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利用不平等指标变化识别与估计干预的分布影响AI 解读

This paper presents estimators of distributional impacts of interventions when selection to the program is based on observable characteristics. Distributional impacts are calculated as differences in inequality measures of the marginal distributions of potential outcomes of receiving and not receiving the treatment. The estimation procedure involves a first non-parametric estimation of the propensity score. In the second step weighted versions of inequality measures are…

检测时间序列模型中具有实质意义的变化AI 解读

Summary Most of the literature on change point analysis by means of hypothesis testing considers hypotheses of the form H0:θ1=θ2 versus H1:θ1≠θ2, where θ1 and θ2 denote parameters of the process before and after a change point. The paper takes a different perspective and investigates the null hypotheses of no relevant changes, i.e. H0:‖θ1−θ2‖⩽Δ, where ‖·‖ is an appropriate norm. This formulation of the testing problem is motivated by the fact that in many applications a…

复杂抽样设计下的经验似然置信区间AI 解读

Summary We define an empirical likelihood approach which gives consistent design-based confidence intervals which can be calculated without the need of variance estimates, designeffects, resampling, joint inclusion probabilities and linearization, even when the point estimator is not linear. It can be used to construct confidence intervals for a large class of sampling designs and estimators which are solutions of estimating equations. It can be used for means, regressions…

函数系数模型的筛工具变量分位数回归估计AI 解读

In this paper we consider sieve instrumental variable quantile regression (IVQR) estimation of functional coefficient models where the coefficients of endogenous regressors are unknown functions of some exogenous covariates. We estimate the functional coefficients by the sieve-IVQR technique and establish the uniform consistency and asymptotic normality of the estimators. Based on the sieve estimates, we propose a nonparametric specification test for the constancy of the…

非参数与半参数分位数模型推断的直接方法AI 解读

We construct a generic confidence interval for a conditional quantile via the direct approach. It avoids estimating the conditional density function of the dependent variable given the covariate and is asymptotically valid for any conditional quantile, any conditional quantile estimator, and any data structure, provided that certain weak convergence of the conditional quantile process holds for the original quantile estimator. We also construct a generic confidence band for…

方程两侧均存在测量误差的非参数模型AI 解读

Measurement errors are often correlated, as in surveys where respondent’s biases or tendencies to err affect multiple reported variables. We extend Schennach (2007) to identify moments of the conditional distribution of a true Y given a true X when both are measured with error, the measurement errors in Y and X are correlated, and the true unknown model of Y given X has nonseparable model errors. After showing nonparametric identification, we provide a sieve generalized…

用分位数检验多元经济限制：斯勒茨基矩阵负半定性AI 解读

This paper is concerned with testing a core economic restriction, negative semidefiniteness of the Slutsky matrix. We consider a system of nonseparable structural equations with infinite dimensional unobservables, and employ quantile regression methods because they allow us to utilize the entire distribution of the data. Difficulties arise because the restriction involves several equations, while the quantile is a univariate concept. We establish that we may use quantiles of…

基于误差分布估计的参数混合效应模型拟合优度检验AI 解读

We address the problem of testing for a parametric function of fixed effects in mixed models. We propose a test based on the distance between two empirical error distribution functions, which are constructed from residuals calculated under the opposing hypotheses. The proposed test statistic has power against all alternatives, and its asymptotic distribution is derived. A simulation study shows that the test outperforms others in the literature. The test is applied to…

随机变量比值的分布AI 解读

Inversion formulae are derived that express the density and distribution function of a ratio of random variables in terms of the joint characteristic function of the numerator and denominator. The resulting expressions are amenable to numerical evaluation and lead to simple asymptotic expansions. The expansions reduce to known results when the denominator is almost surely positive. Their accuracy is demonstrated with numerical examples.

超高维部分线性可加分位数回归AI 解读

We consider a flexible semiparametric quantile regression model for analyzing high dimensional heterogeneous data. This model has several appealing features: (1) By considering different conditional quantiles, we may obtain a more complete picture of the conditional distribution of a response variable given high dimensional covariates. (2) The sparsity level is allowed to be different at different quantile levels. (3) The partially linear additive structure accommodates…

通过 Hilbert 空间变换开展密度函数的函数型数据分析AI 解读

Functional data that are nonnegative and have a constrained integral can be considered as samples of one-dimensional density functions. Such data are ubiquitous. Due to the inherent constraints, densities do not live in a vector space and, therefore, commonly used Hilbert space based methods of functional data analysis are not applicable. To address this problem, we introduce a transformation approach, mapping probability densities to a Hilbert space of functions through a…

效率前沿的非参数工具变量估计AI 解读

The paper investigates endogeneity issues in nonparametric frontier models. It considers a nonseparable model for a cost function C=φ(Y,U) where C and Y are the cost and the output, U is uniform in [0,1] and φ is increasing with respect to U. The cost frontier corresponds to U=0 and U can be interpreted as a normalized level of inefficiency. The endogeneity issue arises when Y is dependent of U. For identification and estimation, we use a nonparametric instrumental variables…

计数过程的广义分位数回归及其重复事件应用AI 解读

In survival analysis, quantile regression has become a useful approach to account for covariate effects on the distribution of an event time of interest. In this paper, we discuss how quantile regression can be extended to model counting processes, and thus lead to a broader regression framework for survival data. We specifically investigate the proposed modeling of counting processes for recurrent events data. We show that the new recurrent events model retains the…

分位数回归中变系数的估计与检验AI 解读

In this article, we establish a novel connection between the null hypothesis H0 on the coefficients and a rank-reducible form of the varying coefficient model in quantile regression. We use B-splines to approximate the varying coefficients in the rank-reducible model, and make use of the fact that the null hypothesis H0 implies a unidimensional structure of a transformed coefficient matrix for the B-spline basis functions. By evaluating the unidimensional structure, we…

病例对照数据二次分析中的分位数回归AI 解读

Case-control design is widely used in epidemiology and other fields to identify factors associated with a disease. Data collected from existing case-control studies can also provide a cost-effective way to investigate the association of risk factors with secondary outcomes. When the secondary outcome is a continuous random variable, most of the existing methods focus on the statistical inference on the mean of the secondary outcome. In this paper, we propose a quantile-based…

医疗支出价格弹性的删失分位数工具变量估计AI 解读

Efforts to control medical care costs depend critically on how individuals respond to prices. I estimate the price elasticity of expenditure on medical care using a censored quantile instrumental variable (CQIV) estimator. CQIV allows estimates to vary across the conditional expenditure distribution, relaxes traditional censored model assumptions, and addresses endogeneity with an instrumental variable. My instrumental variable strategy uses a family member's injury to…

异方差极端值的统计分析AI 解读

Summary We extend classical extreme value theory to non-identically distributed observations. When the tails of the distribution are proportional much of extreme value statistics remains valid. The proportionality function for the tails can be estimated non-parametrically along with the (common) extreme value index. For a positive extreme value index, joint asymptotic normality of both estimators is shown; they are asymptotically independent. We also establish asymptotic…

交易碎片化对英国股票市场质量的影响AI 解读

Summary We investigate the effects of fragmentation in equity markets on the quality of trading outcomes in a panel of FTSE stocks over the period 2008–2011. This period coincided with a great deal of turbulence in the UK equity markets, which had multiple causes that need to be controlled for. To achieve this, we use the common correlated effects estimator for large heterogeneous panels. We extend this estimator to quantile regression to analyse the whole conditional…

组层面处理的工具变量分位数回归：贸易的分布效应AI 解读

We present a methodology for estimating the distributional effects of an endogenous treatment that varies at the group level when there are group-level unobservables, a quantile extension of Hausman and Taylor, 1981. Because of the presence of group-level unobservables, standard quantile regression techniques are inconsistent in our setting even if the treatment is independent of unobservables. In contrast, our estimation technique is consistent as well as computationally…

非线性时间序列模型中条件分位数的统计推断AI 解读

This paper studies the statistical properties of a two-step conditional quantile estimator in nonlinear time series models with unspecified error distribution. The asymptotic distribution of the quasi-maximum likelihood estimators and the filtered empirical percentiles is derived. Three applications of the asymptotic result are considered. First, we construct an interval estimator of the conditional quantile without any distributional assumptions. Second, we develop a…

时间序列与金融计量经济学前沿：概览AI 解读

Two of the fastest growing frontiers in econometrics and quantitative finance are time series and financial econometrics. Significant theoretical contributions to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time series analysis. The purpose of this special issue of the journal on “Frontiers in Time Series and Financial Econometrics” is to highlight several areas of research by leading academics in which novel methods have…

长记忆随机波动模型的样本分位数分析AI 解读

This study investigates asymptotic properties of sample quantile estimates in the context of long-memory stochastic volatility models in which the latent volatility component is an exponential transformation of a linear long-memory time series. We focus on the least absolute deviation quantile estimator and show that while the underlying process is a sequence of stationary martingale differences, the estimation errors are asymptotically normal with the convergence rate which…

分类响应广义线性模型的一种新表述AI 解读

Many regression models for categorical responses have been introduced, motivated by different paradigms, but it is difficult to compare them because of their different specifications. In this paper we propose a unified specification of regression models for categorical responses, based on a decomposition of the link function into an inverse continuous cumulative distribution function and a ratio of probabilities. This allows us to define a new family of reference models for…

共享核贝叶斯筛选AI 解读

This article concerns testing for equality of distribution between groups. We focus on screening variables with shared distributional features such as common support, modes and patterns of skewness. We propose a Bayesian testing method using kernel mixtures, which improves performance by borrowing information across the different variables and groups through shared kernels and a common probability of group differences. The inclusion of shared kernels in a finite mixture,…