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具有过度识别约束的工具变量回归敏感性分析AI 解读

Instrumental variables regression (IV regression) is a method for making causal inferences about the effect of a treatment based on an observational study in which there are unmeasured confounding variables. The method requires one or more valid instrumental variables (IVs); a valid IV is a variable that is associated with the treatment, is independent of unmeasured confounding variables, and has no direct effect on the outcome. Often there is uncertainty about the validity…

结果依赖型随访的纵向研究AI 解读

We propose Bayesian parametric and semiparametric partially linear regression methods to analyze the outcome-dependent follow-up data when the random time of a follow-up measurement of an individual depends on the history of both observed longitudinal outcomes and previous measurement times. We begin with the investigation of the simplifying assumptions of Lipsitz, Fitzmaurice, Ibrahim, Gelber, and Lipshultz, and present a new model for analyzing such data by allowing…

不完全竞争动态模型的估计AI 解读

We describe a two-step algorithm for estimating dynamic games under the assumption that behavior is consistent with Markov perfect equilibrium. In the first step, the policy functions and the law of motion for the state variables are estimated. In the second step, the remaining structural parameters are estimated using the optimality conditions for equilibrium. The second step estimator is a simple simulated minimum distance estimator. The algorithm applies to a broad class…

无单调性非可分模型中边际效应的识别AI 解读

Nonseparable models do not impose any type of additivity between the unobserved part and the observable regressors, and are therefore ideal for many economic applications. To identify these models using the entire joint distribution of the data as summarized in regression quantiles, monotonicity in unobservables has frequently been assumed. This paper establishes that in the absence of monotonicity, the quantiles identify local average structural derivatives of nonseparable…

正态误差成分 Logit 混合模型的参数识别AI 解读

Abstract Although the basic structure of logit‐mixture models is well understood, important identification and normalization issues often get overlooked. This paper addresses issues related to the identification of parameters in logit‐mixture models containing normally distributed error components associated with alternatives or nests of alternatives ( normal error component logit mixture , or NECLM, models). NECLM models include special cases such as unrestricted, fixed…

英国男性的永久与暂时工资：1975—2001年的年份、年龄和队列效应AI 解读

Abstract We examine the mean and variance–covariance structure of log‐wages over calendar time and the life cycle of British men, hereby controlling for birth cohort effects. We attribute the strong increase in mean log‐wage during the 1980s and 1990s to a rise in mean log‐wage with the year of birth. This rise is diminishing with the year of birth, which implies lower wage inequality between cohorts with the year of birth. Wage inequality has increased during the 1980s and…

纵向数据的经验似然半参数回归分析AI 解读

A semiparametric regression model for longitudinal data is considered. The empirical likelihood method is used to estimate the regression coefficients and the baseline function, and to construct confidence regions and intervals. It is proved that the maximum empirical likelihood estimator of the regression coefficients achieves asymptotic efficiency and the estimator of the baseline function attains asymptotic normality when a bias correction is made. Two calibrated…

不可忽略非单调无应答下重复结果均值回归的估计AI 解读

We propose a new class of models for making inference about the mean of a vector of repeated outcomes when the outcome vector is incompletely observed in some study units and missingness is nonmonotone. Each model in our class is indexed by a set of unidentified selection-bias functions which quantify the residual association of the outcome at each occasion t and the probability that this outcome is missing after adjusting for variables observed prior to time t and for the…

利用单调多项式样条估计面板计数数据的均值函数AI 解读

We study nonparametric likelihood-based estimators of the mean function of counting processes with panel count data using monotone polynomial splines. The generalized Rosen algorithm, proposed by Zhang & Jamshidian (2004), is used to compute the estimators. We show that the proposed spline likelihood-based estimators are consistent and that their rate of convergence can be faster than n-super-1/3. Simulation studies with moderate samples show that the estimators have smaller…

竞争风险数据的非参数分位数推断AI 解读

A conceptually simple quantile inference procedure is proposed for cause-specific failure probabilities with competing risks data. The quantiles are defined using the cumulative incidence function, which is intuitively meaningful in the competing–risks set–up. We establish the uniform consistency and weak convergence of a nonparametric estimator of this quantile function. These results form the theoretical basis for extensions of standard one–sample and two–sample quantile…

临床试验的最优自适应随机设计AI 解读

Optimal decision-analytic designs are deterministic. Such designs are appropriately criticized in the context of clinical trials because they are subject to assignment bias. On the other hand, balanced randomized designs may assign an excessive number of patients to a treatment arm that is performing relatively poorly. We propose a compromise between these two extremes, one that achieves some of the good characteristics of both. We introduce a constrained optimal adaptive…

纵向与空间数据相关函数的非参数估计及结肠致癌实验应用AI 解读

In longitudinal and spatial studies, observations often demonstrate strong correlations that are stationary in time or distance lags, and the times or locations of these data being sampled may not be homogeneous. We propose a nonparametric estimator of the correlation function in such data, using kernel methods. We develop a pointwise asymptotic normal distribution for the proposed estimator, when the number of subjects is fixed and the number of vectors or functions within…

外资收购对就业与工资的影响：来自芬兰生产单位的证据AI 解读

This paper examines the effect of foreign acquisition on wages and employment of different skill groups using panel data on Finnish establishments for 1988-2001. Exploiting the availability of a rich set of preacquisition controls, we use various regression and propensity-score matching methods. The results indicate that foreign acquisition has a positive effect on wages. The magnitude of this effect increases with the level of schooling of the workers. The wage increase is…

国际福利比较与多变量随机占优的非参数检验AI 解读

Abstract This paper outlines a class of statistical procedures that permit testing of a broad range of multidimensional stochastic dominance hypotheses and, more generally, welfare hypotheses that rely upon multiple stochastic dominance conditions. We apply the procedures to data on income and leisure hours for individuals in Germany, the UK, and the USA. We find that no country first‐order stochastically dominates the others in both dimensions for all years of comparison.…

控制分组条件 Logit 模型的过度离散：Dirichlet–多项回归的简便应用AI 解读

In this article, we provide a random utility-based derivation of the Dirichlet-multinomial regression and propose it as a convenient alternative for dealing with overdispersed multinomial data. We show that this model is a natural extension of McFadden's conditional logit for grouped data and discuss its relationship with count models. Finally, we use a data set on patient choice of hospitals to illustrate an application of the Dirichlet-multinomial regression. Copyright…

面板数据模型的选择校正：女性工资方程的应用AI 解读

In recent years a number of panel estimators have been suggested for sample selection models, where both the selection equation and the equation of interest contain individual effects which are correlated with the explanatory variables. Not many studies exist that use these methods in practise. We present and compare alternative estimators, and apply them to a typical problem in applied econometrics: the estimation of the wage returns to experience for females. We discuss…

无需条件独立假设的倾向得分匹配：英国性别工资差距应用AI 解读

Propensity score matching is frequently used for estimating average treatment effects. Its applicability, however, is not confined to treatment evaluation. In this paper, it is shown that propensity score matching does not hinge on a selection on observables assumption and can be used to estimate not only adjusted means but also their distributions, even with non-i.i.d. sampling. Propensity score matching is used to analyze the gender wage gap among graduates in the UK. It…

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非参数匹配与位似可分函数的有效估计量AI 解读

For vectors z and w and scalar v, let r(v, z, w) be a function that can be nonparametrically estimated consistently and asymptotically normally, such as a distribution, density, or conditional mean regression function. We provide consistent, asymptotically normal nonparametric estimators for the functions G and H, where r(v, z, w)=H[vG(z), w], and some related models. This framework encompasses homothetic and homothetically separable functions, and transformed partly…

分位数回归模型的非参数工具变量估计AI 解读

We consider nonparametric estimation of a regression function that is identified by requiring a specified quantile of the regression “error” conditional on an instrumental variable to be zero. The resulting estimating equation is a nonlinear integral equation of the first kind, which generates an ill-posed inverse problem. The integral operator and distribution of the instrumental variable are unknown and must be estimated nonparametrically. We show that the estimator is…