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含单位根的门槛自回归模型AI 解读

This paper develops an asymptotic theory of inference for an unrestricted two-regime threshold autoregressive (TAR) model with an autoregressive unit root. We find that the asymptotic null distribution of Wald tests for a threshold are nonstandard and different from the stationary case, and suggest basing inference on a bootstrap approximation. We also study the asymptotic null distributions of tests for an autoregressive unit root, and find that they are nonstandard and…

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样本划分与门槛估计AI 解读

Threshold models have a wide variety of applications in economics. Direct applications include models of separating and multiple equilibria. Other applications include empirical sample splitting when the sample split is based on a continuously-distributed variable such as firm size. In addition, threshold models may be used as a parsimonious strategy for nonparametric function estimation. For example, the threshold autoregressive model (TAR) is popular in the nonlinear time…

非动态面板中的门槛效应：估计、检验与推断AI 解读

Threshold regression methods are developed for non-dynamic panels with individual-specific fixed effects. Least squares estimation of the threshold and regression slopes is proposed using fixed-effects transformations. A non-standard asymptotic theory of inference is developed which allows construction of confidence intervals and testing of hypotheses. The methods are applied to a 15-year sample of 565 US firms to test whether financial constraints affect investment…

A "grid" bootstrap method is proposed for confidence-interval construction, which has improved performance over conventional bootstrap methods when the sampling distribution depends upon the parameter of interest. The basic idea is to calculate the bootstrap distribution over a grid of values of the parameter of interest and form the confidence interval by the no-rejection principle. Our primary motivation is given by autoregressive models, where it is known that…

结构变化检验的近似渐近 p 值AI 解读

Numerical approximations to the asymptotic distributions of recently proposed tests for structural change are presented. This enables easy yet accurate calculation of asymptotic p-values. Keywords: parameter stability, changepoint models

结构变化检验的近似渐近p值AI 解读

Numerical approximations to the asymptotic distributions of recently proposed tests for structural change are presented. This enables easy yet accurate calculation of asymptotic p values. A GAUSS program is available to perform the computations.

无界、相依且异质数组的随机等度连续性AI 解读

This paper establishes stochastic equicontinuity for classes of mixingales. Attention is restricted to Lipschitz-continuous parametric functions. Unlike some other empirical process theory for dependent data, our results do not require bounded functions, stationary processes, or restrictive dependence conditions. Applications are given to martingale difference arrays, strong mixing arrays, and near-epoch dependent arrays.

原假设下干扰参数未被识别时的统计推断AI 解读

The authors study the asymptotic distribution of econometric tests involving nuisance parameters that are not identified under the null hypotheses. In general, the asymptotic distributions depend upon a large number of unknown parameters. The authors show that a transformation based upon a conditional probability measure yields an asymptotic distribution free of nuisance parameters and they show that this transformation can be easily approximated via simulation. The theory…

存在机制转换的协整模型中基于残差的检验AI 解读

In this paper we examine tests for cointegration which allow for the possibility of regime shifts. We propose ADF-, Zα-, and Zt-type tests designed to test the null of no cointegration against the alternative of cointegration in the presence of a possible regime shift. In particular we consider cases where the intercept and/or slope coefficients have a single break of unknown timing. A formal proof is provided for the limiting distributions of the various tests for the…

重新思考单变量单位根检验：利用协变量提高功效AI 解读

In the context of testing for a unit root in a univariate time series, the convention is to ignore information in related time series. This paper shows that this convention is quite costly, as large power gains can be achieved by including correlated stationary covariates in the regression equation. The paper derives the asymptotic distribution of ordinary least-squares estimates of the largest autoregressive root and its t-statistic. The asymptotic distribution is not the…

非平稳波动率下的回归AI 解读

A new asymptotic theory of regression is introduced for possibly nonstationary time series. The regressors are assumed to be generated by a linear process with martingale difference innovations. The conditional variances of these martingale differences are specified as autoregressive stochastic volatility processes with autoregressive roots that are local to unity. The author finds conditions under which the least squares estimates are consistent and asymptotically normal. A…

季节模式是否随时间保持不变？季节稳定性检验AI 解读

This paper introduces Lagrange multiplier tests of the null hypothesis of no unit roots at seasonal frequencies against the alternative of a unit root at either a single seasonal frequency or a set of seasonal frequencies. The tests complement those of D. Dickey, D. Hasza, and W. Fuller (1984) and S. Hylleberg, et al. (1990), which examine the null of seasonal unit roots. The authors derive an asymptotic distribution theory for the tests and investigate their size and power…

GARCH(1,1) 准最大似然估计量的渐近理论AI 解读

This paper investigates the sampling behavior of the quasi-maximum likelihood estimator of the Gaussian GARCH(1,1) model. The rescaled variable (the ratio of the disturbance to the conditional standard deviation) is not required to be Gaussian nor independent over time, in contrast to the current literature. The GARCH process may be integrated (α + β = 1), or even mildly explosive (α + β > 1). A bounded conditional fourth moment of the rescaled variable is sufficient for the…

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相依异质过程向随机积分的收敛AI 解读

This paper provides conditions to establish the weak convergence of stochastic integrals. The theorems are proved under the assumption that the innovations are strong mixing with uniformly bounded 2-h moments. Several applications of the results are given, relevant for the theories of estimation with I (1) processes, I (2) processes, processes with nonstationary variances, near-integrated processes, and continuous time approximations.

异方差协整AI 解读

This paper develops an asymptotic theory of estimation and inference in ‘cointegrated’ regression models with errors displaying nonstationary variances. Least squares estimates are shown to be consistent at a T12 rate. Hypothesis testing requires the use of a robust covariance matrix estimate, in contrast to earlier work on cointegrated regressions. The inference theory is not nuisance-free, but preliminary investigations indicate that approximation by the normal…

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存在确定性趋势时协整向量的有效估计与检验AI 解读

Estimation and inference in cointegrated models is examined in the presence of deterministic trends in the data. It is suggested that trends be excluded in the levels regression for maximal efficiency. Fully modified test statistics are asymptotically chi-square. A chi-square test for the validity of trend exclusion is presented. The asymptotic distributions of standard cointegration test statistics are shown to depend both upon regressor trends and estimation detrending…

含 I(1) 过程回归中的参数不稳定性检验AI 解读

This article derives the large-sample distributions of Lagrange multiplier (LM) tests for parameter instability against several alternatives of interest in the context of cointegrated regression models. The fully modified estimator of Phillips and Hansen is extended to cover general models with stochastic and deterministic trends. The test statistics considered include the SupF test of Quandt, as well as the LM tests of Nyblom and of Nabeya and Tanaka. It is found that the…

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依赖且异质过程的强大数定律AI 解读

This paper presents maximal inequalities and strong law of large numbers for weakly dependent heterogeneous random variables. Specifically considered are L r mixingales for r > 1, strong mixing sequences, and near epoch dependent (NED) sequences. We provide the first strong law for L r -bounded L r mixingales and NED sequences for 1 > r > 2. The strong laws presented for α-mixing sequences are less restrictive than the laws of McLeish [8].

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