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扩散过程之间的长期共动AI 解读

The aim of this paper is to characterize and analyze long-run comovements among diffusion processes. Broadly speaking, if X = ( X 1 ,, X 2 ,;t ≥ 0) is a nonergodic diffusion in R 2 , but there exists a linear combination, say, γ′ X , that is instead ergodic in R, then we say there exists a linear stochastic comovement between the components of X . Linear diffusions exhibiting stochastic comovements admit an error correction representation. Estimation of γ and hypothesis…

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扩散过程的非参数估计及其在短期利率模型中的应用AI 解读

In this paper, we propose a nonparametric identification and estimation procedure for an ltd diffusion process based on discrete sampling observations. The nonparametric kernel estimator for the diffusion function developed in this paper deals with general ltd diffusion processes and avoids any functional form specification for either the drift function or the diffusion function. It is shown that under certain regularity conditions the nonparametric diffusion function…

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非球形扰动线性回归模型系数向量的置信集AI 解读

In this present paper, considering a linear regression model with nonspherical disturbances, improved confidence sets for the regression coefficients vector are developed using the Stein rule estimators. We derive the large-sample approximations for the coverage probabilities and the expected volumes of the confidence sets based on the feasible generalized least-squares estimator and the Stein rule estimator and discuss their ranking.

随机动态规划的近似解AI 解读

This paper examines the properties of various approximation methods for solving stochastic dynamic programs in structural estimation problems. The problem addressed is evaluating the expected value of the maximum of available choices. The paper shows that approximating this by the maximum of expected values frequently has poor properties. It also shows that choosing a convenient distributional assumptions for the errors and then solving exactly conditional on the…

小扰动下非线性系统确定性与随机预测器的比较AI 解读

This paper compares the deterministic and stochastic predictors of nonlinear models when the disturbances are small. Large-sample properties of these predictors have been analyzed extensively in the econometric literature. While the deterministic predictors are asymptotically biased, there are some Monte Carlo experiments that suggest the magnitude of this bias is rather insignificant. Here, we offer a possible explanation of the smallness of the deterministic bias. It is…

逐一估计多个结构断点AI 解读

Sequential (one-by-one) rather than simultaneous estimation of multiple breaks is investigated in this paper. The advantage of this method lies in its computational savings and its robustness to misspecification in the number of breaks. The number of least-squares regressions required to compute all of the break points is of order T , the sample size. Each estimated break point is shown to be consistent for one of the true ones despite underspecification of the number of…

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Cox–Ingersoll–Ross 模型的参数估计AI 解读

The Cox-Ingersoll-Ross model is a diffusion process suitable for modeling the term structure of interest rates. In this paper, we consider estimation of the parameters of this process from observations at equidistant time points. We study two estimators based on conditional least squares as well as a one-step improvement of these, two weighted conditional least-squares estimators, and the maximum likelihood estimator. Asymptotic properties of the various estimators are…

相依异质随机变量的中心极限定理AI 解读

This paper presents central limit theorems for triangular arrays of mixingale and near-epoch-dependent random variables. The central limit theorem for near-epoch-dependent random variables improves results from the literature in various respects. The approach is to define a suitable Bernstein blocking scheme and apply a martingale difference central limit theorem, which in combination with weak dependence conditions renders the result. The most important application of this…

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