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参数稳定性的移动估计检验AI 解读

In this paper a new class of tests for parameter stability, the moving-estimates (ME) test, is proposed. It is shown that in the standard situation the ME test asymptotically equivalent to the maximal likelihood ratio test under the alternative of a temporary parameter shift. It is also shown that the asymptotic null distribution of the ME test is determined by the increments of a vector Brownian bridge and that under a broad class of alternatives the ME test is consistent…

结构稳定性的非参数条件矩检验AI 解读

This paper considers a nonparametric conditional moment test of stability of an econometric model against the alternative of instability. The alternative hypothesis allows for more than one structural change, although in this case it has to be fairly smooth. This complements existing results for stability in a parametric setting. Also, it is shown that the test is always consistent, unlike the available “parametric” tests, which normally rely on the assumption of a correct…

回到未来：构造连续时间马尔可夫过程的矩条件AI 解读

Continuous-time Markov processes can be characterized conveniently by their infinitesimal generators. For such processes there exist forward and reverse-time generators. The authors show how to use these generators to construct moment conditions implied by stationary Markov processes. Generalized method of moments estimators and tests can be constructed using these moment conditions. The resulting econometric methods are designed to be applied to discrete-time data obtained…

含确定性趋势变量的非线性计量模型AI 解读

This paper considers an alternative asymptotic framework to standard sequential asymptotics for nonlinear models with deterministically trending variables. The asymptotic distributions of generalized method of moments estimators and corresponding test statistics are derived using this framework. The asymptotic distributions are shown to be the same with deterministically trending variables as with non-trending variables. That is, the distributions are normal and chi-squared…

利用线性模型与人工神经网络评估期限结构信息的模型选择方法AI 解读

We take a model selection approach to the question of whether forward interest rates are useful in predicting future spot rates, using a variety of out-of-sample forecast-based model selection criteria: forecast mean squared error, forecast direction accuracy, and forecast-based trading system profitability. We also examine the usefulness of a class of novel prediction models called 'artificial neural networks,' and investigate the issue of appropriate window sizes for…

预测准确性的比较AI 解读

We propose and evaluate explicit tests of the null hypothesis of no difference in the accuracy of two competing forecasts. In contrast to previously developed tests, a wide variety of accuracy measures can be used (in particular, the loss function need not be quadratic and need not even be symmetric), and forecast errors can be non-Gaussian, nonzero mean, serially correlated, and contemporaneously correlated. Asymptotic and exact finite-sample tests are proposed, evaluated,…

增广Dickey–Fuller检验的滞后阶数与临界值AI 解读

Response surface analysis is used to obtain approximate finite-sample critical values for the augmented Dickey-Fuller test. Previous studies estimating the critical values for the test have generally ignored their possible dependence on the lag order. This study shows that the lag order, in addition to the sample size, can affect finite-sample behavior of the test. The result points to the importance of correcting for the effect of lag order in applying the augmented…

增广 Dickey–Fuller 检验的滞后阶数与临界值AI 解读

Response surface analysis is used to obtain approximate finite-sample critical values for the augmented Dickey-Fuller test. Previous studies estimating the critical values for the test have generally ignored their possible dependence on the lag order. This study shows that the lag order, in addition to the sample size, can affect finite-sample behavior of the test. The result points to the importance of correcting for the effect of lag order in applying the augmented…

季节模式是否随时间保持不变？季节稳定性检验AI 解读

This paper introduces Lagrange multiplier tests of the null hypothesis of no unit roots at seasonal frequencies against the alternative of a unit root at either a single seasonal frequency or a set of seasonal frequencies. The tests complement those of D. Dickey, D. Hasza, and W. Fuller (1984) and S. Hylleberg, et al. (1990), which examine the null of seasonal unit roots. The authors derive an asymptotic distribution theory for the tests and investigate their size and power…

汇率鞅假设的谱检验AI 解读

Abstract A new family of spectral shape tests was proposed recently by Durlauf (1991) for testing the martingale hypothesis. Unlike the widely used variance ratio test, spectral shape tests are consistent against all stationary non‐white‐noise alternatives from the martingale null. In this paper we examine the finite sample properties of the spectral shape tests and find that the tests have good size and power properties even for small samples. We apply the tests to examine…

长程依赖时间序列的对数周期图回归AI 解读

This paper discusses the estimation of multiple time series models which allow elements of the spectral density matrix to tend to infinity or zero at zero frequency and be unrestricted elsewhere. A form of log-periodogram regression estimate of differencing and scale parameters is proposed, which can provide modest efficiency improvements over a previously proposed method (for which no satisfactory theoretical justification seems previously available) and further…

长程依赖回归模型中的有效位置与回归估计AI 解读

In this paper we construct an efficient weighted least squares estimator for the mean and more generally for the regression parameters in certain Gaussian long range dependent regression models, including polynomial regression. The form of the estimator does not depend on the whole dependence structure of the residuals, but only on the local behaviour of the spectral density at zero. By using an estimator of the self-similarity parameter, we give a fully efficient estimator.…

时间序列差分平稳性的检验AI 解读

This paper addresses the problem of testing the hypothesis that an observed series is difference stationary. The alternative hypothesis is that the series is another nonstationary process; in particular, an autoregressive model with a random parameter is used. A locally best invariant test is developed assuming Gaussianity, and a representation of its asymptotic distribution as a mixture of Brownian motions is found. The performance of the test in finite samples is…

长程依赖正态误差下的非参数回归AI 解读

We consider the fixed-design regression model with long-range dependent normal errors and show that the finite-dimensional distributions of the properly normalized Gasser-Muller and Priestley-Chao estimators of the regression function converge to those of a white noise process. Furthermore, the distributions of the suitably renormalized maximal deviations over an increasingly finer grid converge to the Gumbel distribution. These results contrast with our previous findings…

长程依赖下的密度估计AI 解读

Dehling and Taqqu established the weak convergence of the empirical process for a long-range dependent stationary sequence under Gaussian subordination. We show that the corresponding density process, based on kernel estimators of the marginal density, converges weakly with the same normalization to the derivative of their limiting process. The phenomenon, which carries on for higher derivatives and for functional laws of the iterated logarithm, is in contrast with…

鞅展开与二阶推断AI 解读

The paper develops a one-step triangular array Edgeworth expansion for multivariate martingales that are, essentially, asymptotically ergodic. Both discrete and continuous time are covered. The expansion is in a test function topology. We investigate when the expansion has the usual Edgeworth form, looking in particular at likelihood inference, including Cox regression, and at inference for stationary time series. The triangular array nature of the results make them useful…

基于周期抽样的自相关置信区间AI 解读

Clinger and Van Ness have shown how to sample a stochastic process in a periodic manner such that the autocorrelation function for that process can be estimated at all lags. We derive approximate confidence intervals for these estimates, focusing on low-order autoregressive moving average processes. Our methods are illustrated with an example from plant disease epidemiology.

时间序列分析进展：纪念莫里斯·普里斯特利AI 解读

List of Contributors. Foreword. Preface. Books and Papers by M. B. Priestley. About the Volume and Summary of Papers. Linear Time Series Models. Estimation and Asymptotics for Times Series Models. Spectral Analysis of Stationary Time Series. Nonparametric Statistical Inference in Time Series. Nonlinear and Non Gaussian Time Series Models. Index.

基于周期抽样的自相关置信区间AI 解读

Clinger and Van Ness have shown how to sample a stochastic process in a periodic manner such that the autocorrelation function for that process can be estimated at all lags. We derive approximate confidence intervals for these estimates, focusing on low-order autoregressive moving average processes. Our methods are illustrated with an example from plant disease epidemiology.

非线性自回归的可加性检验AI 解读

Additivity is commonly used in the statistical literature to simplify data analysis, especially in analysis of variance and in multivariate smoothing. In this paper, we propose three procedures for testing additivity in nonlinear time series analysis. The first procedure combines some smoothing techniques with analysis of variance, the second is a Lagrange multiplier test using nonparametric estimation, and the third is a permutation test which uses smoothing techniques to…

时间序列模型的模拟平滑器AI 解读

Recently suggested procedures for simulating from the posterior density of states given a Gaussian state space time series are refined and extended. We introduce and study the simulation smoother, which draws from the multivariate posterior distribution of the disturbances of the model, so avoiding the degeneracies inherent in state samplers. The technique is important in Gibbs sampling with non-Gaussian time series models, and for performing Bayesian analysis of Gaussian…

时间序列线性的非参数检验AI 解读

We introduce tests of linearity for time series based on nonparametric estimates of the conditional mean and the conditional variance. The tests are compared to a number of parametric tests and to nonparametric tests based on the bispectrum. Asymptotic expressions give bad approximations, and the null distribution under linearity is constructed using resampling of the best linear approximation. The new tests perform well on the examples tested.

长期因果关系AI 解读

The definition of causation, discussed in Granger (1980) and elsewhere, has been widely applied in economics and in other disciplines. For this definition, a series y t is said to cause x t +l if it contains information about the forecastability for x t +l contained nowhere else in some large information set, which includes x t − j , j ≥ 0. However, it would be convenient to think of causality being different in extent or direction at seasonal or low frequencies, say, than…

线性回归中突变的最小绝对偏差估计AI 解读

This paper develops the asymptotic theory for least absolute deviation estimation of a shift in linear regressions. Rates of convergence and asymptotic distributions for the estimated regression parameters and the estimated shift point are derived. The asymptotic theory is developed both for fixed magnitude of shift and for shift with magnitude converging to zero as the sample size increases. Asymptotic distributions are also obtained for trending regressors and for…