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预防性动机与家庭投资组合决策AI 解读

Abstract This paper studies the empirical relevance of precautionary and other motives for household portfolio behaviour using recent panel data from the Netherlands. Dutch households' portfolios exhibit low degrees of risk taking and diversification. It is possible that this is the outcome of a rational, precautionary response to unavoidable exposure to background risk (stemming from the labour market or health conditions, etc.). We consider as alternative explanations…

关于部分经验似然的一则说明AI 解读

A partial profile empirical likelihood for a semiparametric mixture model (Zou et al., 2002) is shown to originate in a conditional likelihood involving additional nuisance parameters. The partial likelihood is the conditional likelihood with the nuisance parameters replaced by their estimators from the full likelihood. The conditional likelihood suggests alternative estimators. We demonstrate that the partial likelihood estimator is more efficient than an estimator for…

具有潜在治疗生效滞后时间的加性风险模型AI 解读

In many clinical trials for evaluating treatment efficacy, it is believed that there may exist latent treatment effectiveness lag times after which medical treatment procedure or chemical compound would be in full effect. In this paper, semiparametric regression models are proposed and studied for estimating the treatment effect accounting for such latent lag times. The new models take advantage of the invariant property of the additive hazards model in marginalising over an…

协变量缺失的匹配病例对照研究中的半参数推断AI 解读

We consider the problem of matched studies with a binary outcome that are analysed using conditional logistic regression, and for which data on some covariates are missing for some study participants. Methods for this problem involve either modelling the distribution of missing covariates or modelling the probability of data being missing. For this second approach, the previously proposed method did not make use of data for those persons with missing covariate data except in…

病态逆问题中基于坐标的类经验似然估计AI 解读

In the context of a semiparametric regression model with underlying probability distribution unspecified, an extremum estimator formulation is proposed that makes use of empirical likelihood and information theoretic estimation and inference concepts to mitigate the problem of an ill-conditioned design matrix. A squared error loss measure is used to assess estimator performance in finite samples. In large samples, the estimator can be designed to be consistent and…

半参数线性混合模型的独立同分布蒙特卡洛算法AI 解读

Hybrid versions of independent and identically distributed weighted Chinese restaurant (WCR) algorithms are developed for inference in semiparametric linear mixed models under minimal assumptions for the random-effects distributions. The WCR method of working with the posterior partition structure leads to Rao–Blackwell estimates for higher-order moments of random effects, such as skewness and kurtosis, and can be used to estimate densities for random effects. A key feature…

评价疾病生物标志物的半参数ROC分析AI 解读

The receiver operating characteristic (ROC) curve is a popular method for characterizing the accuracy of diagnostic tests when test results are not binary. Various methodologies for estimating and comparing ROC curves have been developed. One approach, due to Pepe, uses a parametric regression model ROCx(u) = g(h0(u) + θ'0x) with the baseline function h0(u) specified up to a finite-dimensional parameter. In this article we extend the regression models by allowing arbitrary…

品牌选择行为的半参数估计AI 解读

In the marketing literature there does not seem to be a widely accepted answer to the question of whether, when purchasing brands in a given product category, consumers react differently to a reduction in price and an increase in the deal discount. Previous studies that have attempted to address this issue have assumed that prices and deals have a linear effect on a brand's indirect utility. In this article, we estimate the utility of price and discount nonparametrically.…

季节性非线性自回归模型的非参数与半参数识别AI 解读

Non- or semiparametric estimation and lag selection methods are proposed for three seasonal nonlinear autoregressive models of varying seasonal flexibility. All procedures are based on either local constant or local linear estimation. For the semiparametric models, after preliminary estimation of the seasonal parameters, the function estimation and lag selection are the same as nonparametric estimation and lag selection for standard models. A Monte Carlo study demonstrates…

椭圆对称下资本资产定价模型的有效检验：半参数方法AI 解读

Abstract We develop new tests of the capital asset pricing model that take account of and are valid under the assumption that the distribution generating returns is elliptically symmetric; this assumption is necessary and sufficient for the validity of the CAPM. Our test is based on semiparametric efficient estimation procedures for a seemingly unrelated regression model where the multivariate error density is elliptically symmetric, but otherwise unrestricted. The…

迁移与教育回报：多市场 Roy 模型的检验AI 解读

Self-selected migration presents one potential explanation for why observed returns to a college education in local labor markets vary widely even though U.S. workers are highly mobile.To assess the impact of self-selection on estimated returns, this paper first develops a Roy model of mobility and earnings where workers choose in which of the 50 states (plus the District of Columbia) to live and work.Available estimation methods are either infeasible for a selection model…

Self–selected migration presents one potential explanation for why observed returns to a college education in local labor markets vary widely even though U.S. workers are highly mobile. To assess the impact of self–selection on estimated returns, this paper first develops a Roy model of mobility and earnings where workers choose in which of the 50 states (plus the District of Columbia) to live and work. Available estimation methods are either infeasible for a selection model…

参数位于边界时的广义矩估计AI 解读

This article establishes the asymptotic distributions of generalized method of moments (GMM) estimators when the true parameter lies on the boundary of the parameter space. The conditions allow the estimator objective function to be nonsmooth and to depend on preliminary estimators. The boundary of the parameter space may be curved and/or kinked. The article discusses three examples: (1) instrumental variables (IV) estimation of a regression model with nonlinear equality…

变换模型的秩估计量AI 解读

We establish [square root] n -consistency and asymptotic normality of Han's (1987a, Journal of Econometrics 35, 191–209) estimator of the parameters characterizing the transformation function in a semiparametric transformation model. We verify a Vapnik–Cervonenkis (VC) condition for the parameterizations of Box and Cox (1964, Journal of the Royal Statistical Society, Series B 34, 187–200) and Bickel and Doksum (1981, Journal of the American Statistical Association 76,…

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删失数据变换模型的半参数分析AI 解读

A unified estimation procedure is proposed for the analysis of censored data using linear transformation models, which include the proportional hazards model and the proportional odds model as special cases. This procedure is easily implemented numerically and its validity does not rely on the assumption of independence between the covariates and the censoring variable. The estimator is the same as the Cox partial likelihood estimator in the case of the proportional hazards…

现状数据下加性风险回归的有效估计AI 解读

Current status data arise when the exact timing of an event is unobserved, and it is only known at a given point in time whether or not the event has occurred. Recently Lin et al. (1998) studied the additive semiparametric hazards model for current status data. They showed that the analysis of current status data under the additive hazards model reduces to ordinary Cox regression under the assumption that a proportional hazards model may be used to describe the monitoring…

依赖结构未指定的纵向数据半参数模型估计AI 解读

This paper considers an extension of M‐estimators in semiparametric models for independent observations to the case of longitudinal data. We approximate the nonparametric function by a regression spline, and any M‐estimation algorithm for the usual linear models can then be used to obtain consistent estimators of the model and valid large‐sample inferences about the regression parameters without any specification of the error distribution and the covariance structure.…

降维空间的自适应估计AI 解读

Summary Searching for an effective dimension reduction space is an important problem in regression, especially for high dimensional data. We propose an adaptive approach based on semiparametric models, which we call the (conditional) minimum average variance estimation (MAVE) method, within quite a general setting. The MAVE method has the following advantages. Most existing methods must undersmooth the nonparametric link function estimator to achieve a faster rate of…

半参数混合模型的影响诊断与异常值检验AI 解读

Summary Semiparametric mixed models are useful in biometric and econometric applications, especially for longitudinal data. Maximum penalized likelihood estimators (MPLEs) have been shown to work well by Zhang and co-workers for both linear coefficients and nonparametric functions. This paper considers the role of influence diagnostics in the MPLE by extending the case deletion and subject deletion analysis of linear models to accommodate the inclusion of a nonparametric…

极大似然估计中协方差矩阵估计量的效率AI 解读

When econometric models are estimated by maximum likelihood, the conditional information matrix variance estimator is usually avoided in choosing a method for estimating the variance of the parameter estimate. However, the conditional information matrix estimator attains the semiparametric efficiency bound for the variance estimation problem. Unfortunately, for even moderately complex models, the integral involved in computation of the conditional information matrix…

半参数平滑系数模型AI 解读

In this article, we propose a semiparametric smooth coefficient model as a useful yet flexible specification for studying a general regression relationship with varying coefficients. The article proposes a local least squares method with a kernel weight function to estimate the smooth coefficient function. The consistency of the estimator and its asymptotic normality are established. A simple statistic for testing a parametric model versus the semiparametric smooth…

局部多重插补AI 解读

Dealing with missing data via parametric multiple imputation methods usually implies stating several strong assumptions both about the distribution of the data and about underlying regression relationships. If such parametric assumptions do not hold, the multiply imputed data are not appropriate and might produce inconsistent estimators and thus misleading results. In this paper, a fully nonparametric and a semiparametric imputation method are studied, both based on local…