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Self-Weighted Least Absolute Deviation Estimation for Infinite Variance Autoregressive Models

无限方差自回归模型的自加权最小绝对偏差估计

Summary How to undertake statistical inference for infinite variance autoregressive models has been a long-standing open problem. To solve this problem, we propose a self-weighted least absolute deviation estimator and show that this estimator is asymptotically normal if the density of errors and its derivative are uniformly bounded. Furthermore, a Wald test statistic is developed for the linear restriction on the parameters, and it is shown to have non-trivial local power.…

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Nonanticipating estimation applied to sequential analysis and changepoint detection

非预见估计在序贯分析与变点检测中的应用

Suppose a process yields independent observations whose distributions belong to a family parameterized by θ∈Θ. When the process is in control, the observations are i.i.d. with a known parameter value θ0. When the process is out of control, the parameter changes. We apply an idea of Robbins and Siegmund [Proc. Sixth Berkeley Symp. Math. Statist. Probab. 4 (1972) 37–41] to construct a class of sequential tests and detection schemes whereby the unknown post-change parameters…

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Approximating conditional distribution functions using dimension reduction

利用降维近似条件分布函数

Motivated by applications to prediction and forecasting, we suggest methods for approximating the conditional distribution function of a random variable Y given a dependent random d-vector X. The idea is to estimate not the distribution of Y|X, but that of Y|θTX, where the unit vector θ is selected so that the approximation is optimal under a least-squares criterion. We show that θ may be estimated root-n consistently. Furthermore, estimation of the conditional distribution…

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Bootstrapping Unit Root Tests for Autoregressive Time Series

自回归时间序列单位根检验的自助法

The theory developed for bootstrapping unit root tests in an autoregressive (AR) context has been concerned mainly with the large-sample behavior of the methods proposed under the assumption that the null hypothesis is true. No results exist for the relative performance and the power behavior of the bootstrap methods under the alternative. This article studies the properties of different AR bootstrap schemes of the unit root hypothesis, including a new proposal based on…

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Constructing Stationary Time Series Models Using Auxiliary Variables With Applications

利用辅助变量构造平稳时间序列模型及其应用

Here we present a novel method for modeling stationary time series. Our approach is to construct the model with a specified marginal family and build the dependence structure around it. We show that the resulting time series is linear with a simple autocorrelation structure. We construct models that parallel existing structures, namely state-space models, autoregressive conditional heteroscedasticity (ARCH) models, and generalized ARCH models. We use Bayesian techniques to…

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Diagnostic Checking in ARMA Models With Uncorrelated Errors

误差不相关的 ARMA 模型诊断检验

We consider tests for lack of fit in ARMA models with nonindependent innovations. In this framework, the standard Box–Pierce and Ljung–Box portmanteau tests can perform poorly. Specifically, the usual text book formulas for asymptotic distributions are based on strong assumptions and should not be applied without careful consideration. In this article we derive the asymptotic covariance matrix of a vector of autocorrelations for residuals of ARMA models under weak…

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SLEX Analysis of Multivariate Nonstationary Time Series

多元非平稳时间序列的 SLEX 分析

We develop a procedure for analyzing multivariate nonstationary time series using the SLEX library (smooth localized complex exponentials), which is a collection of bases, each basis consisting of waveforms that are orthogonal and time-localized versions of the Fourier complex exponentials. Under the SLEX framework, we build a family of multivariate models that can explicitly characterize the time-varying spectral and coherence properties. Every model has a spectral…

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Solution to Problem Posed in Volume 20(3): 04.3.1. An I(2) Model for VAR(1) Processes—Solution

VAR(1) 过程的 I(2) 模型:第 20 卷第 3 期问题 04.3.1 解答

Let α * be any basis of col(Π) and β * be any basis of col(Π′); we note col(α ⊥ ) = col(α *⊥ ), col(β ⊥ ) = col(β *⊥ ) so no distinction is made between α ⊥ and α *⊥ , β ⊥ and β *⊥ in the following discussion.

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A MONTE CARLO STUDY ON THE SELECTION OF COINTEGRATING RANK USING INFORMATION CRITERIA

用信息准则选择协整秩的蒙特卡洛研究

We conduct Monte Carlo simulations to evaluate the use of information criteria (Akaike information criterion [AIC] and Schwarz information criterion [SC]) as an alternative to various probability-based tests for determining cointegrating rank in multivariate analysis. First, information criteria are used to determine cointegrating rank given the lag order in a levels vector autoregression. Second, information criteria are used to determine the lag order and cointegrating…

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STRONG CONSISTENCY RESULTS FOR LEAST SQUARES ESTIMATORS IN GENERAL VECTOR AUTOREGRESSIONS WITH DETERMINISTIC TERMS

含确定性项的一般向量自回归中最小二乘估计量的强一致性

A vector autoregression with deterministic terms and with no restrictions to its characteristic roots is considered. Strong consistency results for the least squares statistics are presented. This extends earlier results where deterministic terms have not been considered. In addition the convergence rates are improved compared with earlier results.Comments from S. Johansen are gratefully acknowledged.

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A NOTE ON TESTING RESTRICTIONS FOR THE COINTEGRATION PARAMETERS OF A VAR WITH I(2) VARIABLES

含 I(2) 变量的 VAR 协整参数约束检验札记

We give a brief introduction to the vector autoregressive model for cointegrated I(2) variables and show how some plausible economic relations can be formulated in the I(2) framework in such a way that likelihood ratio tests for their validity are asymptotically χ2 distributed.The authors thank Paolo Paruolo for helpful comments and the ESF for financial support in the framework of the EMM network.

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THE VARIANCE RATIO TEST: AN ANALYSIS OF SIZE AND POWER BASED ON A CONTINUOUS-TIME ASYMPTOTIC FRAMEWORK

方差比检验:连续时间渐近框架下的尺寸与功效分析

We consider the statistical properties of the variance ratio statistic in the context of testing for market efficiency defined by uncorrelated returns. The statistic is then the ratio of the variance of K-period returns to the variance of one-period returns scaled by K. We use a continuous-time asymptotic framework whereby we let the sample size increase to infinity keeping the span of the data fixed. We also let the aggregation parameter K increase such that K/T → κ as T,…

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GMM, GEL, Serial Correlation, and Asymptotic Bias

GMM、GEL、序列相关与渐近偏差

For stationary time series models with serial correlation, we consider generalized method of moments (GMM) estimators that use heteroskedasticity and autocorrelation consistent (HAC) positive definite weight matrices and generalized empirical likelihood (GEL) estimators based on smoothed moment conditions. Following the analysis of Newey and Smith (2004) for independent observations, we derive second order asymptotic biases of these estimators. The inspection of bias…

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Asymptotic Distribution Theory for Nonparametric Entropy Measures of Serial Dependence

序列依赖非参数熵度量的渐近分布理论

Entropy is a classical statistical concept with appealing properties. Establishing asymptotic distribution theory for smoothed nonparametric entropy measures of dependence has so far proved challenging. In this paper, we develop an asymptotic theory for a class of kernel-based smoothed nonparametric entropy measures of serial dependence in a time-series context. We use this theory to derive the limiting distribution of Granger and Lin's (1994) normalized entropy measure of…

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Generalized Spectral Tests for Conditional Mean Models in Time Series with Conditional Heteroscedasticity of Unknown Form

未知形式条件异方差下时间序列条件均值模型的广义谱检验

Economic theories in time series contexts usually have implications on and only on the conditional mean dynamics of underlying economic variables. We propose a new class of specification tests for time series conditional mean models, where the dimension of the conditioning information set may be infinite. Both linear and nonlinear conditional mean specifications are covered. The tests can detect a wide range of model misspecifications in mean while being robust to…

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Bias-Corrected Estimation in Dynamic Panel Data Models

动态面板数据模型中的偏误修正估计

This study develops a new bias-corrected estimator for the fixed-effects dynamic panel data model and derives its limiting distribution for finite number of time periods, T, and large number of cross-section units, N. The bias-corrected estimator is derived as a bias correction of the least squares dummy variable (within) estimator. It does not share some of the drawbacks of recently developed instrumental variables and generalized method-of-moments estimators and is…

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ON PLUG-IN ESTIMATION OF LONG MEMORY MODELS

长记忆模型的代入估计

We consider the Gaussian ARFIMA(j,d,l) model, with spectral density and an unknown mean . For this class of models, the n−1-normalized information matrix of the full parameter vector, (μ,θ), is asymptotically degenerate. To estimate θ, Dahlhaus (1989, Annals of Statistics 17, 1749–1766) suggested using the maximizer of the plug-in log-likelihood, , where is any n(1−2d)/2-consistent estimator of μ. The resulting estimator is a plug-in maximum likelihood estimator (PMLE). This…

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FURTHER RESULTS ON THE ASYMPTOTICS FOR NONLINEAR TRANSFORMATIONS OF INTEGRATED TIME SERIES

积分时间序列非线性变换的进一步渐近结果

This paper establishes various results involving functions of integrated processes. Two theorems—which improve similar results by Park and Phillips—are proved for averages of functions of an integrated process that has not been rescaled by the square root of sample size. In addition, two results are given that characterize asymptotic behavior of averages of nonintegrable functions of rescaled integrated processes; the observations close to the pole take over asymptotic…

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BAYESIAN REFERENCE ANALYSIS OF COINTEGRATION

协整的贝叶斯参考分析

A Bayesian reference analysis of the cointegrated vector autoregression is presented based on a new prior distribution. Among other properties, it is shown that this prior distribution distributes its probability mass uniformly over all cointegration spaces for a given cointegration rank and is invariant to the choice of normalizing variables for the cointegration vectors. Several methods for computing the posterior distribution of the number of cointegrating relations and…

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THE RANK OF A SUBMATRIX OF COINTEGRATION

协整矩阵子矩阵的秩检验

This paper proposes a test of the rank of the submatrix of β, where β is a cointegrating matrix. In addition, the submatrix of β⊥, an orthogonal complement to β, is investigated. We construct the test statistic by using the eigenvalues of the quadratic form of the submatrix. We show that the test statistic has a limiting chi-square distribution when data are nontrending, whereas for trending data we have to consider a conservative test or other testing procedure that…

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On testing for unit roots and the initial observation

单位根检验与初始观测值

Recent work has highlighted the crucial dependence of the power of existing unit root tests on the deviation of the initial observation from the deterministic component of the series. In practical applications, it is useful to have a test available with power more robust to the initial condition. In this paper, we propose such a procedure based on a data-dependent weighted average of the standard Dickey--Fuller and Elliott--Rothenberg--Stock tests. Simulation of the new…

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Testing for stationarity in heterogeneous panel data where the time dimension is finite

时间维度有限时异质面板数据的平稳性检验

and hence makes the test valid for any (T, N) combination. The asymptotic distributions of the tests are derived under the null and are shown to be normally distributed. Their moments for T fixed are derived analytically using Ghazal's (1994, Statistics and Probability letters 20, 313--319) 1 lemma 1. Finite sample size and power are considered in a Monte Carlo experiment. The proposed tests have empirical sizes that are very close to the nominal 5% level. The Monte Carlo…

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Weather Forecasting for Weather Derivatives

面向天气衍生品的天气预测

We take a simple time series approach to modeling and forecasting daily average temperature in U.S. cities, and we inquire systematically as to whether it may prove useful from the vantage point of participants in the weather derivatives market. The answer is, perhaps surprisingly, yes. Time series modeling reveals conditional mean dynamics and, crucially, strong conditional variance dynamics in daily average temperature, and it reveals sharp differences between the…

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