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信息性先验的贝叶斯影响评估：哥伦比亚管理与出口改善项目AI 解读

Policymakers often test expensive new programs on relatively small samples. Formally incorporating informative Bayesian priors into impact evaluation offers the promise to learn more from these experiments. We evaluate a Colombian program for 200 firms which aimed to increase exporting. Priors were elicited from academics, policymakers, and firms. Contrary to these priors, frequentist estimation cannot reject null effects in 2019, and finds some negative impacts in 2020. For…

多臂老虎机实验中的风险与最优策略AI 解读

We provide a decision‐theoretic analysis of bandit experiments under local asymptotics. Working within the framework of diffusion processes, we define suitable notions of asymptotic Bayes and minimax risk for these experiments. For normally distributed rewards, the minimal Bayes risk can be characterized as the solution to a second‐order partial differential equation (PDE). Using a limit of experiments approach, we show that this PDE characterization also holds…

平均处理效应的双重稳健贝叶斯推断AI 解读

We propose a double robust Bayesian inference procedure on the average treatment effect (ATE) under unconfoundedness. For our new Bayesian approach, we first adjust the prior distributions of the conditional mean functions, and then correct the posterior distribution of the resulting ATE. Both adjustments make use of pilot estimators motivated by the semiparametric influence function for ATE estimation. We prove asymptotic equivalence of our Bayesian procedure and efficient…

脉冲响应的均匀先验AI 解读

There has been a call for caution regarding the standard procedure for Bayesian inference in set‐identified structural vector autoregressions on the grounds that the common practice of using a uniform prior over the set of orthogonal matrices induces a non‐uniform prior for individual impulse responses or other quantities of interest. This paper challenges this call by formally showing that when the focus is on joint inference, the uniform prior over the set of orthogonal…

有限样本下动态离散博弈的同质性检验AI 解读

The literature on dynamic discrete games often assumes that the conditional choice probabilities and the state transition probabilities are homogeneous across markets and over time. We refer to this as the “homogeneity assumption” in dynamic discrete games. This assumption enables empirical studies to estimate the game's structural parameters by pooling data from multiple markets and from many time periods. In this paper, we propose a hypothesis test to evaluate whether the…

稀有灾难下的学习AI 解读

Financial crises appear to have long‐lasting effects, even after the crisis itself has passed. This paper offers a simple explanation based on Bayesian learning from rare events. Agents face a latent and time‐varying probability of economic disaster. When a disaster occurs, learning results in greater effects on asset prices because agents update their probability of future disasters. Moreover, agents' belief that the disaster risk is high can rationally persist for years,…

使用影子利率 VAR 进行预测AI 解读

Vector autoregressions (VARs) are popular for forecasting, but ill‐suited to handle occasionally binding constraints, like the effective lower bound on nominal interest rates. We examine reduced‐form “shadow rate VARs” that model interest rates as censored observations of a latent shadow rate process and develop an efficient Bayesian estimation algorithm that accommodates large models. When compared to a standard VAR, our better‐performing shadow rate VARs generate superior…

金融危机宏观模型的估计：内生状态切换方法AI 解读

We develop a new model of cycles and crises in emerging markets, featuring an occasionally binding borrowing constraint and stochastic volatility, and estimate it with quarterly data for Mexico since 1981. We propose an endogenous regime‐switching formulation of the occasionally binding borrowing constraint, develop a general perturbation method to solve the model, and estimate it using Bayesian methods. We find that the model fits the Mexican data well without…

偏斜 Bernstein–von Mises 定理与偏斜模态近似AI 解读

Gaussian deterministic approximations are routinely employed in Bayesian statistics to ease inference when the target posterior is intractable. Although these approximations are justified, in asymptotic regimes, by Bernstein-von Mises type results, in practice the expected Gaussian behavior might poorly represent the actual shape of the target posterior, thus affecting approximation accuracy. Motivated by these considerations, we derive an improved class of closed-form and…

基于球极投影的马尔可夫链蒙特卡洛AI 解读

High-dimensional distributions, especially those with heavy tails, are notoriously difficult for off-the-shelf MCMC samplers: the combination of unbounded state spaces, diminishing gradient information, and local moves results in empirically observed “stickiness” and poor theoretical mixing properties—lack of geometric ergodicity. In this paper, we introduce a new class of MCMC samplers that map the original high-dimensional problem in Euclidean space onto a sphere and…

Wenkai Xu 对《安全检验》的讨论AI 解读

The authors propose the framework of e-value testing by investigating the grow-rate-optimal (GRO) constructions of e-variables, that incorporate a comprehensive range of testing scenarios for simple alternative, as well as their composite counterparts. The authors illustrate the versatility of e-value tests via three interpretations, drawing connections to (1) game-theoretical viewpoint, (2) conservative p-values, and (3) Bayes Factors; and devise the determination and…

Pace 与 Salvan 对《安全检验》的讨论贡献AI 解读

We wish to congratulate the authors on their important paper. In this contribution, we will focus on parametric models, where e-values provide a welcome new perspective on likelihood ratios and Bayes factors, as well as a useful addition to the discussion about the foundational concept of statistical evidence. The guarantees sought for in safe testing are frequentist, but prior information may be injected in Bayesian terms, establishing an alliance between traditionally…

田茂再、余克明与王江峰对《安全检验》的讨论AI 解读

We want to congratulate the authors on the publication of ‘Safe Testing’ on JRSS-B. It deepens our understanding of the statistical hypothesis test that is one particular method of statistical inference used to decide whether the data sufficiently support a particular hypothesis. The e-variables and safe tests offer several advantages. The authors develop the theory of hypothesis testing based on the e-value that behave excellently under optional continuation and are…

Joris Mulder 对《安全检验》的讨论评论AI 解读

The potential of e-values (or e-variables) to unite different schools of statistics and allowing optional stopping/continuation in a ‘safe’ manner is a major accomplishment of the authors. The theory implies a change in focus from classical error rates to the expected evidence against the null under the respective hypotheses. Under H0⁠, it is required that the expectation of the evidence against the null, E, should not exceed 1, i.e. EH0[E]≤1⁠, as in formula (1) of ‘Safe…

Robert 与 Bon 对《安全检验》的讨论意见AI 解读

Central to our interest in Bayesian foundations and reference priors, the connection made in this paper between e-values and Bayes factors, despite the cautionary added label of an ‘Almost Bayesian Case’, could bring a formal way to define least favourable priors (Berger, 1985) in a testing environment, albeit in no clear connection with the reference priors of Bayarri and Garcia-Donato (2007). This derivation, formalized as Theorem 1, provides a reversal of the typical…

Joshua Bon与Christian P. Robert对《安全检验》的讨论AI 解读

The central proposal found in this quite original paper could prove relevant for the so-called objective Bayes approach (Berger, 1985; Robert, 2001) as it may open a way to deriving prior distributions from (frequentist) first principles. While some Bayesian schools refuse to consider the concept of testing the veracity of a null hypothesis, most do propose approaches and methodologies to address this challenge. These mainly rely on Jeffreys’ formalization via two prior…

Vladimir Vovk 对《安全检验》的讨论意见AI 解读

The main result of this paper (Theorem 1) is elegant and satisfying, but in this comment I will concentrate on one of its limitations, namely the condition infW0D(Q‖PW0)<∞⁠. (Analogous conditions are present in all generalizations given in the paper.) Even in the toy binary case with an infinite horizon, this condition is typically violated. Consider, e.g., the case of Markov alternative hypotheses Q considered in Ramdas et al. (2022): a nonIID Markov probability measure (or…

安全检验AI 解读

Abstract We develop the theory of hypothesis testing based on the e-value, a notion of evidence that, unlike the p-value, allows for effortlessly combining results from several studies in the common scenario where the decision to perform a new study may depend on previous outcomes. Tests based on e-values are safe, i.e. they preserve type-I error guarantees, under such optional continuation. We define growth rate optimality (GRO) as an analogue of power in an optional…

从局部平均处理效应到平均处理效应：贝叶斯方法AI 解读

We develop a Bayesian model that produces a posterior distribution of the marginal treatment effect (MTE) function. The method provides researchers with a principled way to extrapolate from the observed moments using flexible assumptions, thereby allowing researchers to generate plausible ranges of important and potentially policy-relevant quantities of interest. We then use the model to propose a natural decomposition of the posterior variance into “statistical…

非参数冲击贝叶斯 VAR 的快速且排序不变推断AI 解读

Summary The shocks that hit macroeconomic models such as Vector Autoregressions (VARs) have the potential to be non‐Gaussian, exhibiting asymmetries and fat tails. This consideration motivates the VAR developed in this paper that uses a Dirichlet process mixture (DPM) to model the reduced‐form shocks. However, we do not follow the obvious strategy of simply modeling the VAR errors with a DPM as this would lead to computationally infeasible Bayesian inference in larger VARs…

平滑转换向量自回归模型的易实施贝叶斯估计AI 解读

Summary We develop a tractable way of estimating the parameters ruling the nonlinearity in the popular smooth transition VAR model, and identify structural shocks using external instruments. This jointly offers an alternative to the option of identifying shocks recursively and calibrating key parameters. In an illustration, we show that monetary policy shocks generate larger effects on economic activity during economic expansions compared to economic recessions. We then…

未知流形邻域中的密度估计：贝叶斯非参数方法AI 解读

We study the Bayesian density estimation of data living in the offset of an unknown submanifold of the Euclidean space. In this perspective, we introduce a new notion of anisotropic Hölder for the underlying density and obtain posterior rates that are minimax optimal and adaptive to the regularity of the density, to the intrinsic dimension of the manifold, and to the size of the offset, provided that the latter is not too small—while still allowed to go to zero. Our Bayesian…

高维多平台临床基因组数据的功能整合贝叶斯分析AI 解读

Rapid advancements in collection and dissemination of multi-platform molecular and genomics data has resulted in enormous opportunities to aggregate such data in order to understand, prevent, and treat human diseases. While significant improvements have been made in multi-omic data integration methods to discover biological markers and mechanisms underlying both prognosis and treatment, the precise cellular functions governing these complex mechanisms still need detailed and…

无向高斯图模型的贝叶斯结构学习：文献综述与经验比较AI 解读

Gaussian graphical models provide a powerful framework to reveal the conditional dependency structure between multivariate variables. The process of uncovering the conditional dependency network is known as structure learning. Bayesian methods can measure the uncertainty of conditional relationships and include prior information. However, frequentist methods are often preferred due to the computational burden of the Bayesian approach. Over the last decade, Bayesian methods…