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一种半参数变点模型AI 解读

A semiparametric changepoint model is considered and the empirical likelihood method is applied to detect the change from a distribution to a weighted distribution in a sequence of independent random variables. The maximum likelihood changepoint estimator is shown to be consistent. The empirical likelihood ratio test statistic is proved to have the same limit null distribution as that with parametric models. A data-based test for the validity of the models is also proposed.…

函数型测量误差模型的局部有效半参数估计量AI 解读

A class of semiparametric estimators are proposed in the general setting of functional measurement error models. The estimators follow from estimating equations that are based on the semiparametric efficient score derived under a possibly incorrect distributional assumption for the unobserved ‘measured with error’ covariates. It is shown that such estimators are consistent and asymptotically normal even with misspecification and are efficient if computed under the truth. The…

协整误差序列相关时ADL与动态OLS协整估计量的比较AI 解读

This paper deals with a family of parametric, single-equation cointegration estimators that arise in the context of the autoregressive distributed lag (ADL) models. We particularly focus on a subclass of the ADL models, those that do not involve lagged values of the dependent variable, referred to as augmented static (AS) models. The general ADL and the restricted AS models give rise to the ADL and dynamic OLS (DOLS) estimators, respectively. The relative performance of…

变换模型中的响应误差及其在收入方程估计中的应用AI 解读

This paper considers estimation of a transformation model in which the transformed dependent variable is subject to classical measurement error. We consider cases in which the transformation function is known and unspecified. In special cases (e.g. log and square-root transformations), least-squares or non-linear least-squares estimators are applicable. A flexible approximation approach (based on Taylor expansion) is proposed for a parametrized transformation function (like…

摘要暂缺

空气污染与死亡率的改进半参数时间序列模型AI 解读

In 2002, methodological issues around time series analyses of air pollution and health attracted the attention of the scientific community, policy makers, the press, and the diverse stakeholders concerned with air pollution. As the U. S. Environmental Protection Agency (EPA) was finalizing its most recent review of epidemiologic evidence on particulate matter air pollution (PM), statisticians and epidemiologists found that the S–PLUS implementation of generalized additive…

参数回归中缺失协变量的非参数与半参数模型AI 解读

Robustness of covariate modeling for the missing-covariate problem in parametric regression is studied under the missing-at-random assumption. For a simple missing-covariate pattern, nonparametric covariate model is proposed and is shown to yield a consistent and semiparametrically efficient estimator for the regression parameter. Total robustness is achieved in this situation. For more general missingcovariate patterns, a novel semiparametric modeling approach is proposed…

自建模变形函数AI 解读

Summary The paper introduces a semiparametric model for functional data. The warping functions are assumed to be linear combinations of q common components, which are estimated from the data (hence the name ‘self-modelling’). Even small values of q provide remarkable model flexibility, comparable with nonparametric methods. At the same time, this approach avoids overfitting because the common components are estimated combining data across individuals. As a convenient…

半参数密度估计中的信息合并AI 解读

Summary The density ratio model specifies that the likelihood ratio of m−1 probability density functions with respect to the mth is of known parametric form without reference to any parametric model. We study the semiparametric inference problem that is related to the density ratio model by appealing to the methodology of empirical likelihood. The combined data from all the samples leads to more efficient kernel density estimators for the unknown distributions. We adopt…

随机前沿模型的半参数贝叶斯推断AI 解读

In this paper we propose a semiparametric Bayesian framework for the analysis of stochastic frontiers and efficiency measurement. The distribution of inefficiencies is modelled nonparametrically through a Dirichlet process prior. We suggest prior distributions and implement a Bayesian analysis through an efficient Markov chain Monte Carlo sampler, which allows us to deal with practically relevant sample sizes. We also allow for the efficiency distribution to vary with firm…

基于矩限制的有效半参数估计AI 解读

Conditional moment restrictions can be combined through GMM estimation to construct more efficient semiparametric estimators. This paper is about attainable efficiency for such estimators. We define and use a moment tangent set, the directions of departure from the truth allowed by the moments, to characterize when the semiparametric efficiency bound can be attained. The efficiency condition is that the moment tangent set equals the model tangent set. We apply these results…

面板二元变量与充分性：推广条件 LogitAI 解读

This paper extends the conditional logit approach (Rasch, Andersen, Chamberlain) used in panel data models of binary variables with correlated fixed effects and strictly exogenous regressors. In a two-period two-state model, necessary and sufficient conditions on the joint distribution function of the individual-and-period specific shocks are given such that the sum of individual binary variables across time is a sufficient statistic for the individual effect. By extending a…

协整关系的一致检验AI 解读

In this paper we investigate methods for testing the existence of a cointegration relationship among the components of a nonstationary fractionally integrated (NFI) vector time series. Our framework generalizes previous studies restricted to unit root integrated processes and permits simultaneous analysis of spurious and cointegrated NFI vectors. We propose a modified F-statistic, based on a particular studentization, which converges weakly under both hypotheses, despite the…

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半变系数模型的有效估计AI 解读

Motivated by two practical problems, we propose a new procedure for estimating a semivarying‐coefficient model. Asymptotic properties are established which show that the bias of the parameter estimator is of order h3 when a symmetric kernel is used, where h is the bandwidth, and the variance is of order n−1 and efficient in the semiparametric sense. Undersmoothing is unnecessary for the root‐n consistency of the estimators. Therefore, commonly used bandwidth selection…

纵向数据半参数建模的新估计与模型选择程序AI 解读

Semiparametric regression models are very useful for longitudinal data analysis. The complexity of semiparametric models and the structure of longitudinal data pose new challenges to parametric inferences and model selection that frequently arise from longitudinal data analysis. In this article, two new approaches are proposed for estimating the regression coefficients in a semiparametric model. The asymptotic normality of the resulting estimators is established. An…

多变量极值的条件方法（附讨论）AI 解读

Summary Multivariate extreme value theory and methods concern the characterization, estimation and extrapolation of the joint tail of the distribution of a d-dimensional random variable. Existing approaches are based on limiting arguments in which all components of the variable become large at the same rate. This limit approach is inappropriate when the extreme values of all the variables are unlikely to occur together or when interest is in regions of the support of the…

利用多协变量调整依赖删失的边际生存函数估计AI 解读

One goal in survival analysis of right-censored data is to estimate the marginal survival function in the presence of dependent censoring. When many auxiliary covariates are sufficient to explain the dependent censoring, estimation based on either a semiparametric model or a nonparametric model of the conditional survival function can be problematic due to the high dimensionality of the auxiliary information. In this paper, we use two working models to condense these…

单变量比例风险脆弱性回归模型的稳健推断AI 解读

We consider a class of semiparametric regression models which are one-parameter extensions of the Cox [J. Roy. Statist. Soc. Ser. B 34 (1972) 187–220] model for right-censored univariate failure times. These models assume that the hazard given the covariates and a random frailty unique to each individual has the proportional hazards form multiplied by the frailty. The frailty is assumed to have mean 1 within a known one-parameter family of distributions. Inference is based…

An asymptotically efficient likelihood-based semiparametric estimator is derived for the censored regression (tobit) model, based on a new approach for estimating the density function of the residuals in a partially observed regression. Smoothing the self-consistency equation for the nonparametric maximum likelihood estimator of the distribution of the residuals yields an integral equation, which in some cases can be solved explicitly. The resulting estimated density is…

半参数二元响应模型中的内生性AI 解读

This paper develops and implements semiparametric methods for estimating binary response (binary choice) models with continuous endogenous regressors. It extends existing results on semiparametric estimation in single-index binary response models to the case of endogenous regressors. It develops a control function approach to account for endogeneity in triangular and fully simultaneous binary response models. The proposed estimation method is applied to estimate the income…

二元响应模型中福利评价的半参数方法AI 解读

Applied welfare analysis is commonly based on mean or median benefit estimates. However, the whole conditional distribution of benefits is often of interest for policy makers. This article compares the distributional information recovered by competing semiparametric methods. Results obtained using a valuation study for the improvement of water resources in Brazil suggest that the semiparametric approaches are in line with each other, capturing a rich heterogeneity structure…

利用含分类错误的有序响应模型分析移民口语熟练度AI 解读

We develop parametric models that incorporate misclassification error in an ordered response model and compare them with a semiparametric model that nests the parametric models. We apply these estimators to the analysis of English-speaking fluency of immigrants in the United Kingdom, focusing on Lazear's theory that due to learning or self-selection, there is a negative relation between speaking fluency and the ethnic minority concentration in the region. Specification tests…

德国企业相关服务业公司的绩效表现AI 解读

We analyze the performance of firms from the German business-related service sector for 1994–2000. Performance is measured by ordinal assessment of changes in total sales. We estimate first-order Markov chain models using extensions of the multinomial logit model: a linear index model with alternative specifications of heterogeneity and a semiparametric model. The preferred specification involves heterogeneity connected to the firm and the type of transition. Our findings…