论文检索

对称修剪 Tobit 模型中条件对称性的简单一致检验AI 解读

We propose a “weighted and sample-size adjusted” Kolmogorov–Smirnov type statistic to test the assumption of conditional symmetry maintained in the symmetrically trimmed least-squares (STLS) approach of Powell (1986b), which is widely used to estimate censored or truncated regression models without making distributional assumptions. Our statistic is consistent and does not require any nonparametric smoothing, although we test the validity of a conditional feature. We also…

纯跳半鞅幂变差与活动指数估计的局部稳定 bootstrapAI 解读

We provide a new resampling procedure–the local stable bootstrap–that is able to mimic the dependence properties of realized power variations for pure-jump semimartingales observed at different frequencies. This allows us to propose a bootstrap estimator and inference procedure for the activity index of the underlying process, β, as well as bootstrap tests for whether it obeys a jump-diffusion or a pure-jump process, that is, of the null hypothesis H0:β=2 against the…

复发事件与失效时间的联合尺度变换模型AI 解读

Recurrent event data arise frequently in various fields such as biomedical sciences, public health, engineering, and social sciences. In many instances, the observation of the recurrent event process can be stopped by the occurrence of a correlated failure event, such as treatment failure and death. In this article, we propose a joint scale-change model for the recurrent event process and the failure time, where a shared frailty variable is used to model the association…

高维线性模型的同时推断AI 解读

This article proposes a bootstrap-assisted procedure to conduct simultaneous inference for high-dimensional sparse linear models based on the recent desparsifying Lasso estimator. Our procedure allows the dimension of the parameter vector of interest to be exponentially larger than sample size, and it automatically accounts for the dependence within the desparsifying Lasso estimator. Moreover, our simultaneous testing method can be naturally coupled with the margin screening…

基于距离协方差的独立成分分析AI 解读

This article introduces a novel statistical framework for independent component analysis (ICA) of multivariate data. We propose methodology for estimating mutually independent components, and a versatile resampling-based procedure for inference, including misspecification testing. Independent components are estimated by combining a nonparametric probability integral transformation with a generalized nonparametric whitening method based on distance covariance that…

阈值扩散模型检验AI 解读

The threshold diffusion model assumes a piecewise linear drift term and a piecewise smooth diffusion term, which constitutes a rich model for analyzing nonlinear continuous-time processes. We consider the problem of testing for threshold nonlinearity in the drift term. We do this by developing a quasi-likelihood test derived under the working assumption of a constant diffusion term, which circumvents the problem of generally unknown functional form for the diffusion term.…

高频数据推断的子抽样方法AI 解读

In this paper, we show how to estimate the asymptotic (conditional) covariance matrix, which appears in central limit theorems in high-frequency estimation of asset return volatility. We provide a recipe for the estimation of this matrix by subsampling; an approach that computes rescaled copies of the original statistic based on local stretches of high-frequency data, and then it studies the sampling variation of these. We show that our estimator is consistent both in…

非可分面板数据模型识别假设的检验AI 解读

Recent work on nonparametric identification of average partial effects (APEs) from panel data require restrictions on individual or time heterogeneity. Identifying assumptions under the “generalized first-differencing” category, such as time homogeneity (Chernozhukov et al., 2013), have testable equality restrictions on the distribution of the outcome variable. This paper proposes specification tests based on these restrictions. The bootstrap critical values for the…

乘法误差模型的设定检验AI 解读

The family of multiplicative error models is important for studying non-negative variables such as realized volatility, trading volume, and duration between consecutive financial transactions. Methods are developed for testing the parametric specification of a multiplicative error model, which consists of separate parametric models for the conditional mean and the error distribution. The same method can also be used for testing the specification of the error distribution…

多元 Copula 时间序列模型的拟合优度检验AI 解读

In recent years, stationary time series models based on copula functions became increasingly popular in econometrics to model nonlinear temporal and cross-sectional dependencies. Within these models, we consider the problem of testing the goodness-of-fit of the parametric form of the underlying copula. Our approach is based on a dependent multiplier bootstrap and it can be applied to any stationary, strongly mixing time series. The method extends recent i.i.d. results by…

EuroMInd：欧元区月度国内生产总值的密度估计AI 解读

Summary EuroMInd‐ is a density estimate of monthly gross domestic product (GDP) constructed according to a bottom‐up approach, pooling the density estimates of 11 GDP components, by output and expenditure type. The components' density estimates are obtained from a medium‐size dynamic factor model handling mixed frequencies of observation and ragged‐edged data structures. They reflect both parameter and filtering uncertainty and are obtained by implementing a bootstrap…

计算机模型校准的频率学派方法AI 解读

Summary The paper considers the computer model calibration problem and provides a general frequentist solution. Under the framework proposed, the data model is semiparametric with a non-parametric discrepancy function which accounts for any discrepancy between physical reality and the computer model. In an attempt to solve a fundamentally important (but often ignored) identifiability issue between the computer model parameters and the discrepancy function, the paper proposes…

噪声跳跃扩散与非同步交易下积分协方差估计量的自助法AI 解读

We propose a bootstrap method for estimating the distribution (and functionals of it such as the variance) of various integrated covariance matrix estimators. In particular, we first adapt the wild blocks of blocks bootstrap method suggested for the pre-averaged realized volatility estimator to a general class of estimators of integrated covolatility. We then show the first-order asymptotic validity of this method in the multivariate context with a potential presence of…

利用最大交叉相关检验高维白噪声AI 解读

SUMMARY We propose a new omnibus test for vector white noise using the maximum absolute autocorrelations and cross-correlations of the component series. Based on an approximation by the $L_\infty$-norm of a normal random vector, the critical value of the test can be evaluated by bootstrapping from a multivariate normal distribution. In contrast to the conventional white noise test, the new method is proved to be valid for testing departure from white noise that is not…

区间删失失效时间数据的病例队列研究AI 解读

The case-cohort design has been widely used as a means of cost reduction in assembling or measuring expensive covariates in large cohort studies. The existing literature on the case-cohort design is mainly focused on right-censored data. In practice, however, the failure time is often subject to interval-censoring; it is known only to fall within some random time interval. In this paper, we consider the case-cohort study design for interval-censored failure time and develop…

聚类规模悬殊时的野生自助法推断AI 解读

Summary The cluster robust variance estimator (CRVE) relies on the number of clusters being sufficiently large. Monte Carlo evidence suggests that the ‘rule of 42’ is not true for unbalanced clusters. Rejection frequencies are higher for datasets with 50 clusters proportional to US state populations than with 50 balanced clusters. Using critical values based on the wild cluster bootstrap performs much better. However, this procedure fails when a small number of clusters is…

小单位中的群体隔离测度：部分识别分析AI 解读

We consider the issue of measuring segregation in a population of small units, considering establishments in our application. Each establishment may have a different probability of hiring an individual from the minority group. We define segregation indices as inequality indices on these unobserved, random probabilities. Because these probabilities are measured with error by proportions, standard estimators are inconsistent. We model this problem as a nonparametric binomial…

矩不等式模型中部分识别参数的子向量及其他函数推断AI 解读

This paper introduces a bootstrap-based inference method for functions of the parameter vector in a moment (in)equality model. These functions are restricted to be linear for two-sided testing problems, but may be nonlinear for one-sided testing problems. In the most common case, this function selects a subvector of the parameter, such as a single component. The new inference method we propose controls asymptotic size uniformly over a large class of data distributions and…

中心优势的检验：方法与应用AI 解读

Central dominance (CD) introduced in Gollier (1995, Journal of Economic Theory) is a risk concept that differs from stochastic dominance (SD) in an important way. In particular, CD implies a deterministic comparative static of a change in decision when risk changes, but SD does not have such an implication. In this paper, we propose the first test of central dominance, which amounts to checking a functional inequality. We derive the asymptotic distribution of a lower bound…

非参数条件分位数推断的分数阶次序统计量近似AI 解读

Using and extending fractional order statistic theory, we characterize the O(n−1) coverage probability error of the previously proposed (Hutson, 1999) confidence intervals for population quantiles using L-statistics as endpoints. We derive an analytic expression for the n−1 term, which may be used to calibrate the nominal coverage level to get O(n−3/2[log(n)]3) coverage error. Asymptotic power is shown to be optimal. Using kernel smoothing, we propose a related method for…

多元 GARCH 模型的条件椭圆性检验AI 解读

Tests are proposed for the assumption that the conditional distribution of a multivariate GARCH process is elliptic. These tests are of Kolmogorov–Smirnov and Cramér–von Mises-type and make use of the common geometry underlying the characteristic function of any spherically symmetric distribution. The asymptotic null distribution of the test statistics as well as the consistency of the tests is investigated under general conditions. It is shown that both the finite sample…

强横截面相关下大规模动态面板的推断与时间断点检验AI 解读

In this paper we provide a new Central Limit Theorem for estimators of the slope papers in large dynamic panel data models (where both n and T increase without bound) in the presence of, possibly, strong cross-sectional dependence. We proceed by providing two related tests for breaks/homogeneity in the time dimension. The first test is based on the CUSUM principle; the second test is based on a Hausman–Durbin–Wu approach. Some of the key features of the tests are that they…

工具变量分位数回归的平滑估计方程AI 解读

The moment conditions or estimating equations for instrumental variables quantile regression involve the discontinuous indicator function. We instead use smoothed estimating equations (SEE), with bandwidth h . We show that the mean squared error (MSE) of the vector of the SEE is minimized for some h > 0, leading to smaller asymptotic MSE of the estimating equations and associated parameter estimators. The same MSE-optimal h also minimizes the higher-order type I error of a…

组成性支出数据的方向混合效应模型AI 解读

Compositional data are vectors of proportions defined on the unit simplex and this type of constrained data occur frequently in Government surveys. It is also possible for the compositional data to be correlated due to the clustering or grouping of the observations within small domains or areas. We propose a new class of the mixed model for compositional data based on the Kent distribution for directional data, where the random effects also have Kent distributions. One…