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ALTERNATIVE FREQUENCY AND TIME DOMAIN VERSIONS OF FRACTIONAL BROWNIAN MOTION

分数布朗运动的不同频域与时域版本

This paper compares models of fractional processes and associated weak convergence results based on moving average representations in the time domain with spectral representations. Both approaches have been applied in the literature on fractional processes. We point out that the conventional forms of these models are not equivalent, as is commonly assumed, even under a Gaussianity assumption. We show that it is necessary to distinguish between “two-sided” processes depending…

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DISTRIBUTION-FREE TESTS OF FRACTIONAL COINTEGRATION

分数协整的无分布检验

We propose tests of the null of spurious relationship against the alternative of fractional cointegration among the components of a vector of fractionally integrated time series. Our test statistics have an asymptotic chi-square distribution under the null and rely on generalized least squares–type of corrections that control for the short-run correlation of the weak dependent components of the fractionally integrated processes. We emphasize corrections based on…

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TESTING FOR LONG MEMORY

长记忆检验

This paper introduces a new test statistic for the null hypothesis of short memory against long memory alternatives. The novelty of our statistic is that it is based on only high-order sample autocovariances and by construction eliminates the effects of nuisance parameters typically induced by short memory autocorrelation. For practically relevant situations where the short memory process is not directly observed, but instead appears as the disturbance term in a…

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COINTEGRATION FOR PERIODICALLY INTEGRATED PROCESSES

周期单整过程的协整

Integration for seasonal time series can take the form of seasonal periodic or nonperiodic integration. When seasonal time series are periodically integrated, we show that any cointegration is either full periodic cointegration or full nonperiodic cointegration, with no possibility of cointegration applying for only some seasons. In contrast, seasonally integrated series can be seasonally, periodically or nonperiodically cointegrated, with the possibility of cointegration…

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TESTING FOR UNIT ROOTS IN PANELS WITH A FACTOR STRUCTURE

具有因子结构的面板单位根检验

This paper considers various tests of the unit root hypothesis in panels where the cross-section dependence is due to common dynamic factors. Three situations are studied. First, the common factors and idiosyncratic components may both be nonstationary. In this case test statistics based on generalized least squares (GLS) possess a standard normal limiting distribution, whereas test statistics based on ordinary least squares (OLS) are invalid. Second, if the common component…

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TESTING FOR TREND

趋势检验

The paper examines various tests for assessing whether a time series model requires a slope component. We first consider the simple t-test on the mean of first differences and show that it achieves high power against the alternative hypothesis of a stochastic nonstationary slope and also against a purely deterministic slope. The test may be modified, parametrically or nonparametrically, to deal with serial correlation. Using both local limiting power arguments and…

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ADMISSIBLE AND NONADMISSIBLE TESTS IN UNIT-ROOT-LIKE SITUATIONS

类单位根情形中的可容许与不可容许检验

This paper investigates the asymptotic behavior of tests in situations where the likelihood is locally asymptotically quadratic. Necessary and sufficient conditions are given for a test to be admissible. Even without these restrictive parametric assumptions, it is shown that certain common procedures—such as the augmented Dickey–Fuller test in cases where no deterministic trend is present or standard tests for restrictions on cointegrating relationships—are asymptotically…

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LONG MEMORY TESTING IN THE TIME DOMAIN

时域中的长记忆检验

An integration test against fractional alternatives is suggested for univariate time series. The new test is a completely regression-based, lag augmented version of the Lagrange multiplier (LM) test by Robinson (1991, Journal of Econometrics 47, 67–84). Our main contributions, however, are the following. First, we let the short memory component follow a general linear process. Second, the innovations driving this process are martingale differences with eventual conditional…

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BOOTSTRAP UNIT ROOT TESTS FOR TIME SERIES WITH NONSTATIONARY VOLATILITY

非平稳波动率时间序列的自助法单位根检验

The presence of permanent volatility shifts in key macroeconomic and financial variables in developed economies appears to be relatively common. Conventional unit root tests are unreliable in the presence of such behavior, having nonpivotal asymptotic null distributions. In this paper we propose a bootstrap approach to unit root testing that is valid in the presence of a wide class of permanent variance changes that includes single and multiple (abrupt and smooth transition)…

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DETERMINANTS OF COVARIANCE MATRICES OF DIFFERENCED AR(1) PROCESSES

差分AR(1)过程协方差矩阵的行列式

In this note, determinants are explicitly calculated for the covariance matrices of differenced and double-differenced AR(1) variables.The author thanks Peter C.B. Phillips for introducing the author to Grenander and Szegö's book on Toeplitz matrices and giving useful comments. The author also thanks two anonymous referees for helpful comments on earlier drafts of the note.

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LONG-RUN COVARIANCE MATRICES FOR FRACTIONALLY INTEGRATED PROCESSES

分数单整过程的长期协方差矩阵

An asymptotic expansion is given for the autocovariance matrix of a vector of stationary long-memory processes with memory parameters d ∈ [0,½). The theory is then applied to deliver formulas for the long-run covariance matrices of multivariate time series with long memory.Phillips acknowledges partial support from a Kelly Fellowship and from the NSF under grant SES 04-142254. This may be proved directly using a Fourier integral asymptotic expansion when the spectrum of the…

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ON RANK ESTIMATION IN SYMMETRIC MATRICES: THE CASE OF INDEFINITE MATRIX ESTIMATORS

对称矩阵的秩估计:不定矩阵估计量情形

In this paper we consider estimating the rank of an unknown symmetric matrix based on a symmetric, asymptotically normal estimator of the matrix. The related positive definite limit covariance matrix is assumed to be estimated consistently and to have either a Kronecker product or an arbitrary structure. These assumptions are standard although they exclude the case when the matrix estimator is positive or negative semidefinite. We adapt and reexamine here some available rank…

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TESTING FOR UNIT ROOTS IN AUTOREGRESSIONS WITH MULTIPLE LEVEL SHIFTS

存在多次水平突变的自回归单位根检验

The asymptotic distributions of augmented Dickey–Fuller (ADF) unit root tests for autoregressive processes with a unit or near-unit root are discussed in the presence of multiple stochastic level shifts of large size occurring independently in time. The distributions depend on a Brownian motion and a Poisson-type jump process. Due to the latter, tests based on standard critical values experience power losses increasing rapidly with the number and the magnitude of the shifts.…

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HIGHER ORDER ASYMPTOTIC THEORY WHEN A PARAMETER IS ON A BOUNDARY WITH AN APPLICATION TO GARCH MODELS

参数位于边界时的高阶渐近理论及其GARCH应用

Andrews (1999, Econometrica 67, 1341–1383) derived the first-order asymptotic theory for a very general class of estimators when a parameter is on a boundary. We derive the second-order asymptotic theory in this setting in some special cases. We focus on the behavior of the quasi maximum likelihood estimator (QMLE) in stationary and nonstationary generalized autoregressive conditionally heteroskedastic (GARCH) models when constraints are imposed in the maximization…

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MONITORING PROCEDURES TO DETECT UNIT ROOTS AND STATIONARITY

检测单位根与平稳性的序贯监测程序

When analyzing time series an important issue is to decide whether the time series is stationary or a random walk. Relaxing these notions, we consider the problem to decide in favor of the I(0) or I(1) property. Fixed-sample statistical tests for that problem are well studied in the literature. In this paper we provide first results for the problem of monitoring sequentially a time series. Our stopping times are based on a sequential version of a kernel-weighted…

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RANK TESTS FOR INSTRUMENTAL VARIABLES REGRESSION WITH WEAK INSTRUMENTS

弱工具变量回归中的秩检验

This paper considers tests in an instrumental variable (IVs) regression model with IVs that may be weak. Tests that have near-optimal asymptotic power properties with Gaussian errors for weak and strong IVs have been determined in Andrews, Moreira, and Stock (2006, Econometrica 74, 715–752). In this paper, we seek tests that have near-optimal asymptotic power with Gaussian errors and improved power with non-Gaussian errors relative to existing tests. Tests with such…

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PRESENT VALUE RELATIONS, GRANGER NONCAUSALITY, AND VAR STABILITY

现值关系、格兰杰非因果性与VAR稳定性

When in the class of “exact” present value (PV) relations the decision variables do not Granger cause the explanatory variables, and a vector autoregressive (VAR) process is used to derive the cross-equation restrictions, the system embodies explosive roots, which hardly can be reconciled with the typical features observed in most macroeconomic time series. This paper investigates the issue.I thank Paolo Paruolo and two anonymous referees for helpful comments and suggestions…

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OPTIMALITY OF GLS FOR ONE-STEP-AHEAD FORECASTING WITH REGARIMA AND RELATED MODELS WHEN THE REGRESSION IS MISSPECIFIED

回归误设时GLS在RegARIMA及相关模型一步预测中的最优性

We consider the modeling of a time series described by a linear regression component whose regressor sequence satisfies the generalized asymptotic sample second moment stationarity conditions of Grenander (1954, Annals of Mathematical Statistics 25, 252–272). The associated disturbance process is only assumed to have sample second moments that converge with increasing series length, perhaps after a differencing operation. The model's regression component, which can be…

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WORLDWIDE ECONOMETRICS RANKINGS: 1989–2005

全球计量经济学发表活动排名:1989—2005年

This paper updates Baltagi's (2003, Econometric Theory 19, 165–224) rankings of academic institutions by publication activity in econometrics over the period 1989–1999 to the period 1989–2005. This ranking is based on 16 leading international journals that publish econometrics articles. It is compared with the prior rankings by Hall (1987, Econometric Theory 3, 171–194; 1990, Econometric Theory 6, 1–16) for the period 1980–1988. In addition, a list of the top 150 individual…

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THE ASYMPTOTIC VARIANCE OF THE PSEUDO MAXIMUM LIKELIHOOD ESTIMATOR

伪最大似然估计量的渐近方差

We present an analytical closed-form expression for the asymptotic variance matrix in the misspecified multivariate regression model.I am grateful to Hamparsum Bozdogan of the University of Tennessee for bringing the idea of the sandwich variance matrix within the context of the misspecified multivariate regression model to my attention and to two referees for their constructive and useful comments.

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THE APPROXIMATE MOMENTS OF THE LEAST SQUARES ESTIMATOR FOR THE STATIONARY AUTOREGRESSIVE MODEL UNDER A GENERAL ERROR DISTRIBUTION

一般误差分布下平稳自回归模型最小二乘估计量的近似矩

I derive the approximate bias and mean squared error of the least squares estimator of the autoregressive coefficient in a stationary first-order dynamic regression model, with or without an intercept, under a general error distribution. It is shown that the effects of nonnormality on the approximate moments of the least squares estimator come into play through the skewness and kurtosis coefficients of the nonnormal error distribution.The author is grateful to the co-editor…

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A LIMIT THEOREM FOR QUADRATIC FORMS AND ITS APPLICATIONS

二次型的极限定理及其应用

We consider quadratic forms of martingale differences and establish a central limit theorem under mild and easily verifiable conditions. By approximating Fourier transforms of stationary processes by martingales, our central limit theorem is applied to the smoothed periodogram estimate of spectral density functions. Our results go beyond earlier ones by allowing a variety of nonlinear time series and by avoiding strong mixing and/or summability conditions on joint…

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NONPARAMETRIC ESTIMATION OF SECOND-ORDER STOCHASTIC DIFFERENTIAL EQUATIONS

二阶随机微分方程的非参数估计

We propose nonparametric estimators of the infinitesimal coefficients associated with second-order stochastic differential equations. We show that under appropriate conditions, the proposed estimators are consistent. Also, we state conditions ensuring the asymptotic normality of these estimators. We conclude our paper with a Monte Carlo experiment in which we assess the response of the nonparametric estimators with respect to the step of discretization.I thank two anonymous…

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