STRONG CONSISTENCY RESULTS FOR LEAST SQUARES ESTIMATORS IN GENERAL VECTOR AUTOREGRESSIONS WITH DETERMINISTIC TERMS
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Publication:5697614
DOI10.1017/S0266466605050310zbMath1085.62105MaRDI QIDQ5697614
Publication date: 18 October 2005
Published in: Econometric Theory (Search for Journal in Brave)
sample correlationsdecomposition of processeslargest and smallest eigenvalues of denominator matrices
Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)
Related Items (9)
The empirical process of autoregressive residuals ⋮ Finite time identification in unstable linear systems ⋮ ANALYSIS OF COEXPLOSIVE PROCESSES ⋮ Simulating Properties of the Likelihood Ratio Test for a Unit Root in an Explosive Second-Order Autoregression ⋮ ASYMPTOTIC BEHAVIOR OF THE CUSUM OF SQUARES TEST UNDER STOCHASTIC AND DETERMINISTIC TIME TRENDS ⋮ Representation of Cointegrated Autoregressive Processes with Application to Fractional Processes ⋮ CUMULATED SUM OF SQUARES STATISTICS FOR NONLINEAR AND NONSTATIONARY REGRESSIONS ⋮ Unnamed Item ⋮ ALMOST SURE BOUNDS ON THE ESTIMATION ERROR FOR OLS ESTIMATORS WHEN THE REGRESSORS INCLUDE CERTAIN MFI(1) PROCESSES
Cites Work
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- On the strong approximation of the distributions of estimators in linear stochastic models, I and II: Stationary and explosive AR models
- Estimation of the parameters of stochastic difference equations
- On predictive least squares principles
- Model selection under nonstationarity: Autoregressive models and stochastic linear regression models
- Asymptotic properties of general autoregressive models and strong consistency of least-squares estimates of their parameters
- A BARTLETT CORRECTION FACTOR FOR TESTS ON THE COINTEGRATING RELATIONS
- On Asymptotic Distributions of Estimates of Parameters of Stochastic Difference Equations
- Optimal Inference in Cointegrated Systems
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- The Asymptotic Distribution of Unit Root Tests of Unstable Autoregressive Processes
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