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非参数删失回归分位数的全局 Bahadur 表示及其应用AI 解读

This paper is concerned with the nonparametric estimation of regression quantiles of a response variable that is randomly censored. Using results on the strong uniform convergence rate of U-processes, we derive a global Bahadur representation for a class of locally weighted polynomial estimators, which is sufficiently accurate for many further theoretical analyses including inference. Implications of our results are demonstrated through the study of the asymptotic properties…

加速失效时间竞争风险模型的非参数识别AI 解读

We provide new conditions for identification of accelerated failure time competing risks models. These include Roy models and some auction models. In our setup, unknown regression functions and the joint survivor function of latent disturbance terms are all nonparametric. We show that this model is identified given covariates that are independent of latent errors, provided that a certain rank condition is satisfied. We present a simple example in which our rank condition for…

含测量误差协变量的逆概率加权AI 解读

Inverse probability-weighted estimators are widely used in applications where data are missing due to nonresponse or censoring and in the estimation of causal effects from observational studies. Current estimators rely on ignorability assumptions for response indicators or treatment assignment and outcomes being conditional on observed covariates which are assumed to be measured without error. However, measurement error is common for the variables collected in many…

序贯治疗决策中最优动态治疗方案的稳健估计AI 解读

A dynamic treatment regime is a list of sequential decision rules for assigning treatment based on a patient's history. Q- and A-learning are two main approaches for estimating the optimal regime, i.e., that yielding the most beneficial outcome in the patient population, using data from a clinical trial or observational study. Q-learning requires postulated regression models for the outcome, while A-learning involves models for that part of the outcome regression…

概率因果性与相互依赖模式集合的检测AI 解读

Summary Interdependent effects are usually distinguished from statistical interaction by using the sufficient causes framework. This almost always involves expressing probability distributions as deterministic logic functions, where certain conditions invariably produce or prevent an outcome. Using an idea from the philosophy literature, that a cause is defined as an event which increases the probability of an outcome, a probabilistic sufficient causes framework is developed…

第一价格拍卖应采用何种进入模型？一种非参数方法AI 解读

We develop a selective entry model for first-price auctions that nests two polar models often estimated in the empirical literature on auctions, Levin and Smith (1994), and Samuelson (1985). The selective entry model features a pro-competitive selection effect. The selection effect is shown to be nonparametrically identifiable, and a nonparametric test for its presence is proposed. This test can be used to discriminate between the two polar models.

分析师覆盖的负面影响：企业创新的证据AI 解读

We examine the effects of financial analysts on the real economy in the case of innovation. Our baseline results show that firms covered by a larger number of analysts generate fewer patents and patents with lower impact. To establish causality, we use a difference-in-differences approach that relies on the variation generated by multiple exogenous shocks to analyst coverage, as well as an instrumental variable approach. Our identification strategies suggest a negative…

利用次要结局改进存在不依从的随机实验推断AI 解读

We develop new methods for analyzing randomized experiments with noncompliance and, by extension, instrumental variable settings, when the often controversial, but key, exclusion restriction assumption is violated. We show how existing large-sample bounds on intention-to-treat effects for the subpopulations of compliers, never-takers, and always-takers can be tightened by exploiting the joint distribution of the outcome of interest and a secondary outcome, for which the…

随机临床试验中依方案生存终点疗效的敏感性分析AI 解读

Assessing per-protocol treatment effcacy on a time-to-event endpoint is a common objective of randomized clinical trials. The typical analysis uses the same method employed for the intention-to-treat analysis (e.g., standard survival analysis) applied to the subgroup meeting protocol adherence criteria. However, due to potential post-randomization selection bias, this analysis may mislead about treatment efficacy. Moreover, while there is extensive literature on methods for…

通过幂变换估计极端条件分位数AI 解读

The estimation of extreme conditional quantiles is an important issue in numerous disciplines. Quantile regression (QR) provides a natural way to capture the covariate effects at different tails of the response distribution. However, without any distributional assumptions, estimation from conventional QR is often unstable at the tails, especially for heavy-tailed distributions due to data sparsity. In this article, we develop a new three-stage estimation procedure that…

含固定效应的面板删失分位数回归估计AI 解读

This article investigates estimation of censored quantile regression (QR) models with fixed effects. Standard available methods are not appropriate for estimation of a censored QR model with a large number of parameters or with covariates correlated with unobserved individual heterogeneity. Motivated by these limitations, the article proposes estimators that are obtained by applying fixed effects QR to subsets of observations selected either parametrically or…

纵向研究中时变变换模型的条件分布与秩追踪概率估计AI 解读

An objective of longitudinal analysis is to estimate the conditional distributions of an outcome variable through a regression model. The approaches based on modeling the conditional means are not appropriate for this task when the conditional distributions are skewed or cannot be approximated by a normal distribution through a known transformation. We study a class of time-varying transformation models and a two-step smoothing method for the estimation of the conditional…

纵向数据的时变加性模型AI 解读

The additive model is an effective dimension-reduction approach that also provides flexibility in modeling the relation between a response variable and key covariates. The literature is largely developed to scalar response and vector covariates. In this article, more complex data are of interest, where both the response and the covariates are functions. We propose a functional additive model together with a new backfitting algorithm to estimate the unknown regression…

消费者选择行为异质性的替代模型比较AI 解读

SUMMARY When modeling demand for differentiated products, it is vital to adequately capture consumer taste heterogeneity, But there is no clearly preferred approach. Here, we compare the performance of six alternative models. Currently, the most popular are mixed logit (MIXL), particularly the version with normal mixing (N‐MIXL), and latent class (LC), which assumes discrete consumer types. Recently, several alternative models have been developed. The 'generalized…

具有灵活相关效应的面板 Probit：潜在异质性下的技术溢出量化AI 解读

SUMMARY In this paper, we introduce a Bayesian panel probit model with two flexible latent effects: first, unobserved individual heterogeneity that is allowed to vary in the population according to a nonparametric distribution; and second, a latent serially correlated common error component. In doing so, we extend the approach developed in Albert and Chib ( Journal of the American Statistical Association 1993; 88 : 669–679; in Bayesian Biostatistics , Berry DA, Stangl DK…

无排除限制的处理效应估计：学校早餐计划应用AI 解读

SUMMARY The increase in childhood obesity has garnered the attention of many in policymaking circles. Consequently, school nutrition programs such as the School Breakfast Program (SBP) have come under scrutiny. The identification of the causal effects of such programs, however, is difficult owing to non‐random selection into the program and the lack of exclusion restrictions. Here, we propose two new estimators aimed at addressing this situation. We compare our new…

第一价格采购拍卖中进入成本的非参数估计AI 解读

SUMMARY In this paper, I investigate Samuelson's low‐price auction model with entry costs. The model's equilibrium implies that the distribution of bids is truncated at the threshold for participation. I use the model to estimate the cost of participation in Michigan highway procurement auctions. The null hypothesis of zero entry costs is rejected. Using my empirical results, I then construct an estimate of the optimal auction, which employs regular policy tools such as…

随机分块模型最大似然估计及其变分近似的渐近正态性AI 解读

Variational methods for parameter estimation are an active research area, potentially offering computationally tractable heuristics with theoretical performance bounds. We build on recent work that applies such methods to network data, and establish asymptotic normality rates for parameter estimates of stochastic blockmodel data, by either maximum likelihood or variational estimation. The result also applies to various sub-models of the stochastic blockmodel found in the…

大型稀疏网络社区检测的伪似然方法AI 解读

Many algorithms have been proposed for fitting network models with communities, but most of them do not scale well to large networks, and often fail on sparse networks. Here we propose a new fast pseudo-likelihood method for fitting the stochastic block model for networks, as well as a variant that allows for an arbitrary degree distribution by conditioning on degrees. We show that the algorithms perform well under a range of settings, including on very sparse networks, and…

稀疏有向无环图马尔可夫等价类上的可逆MCMCAI 解读

Graphical models are popular statistical tools which are used to represent dependent or causal complex systems. Statistically equivalent causal or directed graphical models are said to belong to a Markov equivalent class. It is of great interest to describe and understand the space of such classes. However, with currently known algorithms, sampling over such classes is only feasible for graphs with fewer than approximately 20 vertices. In this paper, we design reversible…

含未观测协变量的非线性动态面板模型：识别与估计AI 解读

This paper considers nonparametric identification of nonlinear dynamic models for panel data with unobserved covariates. Including such unobserved covariates may control for both the individual-specific unobserved heterogeneity and the endogeneity of the explanatory variables. Without specifying the distribution of the initial condition with the unobserved variables, we show that the models are nonparametrically identified from two periods of the dependent variable Yit and…

个人税收影响资本结构吗？来自2003年减税的证据AI 解读

Because the personal tax treatments of interest and dividend income likely affect the relative cost of debt and equity financing, a sharp change in tax treatment could affect firms' optimal leverage. This paper examines the effect of the 2003 equity income tax cut on firms' debt usage. Because this tax cut affected only individual investors, we can use a difference-in-differences method to identify the effect of personal tax on firms' leverage. Previous research has found…

金融冲击的实体效应：来自分析师覆盖外生变化的证据AI 解读

ABSTRACT We study the causal effects of analyst coverage on corporate investment and financing policies. We hypothesize that a decrease in analyst coverage increases information asymmetry and thus increases the cost of capital; as a result, firms decrease their investment and financing. We use broker closures and broker mergers to identify changes in analyst coverage that are exogenous to corporate policies. Using a difference‐in‐differences approach, we find that firms that…

失业、人力资本折旧与失业保险政策AI 解读

SUMMARY This paper presents a structural estimation of a life cycle model with unemployment risk. The model allows for human capital depreciation during unemployment. It is estimated using German and US household‐level data. The data suggest that the adverse impact of unemployment on individual productivity is important in both countries, but quantitatively more relevant in Germany. Moreover, simulations show that the combination of skill depreciation with the generous…