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非平稳分数单位根AI 解读

This paper deals with a scalar I ( d ) process { y j }, where the integration order d is any real number. Under this setting, we first explore asymptotic properties of various statistics associated with { y j }, assuming that d is known and is greater than or equal to ½. Note that { y j } becomes stationary when d < ½, whose case is not our concern here. It turns out that the case of d = ½ needs a separate treatment from d > ½. We then consider, under the normality…

具有分数单整误差的协整时间序列渐近推断AI 解读

Vector valued autoregressive models with fractionally integrated errors are considered. The possibility of the coefficient matrix of the model having eigenvalues with absolute values equal or close to unity is included. Quadratic approximation to the log-likelihood ratios in the vicinity of auxiliary estimators of the parameters is obtained and used to make a rough identification of the approximate unit eigenvalues, including complex ones, together with their multiplicities.…

协整回归中的有效去趋势AI 解读

This paper studies efficient detrending in cointegrating regression and develops modified tests for cointegration that use efficient detrending procedures. Asymptotics for these tests are derived. Monte Carlo experiments are conducted to evaluate the detrending procedures in finite samples and to compare tests for cointegration based on different detrending procedures. The limit theory allows for increasingly remote initial condition effects as the sample size goes to…

具有多种隐含单位根的多元时间序列：第二部分AI 解读

This paper extends the statistical results obtained by Gregoir and Laroque (1994, Journal of Econometrics 63, 183–214). It develops statistical tools to analyze multivariate time series that can be represented under an autoregressive equation of finite order with various polynomial error correction terms at various frequencies with possibly a non-null deterministic part as introduced by Gregoir (1999, Econometric Theory 15, 435–468). We propose an estimation procedure that…

具有多种隐含单位根的多元时间序列：第一部分AI 解读

Following the approach proposed by Gregoir and Laroque (1993, Econometric Theory 9, 329–342), we consider a class of multivariate processes that, when differenced enough, yields covariance stationary processes whose determinant of the matrix series associated with their Wold representation has various unit roots with various orders of multiplicity we restrict to be integers. A representation theorem is provided that involves different polynomial error correction terms at…

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贝叶斯套利阈值分析AI 解读

A Bayesian estimation procedure is developed for estimating multiple-regime (multiple-threshold) error-correction models appropriate for deviations from financial arbitrage relationships. This approach has clear advantages over classical stepwise threshold autoregressive analysis. Unlike many other applications of threshold models, the knowledge of some costs involved in setting up arbitrage positions allows us to specify an informative prior. To illustrate the Bayesian…

含平稳回归变量的VAR模型协整秩推断AI 解读

The issue of including stationary explanatory variables is addressed in the vector autoregressive (VAR) model, when testing for cointegration rank. It is shown that simply in-cluding stationary explanatory variables as extra regressors will lead to nuisance parameters in the asymptotic distribution of the trace statistic for cointegration rank. The nuisance parame-ters are characterized as canonical correlations between the common trends (which in this case also involve the…

动态异质面板的混合均值组估计AI 解读

It is now quite common to have panels in which both T, the number of time series observations, and N, the number of groups, are quite large and of the same order of magnitude. The usual practice is either to estimate N separate regressions and calculate the coefficient means, which we call the mean group (MG) estimator, or to pool the data and assume that the slope coefficients and error variances are identical. In this article we propose an intermediate procedure, the…

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面板数据中的伪回归与残差型协整检验AI 解读

In the first half of the paper I study spurious regressions in panel data. Asymptotic properties of the least-squares dummy variable (LSDV) estimator and other conventional statistics are examined. The asymptotics of LSDV estimator are different from those of the spurious regression in the pure time-series. This has an important consequence for residual-based cointegration tests in panel data, because the null distribution of residual-based cointegration tests depends on the…

资产收益波动率的单位根检验AI 解读

It is now well established that the volatility of asset returns is time varying and highly persistent. One leading model that is used to represent these features of the data is the stochastic volatility model. The researcher may test for non‐stationarity of the volatility process by testing for a unit root in the log‐squared time series. This strategy for inference has many advantages, but is not followed in practice because these unit root tests are known to have very poor…

季节性非平稳时间序列中的共同周期AI 解读

This paper extends the notion of common cycles to quarterly time series having unit roots both at the zero and seasonal frequencies. It is shown that common cycles are present in the Hylleberg–Engle–Granger–Yoo decomposition of these series when there exists a linear combination of their seasonal differences which follows an MA process of order, at most, three. The pitfalls of seasonal adjustment for common cycles analysis are also documented. Inference on common cycles in…

季节性非平稳时间序列中的共同周期AI 解读

This paper extends the notion of common cycles to quarterly time series having unit roots both at the zero and seasonal frequencies. It is shown that common cycles are present in the Hylleberg-Engle-Granger-Yoo decomposition of these series when there exists a linear combination of their seasonal differences which follows an MA process of order, at most, three. The pitfalls of seasonal adjustment for common cycles analysis are also documented. Inference on common cycles in…

资产收益波动率的单位根检验AI 解读

It is now well established that the volatility of asset returns is time varying and highly persistent. One leading model that is used to represent these features of the data is the stochastic volatility model. The researcher may test for non-stationarity of the volatility process by testing for a unit root in the log-squared time series. This strategy for inference has many advantages, but is not followed in practice because these unit root tests are known to have very poor…

误差修正机制的非对称生成器及其在银行抵押贷款利率动态中的应用AI 解读

Empirical evidence supports asymmetries in the adjustment of prices, interest rates, and other economic variables. The asymmetry hypothesis, however, is often procedurally difficult to set up and test. This article shows that a wide variety of such mechanisms can be nested within an asymmetry generator, which represents the interactions between the disequilibrium term of an error-correction mechanism and an ancillary driver process. The asymmetry hypothesis can then be…

向量自回归过程中协整向量有效归一化的检验AI 解读

This article develops test procedures for checking the validity of general normalizing restrictions imposed on cointegrating vectors in vector autoregressive processes. Such test procedures are of importance because normalizing restrictions, possibly combined with overidentifying restrictions, are often necessary for a proper interpretation of cointegrating vectors. The null hypothesis of the authors' tests assumes that the employed normalization is valid or, alternatively,…

误差修正机制的非对称性生成器及银行按揭利率动态应用AI 解读

Empirical evidence supports asymmetries in the adjustment of prices, interest rates, and other economic variables. The asymmetry hypothesis, however, is often procedurally difficult to set up and test. This article shows that a wide variety of such mechanisms can be nested within an asymmetry generator, which represents the interactions between the disequilibrium term of an error-correction mechanism and an ancillary driver process. The asymmetry hypothesis can then be…

采用数据依赖模型选择规则的修正平稳性检验AI 解读

We describe some simple methods for improving the performance of stationarity tests (i.e., tests that have a stationary null and a unit-root alternative). Specifically, we increase the rate of convergence of the test under the unit-root alternative from O p(T) to O p (T 2), then suggest an optimal method of selecting the order of the autoregressive component in the fitted autoregressive integrated moving average model on which the test is based. Simulation evidence suggests…

自回归过程的柯西估计量及单位根检验与置信区间AI 解读

For autoregressive processes, we propose new estimators whose pivotal statistics have the standard normal limiting distribution for all ranges of the autoregressive parameters. The proposed estimators are approximately median unbiased. For seasonal time series, the new estimators give us unit root tests that have limiting normal distribution regardless of period of the seasonality. Using the estimators, confidence intervals of the autoregressive parameters are constructed. A…

单位根检验统计量的校正因子AI 解读

Despite the fact that it is not correct to speak of Bartlett corrections in the case of nonstationary time series, this paper shows that a Bartlett-type correction to the likelihood ratio test for a unit root can be an effective tool to control size distortions. Using well-known formulae, we obtain second-order (numerical) approximations to the moments and cumulants of the likelihood ratio, which makes it possible to calculate a Bartlett-type factor. It turns out that the…

随机回归模型的残差经验过程及时间序列应用AI 解读

Motivated by Gaussian tests for a time series, we are led to investigate the asymptotic behavior of the residual empirical processes of stochastic regression models. These models cover the fixed design regression models as well as general AR$(q)$ models. Since the number of the regression coeffi-cients is allowed to grow as the sample size increases, the obtained results are also applicable to nonlinear regression and stationary AR$(\infty)$ models. In this paper, we first…

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