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Thresholding Events of Extreme in Simultaneous Monitoring of Multiple Risks

多重风险同步监测中极端事件的阈值划分

This article develops a threshold system for monitoring airline performance. This threshold system divides the sample space into regions with increasing levels of risk and allows instant assessments of risk level of any observed airline performance. Of particular concern is the performance with extreme risk. In this article, a multivariate extreme value theory approach is used to establish thresholds for signaling varying levels of extremeness in the context of simultaneous…

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EXACT PROPERTIES OF THE CONDITIONAL LIKELIHOOD RATIO TEST IN AN IV REGRESSION MODEL

工具变量回归中条件似然比检验的精确性质

For a simplified structural equation/IV regression model with one right-side endogenous variable, we derive the exact conditional distribution function of Moreira's (2003) conditional likelihood ratio (CLR) test statistic. This is used to obtain the critical value function needed to implement the CLR test, and reasonably comprehensive graphical versions of this function are provided for practical use. The analogous functions are also obtained for the case of testing more…

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Local structural quantile effects in a model with a nonseparable control variable

具有非可分控制变量模型中的局部结构分位数效应

I consider a semiparametric version of the nonseparable triangular model of Chesher [Chesher, A., 2003. Identification in nonseparable models. Econometrica 71, 1405-1441]. The proposed model is linear in coefficients, where the coefficients are unknown functions of unobserved latent variables. Using a control variable idea and quantile regression methods, I propose a simple two-step estimator for the coefficients evaluated at particular values of the latent variables. Under…

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Robust Nonparametric Quantile Estimation of Efficiency and Productivity Change in U.S. Commercial Banking, 1985–2004

美国商业银行效率与生产率变化的稳健非参数分位数估计:1985—2004年

This article uses a new nonparametric, unconditional, hyperbolic order-αquantile estimator to construct a hyperbolic version of the Malmquist index. Unlike traditional nonparametric efficiency estimators, the new estimator is both robust to data outliers and has a root-n convergence rate. We use this estimator to examine changes in the efficiency and productivity of U.S. banks between 1985 and 2004. We find that larger banks experienced larger efficiency and productivity…

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Saddlepoint approximation for mixture models

混合模型的鞍点近似

Two-component mixture distributions with one component a point mass and the other a continuous density may be used as priors for Bayesian inference when sparse representation of an underlying signal is required. We show how saddlepoint approximation in such models can yield highly accurate quantiles for posterior distributions, and illustrate this numerically, using wavelet regression with point mass/Laplace and point mass/normal prior distributions.

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Limit distribution theory for maximum likelihood estimation of a log-concave density

对数凹密度最大似然估计的极限分布理论

We find limiting distributions of the nonparametric maximum likelihood estimator (MLE) of a log-concave density, i.e. a density of the form f(0) = exp varphi(0) where varphi(0) is a concave function on R. Existence, form, characterizations and uniform rates of convergence of the MLE are given by Rufibach (2006) and Dümbgen and Rufibach (2007). The characterization of the log-concave MLE in terms of distribution functions is the same (up to sign) as the characterization of…

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Quantile cointegrating regression

分位数协整回归

Quantile regression has important applications in risk management, portfolio optimization, and asset pricing. The current paper studies estimation, inference and financial applications of quantile regression with cointegrated time series. In addition, a new cointegration model with quantile-varying coefficients is proposed. In the proposed model, the value of cointegrating coefficients may be affected by the shocks and thus may vary over the innovation quantile. The proposed…

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Assessing value at risk with CARE, the Conditional Autoregressive Expectile models

使用条件自回归期望分位数模型评估风险价值

In this paper we propose a downside risk measure, the expectile-based Value at Risk (EVaR), which is more sensitive to the magnitude of extreme losses than the conventional quantile-based VaR (QVaR). The index [theta] of an EVaR is the relative cost of the expected margin shortfall and hence reflects the level of prudentiality. It is also shown that a given expectile corresponds to the quantiles with distinct tail probabilities under different distributions. Thus, an EVaR…

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Inferring Optimal Peer Assignment From Experimental Data

从实验数据推断最优同伴分配

This article studies the problem of optimally dividing individuals into peer groups to maximize social gains from heterogeneous peer effects. The specific setting analyzed here concerns efficient ways of allocating roommates in college dormitories. Using confidential data on a sample of Dartmouth College freshmen who were randomly assigned to be roommates, the article derives efficient roommate pairing rules, based on demographic and academic background, which maximize…

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Reliable inference for the Gini index

基尼系数的可靠推断

Although attention has been given to obtaining reliable standard errors for the plug-in estimator of the Gini index, all standard errors suggested until now are either complicated or quite unreliable. An approximation is derived for the estimator by which it is expressed as a sum of IID random variables. This approximation allows us to develop a reliable standard error that is simple to compute. A simple but effective bias correction is also derived. The quality of inference…

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Edgeworth expansions and normalizing transforms for inequality measures

不平等测度的 Edgeworth 展开与正态化变换

Finite sample distributions of studentized inequality measures differ substantially from their asymptotic normal distribution in terms of location and skewness. We study these aspects formally by deriving the second-order expansion of the first and third cumulant of the studentized inequality measure. We state distribution-free expressions for the bias and skewness coefficients. In the second part we improve over first-order theory by deriving Edgeworth expansions and…

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Estimating a concave distribution function from data corrupted with additive noise

从含加性噪声的数据估计凹分布函数

We consider two nonparametric procedures for estimating a concave distribution function based on data corrupted with additive noise generated by a bounded decreasing density on (0, ∞). For the maximum likelihood (ML) estimator and least squares (LS) estimator, we state qualitative properties, prove consistency and propose a computational algorithm. For the LS estimator and its derivative, we also derive the pointwise asymptotic distribution. Moreover, the rate n−2/5 achieved…

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Inference for censored quantile regression models in longitudinal studies

纵向研究中删失分位数回归模型的推断

We develop inference procedures for longitudinal data where some of the measurements are censored by fixed constants. We consider a semi-parametric quantile regression model that makes no distributional assumptions. Our research is motivated by the lack of proper inference procedures for data from biomedical studies where measurements are censored due to a fixed quantification limit. In such studies the focus is often on testing hypotheses about treatment equality. To this…

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Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality

用局部工具变量估计潜在结果分布:大学入学与工资不平等应用

This paper extends the method of local instrumental variables developed by Heckman and Vytlacil [Heckman, J., Vytlacil E., 2005. Structural equations, treatment, effects and econometric policy evaluation. Econometrica 73(3), 669-738] to the estimation of not only means, but also distributions of potential outcomes. The newly developed method is illustrated by applying it to changes in college enrollment and wage inequality using data from the National Longitudinal Survey of…

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Semiparametric binary regression models under shape constraints with an application to Indian schooling data

形状约束下的半参数二元回归及印度入学数据应用

We consider estimation of the regression function in a semiparametric binary regression model defined through an appropriate link function (with emphasis on the logistic link) using likelihood-ratio based inversion. The dichotomous response variable [Delta] is influenced by a set of covariates that can be partitioned as (X,Z) where Z (real valued) is the covariate of primary interest and X (vector valued) denotes a set of control variables. For any fixed X, the conditional…

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ON THE CONDITIONAL LIKELIHOOD RATIO TEST FOR SEVERAL PARAMETERS IN IV REGRESSION

工具变量回归中多个参数的条件似然比检验

For the problem of testing the hypothesis that all m coefficients of the right-hand-side endogenous variables in an instrumental variables (IV) regression are zero, the likelihood ratio (LR) test can, if the reduced form covariance matrix is known, be rendered similar by a conditioning argument. To exploit this fact requires knowledge of the relevant conditional cumulative distribution function (c.d.f.) of the LR statistic, but the statistic is a function of the smallest…

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Variable Selection for Partially Linear Models With Measurement Errors

带测量误差的部分线性模型变量选择

This article focuses on variable selection for partially linear models when the covariates are measured with additive errors. We propose two classes of variable selection procedures, penalized least squares and penalized quantile regression, using the nonconvex penalized principle. The first procedure corrects the bias in the loss function caused by the measurement error by applying the so-called correction-for-attenuation approach, whereas the second procedure corrects the…

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Nonparametric Quantile Estimations for Dynamic Smooth Coefficient Models

动态平滑系数模型的非参数分位数估计

In this article, quantile regression methods are suggested for a class of smooth coefficient time series models. We use both local polynomial and local constant fitting schemes to estimate the smooth coefficients in a quantile framework. We establish the asymptotic properties of both the local polynomial and local constant estimators for α-mixing time series. Also, a bandwidth selector based on the nonparametric version of the Akaike information criterion is suggested,…

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Public insurance and private savings: who is affected and by how much?

公共保险与私人储蓄:谁受影响,影响多大?

Abstract This paper employs a recently developed instrumental quantile regression method to investigate the effect of Medicaid on household savings across different wealth groups. It finds that the disincentive effect of Medicaid on household savings is heavily concentrated in the middle net‐worth households. In contrast, the effects on the bottom and top net‐worth households are quite small and insignificant. These heterogeneous incentive effects are partly explained by…

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Identification and estimation of local average derivatives in non-separable models without monotonicity

无单调性非可分模型中局部平均导数的识别与估计

In many structural economic models there are no good arguments for additive separability of the error. Recently, this motivated intensive research on non-separable structures. For instance, in equation case was considered, and it was established that in the absence of the frequently employed monotonicity assumption local average structural derivatives (LASD) are still identified. In this paper, we introduce an estimator for the LASD. The estimator we propose is based on…

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Quantile pyramids for Bayesian nonparametrics

贝叶斯非参数推断的分位数金字塔

Pólya trees fix partitions and use random probabilities in order to construct random probability measures. With quantile pyramids we instead fix probabilities and use random partitions. For nonparametric Bayesian inference we use a prior which supports piecewise linear quantile functions, based on the need to work with a finite set of partitions, yet we show that the limiting version of the prior exists. We also discuss and investigate an alternative model based on the…

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A nonparametric test for equality of distributions with mixed categorical and continuous data

混合分类与连续数据的分布相等非参数检验

In this paper we consider the problem of testing for equality of two density or two conditional density functions defined over mixed discrete and continuous variables. We smooth both the discrete and continuous variables, with the smoothing parameters chosen via least-squares cross-validation. The test statistics are shown to have (asymptotic) normal null distributions. However, we advocate the use of bootstrap methods in order to better approximate their null distribution…

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A note on cause-specific residual life

关于原因别剩余寿命的札记

In medical research, investigators often wish to characterize the distributions of remaining lifetimes. While nonparametric analyses of residual life distributions have been widely studied with independently right-censored data, residual life analysis has not been examined in the competing risks setting, with multiple, potentially dependent, failure types. We define the cause-specific residual life distribution as the residual cumulative incidence function conditionally on…

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Non-Parametric Tests for Distributional Treatment Effect for Randomly Censored Responses

随机删失结果的分布处理效应非参数检验

Summary For a binary treatment ν = 0, 1 and the corresponding ‘potential response’Y0 for the control group (ν = 0) and Y1 for the treatment group (ν = 1), one definition of no treatment effect is that Y0 and Y1 follow the same distribution given a covariate vector X. Koul and Schick have provided a non-parametric test for no distributional effect when the realized response (1−ν)Y0+νY1 is fully observed and the distribution of X is the same across the two groups. This test is…

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