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Mixed signals among tests for cointegration

协整检验之间的混合信号

Abstract This paper illustrates that, under the null hypothesis of no cointegration, the correlation of p ‐values from a single‐equation residual‐based test (i.e., ADF or $\widehat{Z}_{\alpha}$ ) with a system‐based test (trace or maximum eigenvalue) is very low even as the sample size gets large. With data‐generating processes under the null or ‘near’ it, the two types of tests can yield virtually any combination of p ‐values regardless of sample size. As a practical…

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The stochastic implications of rent maximization: an application to stumpage rates for timber in British Columbia

租金最大化的随机含义:不列颠哥伦比亚木材立木费率的应用

Abstract We construct a model of rent‐maximizing behaviour by a single seller of timber in the absence of a formal market, deriving the stochastic implications of rent maximization for timber prices (stumpage rates) when other input and output (lumber) prices are random. Subsequently, we examine the model's ability to describe monthly, time‐series, stumpage‐rate data from British Columbia, Canada between January 1979 and October 1999. Deviations of stumpage rates from their…

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On Markov error‐correction models, with an application to stock prices and dividends

马尔可夫误差修正模型:股票价格与股息应用

Abstract This paper considers Markov error‐correction (MEC) models in which deviations from the long‐run equilibrium are characterized by different rates of adjustment. To motivate our analysis and illustrate the various issues involved, our discussion is structured around the analysis of the long‐run properties of US stock prices and dividends. It is shown that the MEC model is flexible enough to account for situations where deviations from the long‐run equilibrium are…

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Observation-driven models for Poisson counts

Poisson计数的观测驱动模型

This paper is concerned with a general class of observation‐driven models for time series of counts whose conditional distributions given past observations and explanatory variables follow a Poisson distribution. These models provide a flexible framework for modelling a wide range of dependence structures. Conditions for stationarity and ergodicity of these processes are established from which the large‐sample properties of the maximum likelihood estimators can be derived.…

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Autoregressive-aided periodogram bootstrap for timeseries

时间序列的自回归辅助周期图自助法

A bootstrap methodology for the periodogram of a stationary process is proposed which is based on a combination of a time domain parametric and a frequency domain nonparametric bootstrap. The parametric fit is used to generate periodogram ordinates that imitate the essential features of the data and the weak dependence structure of the periodogram while a nonparametric (kernel-based) correction is applied in order to catch features not represented by the parametric fit. The…

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Estimating deformations of stationary processes

平稳过程变形的估计

This paper studies classes of nonstationary processes, such as warped processes and frequency-modulated processes, that result from the deformation of stationary processes. Estimating deformations can often provide important information about an underlying physical phenomenon. A computational harmonic analysis viewpoint shows that the deformed autocovariance satisfies a transport equation at small scales, with a velocity proportional to a deformation gradient. We derive an…

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Tests for a change in persistence against the null of difference‐stationarity

以差分平稳为原假设的持久性变化检验

Economists have recognized the possibility that a time series may change structure from trend-stationarity to difference-stationarity, or vice versa. Taking difference-stationarity as the null hypothesis, we develop tests for this possibility, where neither the location nor direction of any possible change under the alternative hypothesis need be specified. Copyright Royal Economic Society, 2003

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Strong rules for detecting the number of breaks in a time series

检测时间序列结构突变数量的强一致规则

This paper proposes a new approach for detecting the number of structural breaks in a time series when estimation of the breaks is performed one at the time. We consider the case of shifts in the mean of a possibly nonlinear process, allowing for dependent and heterogeneous observations. This is accomplished through a simple, sequential, almost sure rule ensuring that, in large samples, both the probabilities of overestimating and underestimating the number of breaks are…

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Adaptive Estimators and Tests of Stationary and Nonstationary Short- and Long-Memory ARFIMA–GARCH Models

平稳与非平稳短长记忆 ARFIMA–GARCH 模型的自适应估计与检验

This article considers the fractionally autoregressive integrated moving average [ARFIMA(p,d,q)] models with GARCH errors. The process generated by this model is short memory, long memory, stationary, and nonstationary, respectively, when d ∈ (-1/2, 0), d ∈ (0, 1/2), d ∈ (-1/2, 1/2), and d ∈ (1/2, ∞). Using a unified approach, the local asymptotic normality of the model is established for d ∈ ∪∞j = 0(J - 1/2, J + 1/2). The adaptivity and efficiency of the estimating…

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More Efficient Local Polynomial Estimation in Nonparametric Regression With Autocorrelated Errors

自相关误差下更高效的非参数局部多项式估计

We propose a modification of local polynomial time series regression estimators that improves efficiency when the innovation process is autocorrelated. The procedure is based on a pre-whitening transformation of the dependent variable that must be estimated from the data. We establish the asymptotic distribution of our estimator under weak dependence conditions. We show that the proposed estimation procedure is more efficient than the conventional local polynomial method. We…

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Bayesian Modeling and Forecasting of Intraday Electricity Load

日内电力负荷的贝叶斯建模与预测

The advent of wholesale electricity markets has brought renewed focus on intraday electricity load forecasting. This article proposes a multi-equation regression model with a diagonal first-order stationary vector autoregresson (VAR) for modeling and forecasting intraday electricity load. The correlation structure of the disturbances to the VAR and the appropriate subset of regressors are explored using Bayesian model selection methodology. The full spectrum of finite-sample…

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Forecast Uncertainties in Macroeconomic Modeling

宏观经济建模中的预测不确定性

Weargue that probability forecasts convey information on the uncertainties that surround macroeconomic forecasts in a straightforward manner that is preferable to other alternatives, including the use of confidence intervals. Probability forecasts obtained using a small benchmark macroeconometric model and a number of other alternatives are presented and evaluated using recursive forecasts generated over the period 1999q1–2001q1. Out-of-sample probability forecasts of…

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CRITICAL VALUES AND P VALUES OF BESSEL PROCESS DISTRIBUTIONS: COMPUTATION AND APPLICATION TO STRUCTURAL BREAK TESTS

贝塞尔过程分布的临界值与 p 值:计算及结构突变检验应用

The p values of structural break tests, when the break date or dates are unknown, must be calculated in terms of the probability distributions of functions of Bessel processes. The literature so far has maintained that direct computation of these p values and of the corresponding critical values is too difficult and has relied on approximations based on simulations, asymptotic expansions, or curve fitting. This paper presents a fast simple method of calculating exact p…

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DIAGNOSTIC CHECKING FOR THE ADEQUACY OF NONLINEAR TIME SERIES MODELS

非线性时间序列模型充分性的诊断检验

We propose a new diagnostic test for linear and nonlinear time series models, using a generalized spectral approach. Under a wide class of time series models that includes autoregressive conditional heteroskedasticity (ARCH) and autoregressive conditional duration (ACD) models, the proposed test enjoys the appealing “nuisance-parameter-free” property in the sense that model parameter estimation uncertainty has no impact on the limit distribution of the test statistic. It is…

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HIGHER ORDER ASYMPTOTIC THEORY FOR MINIMUM CONTRAST ESTIMATORS OF SPECTRAL PARAMETERS OF STATIONARY PROCESSES

平稳过程谱参数最小对比估计量的高阶渐近理论

Let g(λ) be the spectral density of a stationary process and let fθ(λ), θ ∈ Θ, be a fitted spectral model for g(λ). A minimum contrast estimator of θ is defined that minimizes a distance between , where is a nonparametric spectral density estimator based on n observations. It is known that is asymptotically Gaussian efficient if g(λ) = fθ(λ). Because there are infinitely many candidates for the distance function , this paper discusses higher order asymptotic theory for in…

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COVARIANCE MATRIX ESTIMATION AND THE LIMITING BEHAVIOR OF THE OVERIDENTIFYING RESTRICTIONS TEST IN THE PRESENCE OF NEGLECTED STRUCTURAL INSTABILITY

遗漏结构不稳定时协方差估计与过度识别检验的极限行为

We consider the limiting behavior of the overidentifying restrictions test in the presence of neglected structural instability at a single “break point.” It is shown that the test need not be consistent against this type of misspecification. If it is consistent then it emerges that the limiting behavior of this test statistic depends on the covariance matrix estimator employed. In this paper we consider the case in which a heteroskedasticity autocorrelation covariance (HAC)…

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THE CONTINUITY OF THE LIMIT DISTRIBUTION IN THE PARAMETER OF INTEREST IS NOT ESSENTIAL FOR THE VALIDITY OF THE BOOTSTRAP

极限分布对目标参数连续并非 Bootstrap 有效性的必要条件

It is well known that the unrestricted bootstrap estimator of the slope parameter in the random walk model without drift converges to a random distribution. This bootstrap failure is commonly attributed to the discontinuity of the limit distribution of the least-squares estimator in the parameter of interest. We demonstrate by counterexample that this type of continuity is not essential for the validity of the bootstrap nor is it essential that the rate of convergence of the…

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AR(1) MODELS, UNIT ROOTS, AND ADJUSTED PROFILE LIKELIHOOD

AR(1) 模型、单位根与调整剖面似然

An unobserved components and a conventional first-order autoregressive (AR) model with constant are analyzed with the adjusted profile likelihood of Cox and Reid (1987, Journal of the Royal Statistical Society, Series B 49, 1–39; 1993, Journal of the Royal Statistical Society, Series B 55, 467–71). Both the unobserved components model and the Cox–Reid adjustment can provide more accurate estimates of an AR coefficient of unity. The unobserved components model yields more…

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A full-factor multivariate GARCH model

全因子多元 GARCH 模型

A new multivariate time series model with time varying conditional variances and covariances is presented and analysed. A complete analysis of the proposed model is presented consisting of parameter estimation, model selection and volatility prediction. Classical and Bayesian techniques are used for the estimation of the model parameters. It turns out that the construction of our proposed model allows easy maximum likelihood estimation and construction of well-mixing Markov…

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Nonparametric Methods for Deconvolving Multiperiodic Functions

多周期函数解卷积的非参数方法

Summary Multiperiodic functions, or functions that can be represented as finite additive mixtures of periodic functions, arise in problems related to stellar radiation. There they represent the overall variation in radiation intensity with time. The individual periodic components generally correspond to different sources of radiation and have intrinsic physical meaning provided that they can be ‘deconvolved’ from the mixture. We suggest a combination of kernel and orthogonal…

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On-Line Inference for Hidden Markov Models via Particle Filters

利用粒子滤波进行隐马尔可夫模型的在线推断

Summary We consider the on-line Bayesian analysis of data by using a hidden Markov model, where inference is tractable conditional on the history of the state of the hidden component. A new particle filter algorithm is introduced and shown to produce promising results when analysing data of this type. The algorithm is similar to the mixture Kalman filter but uses a different resampling algorithm. We prove that this resampling algorithm is computationally efficient and…

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Inference on Predictability of Foreign Exchange Rates via Generalized Spectrum and Nonlinear Time Series Models

利用广义谱与非线性时间序列模型推断汇率可预测性

It is often documented, based on autocorrelation, variance ratio, and power spectrum, that exchange rates approximately follow a martingale process. Because these data check serial uncorrelatedness rather than martingale difference, they may deliver misleading conclusions in favor of the martingale hypothesis when the test statistics are insignificant. In this paper, we explore whether there exists a gap between serial uncorrelatedness and martingale difference for exchange…

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