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线性过程非线性变换下的单位根检验AI 解读

We consider the unit root testing problem with errors being nonlinear transforms of linear processes. When the linear processes are long-range dependent, the asymptotic distributions in the unit root testing problem are shown to be functionals of Hermite processes. Functional limit theorems for nonlinear transforms of linear processes are established. The obtained results differ sharply from the classical cases where asymptotic distributions are functionals of Brownian…

微分方程解的非参数研究AI 解读

The solution of differential equations lies at the heart of many problems in structural economics. In econometrics the general nonparametric analysis of consumer welfare is historically the most obvious application, but there are also many applications in finance and other fields. This work considers the general nonparametric form for these problems and identification conditions. It derives a kernel-based estimator and shows consistency and asymptotic normality.In…

非参数自相关误差下非参数回归的更有效估计AI 解读

We define a three-step procedure for more efficient estimation of the nonparametric regression mean with nonparametric autocorrelated errors. The procedure is based upon a nonparametric prewhitening transformation of the dependent variable that has to be estimated from the data by a local polynomial technique. We establish the asymptotic distribution of our estimator under weak dependence conditions and show that it is more efficient than the conventional local polynomial…

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数值求解动态模型的似然收敛性质AI 解读

This paper studies the econometrics of computed dynamic models. Since these models generally lack a closed-form solution, their policy functions are approximated by numerical methods. Hence, the researcher can only evaluate an approximated likelihood associated with the approximated policy function rather than the exact likelihood implied by the exact policy function. What are the consequences for inference of the use of approximated likelihoods? First, we find conditions…

平均处理效应匹配估计量的大样本性质AI 解读

Matching estimators for average treatment effects are widely used in evaluation research despite the fact that their large sample properties have not been established in many cases. The absence of formal results in this area may be partly due to the fact that standard asymptotic expansions do not apply to matching estimators with a fixed number of matches because such estimators are highly nonsmooth functionals of the data. In this article we develop new methods for…

多矩条件下的广义矩估计AI 解读

This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimators when the number of moment conditions is allowed to increase with the sample size and the moment conditions may be weak. Examples in which these asymptotics are relevant include instrumental variable (IV) estimation with many (possibly weak or uninformed) instruments and some panel data models covering moderate time spans and with correspondingly large numbers of…

利用间距检验面板数据的横截面相关性AI 解读

This article provides tools for characterizing the extent of cross-section correlation in panel data when we do not know a priori how many and which series are correlated. Our tests are based on the probability integral transformation of the ordered correlations. We first split the transformed correlations by their size into two groups, then evaluate the variance ratio of the two subsamples. The problem of testing cross-section correlation thus becomes one of identifying…

空间响应面的梯度及其在城市土地价值中的应用AI 解读

For point-referenced spatial data, we often create explanatory models that introduce regression structure with error consisting of a spatial term and a white noise term. Here we consider more flexible regression structures that allow spatially varying regression coefficients. The resulting mean becomes a spatial response surface that is a linear combination of the components of the spatially varying coefficient vector. Of possible interest in this setting would be gradients…

自回归条件持续期模型的评价AI 解读

This article contains two novelties. First, a unified framework for testing and evaluating the adequacy of an estimated autoregressive conditional duration (ACD) model is presented. Second, two new classes of ACD models, the smooth transition ACD model and the time-varying ACD model, are introduced and their properties discussed. New misspecification tests for the ACD class of models are introduced. These are Lagrange multiplier and Lagrange multiplier–type tests against…

统计发布机构做对了吗？数据理性与经济周期不对称AI 解读

This article provides new evidence on the rationality of early releases of industrial production (IP) and producer price index (PPI) data. Rather than following the usual practice of examining only first available and fully revised data, we examine the entire revision history for each variable. Thus we are able to assess, for example, whether earlier releases of data are in any sense “less” rational than later releases, and when data become rational. Our findings suggest…

实际消费、收入与财富之间的关系AI 解读

Many studies relate real nondurables and services consumption to real income and wealth, with the latter measures obtained by deflating with a price index for total consumption expenditures. This procedure is appropriate only if real nondurables and services consumption is a constant multiple of aggregate real consumption outlays, which is not the case in U.S. data. We develop an alternative approach that exploits the fact that the ratio of these series has historically been…

多变量 GARCH 模型综述AI 解读

Abstract This paper surveys the most important developments in multivariate ARCH‐type modelling. It reviews the model specifications and inference methods, and identifies likely directions of future research. Copyright © 2006 John Wiley & Sons, Ltd.

随机参数的最优置信区域AI 解读

Suppose that, under a two-level hierarchical model, the distribution of the vector of random parameters is known or can be estimated well. The data are generated via a fixed, but unobservable, realisation of the vector. We derive the smallest confidence region for a specific component of this random vector under a joint Bayesian/frequentist paradigm. On average this optimal region can be much smaller than the corresponding Bayesian highest posterior density region. The new…

高维完全独立性检验AI 解读

A simple statistic is proposed for testing the complete independence of random variables having a multivariate normal distribution. The asymptotic null distribution of this statistic, as both the sample size and the number of variables go to infinity, is shown to be normal. Consequently, this test can be used when the number of variables is not small relative to the sample size and, in particular, even when the number of variables exceeds the sample size. The finite sample…

能否兼得 AIC 与 BIC 的优势？模型识别与回归估计的冲突AI 解读

A traditional approach to statistical inference is to identify the true or best model first with little or no consideration of the specific goal of inference in the model identification stage. Can the pursuit of the true model also lead to optimal regression estimation? In model selection, it is well known that BIC is consistent in selecting the true model, and AIC is minimax-rate optimal for estimating the regression function. A recent promising direction is adaptive model…

利用最小二乘估计非参数回归的残差方差AI 解读

We propose a new estimator for the error variance in a nonparametric regression model. We estimate the error variance as the intercept in a simple linear regression model with squared differences of paired observations as the dependent variable and squared distances between the paired covariates as the regressor. For the special case of a one-dimensional domain with equally spaced design points, we show that our method reaches an asymptotic optimal rate which is not achieved…

降低近似贝叶斯 bootstrap 插补方差估计偏差的一则札记AI 解读

Rubin & Schenker (1986) proposed the approximate Bayesian bootstrap, a two-stage resampling procedure, as a method of creating multiple imputations when missing data are ignorable. Kim (2002) showed that the multiple imputation variance estimator is biased for moderate sample sizes when this method is used. To reduce the bias, Kim (2002) proposed modifying the number of samples drawn at the first stage of the Bayesian bootstrap procedure. In this note, we suggest an…

比例风险回归的一致性概率与区分能力AI 解读

The concordance probability is used to evaluate the discriminatory power and the predictive accuracy of nonlinear statistical models. We derive an analytical expression for the concordance probability in the Cox proportional hazards model. The proposed estimator is a function of the regression parameters and the covariate distribution only and does not use the observed event and censoring times. For this reason it is asymptotically unbiased, unlike Harrell's c-index based on…

空间统计中两种渐近框架的协调AI 解读

Two asymptotic frameworks, increasing domain asymptotics and infill asymptotics, have been advanced for obtaining limiting distributions of maximum likelihood estimators of covariance parameters in Gaussian spatial models with or without a nugget effect. These limiting distributions are known to be different in some cases. It is therefore of interest to know, for a given finite sample, which framework is more appropriate. We consider the possibility of making this choice on…

一阶内蕴自回归与 de Wijs 过程AI 解读

We discuss intrinsic autoregressions for a first-order neighbourhood on a two-dimensional rectangular lattice and give an exact formula for the variogram that extends known results to the asymmetric case. We obtain a corresponding asymptotic expansion that is more accurate and more general than previous ones and use this to derive the de Wijs variogram under appropriate averaging, a result that can be interpreted as a two-dimensional spatial analogue of Brownian motion…

一般依赖结构下多重关联检验中非真零假设数量的下界AI 解读

We propose probabilistic lower bounds for the number of false null hypotheses when testing multiple hypotheses of association simultaneously. The bounds are valid under general and unknown dependence structures between the test statistics. The power of the proposed estimator to detect the full proportion of false null hypotheses is discussed and compared to other estimators. The proposed estimator is shown to deliver a tight probabilistic lower bound for the number of false…