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INSTRUMENTAL VARIABLE ESTIMATION OF STRUCTURAL VAR MODELS ROBUST TO POSSIBLE NONSTATIONARITY

对潜在非平稳性稳健的结构 VAR 工具变量估计

This paper considers the estimation of dynamic causal effects using a proxy structural vector-autoregressive model with possibly nonstationary regressors. We provide general conditions under which the asymptotic normal approximation remains valid. In this case, the asymptotic variance depends on the persistence property of each series. We further provide a consistent asymptotic covariance matrix estimator that requires neither knowledge of the presistence properties of the…

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Shrinkage Estimation of High-Dimensional Factor Models with Structural Instabilities

存在结构不稳定性的高维因子模型收缩估计

In large-scale panel data models with latent factors the number of factors and their loadings may change over time. Treating the break date as unknown, this article proposes an adaptive group-LASSO estimator that consistently determines the numbers of pre- and post-break factors and the stability of factor loadings if the number of factors is constant. We develop a cross-validation procedure to fine-tune the data-dependent LASSO penalties and show that after the number of…

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Forecasting with factor-augmented regression: A frequentist model averaging approach

因子增广回归预测:频率学派模型平均方法

This paper considers forecast combination with factor-augmented regression. In this framework, a large number of forecasting models are available, varying by the choice of factors and the number of lags. We investigate forecast combination across models using weights that minimize the Mallows and the leave-h-out cross validation criteria. The unobserved factor regressors are estimated by principle components of a large panel with N predictors over T periods. With these…

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Cointegrating rank selection in models with time-varying variance

时变方差模型中的协整秩选择

Reduced rank regression (RRR) models with time varying heterogeneity are considered. Standard information criteria for selecting cointegrating rank are shown to be weakly consistent in semiparametric RRR models in which the errors have general nonparametric short memory components and shifting volatility provided the penalty coefficient Cn→∞ and Cn/n→0 as n→∞. The AIC criterion is inconsistent and its limit distribution is given. The results extend those in Cheng and…

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Semiparametric cointegrating rank selection

半参数协整秩选择

. The limit distribution of the AIC criterion, which is inconsistent, is also obtained. The analysis provides a general limit theory for semiparametric reduced rank regression under weakly dependent errors. The method does not require the specification of a full model, is convenient for practical implementation in empirical work, and is sympathetic with semiparametric estimation approaches to co-integration analysis. Some simulation results on the finite sample performance…

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