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单位根与协整:单位根检验、协整、误差修正与长期关系。
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ON THE ROBUSTNESS OF HYPOTHESIS TESTING BASED ON FULLY MODIFIED VECTOR AUTOREGRESSION WHEN SOME ROOTS ARE ALMOST ONE

部分根接近一时完全修正 VAR 假设检验的稳健性

This paper proves that the fully modified vector autoregression (FM-VAR) estimator has second-order bias effects when some roots are local to unity. These bias effects are shown to result in potentially severe size distortions in FM-VAR testing when the hypothesis involves near unit root variables. In addition, the paper reveals that with the FM-VAR method near unit roots become estimated as exact unit roots with convergence speed faster than the order of the sample size.…

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COINTEGRATING SMOOTH TRANSITION REGRESSIONS

协整平滑转换回归

This paper studies the smooth transition regression model where regressors are I(1) and errors are I(0). The regressors and errors are assumed to be dependent both serially and contemporaneously. Using the triangular array asymptotics, the nonlinear least squares estimator is shown to be consistent, and its asymptotic distribution is derived. It is found that the asymptotic distribution involves a bias under the regressor-error dependence, which implies that the nonlinear…

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ROBUST TESTS OF THE UNIT ROOT HYPOTHESIS SHOULD NOT BE “MODIFIED”

稳健单位根检验不应被“修改”

The rank-based unit root tests proposed by Hasan and Koenker (1997, Econometrica 65, 133–161) have power equal to size for normal innovations. Unit root tests based on M-estimators exhibit the same behavior. The problem occurs because the test statistics are transformed to obtain computationally convenient critical values. I describe a convenient way to compute critical values without transforming the test statistics. The resulting tests are almost as powerful as least…

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Testing for the Cointegrating Rank of a VAR Process with Level Shift at Unknown Time

A systems cointegration rank test is proposed that is applicable for vector autoregressive (VAR) processes with a structural shift at unknown time. The structural shift is modeled as a simple shift in the level of the process. It is proposed to estimate the break date first on the basis of a full unrestricted VAR model. Two alternative estimators are considered and their asymptotic properties are derived. In the next step the deterministic part of the process including the…

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GMM Estimation of Autoregressive Roots Near Unity with Panel Data

This paper investigates a generalized method of moments (GMM) approach to the estimation of autoregressive roots near unity with panel data and incidental deterministic trends. Such models arise in empirical econometric studies of firm size and in dynamic panel data modeling with weak instruments. The two moment conditions in the GMM approach are obtained by constructing bias corrections to the score functions under OLS and GLS detrending, respectively. It is shown that the…

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More powerful panel data unit root tests with an application to mean reversion in real exchange rates

更高功效的面板单位根检验及其实际汇率均值回复应用

Abstract Unit root tests, seeking mean or trend reversion, are frequently applied to panel data. We show that more powerful variants of commonly applied tests are readily available. Moreover, power gains persist when the modifications are applied to bootstrap procedures that may be employed when cross‐correlation of a rather general sort among individual panel members is suspected. Copyright © 2004 John Wiley & Sons, Ltd.

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ON TESTS FOR DOUBLE DIFFERENCING: METHODS OF DEMEANING AND DETRENDING AND THE ROLE OF INITIAL VALUES

二次差分检验:去均值、去趋势方法与初始值的作用

In this paper we investigate the impact that starting values have upon the double differencing tests of Hasza and Fuller (1979, Annals of Statistics 7, 1106–1120) and Sen and Dickey (1987, Journal of Business and Economic Statistics 5, 463–473), based on ordinary least squares (OLS) and simple symmetric least squares (SSLS) estimation, respectively. We demonstrate that, contrary to what is observed for conventional unit root tests, when based on data that have been demeaned,…

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OPTIMAL VERSUS ROBUST INFERENCE IN NEARLY INTEGRATED NON-GAUSSIAN MODELS

近积分非高斯模型中的最优推断与稳健推断

Elliott, Rothenberg, and Stock (1996, Econometrica 64, 813–836) derive a class of point-optimal unit root tests in a time series model with Gaussian errors. Other authors have proposed “robust” tests that are not optimal for any model but perform well when the error distribution has thick tails. I derive a class of point-optimal tests for models with non-Gaussian errors. When the true error distribution is known and has thick tails, the point-optimal tests are generally more…

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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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Standard error correction in two‐stage estimation with nested samples

嵌套样本两阶段估计的标准误修正

Data at different levels of aggregation are often used in two-stage estimation, with estimates obtained at the higher level of aggregation entering the estimation at the lower level of aggregation. An example is customers within markets: first-stage estimates on market data provide variables that enter the second-stage model on customers. We derive the asymptotic covariance matrix of the second-stage estimates for situations such as these. We implement the formulae in the…

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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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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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Bootstrap Unit Root Tests

Bootstrap 单位根检验

We consider the bootstrap unit root tests based on finite order autoregressive integrated models driven by iid innovations, with or without deterministic time trends. A general methodology is developed to approximate asymptotic distributions for the models driven by integrated time series, and used to obtain asymptotic expansions for the Dickey–Fuller unit root tests. The second-order terms in their expansions are of stochastic orders Op(n−1/4) and Op(n−1/2), and involve…

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Cointegration in Fractional Systems with Unknown Integration Orders

积分阶数未知的分数系统中的协整

Cointegrated bivariate nonstationary time series are considered in a fractional context, without allowance for deterministic trends. Both the observable series and the cointegrating error can be fractional processes. The familiar situation in which the respective integration orders are 1 and 0 is nested, but these values have typically been assumed known. We allow one or more of them to be unknown real values, in which case Robinson and Marinucci (2001, 2003) have justified…

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An Empirical Analysis of Analysts' Target Prices: Short‐term Informativeness and Long‐term Dynamics

分析师目标价的实证分析:短期信息含量与长期动态

Abstract Using a large database of analysts' target prices issued over the period 1997–1999, we examine short‐term market reactions to target price revisions and long‐term comovement of target and stock prices. We find a significant market reaction to the information contained in analysts' target prices, both unconditionally and conditional on contemporaneously issued stock recommendation and earnings forecast revisions. Using a cointegration approach, we analyze the…

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Bayes Estimates of Markov Trends in Possibly Cointegrated Series

可能协整序列中马尔可夫趋势的贝叶斯估计

Stylized facts show that average growth rates of U.S. per capita consumption and income differ in recession and expansion periods. Because a linear combination of such series does not have to be a constant mean process, standard cointegration analysis between the variables to examine the permanent income hypothesis may not be valid. To model the changing growth rates in both series, we introduce a multivariate Markov trend model that accounts for different growth rates in…

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SOME LIMIT THEORY FOR AUTOCOVARIANCES WHOSE ORDER DEPENDS ON SAMPLE SIZE

滞后阶数随样本量变化的自协方差极限理论

In this paper we provide some weak convergence results for sample statistics of the product of a variable with its kth-order lag. We assume the variable is a stationary vector that can be represented by linear process, and the lag length k is allowed to be a function of the sample size. Employing the Beveridge–Nelson decomposition, we derive a new functional central limit theorem for this situation and establish related stochastic integral convergence results. We then…

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Semiparametric Estimation of Multivariate Fractional Cointegration

多元分数协整的半参数估计

We consider the semiparametric estimation of fractional cointegration in a multivariate process of cointegrating rank r > 0. We estimate the cointegrating relationships by the eigenvectors corresponding to the r smallest eigenvalues of an averaged periodogram matrix of tapered, differenced observations. The number of frequencies m used in the periodogram average is held fixed as the sample size grows. We first show that the averaged periodogram matrix converges in…

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ASYMPTOTIC INFERENCE FOR UNIT ROOT PROCESSES WITH GARCH(1,1) ERRORS

具有 GARCH(1,1) 误差的单位根过程渐近推断

This paper investigates the so-called one-step local quasi–maximum likelihood estimator for the unit root process with GARCH(1,1) errors. When the scaled conditional errors (the ratio of the disturbance to the conditional standard deviation) follow a symmetric distribution, the asymptotic distribution of the estimated unit root is derived only under the second-order moment condition. It is shown that this distribution is a functional of a bivariate Brownian motion as in Ling…

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