Sieve bootstrap t-tests on long-run average parameters
نویسنده
چکیده
Panel estimators can provide consistent measures of a long-run average parameter even if the individual regressions are spurious. However, the t-test on this parameter is fraught with problems because the limit distribution of the test statistic is non-standard and rather complicated, particularly in panels with mixed (non-)stationary errors. A sieve bootstrap framework is suggested to approximate the distribution of the t-statistic. An extensive Monte Carlo study demonstrates that the bootstrap is quite useful in this context. c © 2007 Elsevier B.V. All rights reserved.
منابع مشابه
Bootstrap-based design of residual control charts
One approach to monitoring autocorrelated data consists of applying a control chart to the residuals of a time series model estimated from process observations. Recent research shows that the impact of estimation error on the run length properties of the resulting charts is not negligible. In this paper a general strategy for implementing residual-based control schemes is investigated. The desi...
متن کاملEstimating MA parameters through factorization of the autocovariance matrix and an MA-sieve bootstrap
A new method to estimate the moving-average (MA) coefficients of a stationary time series is proposed. The new approach is based on the modified Cholesky factorization of a consistent estimator of the autocovariance matrix. Convergence rates are established, and the new estimates are used in order to implement a MA-type sieve bootstrap. Finite-sample simulations corroborate the good performance...
متن کاملUnit Root Inference for Non-Stationary Linear Processes driven by Infinite Variance Innovations∗
The contribution of this paper is two-fold. First, we derive the asymptotic null distribution of the familiar augmented Dickey-Fuller [ADF] statistics in the case where the shocks follow a linear process driven by infinite variance innovations. We show that these distributions are free of serial correlation nuisance parameters but depend on the tail index of the infinite variance process. These...
متن کاملAn Invariance Principle for Sieve Bootstrap in Time Series
This paper establishes an invariance principle applicable for the asymptotic analysis of sieve bootstrap in time series+ The sieve bootstrap is based on the approximation of a linear process by a finite autoregressive process of order increasing with the sample size, and resampling from the approximated autoregression+ In this context, we prove an invariance principle for the bootstrap samples ...
متن کاملInvestigating Regional House Price Convergence in the United States: Evidence from a Pair-wise Approach
In this paper we examine long-run house price convergence across US states using a novel econometric approach advocated by Pesaran (2007) and Pesaran et al. (2009). Our empirical modelling exercise employs a probabilistic test statistic for convergence based on the percentage of unit root rejections among all state house price differentials. Using a sieve bootstrap procedure, we construct confi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Computational Statistics & Data Analysis
دوره 52 شماره
صفحات -
تاریخ انتشار 2008