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弱识别下的广义经验似然统计量AI 解读

The central concern of this paper is the provision in a time series moment condition framework of practical recommendations of confidence regions for parameters whose coverage probabilities are robust to the strength or weakness of identification. To this end we develop Pearson-type test statistics based on GEL implied probabilities formed from general kernel smoothed versions of the moment indicators. We also modify the statistics suggested in Guggenberger and Smith (2008)…

基于回归的季节性单位根检验AI 解读

The contribution of this paper is threefold. First, a characterization theorem of the subhypotheses comprising the seasonal unit root hypothesis is presented that provides a precise formulation of the alternative hypotheses associated with regression- based seasonal unit root tests. Second, it proposes regression-based tests for the seasonal unit root hypothesis that allow a general seasonal aspect for the data and are similar both exactly and asymptotically with respect to…

部分、弱与强识别下的广义经验似然估计与检验AI 解读

The purpose of this paper is to describe the performance of generalized empirical likelihood (GEL) methods for time series instrumental variable models specified by nonlinear moment restrictions as in Stock and Wright (2000, Econometrica 68, 1055–1096) when identification may be weak. The paper makes two main contributions. First, we show that all GEL estimators are first-order equivalent under weak identification. The GEL estimator under weak identification is inconsistent…

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经济活动的自动先行指标：欧洲国家GDP增长预测AI 解读

In the construction of a leading indicator model of economic activity, economists must select among a pool of variables which lead output growth. Usually the pool of variables is large and a selection of a subset must be carried out. This paper proposes an automatic leading indicator model which, rather than preselection, uses a dynamic factor model to summarize the information content of a pool of variables. Results using quarterly data for France, Germany, Italy and the…

水平关系分析的界限检验方法AI 解读

Abstract This paper develops a new approach to the problem of testing the existence of a level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend‐ or first‐difference stationary. The proposed tests are based on standard F ‐ and t ‐statistics used to test the significance of the lagged levels of the variables in a univariate equilibrium correction mechanism. The asymptotic…

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局部异方差积分下若干差分平稳检验的功效AI 解读

This article considers the power properties of the McCabe and Tremayne (MT) test for the difference stationarity of a time series. The limiting distribution of the MT test is derived under sequences of locally heteroscedastic and locally explosive autoregressive (AR) alternatives. The limiting distribution of Dickey–Fuller (DF) statistics is also considered under a sequence of locally heteroscedastic alternatives. Whereas the MT test possesses asymptotic power against both…

会计约束下的测量误差：潜在数据的点与区间估计及英国 GDP 应用AI 解读

An econometric methodology is proposed for reconciling inaccurate measures of latent data which are subject to accounting constraints. The method deals with the case in which the measurement errors are serially correlated, generalizing previous contributions. A class of efficient estimators are derived for the latent data. Consistent estimators for the weight matrices applied to the observed information based on a linear regression procedure are obtained together with…

使用有限信息的渐近最优检验与外生性检验AI 解读

By appropriately partitioning the joint hypothesis of weak exogeneity and the maintained overidentifying restrictions in the linear dynamic simultaneous equations model and showing that the component subhypotheses are separable, asymptotically optimal tests for the weak exogeneity hypothesis may be constructed using limited information statistics. A necessary and sufficient condition for the separability of parametric hypotheses of the mixed implicit function and constraint…

替代性渐近最优检验及其在动态设定中的应用AI 解读

A method is presented for generating test statistics which share the same first order asymptotic optimality properties of the classical statistics. Generalizing Neyman's (1959) work, the linearised classical statistic tests restrictions in implicit function form using a parameter estimator which is consistent and asymptotically normally distributed under the alternative hypothesis. By judicious choice of estimator and form of restrictions at which to evaluate the statistic,…