论文检索

分类响应广义线性模型的一种新表述AI 解读

Many regression models for categorical responses have been introduced, motivated by different paradigms, but it is difficult to compare them because of their different specifications. In this paper we propose a unified specification of regression models for categorical responses, based on a decomposition of the link function into an inverse continuous cumulative distribution function and a ratio of probabilities. This allows us to define a new family of reference models for…

治疗分配与终止相竞争时治疗下平均结局的直接估计AI 解读

Several authors have investigated the challenges of statistical analyses and inference in the presence of early treatment termination, including a loss of efficiency in randomized controlled trials and a connection to dynamic regimes in observational studies. Popular estimation strategies for causal estimands in dynamic regimes lend themselves to studies where treatment is assigned at a finite number of points and the extension to continuous treatment assignment is…

探索效应修饰的观察性研究中族错误率的强控制AI 解读

An effect modifier is a pretreatment covariate that affects the magnitude of the treatment effect or its stability. When there is effect modification, an overall test that ignores an effect modifier may be more sensitive to unmeasured bias than a test that combines results from subgroups defined by the effect modifier. If there is effect modification, one would like to identify specific subgroups for which there is evidence of effect that is insensitive to small or moderate…

共享核贝叶斯筛选AI 解读

This article concerns testing for equality of distribution between groups. We focus on screening variables with shared distributional features such as common support, modes and patterns of skewness. We propose a Bayesian testing method using kernel mixtures, which improves performance by borrowing information across the different variables and groups through shared kernels and a common probability of group differences. The inclusion of shared kernels in a finite mixture,…

识别断点回归模型中改变政策门槛的效应AI 解读

Regression discontinuity models are commonly used to nonparametrically identify and estimate a local average treatment effect (LATE).We show that the derivative of the treatment effect with respect to the running variable at the cutoff, referred to as the treatment effect derivative (TED), is nonparametrically identified, easily estimated, and has implications for testing external validity and extrapolating the estimated LATE away from the cutoff. Given a local policy…

请再次致电：校正处理效应模型中的无应答偏差AI 解读

We propose a novel selectivity correction procedure to deal with survey attrition in treatment effect models, at the crossroads of the Heckit model and the bounding approach of Lee (2009). As a substitute for the instrument needed in sample selectivity correction models, we use information on the number of prior calls made to each individual before obtaining a response to the survey. We obtain sharp bounds to the average treatment effect on the common support of responding…

医疗监管与容量竞争：来自美国透析市场的证据AI 解读

This paper studies entry and capacity decisions by dialysis providers in the United States. We estimate a structural model where providers make continuous strategic choices of capacity based on their private information about own costs and knowledge of the distribution of competitors’ private information. We evaluate the impact on the market structure and providers’ profits under counterfactual regulatory policies that increase the costs or reduce the payment per unit of…

航空业进入壁垒：AIR-21 法案的多维断点回归分析AI 解读

We investigate the success of legislation aimed at increasing competition at highly concentrated U.S. airports, mainly by forcing these airports to increase the availability of scarce facilities. We use a multidimensional regression-discontinuity approach to exploit a sharp discontinuity in the law’s implementation and identify its effects. We find that fares decrease by 13.4% (20.2%) in markets with one (both) end point(s) covered. Approximately half of the decline is…

正特征函数的非参数识别AI 解读

Important features of certain economic models may be revealed by studying positive eigenfunctions of appropriately chosen linear operators. Examples include long-run risk–return relationships in dynamic asset pricing models and components of marginal utility in external habit formation models. This paper provides identification conditions for positive eigenfunctions in nonparametric models. Identification is achieved if the operator satisfies two mild positivity conditions…

正则变动与广义加速失效时间模型的识别AI 解读

Ridder (1990, Review of Economic Studies 57, 167–182) provides an identification result for the Generalized Accelerated Failure-Time (GAFT) model. We point out that Ridder’s proof of this result is incomplete, and provide an amended proof with an additional necessary and sufficient condition that requires that a function varies regularly at 0 and ∞. We also give more readily interpretable sufficient conditions on the tails of the error distribution or the asymptotic behavior…

相依随机变量函数的极端分位数估计AI 解读

Summary We propose a new method for estimating the extreme quantiles for a function of several dependent random variables. In contrast with the conventional approach based on extreme value theory, we do not impose the condition that the tail of the underlying distribution admits an approximate parametric form, and, furthermore, our estimation makes use of the full observed data. The method proposed is semiparametric as no parametric forms are assumed on the marginal…

似乎不相关回归系统的平滑系数估计AI 解读

This paper proposes estimation and inference for the semiparametric smooth coefficient seemingly unrelated regression model. We discuss the imposition of cross-equation restrictions which are required by economic theory as well as methods for data driven bandwidth selection. A test of correct functional form for the entire system of equations is also constructed. Asymptotic and finite sample results are given. We illustrate our estimator by applying it to a cost system for…

完全信息博弈的识别AI 解读

This paper establishes sufficient conditions for point identification of the utility functions in generalized complete information game models. These models allow generalized interaction structures and generalized behavioral assumptions. The generalized interaction structures allow that the dependence of an agent’s utility function on the other agents’ actions can itself depend on characteristics of the agents, including an endogenous network of connections among the agents.…

断点未知的断点回归设计：检验与估计AI 解读

The regression discontinuity design has become a common framework among applied economists for measuring treatment effects. A key restriction of the existing literature is the assumption that the discontinuity point is known, which does not always hold in practice. This paper extends the applicability of the regression discontinuity design by allowing for an unknown discontinuity point. First, we construct a unified test statistic to check whether there are selection or…

利用排除变量识别和估计不完全信息博弈AI 解读

We show structural components in binary games with incomplete information are nonparametrically identified using variation in player-specific excluded regressors. An excluded regressor for a player i is a sufficiently varying state variable that does not affect other players’ utility and is additively separable from other components in i’s payoff. Such excluded regressors arise in various empirical contexts. Our identification method is constructive, and provides a basis for…

基于局部多项式平滑的二元分位数回归AI 解读

Manski (1975, 1985) proposed the maximum score estimator for the binary choice model under a weak conditional median restriction that converges at the rate of n−1/3 and the standardized version has a nonstandard distribution. By imposing additional smoothness conditions, Horowitz (1992) proposed a smoothed maximum score estimator that often has large finite sample biases and is quite sensitive to the choice of smoothing parameter. In this paper we propose a novel framework…

协变量可能多于观测时平均处理效应的稳健推断AI 解读

This paper concerns robust inference on average treatment effects following model selection. Under selection on observables, we construct confidence intervals using a doubly-robust estimator that are robust to model selection errors and prove their uniform validity over a large class of models that allows for multivalued treatments with heterogeneous effects and selection amongst (possibly) more covariates than observations. The semiparametric efficiency bound is attained…

样本选择模型中条件独立假设的检验AI 解读

Identification in most sample selection models depends on the independence of the regressors and the error terms conditional on the selection probability. All quantile and mean functions are parallel in these models; this implies that quantile estimators cannot reveal any—per assumption non-existing—heterogeneity. Quantile estimators are nevertheless useful for testing the conditional independence assumption because they are consistent under the null hypothesis. We propose…

Medigap 保险市场的激励与选择效应：Dirichlet 过程混合模型应用AI 解读

This paper presents an empirical study of endogenous treatment effects in the presence of heterogeneous responses. We estimate the incentive and selection effects of having prescription drug coverage on total drug expenditures using a sample from the Medicare Current Beneficiary Survey (MCBS). A Dirichlet process mixture (DPM) model is used to model the heterogeneity in treatment effects. Rather than estimating a finite mixture model with a fixed number of components, we…

含测量误差内生变量的非可分模型估计AI 解读

We study the identification and estimation of covariate-conditioned average marginal effects of endogenous regressors in nonseparable structural systems when the regressors are mismeasured. We control for the endogeneity by making use of covariates as control variables; this ensures conditional independence between the endogenous causes of interest and other unobservable drivers of the dependent variable. Moreover, we recover distributions of the underlying true causes from…

不完全信息动态离散选择博弈的估计AI 解读

We investigate the estimation of models of dynamic discrete-choice games of incomplete information, formulating the maximum-likelihood estimation exercise as a constrained optimization problem that can be solved using state-of-the-art constrained optimization solvers. Under the assumption that only one equilibrium is played in the data, our approach avoids repeatedly solving the dynamic game or finding all equilibria for each candidate vector of the structural parameters. We…

通过重随机化平衡不同重要性层级的协变量AI 解读

When conducting a randomized experiment, if an allocation yields treatment groups that differ meaningfully with respect to relevant covariates, groups should be rerandomized. The process involves specifying an explicit criterion for whether an allocation is acceptable, based on a measure of covariate balance, and rerandomizing units until an acceptable allocation is obtained. Here we illustrate how rerandomization could have improved the design of an already conducted…

远离断点的考试选拔学校效应：回归不连续识别与估计AI 解读

In regression discontinuity (RD) studies exploiting an award or admissions cutoff, causal effects are nonparametrically identified for those near the cutoff. The effect of treatment on inframarginal applicants is also of interest, but identification of such effects requires stronger assumptions than those required for identification at the cutoff. This article discusses RD identification and estimation away from the cutoff. Our identification strategy exploits the…

最优数据驱动的回归不连续图AI 解读

Exploratory data analysis plays a central role in applied statistics and econometrics. In the popular regression-discontinuity (RD) design, the use of graphical analysis has been strongly advocated because it provides both easy presentation and transparent validation of the design. RD plots are nowadays widely used in applications, despite its formal properties being unknown: these plots are typically presented employing ad hoc choices of tuning parameters, which makes these…