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自适应回归估计量的二阶近似AI 解读

We derive asymptotic expansions for semiparametric adaptive regression estimators. In particular, we derive the asymptotic distribution of the second-order effect of an adaptive estimator in a linear regression whose error density is of unknown functional form. We then show how the choice of smoothing parameters influences the estimator through higher order terms. A method of bandwidth selection is defined by minimizing the second-order mean squared error. We examine both…

如何估计接近单位根的自回归根AI 解读

A new model of near integration is formulated in which the local to unity parameter is identifiable and consistently estimable with time series data. The properties of the model are investigated, new functional laws for near integrated time series are obtained that lead to mixed diffusion processes, and consistent estimators of the localizing parameter are constructed. The model provides a more complete interface between I (0) and I (1) models than the traditional local to…

协整回归中的有效去趋势AI 解读

This paper studies efficient detrending in cointegrating regression and develops modified tests for cointegration that use efficient detrending procedures. Asymptotics for these tests are derived. Monte Carlo experiments are conducted to evaluate the detrending procedures in finite samples and to compare tests for cointegration based on different detrending procedures. The limit theory allows for increasingly remote initial condition effects as the sample size goes to…

This paper proposes an Augmented Dickey-Fuller (ADF) coefficient test for detecting the presence of a unit root in autoregressive moving average (ARMA) models of unknown order. Although the limit distribution of the coefficient estimate depends on nuisance parameters, a simple transformation can be applied to eliminate the nuisance parameter asymptotically, providing an ADF coefficient test for this case. When the time series has an unknown deterministic trend, we propose a…

频域时间序列回归的高阶近似AI 解读

Second-order expansions and mean squared error approximations are given for efficient frequency domain regression estimators. While bandwidth choices do not figure in first order asymptotics for these estimators, they do influence second-order terms and it is shown how suitable choices will enhance second-order efficiency. Data-based bandwidth selection rules are given for practical implementation of these procedures. Two commonly used and asymptotically equivalent spectral…