论文检索

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…

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…

右删失下具有协变量阈值变点的变换模型推断AI 解读

We consider linear transformation models applied to right censored survival data with a change-point in the regression coefficient based on a covariate threshold. We establish consistency and weak convergence of the nonparametric maximum likelihood estimators. The change-point parameter is shown to be n-consistent, while the remaining parameters are shown to have the expected root-n consistency. We show that the procedure is adaptive in the sense that the nonthreshold…

含测量误差的受限因变量模型的两阶段估计AI 解读

This paper deals with censored or truncated regression models where the explanatory variables are measured with additive errors. We propose a two-stage estimation procedure that combines the instrumental variable method and the minimum distance estimation. This approach produces consistent and asymptotically normally distributed estimators for model parameters. When the predictor and instrumental variables are normally distributed, we also propose a maximum likelihood based…

摘要暂缺

摘要暂缺

摘要暂缺

摘要暂缺

摘要暂缺

摘要暂缺

摘要暂缺

摘要暂缺

摘要暂缺

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…

从不可比调查计算可比统计量：以印度贫困为例AI 解读

Applied economists are often interested in studying trends in economic indicators such as inequality or poverty; however, comparisons over time can be made impossible by changes in data collection methodology. We describe an easily implemented procedure, based on inverse probability weighting, that allows recovery of comparability of estimated parameters identified implicitly by a moment condition. The validity of the procedure requires the existence of a set of auxiliary…

分组数据的改进测量误差估计量AI 解读

Grouping models are widely used in economics but are subject to finite sample bias. I show that the standard errors-in-variables estimator is exactly equivalent to the jackknife instrumental variables estimator and use this relationship to develop an estimator which, unlike the standard errors-in-variables estimator, is unbiased in finite samples. The theoretical results are demonstrated using Monte Carlo experiments. Finally, I implement a model of intertemporal male labor…

基于系数符号预测的模型选择方法AI 解读

Summary We consider a Bayesian model selection strategy based on predicting the signs of the coefficients in a regression model, i.e. we consider identification of coefficients in a full or encompassing model for which we can confidently predict whether they are positive or negative. This is useful when our main purpose in doing model selection is interpretation, since the sign of a coefficient is often of primary importance for this task. In the case of a linear model with…

存在不依从且结局为二元变量的随机试验中治疗效应的估计AI 解读

Summary We propose a class of estimators of the treatment effect on a dichotomous outcome among the treated subjects within covariate and treatment arm strata in randomized trials with non-compliance. Recent papers by Vansteelandt and Goetghebeur, and Robins and Rotnitzky have presented consistent and asymptotically linear estimators of a causal odds ratio, which rely, beyond correct specification of a model for the causal odds ratio, on a correctly specified model for a…

广义矩估计中的信息与基于熵的矩条件选择AI 解读

In this paper, we make five contributions to the literature on information and entropy in generalized method of moments (GMM) estimation. First, we introduce the concept of the long run canonical correlations (LRCCs) between the true score vector and the moment function f (vt, θ0) and show that they provide a metric for the information contained in the population moment condition E [f (vt, θ0)] = 0. Second, we show that the entropy of the limiting distribution of the GMM…

约束统计推断中的高维小样本视角AI 解读

High-dimensional categorical data models, often with inadequately large sample sizes, crop up in many fields of application. The SARS epidemic, originating in southern China in 2002, had an identified single-stranded and positive-sense RNA virus with large genome size and moderate mutation rate. The present genomic study is used as a prime illustration for motivating appropriate statistical methodology for comprehending the genomic variation in such high-dimensional…

残疾与就业AI 解读

Measurement error in health and disability status has been widely accepted as a central problem in social science research. Long-standing debates about the prevalence of disability, the role of health in labor market outcomes, and the influence of federal disability policy on declining employment rates have all emphasized issues regarding the reliability of self-reported disability. In addition to random error, inaccuracy in survey datasets may be produced by a host of…

多元 GARCH 模型的参数化AI 解读

This paper deals with issues of structure and parametrization of VECH models proposed in Bollerslev, Engle, and Wooldridge (1988) and Baba, Engle, Kraft, and Kroner (BEKK) models. Both general models and also restricted versions such as the widely used diagonal VECH (DVECH) and factor generalized autoregressive conditional heteroskedastic (F-GARCH) models are discussed. A simple algorithm is presented that checks whether a given VECH model may be cast as a BEKK model. It is…

单位根检验的稳健贝叶斯方法AI 解读

In this paper we deal with the identification of an autoregressive model for an observed time series and the detection of a unit root in its characteristic polynomial. This is a big issue concerned with distinguishing stationary time series from time series for which differencing is required to induce stationarity. We consider a Bayesian approach, and particular attention is devoted to the problem of the sensitivity of the standard Bayesian analysis with respect to the…

摘要暂缺