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贝叶斯路径与单位根：先验问题始终值得争论AI 解读

Abstract This paper provides detailed responses to the following eight discussants of my paper ‘To criticize the critics: an objective Bayesian analysis of stochastic trends’: Gary Koop and Mark Steel; Edward Learner; In‐Moo Kim and G. S. Maddala; Dale J. Poirier; Peter C. Schotman and Herman K. van Dijk; James H. Stock; David DeJong and Charles H. Whiteman; and Christopher Sims. This reply puts new emphasis on the call made in the earlier paper for objective Bayesian…

批评批评者：随机趋势的客观贝叶斯分析AI 解读

Abstract In two recent articles, Sims (1988) and Sims and Uhlig (1988/1991) question the value of much of the ongoing literature on unit roots and stochastic trends. They characterize the seeds of this literature as ‘sterile ideas’, the application of nonstationary limit theory as ‘wrongheaded and unenlightening’, and the use of classical methods of inference as ‘unreasonable’ and ‘logically unsound’. They advocate in place of classical methods an explicit Bayesian approach…

连续时间中的误差修正与长期均衡AI 解读

This paper deals with error correction models (ECM's) and cointegrated systems that are formulated in continuous time. Long-run equilibrium coefficients in the continuous system are always identified in the discrete time reduced form, so that there is no aliasing problem for these parameters. The long- run relationships are also preserved under quite general data filtering. Frequency domain procedures are outlined for estimation and inference. These methods are…

协整系统中的最优推断AI 解读

Properties of maximum likelihood estimates of cointegrated systems are studied. Alternative formulations are considered, including a new triangular system error correction mechanism. We demonstrate that full system maximum likelihood brings the problem of inference within the family covered by the locally asymptotically mixed normal asymptotic theory, provided all unit roots have been eliminated by specification and data transformation. Methodological issues provide a major…

基于残差的协整检验的渐近性质AI 解读

This paper develops an asymptotic theory for residual based tests for cointegration. These tests involve procedures that are designed to detect the presence of a unit root in the residuals of (cointegrating) regressions among the levels of economic time series. Attention is given to the augmented Dickey-Fuller (ADF) test that is recommended by Engle-Granger (1987) and the Z(a) and Z(t) unit root tests recently proposed by Phillips (1987). Two new tests are also introduced,…

近整合时间序列的回归理论AI 解读

On introduit le concept de processus aleatoire vectoriel presque integre. Ce type de processus aide a travailler vers une theorie asymptotique generale de la regression pour des series temporelles multiples

含单整回归变量时普通最小二乘与广义最小二乘的渐近等价性AI 解读

It is shown that in the multiple regression model y 1 = x 1′β + u t, where u t, is a stationary autoregressive process and x 1 is an integrated m-vector process, the asymptotic distributions of the ordinary least squares (OLS) and generalized least squares (GLS) estimators of β are identical. This generalizes a result obtained by Krämer (1986) for two-variate regression and extends fixed regressor theory developed by Grenander and Rosenblatt (1957). Our approach uses a…

迈向自回归模型的统一渐近理论AI 解读

This paper develops an asymptotic theory for a first order autoregression with a root near unity. Deviations from the unit root theory are measured through a noncentrality parameter. When this parameter is negative we have a local alternative that is stationary; when it is positive, the local alternative is explosive; and when it is zero we have the standard unit root theory. Our asymptotic theory accommodates these alternatives and helps to unify earlier theory in which the…

含单位根的时间序列回归AI 解读

This paper studies the random walk in a general time series setting that allows for weakly dependent and heterogeneously distributed innovations. It is shown that simple least squares regression consistently estimates a unit root under very general conditions in spite of the presence of autocorrelated errors. The limiting distribution of the standardized estimator and the associated regression t statistic are found using functional central limit theory. New tests of the…

非平稳向量自回归中的渐近展开AI 解读

This paper studies the statistical properties of vector autoregressions (VAR's) for quite general multiple time series which are integrated processes of order one. Functional central limit theorems are given for multivariate partial sums of weakly dependent innovations and these are applied to yield first-order asymptotics in nonstationary VAR's. Characteristic and cumulant functionals for generalized random processes are introduced as a means of developing a refinement of…

迈向统一的自回归渐近理论AI 解读

This paper develops an asymptotic theory for a first-order autoregression with a root near unity. Deviations from the unit root theory are measured through a noncentrality parameter. When this parameter is negative we have a local alternative that is stationary; when it is positive the local alternative is explosive; and when it is zero we have the standard unit root theory. Our asymptotic theory accommodates these possibilities and helps to unify earlier theory in which the…

含一阶单整过程的多元时间序列回归AI 解读

This paper develops a general asymptotic theory of regression for processes which are integrated of order one. The theory includes vector autoregressions and multivariate regressions amongst integrated processes that are driven by innovation sequences which allow for a wide class of weak dependence and heterogeneity. The models studied cover cointegrated systems such as those advanced recently by Granger and Engle and quite general linear simultaneous equations systems with…

扩展有理逼近（ERA）：小样本理论的新方法AI 解读

This article proposes a new approach to small sample theory that achieves a meaningful integration of earlier directions of research in this field. The approach centers on the constructive technique of approximating distributions developed recently by the author in [10]. This technique utilizes extended rational approximants (ERA's) which methods (such as those based on asymptotic expansions) and which simultaneously blend information from diverse analytic, numerical and…

一阶非循环自回归中的Edgeworth与鞍点近似AI 解读

The first-order noncircular autoregressive model is considered and Edgeworth and saddlepoint approximations are given for the distribution of the least squares estimator of the autoregressive coefficient. Numerical calculations are used to compare the two approximations with the exact distribution, found by numerical integration. Both approximations are unsatisfactory when the autoregressive coefficient is moderately large and the sample size small, the saddlepoint because…

一阶非循环自回归中的 Edgeworth 与鞍点近似AI 解读

The first-order noncircular autoregressive model is considered and Edgeworth and saddlepoint approximations are given for the distribution of the least squares estimator of the autoregressive coefficient. Numerical calculations are used to compare the two approximations with the exact distribution, found by numerical integration. Both approximations are unsatisfactory when the autoregressive coefficient is moderately large and the sample size small, the saddlepoint because…

一阶随机差分方程相关有限样本分布的近似AI 解读

Edgeworth series expansions are obtained of the finite sample distributions of the least squares estimator and the associated t ratio test statistic in the context of a first-order noncircular stochastic difference equation. General formulae are given for these expansions up to 0(Th1) where T is the sample size and explicit representations of these in terms of the true parameters are derived up to 0(12). Some numerical comparisons of the approximations and the exact…

若干连续时间模型的估计AI 解读

When a continuous time model is estimated from its non-recursive discrete approximation, the presence of identities and exogenous variables in the system does not preclude the use of standard procedures. However, if we wish to use the exact discrete model for estimation purposes, the treatment of identities and exogenous variables is not so straightforward. It is found that the procedure based on the exact discrete model is unlikely to be affected by the presence of…