日期精度：到日 888 篇 · 到月 971 篇 · 到年 66 篇 · 未提供 1 篇
变换模型的成对差分秩估计
coefficient vector in a transformation model. These estimators, like other existing rank estimators, require no subjective bandwidth choice. Monte Carlo simulations, numerical asymptotic efficiency comparisons, and two empirical applications suggest that the proposed estimators perform well in comparison with existing semiparametric estimators.
风险溢价的形状
We examine the relationship between the risk premium on the Center for Research on Security Prices (CRSP) value-weighted index total return and its conditional variance. We propose a new semiparametric model in which the conditional variance process is parametric and the conditional mean is an arbitrary function of the conditional variance. For monthly CRSP value-weighted excess returns, the relationship between the two moments that we uncover is nonlinear and nonmonotonic.
新近两阶段样本选择方法及其在性别工资差距中的应用
Recently developed two-stage estimation methods of sample selection models are used, in the context of data from the 1989 Labor Market Activity Survey, to examine labor supply decisions and wage outcomes for employed men and women. Recent hypothesis test procedures are used to test for no sample selection and to test for a parametric against a semiparametric selection-correction procedure. We conclude that selection is indeed an issue for the sample at hand and that the…
基于半参数模型的判别分析
We consider a semiparametric generalisation of normal‐theory discriminant analysis. The semiparametric model assumes that, after unspecified univariate monotone transformations, the class distributions are multivariate normal. We introduce an estimation procedure based on the distribution quantiles, in which the parameters of the semiparametric model are estimated directly without estimating the nonparametric transformations. The procedure is computationally fast and the…
加速失效时间模型的秩推断
A broad class of rank‐based monotone estimating functions is developed for the semiparametric accelerated failure time model with censored observations. The corresponding estimators can be obtained via linear programming, and are shown to be consistent and asymptotically normal. The limiting covariance matrices can be estimated by a resampling technique, which does not involve nonparametric density estimation or numerical derivatives. The new estimators represent consistent…
删失数据的非参数协方差分析
The fully nonparametric model for nonlinear analysis of covariance, proposed in Akritas et al. (2000), is considered in the context of censored observations. Under this model, the distributions for each factor level combination and covariate value are not restricted to comply to any parametric or semiparametric model. The data can be continuous or ordinal categorical. The possibility of different shapes of covariate effect in different factor level combinations is also…
受试者工作特征曲线下面积的半参数回归
Medical advances continue to provide new and potentially better means for detecting disease. Such is true in cancer, for example, where biomarkers are sought for early detection and where improvements in imaging methods may pick up the initial functional and molecular changes associated with cancer development. In other binary classification tasks, computational algorithms such as neural networks, support vector machines, and evolutionary algorithms have been applied to…
丹尼斯·萨根：若干历史视角
I attempt to present Denis Sargan's work in some kind of historical perspective, in two ways. First, I discuss some previous members of the Tooke Chair of Economic Science and Statistics, which was founded in 1859 and which Sargan held. Second, I discuss one of his articles, “Asymptotic Theory and Large Models,” in relation to modern preoccupations with semiparametric econometrics.This research was supported by a Leverhulme Trust Personal Research Professorship and ESRC…
具有平滑随机效应的函数型准似然回归模型
Summary We propose a class of semiparametric functional regression models to describe the influence of vector-valued covariates on a sample of response curves. Each observed curve is viewed as the realization of a random process, composed of an overall mean function and random components. The finite dimensional covariates influence the random components of the eigenfunction expansion through single-index models that include unknown smooth link and variance functions. The…
长记忆参数的高阶核半参数 M 估计
Econometric interest in the possibility of long memory has developed as a flexible alternative to, or compromise between, the usual short memory or unit root prescriptions, for example in the context of modelling cointegrating or other relationships and in describing the dependence structure of nonlinear functions of financial returns. Semiparametric methods of estimating the memory parameter can avoid bias incurred by misspecification of the short memory component. We…
半参数弱工具变量回归及其风险—收益权衡应用
We extend the local-to-zero analysis of models with weak instruments to models with estimated instruments and regressors and with higher-order dependence between instruments and disturbances. This framework is applicable to linear models with expectation variables that are estimated nonparametrically, such as the risk-return tradeoff in finance and the effect of inflation uncertainty on real economic activity. Our simulation evidence suggests that Lagrange multiplier…
自回归模型随机系数的有效检测
The problem of detecting randomness in the coefficients of an AR(p) model, that is, the problem of testing ordinary AR(p) dependence against the alternative of a random coefficient autoregressive [RCAR(p)] model is considered. A nonstandard LAN property is established for RCAR(p) models in the vicinity of AR(p) ones. Two main problems arise in this context. The first problem is related to the statistical model itself: Gaussian assumptions are highly unrealistic in a…
条件资产定价模型的有效估计
parameters of multivariate generalized autoregressive conditional heteroscedasticity-in-mean models when the disturbances have a conditional distribution assumed to be elliptically symmetric but otherwise unrestricted. Under high-level assumptions, the resulting estimator achieves the asymptotic semiparametric efficiency bound. The elliptical symmetry assumption allows us to avert the curse of dimensionality problem that would otherwise arise in estimating the unknown error…
半参数家庭等价尺度的有效估计：来自南非的证据
base-independent equivalence scales. The partial linear index specification permits simultaneous estimation across multiple household types and multiple goods and also the incorporation of continuous and discrete household attributes. Furthermore, asymptotic properties of estimated equivalence scales and tests of base independence are readily obtained. The efficiency gains from the proposed models and estimators are particularly helpful for developing country data where…
考虑个体内相关性的边际非参数核回归
There has been substantial recent interest in non‐ and semiparametric methods for longitudinal or clustered data with dependence within clusters. It has been shown rather inexplicably that, when standard kernel smoothing methods are used in a natural way, higher efficiency is obtained by assuming independence than by using the true correlation structure. It is shown here that this result is a natural consequence of how standard kernel methods incorporate the within‐subject…
狄利克雷过程混合模型的边际似然与贝叶斯因子
We present a method for comparing semiparametric Bayesian models, constructed under the Dirichlet process mixture (DPM) framework, with alternative semiparameteric or parameteric Bayesian models. A distinctive feature of the method is that it can be applied to semiparametric models containing covariates and hierarchical prior structures, and is apparently the first method of its kind. Formally, the method is based on the marginal likelihood estimation approach of Chib (1995)…
两阶段抽样回归问题的伪得分估计量
Two-phase stratified sampling designs yield efficient estimates of population parameters in regression models while minimizing the costs of data collection. In measurement error problems, for example, error-free covariates are ascertained only for units selected in a validation sample. Estimators proposed heretofore for such designs require all units to have positive probability of being selected. We describe a new semiparametric estimator that relaxes this assumption and…
单调缺失纵向数据分析中的模式混合模型与选择模型
Summary We examine three pattern–mixture models for making inference about parameters of the distribution of an outcome of interest Y that is to be measured at the end of a longitudinal study when this outcome is missing in some subjects. We show that these pattern–mixture models also have an interpretation as selection models. Because these models make unverifiable assumptions, we recommend that inference about the distribution of Y be repeated under a range of plausible…
部分线性分位数回归模型的有效半参数估计
This paper is concerned with estimating a conditional quantile function that is assumed to be partially linear. The paper develops a simple estimator of the parametric component of the conditional quantile. The semiparametric efficiency bound for the parametric component is derived, and two types of efficient estimators are considered. Asymptotic properties of the proposed estimators are established under regularity conditions. Some Monte Carlo experiments indicate that the…
具有多重均衡的不完全联立离散响应模型
A bivariate simultaneous discrete response model which is a stochastic representation of equilibria in a two-person discrete game is studied. The presence of multiple equilibria in the underlying discrete game maps into a region for the exogenous variables where the model predicts a nonunique outcome. This is an example of an incomplete econometric structure. Economists using this model have made simplifying assumptions to avoid multiplicity. I make a distinction between…
第一价格拍卖最优保留价的半参数估计
generally expressed as a functional of the latent distribution of private signals, which is by nature unobserved. This feature has limited the implementation of the optimal reserve price in practice. In this article, we consider first-price auctions within the general affiliated private values paradigm. We show that the seller's expected profit can be written as a functional of the observed bid distribution. We propose a semiparametric extremum estimator for estimating…