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平稳与部分非平稳 VARMA 过程精确似然的快速算法AI 解读

An expression for the likelihood function of a stationary vector autoregressive-moving average process is developed. The expression is very efficient numerically and applies to any stationary but not necessarily invertible model. In particular, when the multivariate process is autoregressive, the exact likelihood can be evaluated with a small number of operations depending on the order of the autoregressive operator and the process dimension, but not on the size of the…

通过变量增广检验工具变量估计动态模型中的序列相关AI 解读

Instrumental variable tests for serial correlation can be carried out by adding lagged residuals from initial estimation to the regressors of the model under scrutiny and then checking their joint significance. It is shown that asymptotically valid tests are obtained if the lagged residuals are also added to the initial instrument set. Monte Carlo evidence suggests that useful improvements in finite sample behavior under null and alternative hypotheses can be produced when…

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AR(1) 模型的先验：参数化问题与时间序列考量AI 解读

Two issues have come up in the specification of a prior in the Bayesian analysis of time series with possible unit roots. The first issue deals with the singularity that is due to the local identification problem of the unconditional mean of an AR(1) process in the limit of a random walk. This singularity problem is related to the difference between a structural parameterization and the linear reduced form in a standard regression model with fixed regressors. The second is…

长期与短期结构的识别：ISLM 模型应用AI 解读

In this paper we discuss the problem of identification in a model with cointegration. It is pointed out that there is an identification problem for both long-run parameters and short-run parameters. The identification of the equations and the cointegrating relations is achieved by linear restrictions on the parameters and a criterion for a statistical model to be identifying is given. We also define empirical identification of an estimated structure. A switching algorithm…

存在未观测异质性时的比例风险假设检验AI 解读

Abstract This paper develops a discrete‐time hazard model which accounts for unmeasured hetergeneity while allowing the coefficients of the regressors to vary over time. Sufficient conditions for nonparametric identifiability of the unmeasured heterogeneity distribution are derived. Testing for time‐varying coefficients in this model is, under suitable conditions, equivalent to testing the proportionality assumption of the underlying continuous‐time hazard model. Some Monte…

紧区间上多项式回归的辨别设计AI 解读

In the polynomial regression model of degree $m \in \mathbb{N}$ we consider the problem of determining a design for the identification of the correct degree of the underlying regression. We propose a new optimality criterion which minimizes a weighted $p$-mean of the variances of the least squares estimators for the coefficients of $x^l$ in the polynomial regression models of degree $l = 1,\cdots, m$. The theory of canonical moments is used to determine the optimal designs…

最大似然估计与后验分布非正态性的若干诊断AI 解读

Standard large-sample maximum likelihood and Bayesian inference, based on limiting multivariate normal distributions, may be dubious when applied with small or moderate sample sizes. We define and discuss several measures of nonnormality of MLE and posterior distributions that may be used as diagnostics and can indicate whether reparameterization will be effective in improving inferences. We begin by showing how the nonlinearity measures introduced by Beale and Bates and…

正态模型能够容忍多大程度的 t 分布偏离AI 解读

Suppose that the normal model is used for data Y 1,…, Y n, but that the true distribution is a t distribution with location and scale parameters ζ and σ and m degrees of freedom. The normal model corresponds to m = ∞. Using a local asymptotic framework where m is allowed to increase with n, two classes of estimands are identified. One small class, which in particular contains the functions of ζ alone, is affected by t-ness only to the second order, and maximum likelihood…

通过重加权使回归协变量呈椭圆对称分布AI 解读

We investigate a method of constructing weights to induce elliptically contoured covariates in regression analyses. Much recent work in regression has identified various data analytic and model robustness advantages associated with such covariates. In particular, new estimation methods like SIR, SIRII, SAVE, and PHD have been built around the assumption of elliptically contoured covariates. Finite samples of regression covariates may deviate from this ideal in practice, and…

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工具变量估计量分布的替代近似AI 解读

This paper considers the instrument variable and method-of-moments estimators, as generalizations of two-stage least squares and limited information maximum likelihood, of the coefficients of a single equation. Motivated by a simple principle, asymptotic distributions are derived based on a parameter sequence where both the number of instruments and the sample size increase. The approximations to the distributions provided by this sequence are more accurate than traditional…

大冲击、小冲击与经济波动：宏观时间序列中的异常值AI 解读

Abstract We analyse fifteen post‐World War II US macroeconomic time series using a modified outlier identification procedure based on Tsay (1988a). ‘Large shocks’ appear to be present in all the series we examined. Furthermore, there are three basic outlier patterns: (1) outliers seem to be associated with business cycles, (2) outliers are clustered together—both over time and across series, (3) there appears to be a dichotomy between outlier behaviour of real versus nominal…

利用一阶累积特征识别非线性时间序列AI 解读

A new approach to the problem of identifying a nonlinear time series model is considered. We argue that cumulative lagged conditional mean and variance functions are the appropriate "signatures" of a nonlinear time series for the purpose of model identification, being analogous to cumulative distribution functions or cumulative hazard functions in iid models. We introduce estimators of the cumulative lagged conditional mean and variance functions and study their asymptotic…

对称锥上指数变换模型的精确分解与相关分布的统一视角AI 解读

A class of exponential transformation models is defined on symmetric cones $\Omega$ with the group of automorphisms on $\Omega$ as the acting group. We show that these models are reproductive and the exponent of their joint distribution for a given sample of size $q$ can be split into $q$ independent components, introducing one sample point at a time. The automorphism group can be factorized into the group of positive dilation and another group. Accordingly, the symmetric…

含噪图像的分割与分析模型AI 解读

This article proposes a statistical model for image generation that provides automatic segmentation of images into intensity-differentiated regions and facilitates the quantitative assessment of uncertainty associated with identified image features. The model is specified hierarchically within the Bayesian paradigm. At the lowest level in the hierarchy, a Gibbs distribution is used to specify a probability distribution on the space of all possible partitions of the…

一种双重删失数据的非参数估计及其在艾滋病研究中的应用AI 解读

In many epidemiologic studies of human immunodeficiency virus (HIV) disease, interest focuses on the distribution of the length of the interval of time between two events. Two such problems are considered here, estimation of the distribution of time or number of sexual contacts between infection of an individual (an index case) and transmission of HIV to their sexual partner, and estimation of the distribution of time between infectiousness as a blood donor and the…

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工具变量可采纳性检验：若干精细渐近结果AI 解读

This paper is concerned with the refined asymptotic properties of several tests for the admissibility of a subset of (overidentifying) instrumental variables. It derives maximum likelihood and linearized maximum likelihood tests and calculates size corrections to the order 1/T. The local power function of the size-corrected tests is the same to the order 1/T, irrespectively of the form of the test statistic or the limited information estimator used in its computation.…

局部平均处理效应的识别与估计AI 解读

We investigate conditions sufficient for identification of average treatment effects using instrumental variables. First we show that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect. We then establish that the combination of an instrument and a condition on the relation between the instrument and the participation status is sufficient for identification of a local average treatment effect for those who can be induced…

Haavelmo 的识别理论AI 解读

This paper treats the theory of identification presented in Haavelmo's classic work, The Probability Approach in Econometrics . This was the first identification theory for stochastic models to be developed in econometrics. The paper presents a detailed commentary on Haavelmo's analysis. It also examines the development of Haavelmo's theory from Frisch's analysis of multicollinearity and also the relationship between Haavelmo's analysis and later work on identification.

解释变量与双向误差分量相关时的面板模型估计AI 解读

In this paper, we derive an instrumental variables estimator for the generalized Hausman and Taylor [4] model with a two-way error component. We also extend the work of Breusch, Mizon, and Schmidt [2] to this model and derive two additional instrumental variables estimators. Consistency and asymptotic normality of the parameter estimator is demonstrated, allowing both the number of time periods as well as the number of individuals to increase, their ratio bounded. Consistent…

回归泛函的级数估计AI 解读

Two-step estimators, where the first step is the predicted value from a nonparametric regression, are useful in many contexts. Examples include a non-parametric residual variance, probit with nonparametric generated regressors, efficient GMM estimation with randomly missing data, heteroskedasticity corrected least squares, semiparametric regression, and efficient nonlinear instrumental variables estimators. The purpose of this paper is the development of consistency and…