolist has sufficiently precise information about the buyer's valuations: Now, pure bundling always outperforms separate sales; moreover, there is…

AI 解读阅读原文 ↗BibTeX ↓

Subgroup Decomposition of the Gini Coefficient: A New Solution to an Old Problem

基尼系数的子群分解:老问题的新解法

We derive a novel decomposition of the Gini coefficient into within‐ and between‐group inequality terms that sum to the aggregate Gini coefficient. This decomposition is derived from a set of axioms that ensure desirable behavior for the within‐ and between‐group inequality terms. The decomposition of the Gini coefficient is unique given our axioms, easy to compute, and can be interpreted geometrically.

AI 解读阅读原文 ↗BibTeX ↓