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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…

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E.J.（Ted）Hannan：学术生涯与影响AI 解读

after having been a professor of statistics there for the 27 years preceding his retirement in 1986.He held visiting appointments at many overseas universities, including Stanford and Yale, and received numerous honors for his work, including a fellowship of the Econometric Society, the Pitman medal of the Australian Statistical Society, and the Lyle medal of the Australian Academy of Sciences.For many years, Ted was the sole Fellow of the Econometric Society in Australia,…

部分受限简化式估计量的若干精确分布结果AI 解读

This paper considers some finite sample properties of the partially restricted reduced form estimators in a general ( n + 1) endogenous variable model. In particular, the characteristic functions, density functions, and moments are examined for both the vector of estimators and a linear combination. The approach utilizes both invariant polynomials of matrix argument (see Chikuse and Davis [4] and Davis [6]) and fractional calculus techniques (see Phillips [20,25,26]).

GARCH(1,1) 准最大似然估计量的渐近理论AI 解读

This paper investigates the sampling behavior of the quasi-maximum likelihood estimator of the Gaussian GARCH(1,1) model. The rescaled variable (the ratio of the disturbance to the conditional standard deviation) is not required to be Gaussian nor independent over time, in contrast to the current literature. The GARCH process may be integrated (α + β = 1), or even mildly explosive (α + β > 1). A bounded conditional fourth moment of the rescaled variable is sufficient for the…

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备择局部误设下的模型设定检验AI 解读

It is well known that most of the standard specification tests are not robust when the alternative is misspecified. Using the asymptotic distributions of standard Lagrange multiplier (LM) test under local misspecification, we suggest a robust specification test. This test essentially adjusts the mean and covariance matrix of the usual LM statistic. We show that for local misspecification the adjusted test is asymptotically equivalent to Neyman's C (α) test, and therefore,…

最小渐近协方差矩阵估计量的确定AI 解读

We give a straightforward condition sufficient for determining the minimum asymptotic variance estimator in certain classes of estimators relevant to econometrics. These classes are relatively broad, as they include extremum estimation with smooth or nonsmooth objective functions; also, the rate of convergence to the asymptotic distribution is not required to be n −½ . We present examples illustrating the content of our result. In particular, we apply our result to a class…

基于资产定价模型数值解的矩估计量一致性AI 解读

This paper considers the properties of estimators based on numerical solutions to a class of economic models. In particular, the numerical methods discussed are those applied in the solution of linear integral equations, specifically Fredholm equations of the second kind. These integral equations arise out of economic models in which endogenous variables appear linearly in the Euler equations, but for which easily characterized solutions do not exist. Tauchen and Hussey [24]…

平稳遍历性的一致检验AI 解读

A formal statistical test of stationary-ergodicity is developed for known Markovian processes on ℝ d This makes it applicable to testing models and algorithms, as well as estimated time series processes ignoring the estimation error. The analysis is conducted by examining the asymptotic properties of the Markov operator on density space generated by the transition in the state space. The test is developed under the null of stationary-ergodicity, and it is shown to be…

无限方差误差下动态线性回归模型的估计AI 解读

This paper considers the asymptotic behavior of M -estimates in a dynamic linear regression model where the errors have infinite second moments but the exogenous regressors satisfy the standard assumptions. It is shown that under certain conditions, the estimates of the parameters corresponding to the exogenous regressors are asymptotically normal and converge to the true values at the standard n −½ rate.

ARCH 模型中的自适应估计AI 解读

We construct efficient estimators of the identifiable parameters in a regression model when the errors follow a stationary parametric ARCH( P ) process. We do not assume a functional form for the conditional density of the errors, but do require that it be symmetric about zero. The estimators of the mean parameters are adaptive in the sense of Bickel [2]. The ARCH parameters are not jointly identifiable with the error density. We consider a reparameterization of the variance…

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