论文检索

半参数 IGARCH(1,1) 模型的估计AI 解读

We propose a semiparametric IGARCH model that allows for persistence in variance but also allows for more flexible functional form. We assume that the difference of the squared process is weakly stationary. We propose an estimation strategy based on the nonparametric instrumental variable method. We establish the rate of convergence of our estimator.

非参数工具变量回归中的惩罚识别与估计AI 解读

The nonparametric estimation of a regression function from conditional moment restrictions involving instrumental variables is considered. The rate of convergence of penalized estimators is studied in the case where the regression function is not identified from the conditional moment restriction. We also study the gain of modifying the penalty in the estimation, considering derivatives in the penalty. We analyze the effect of this modification on the identification of the…

计量经济学病态逆问题的收敛率最优性AI 解读

In this paper we clarify the relations between the existing sets of regularity conditions for convergence rates of nonparametric indirect regression (NPIR) and nonparametric instrumental variables (NPIV) regression models. We establish minimax risk lower bounds in mean integrated squared error loss for the NPIR and NPIV models under two basic regularity conditions: the approximation number and the link condition. We show that both a simple projection estimator for the NPIR…

密度反卷积的谱方法AI 解读

We propose a new estimator for the density of a random variable observed with an additive measurement error. This estimator is based on the spectral decomposition of the convolution operator, which is compact for an appropriate choice of reference spaces. The density is approximated by a sequence of orthonormal eigenfunctions of the convolution operator. The resulting estimator is shown to be consistent and asymptotically normal. While most estimation methods assume that the…

利用控制函数识别三角系统AI 解读

This note discusses identification in nonparametric, continuous triangular systems. It provides conditions that are both necessary and sufficient for the existence of control functions satisfying conditional independence and support requirements. Confirming a commonly noticed pattern, these conditions restrict the admissible dimensionality of unobserved heterogeneity in the first-stage structural relation, or more generally the dimensionality of the family of conditional…

非参数工具变量问题中的完备性条件AI 解读

The notion of completeness between two random elements has been considered recently to provide identification in nonparametric instrumental problems. This condition is quite abstract, however, and characterizations have been obtained only in special cases. This paper considers a nonparametric model between the two variables with an additive separability and a large support condition. In this framework, different versions of completeness are obtained, depending on which…

含弱识别干扰参数的 GMM 新投影推断方法AI 解读

Projection-based tests for subsets of parameters are useful because they do not over-reject the true parameter values when either it is difficult to estimate the nuisance parameters or their identification status is questionable. However, they are also often criticized for being overly conservative. We overcome this conservativeness by introducing a new projection-based test that is more powerful than the traditional projection-based tests. The new test is even…

利用显示偏好数据识别风险偏好的全局问题AI 解读

The concept of parameter identification (for a given specification) is differentiated from global identification (which specification is right). First-order conditions for production under risk are shown to admit many alternative specification pairs representing risk preferences and either perceived price risk, production risk, or the deterministic production structure. Imposing an arbitrary specification on any of the latter three determines which risk preference…

处理状态误分类与处理效应：英国教育回报的应用AI 解读

We study the impact of misreported treatment status on the estimation of causal treatment effects, focusing on applications where no additional information or repeated measurements are available. We first characterize the bias introduced by misclassification on the average treatment effect on the treated (ATT) under a conditional independence assumption, in both a binary and a multiple-treatment setting. We find that the bias of matching-type estimators computed from…

含噪声与高维尺度下的低秩及近低秩矩阵估计AI 解读

We study an instance of high-dimensional inference in which the goal is to estimate a matrix Θ∗∈ℝm1×m2 on the basis of N noisy observations. The unknown matrix Θ∗ is assumed to be either exactly low rank, or “near” low-rank, meaning that it can be well-approximated by a matrix with low rank. We consider a standard M-estimator based on regularization by the nuclear or trace norm over matrices, and analyze its performance under high-dimensional scaling. We define the notion of…

线性结构方程模型的全局可识别性AI 解读

Structural equation models are multivariate statistical models that are defined by specifying noisy functional relationships among random variables. We consider the classical case of linear relationships and additive Gaussian noise terms. We give a necessary and sufficient condition for global identifiability of the model in terms of a mixed graph encoding the linear structural equations and the correlation structure of the error terms. Global identifiability is understood…

可能非线性模型中的弱识别检验AI 解读

In this paper we propose a chi-square test for identification. Our proposed test statistic is based on the distance between two shrinkage extremum estimators. The two estimators converge in probability to the same limit when identification is strong, and their asymptotic distributions are different when identification is weak. The proposed test is consistent not only for the alternative hypothesis of no identification but also for the alternative of weak identification,…

匹配与半参数工具变量估计：距离型迁移指标及青年男性工资AI 解读

Our paper estimates the effect of US internal migration on wage growth for young men between their first and second job. Our analysis of migration extends previous research by: (i) exploiting the distance-based measures of migration in the National Longitudinal Surveys of Youth 1979 (NLSY79); (ii) allowing the effect of migration to differ by schooling level and (iii) using propensity score matching to estimate the average treatment effect on the treated (ATET) for movers…

三角系统中更紧的识别界AI 解读

We study a nonparametric triangular system with (potentially discrete) endogenous regressors and nonseparable errors. Like in other work in this area, the parameter of interest is the structural function evaluated at particular values. We impose a global exclusion and exogeneity condition, in contrast to Chesher (2005), but develop a rank condition which is weaker than Chesher's. The alternative rank condition can be satisfied for binary endogenous regressors, and it often…

恢复连续线性泛函的工具变量方法AI 解读

This paper develops methods for estimating continuous linear functionals in nonparametric instrumental variable problems. Examples of such functionals include consumer surplus and weighted average derivatives. The estimation procedure is robust to a setting where the underlying model is not identified but the linear functional is. In order to attain such robustness, it is necessary to employ a partially identified nuisance parameter. We address this problem by consistently…

含共同非货币回报的 Roy 模型：非参数识别与估计AI 解读

We consider identification and estimation of a Roy model that includes a common nonpecuniary utility component associated with each choice alternative. This augmented Roy model has broader applications to many polychotomous choice problems in addition to occupational sorting. We develop a pair of nonparametric estimators for this model, derive asymptotics, and illustrate small-sample properties with a series of Monte Carlo experiments. We apply one of these models to…

弱识别线性联立方程中的渐近枢轴结构变化检验AI 解读

Asymptotically pivotal structural change tests are developed for simultaneous equations with weakly identified parameters, extending the boundedly pivotal tests of Caner (2007, Journal of Econometrics 137, 28–67) by means of a simple reparametrization of the model.

股市崩盘与美国家庭预期AI 解读

Abstract This paper utilizes data on subjective probabilities to study the impact of the stock market crash of 2008 on households' expectations about the returns on the stock market index. We use data from the Health and Retirement Study that was fielded in February 2008 through February 2009. The effect of the crash is identified from the date of the interview, which is shown to be exogenous to previous stock market expectations. We estimate the effect of the crash on the…

将高维数据串联为函数型数据进行分析AI 解读

We propose stringing, a class of methods where one views high-dimensional observations as functional data. Stringing takes advantage of the high dimension by representing such data as discretized and noisy observations that originate from a hidden smooth stochastic process. Assuming that the observations result from scrambling the original ordering of the observations of the process, stringing reorders the components of the high-dimensional vectors, followed by transforming…

北大西洋热带气旋记录中的变点AI 解读

This article examines the North Atlantic tropical cyclone record for statistical discontinuities (changepoints). This is a controversial area and indeed, our end conclusions are opposite of those made in Dr. Kelvin Droegemeier’s July 28, 2009 Senate testimonial. The methods developed here should help rigorize the debate. Elaborating, we develop a level-α test for a changepoint in a categorical data sequence sampled from a multinomial distribution. The proposed test statistic…

基于贝叶斯空间点过程的功能神经影像元分析AI 解读

As the discipline of functional neuroimaging grows there is an increasing interest in meta analysis of brain imaging studies. A typical neuroimaging meta analysis collects peak activation coordinates (foci) from several studies and identifies areas of consistent activation. Most imaging meta analysis methods only produce null hypothesis inferences and do not provide an interpretable fitted model. To overcome these limitations, we propose a Bayesian spatial hierarchical model…

分布式计算故障识别的在线模型聚类AI 解读

Large-scale distributed computing systems can suffer from occasional severe violation of performance goals; due to the complexity of these systems, manual diagnosis of the cause of the crisis is too slow to inform interventions taken during the crisis. Rapid automatic recognition of the recurrence of a problem can lead to cause diagnosis and informed intervention. We frame this as an online clustering problem, where the labels (causes) of some of the previous crises may be…

有偏抽样设计中参数可识别性与估计的统一框架AI 解读

Based on the odds ratio representation of a joint density, we propose a unified framework to study parameter identifiability in biased sampling designs. It is shown that most of these designs encountered in practice can be reformulated within the proposed framework and, as a result, the question of parameter identifiability can be largely clarified. Estimation of the identifiable parameters is considered and traditional results on the equivalence of the prospective and…

面向大规模成像数据的 FDRL 多重检验AI 解读

The multiple testing procedure plays an important role in detecting the presence of spatial signals for large-scale imaging data. Typically, the spatial signals are sparse but clustered. This paper provides empirical evidence that for a range of commonly used control levels, the conventional FDR procedure can lack the ability to detect statistical significance, even if the p-values under the true null hypotheses are independent and uniformly distributed; more generally,…