THE APPROXIMATE MOMENTS OF THE LEAST SQUARES ESTIMATOR FOR THE STATIONARY AUTOREGRESSIVE MODEL UNDER A GENERAL ERROR DISTRIBUTION
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Publication:2886973
DOI10.1017/S0266466607070405zbMath1237.62110OpenAlexW2162265815MaRDI QIDQ2886973
Publication date: 14 May 2012
Published in: Econometric Theory (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1017/s0266466607070405
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10) Stationary stochastic processes (60G10)
Related Items (9)
Joint confidence sets for structural impulse responses ⋮ Improved variance estimation of maximum likelihood estimators in stable first-order dynamic regression models ⋮ Impulse response matching estimators for DSGE models ⋮ Higher-order asymptotic expansions of the least-squares estimation bias in first-order dynamic regression models ⋮ Improving the estimation and predictions of small time series models ⋮ Bias in the estimation of the mean reversion parameter in continuous time models ⋮ Jackknife estimation of stationary autoregressive models ⋮ Expectation of quadratic forms in normal and nonnormal variables with applications ⋮ Least Squares Bias in Time Series with Moderate Deviations from a Unit Root
Cites Work
- A comparison of minimum MSE and maximum power for the nearly integrated non-Gaussian model
- The exact moments of OLS in dynamic regression models with non-normal errors
- The exact moments of the least squares estimator for the autoregressive model
- Properties of shrinkage estimators in linear regression when disturbances are not normal
- The Bias and Moment Matrix of the General k-Class Estimators of the Parameters in Simultaneous Equations
- Testing for Unit Roots: 2
- Approximations to Some Finite Sample Distributions Associated with a First-Order Stochastic Difference Equation
- Asymptotic expansions for the mean and variance of the serial correlation coefficient
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