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Breaking the panels: An application to the GDP per capita

允许结构突变的面板平稳性检验:人均GDP应用

This paper proposes a test statistic for the null hypothesis of panel stationarity that allows for the presence of multiple structural breaks. Two different specifications are considered depending on the structural breaks affecting the individual effects and/or the time trend. The model is flexible enough to allow the number of breaks and their position to differ across individuals. The test is shown to have a standard normal limit distribution with a good finite sample…

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Moment approximation for least‐squares estimators in dynamic regression models with a unit root

含单位根动态回归模型中最小二乘估计量的矩近似

To find approximations for bias, variance and mean-squared error of least-squares estimators for all coefficients in a linear dynamic regression model with a unit root, we derive asymptotic expansions and examine their accuracy by simulation. It is found that in this particular context useful expansions exist only when the autoregressive model contains at least one non-redundant exogenous explanatory variable. Surprisingly, the large-sample and small-disturbance asymptotic…

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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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Counts with an endogenous binary regressor: A series expansion approach

We propose an estimator for count data regression models where a binary regressor is endogenously determined. This estimator departs from previous approaches by using a flexible form for the conditional probability function of the counts. Using a Monte Carlo experiment we show that our estimator improves the fit and provides a more reliable estimate of the impact of regressors on the count when compared to alternatives which do restrict the mean to be linear‐exponential. In…

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Bootstrap estimation of covariance matrices via the percentile method

Consistency of the bootstrap second moments does not usually follow from the proofs of consistency of the distribution of the bootstrap. Here it is shown that the convergence of the bootstrap distribution to a normal variate implicitly defines a consistent estimator for the asymptotic second moments. The estimator is based on the L-estimation of the scale parameter of arbitrary linear combinations of the bootstrap sequence and uses Classical Minimum Distance techniques to…

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Vector equilibrium correction models with non‐linear discontinuous adjustments

Cointegration is studied for a non‐linear autoregressive process characterized by discontinuous and regime‐dependent equilibrium or error correction. Here the disequilibrium, as measured by the norm of linear ‘stable’ or cointegrating relations, determines the regime and hence the equilibrium correction of the process. Importantly, switching between regimes is thereby allowed to be caused endogenously. The transition function may be either observable as in, e.g. threshold…

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A comparison of autoregressive distributed lag and dynamic OLS cointegration estimators in the case of a serially correlated cointegration error

协整误差序列相关时ADL与动态OLS协整估计量的比较

This paper deals with a family of parametric, single-equation cointegration estimators that arise in the context of the autoregressive distributed lag (ADL) models. We particularly focus on a subclass of the ADL models, those that do not involve lagged values of the dependent variable, referred to as augmented static (AS) models. The general ADL and the restricted AS models give rise to the ADL and dynamic OLS (DOLS) estimators, respectively. The relative performance of…

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Forecasting in dynamic factor models using Bayesian model averaging

动态因子模型中的贝叶斯模型平均预测

This paper considers the problem of forecasting in dynamic factor models using Bayesian model averaging. Theoretical justifications for averaging across models, as opposed to selecting a single model, are given. Practical methods for implementing Bayesian model averaging with factor models are described. These methods involve algorithms which simulate from the space defined by all possible models. We discuss how these simulation algorithms can also be used to select the…

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Testing for duration dependence in economic cycles

经济周期持续期依赖的检验

In this paper, we discuss discrete-time tests for duration dependence. Two of our test statistics are new to the econometrics literature, and we make an important distinction between the discrete and continuous time frameworks. We then test for duration dependence in business and stock market cycles, and compare our results for business cycles with those of Diebold and Rudebusch (1990, 1991). Our null hypothesis is that once an expansion or contraction has exceeded some…

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Asymptotic confidence intervals for impulse responses of near‐integrated processes

近积分过程脉冲响应的渐近置信区间

Many economic time series are characterized by high persistence which typically requires nonstandard limit theory for inference. This paper proposes a new method for constructing confidence intervals for impulse response functions and half-lives of nearly non-stationary processes. It is based on inverting the acceptance region of the likelihood ratio statistic under a sequence of null hypotheses of possible values for the impulse response or the half-life. This paper shows…

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On the forecasting ability of ARFIMA models when infrequent breaks occur

低频结构突变下 ARFIMA 模型的预测能力

Recent research has focused on the links between long memory and structural breaks, stressing the memory properties that may arise in models with parameter changes. In this paper, we question the implications of this result for forecasting. We contribute to this research by comparing the forecasting abilities of long memory and Markov switching models. Two approaches are employed: the Monte Carlo study and an empirical comparison, using the quarterly Consumer Price inflation…

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More on testing exact rational expectations in cointegrated vector autoregressive models: Restricted constant and linear term

协整向量自回归中精确理性预期的进一步检验:受限常数项与线性项

In this note we develop the likelihood-ratio test for some linear restrictions implied by rational expectations hypotheses in a cointegrated vector autoregressive model for I(1) variables, when the constant or linear term is restricted to the cointegration space. Copyright Royal Economic Socciety 2004

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Response error in a transformation model with an application to earnings‐equation estimation*

变换模型中的响应误差及其在收入方程估计中的应用

This paper considers estimation of a transformation model in which the transformed dependent variable is subject to classical measurement error. We consider cases in which the transformation function is known and unspecified. In special cases (e.g. log and square-root transformations), least-squares or non-linear least-squares estimators are applicable. A flexible approximation approach (based on Taylor expansion) is proposed for a parametrized transformation function (like…

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Testing linearity in cointegrating smooth transition regressions

协整平滑转换回归中的线性检验

This paper develops statistical tests that can be used to test linearity in cointegrating smooth transition regression models. These tests extend previous similar tests by considering I(1) regressors instead of stationary or mixing regressors and they also allow for more general transition mechanisms than in previous studies. As is typical in cointegrating regressions, the regressors and errors of the model can be serially and contemporaneously correlated. In order to allow…

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Identification of causal factor models of stationary time series

平稳时间序列因果因子模型的识别

We consider identification of a class of dynamic factor model. We show that identification holds under reasonably general conditions. The results apply to many of the dynamic factor models that have appeared in the literature and to many worthwhile generalizations of those models. Copyright Royal Economic Socciety 2004

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Cointegration analysis in the presence of outliers

存在异常值时的协整分析

The effects of innovational outliers and additive outliers in cointegrated vector autoregressive models are examined and it is analyzed how outliers can be modelled with dummy variables. A Monte Carlo simulation illustrates that additive outliers are more distortionary than innovational outliers, and misspecified dummies may distort inference on the cointegration rank in finite samples. These findings question the common practice in applied cointegration analyses of…

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Asymptotic inference results for multivariate long‐memory processes

多元长记忆过程的渐近推断结果

In this paper, we extend the well-known Sims, Stock and Watson (SSW) (Sims et al. 1990; Econometrica 56, 113-44), analysis on estimation and testing in vector autoregressive process (VARs) with integer unit roots and deterministic components to a more general set-up where non-stationary fractionally integrated (NFI) processes are considered. In particular, we focus on partial VAR models where the conditioning variables are NFI since this is the only finite-lag VAR model…

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Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques*

利用桥采样估计混合模型与马尔可夫转换模型的边际似然

This paper discusses the problem of estimating marginal likelihoods for mixture and Markov switching model. Estimation is based on the method of bridge sampling (Meng and Wong 1996; Statistica Sinica 11, 552-86.) where Markov Chain Monte Carlo (MCMC) draws from the posterior density are combined with an i.i.d. sample from an importance density. The importance density is constructed in an unsupervised manner from the MCMC draws using a mixture of complete data posteriors.…

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Efficient inference in multivariate fractionally integrated time series models

A computationally simple maximum likelihood procedure for multivariate fractionally integrated time series models is introduced. This allows, e.g., efficient estimation of the memory parameters of fractional models or efficient testing of the hypothesis that two or more series are integrated of the same possibly fractional order. In particular, we show the existence of a local time domain maximum likelihood estimator and its asymptotic normality, and under Gaussianity…

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Linearity tests and stationarity

线性检验与平稳性

This paper shows that the asymptotic distributions of LM-type linearity tests against Smooth Transition Autoregressive (STAR) models, in the presence of a unit root, are non-standard and using standard χ2 critical values may lead to incorrect inference as the tails of the distribution of tests will be thicker than the χ2. This finding also indicates that one needs to test for stationarity prior to applying linearity tests. Copyright Royal Economic Socciety 2004

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Least squares estimation and tests of breaks in mean and variance under misspecification

误设下均值与方差断点的最小二乘估计及检验

In this paper we investigate the consequences of misspecification on the large sample properties of change-point estimators and the validity of tests of the null hypothesis of linearity versus the alternative of a structural break. Specifically this paper concentrates on the interaction of structural breaks in the mean and variance of a time series when either of the two is omitted from the estimation and inference procedures. Our analysis considers the case of a break in…

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Estimation with weak instruments: Accuracy of higher‐order bias and MSE approximations

弱工具变量下的估计:高阶偏误与均方误差近似的准确性

In this paper, we consider parameter estimation in a linear simultaneous equations model. It is well known that two-stage least squares (2SLS) estimators may perform poorly when the instruments are weak. In this case 2SLS tends to suffer from the substantial small sample biases. It is also known that LIML and Nagar-type estimators are less biased than 2SLS but suffer from large small sample variability. We construct a bias-corrected version of 2SLS based on the Jackknife…

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Two‐stage quantile regression when the first stage is based on quantile regression

第一阶段基于分位数回归的两阶段分位数回归

We present the asymptotic properties of double-stage quantile regression estimators with random regressors, where the first stage is based on quantile regressions with the same quantile as in the second stage, which ensures robustness of the estimation procedure. We derive invariance properties with respect to the reformulation of the dependent variable. We propose a consistent estimator of the variance--covariance matrix of the new estimator. Finally, we investigate finite…

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