A general method for third-order bias and variance corrections on a nonlinear estimator

DOI10.1016/j.jeconom.2014.07.003zbMath1331.62490OpenAlexW2098954432MaRDI QIDQ2346025

Zhenlin Yang

Publication date: 29 May 2015

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://ink.library.smu.edu.sg/soe_research/1586

zbMATH Keywords

bootstrapMonte Carlostochastic expansionspatial layoutconcentrated estimating equationthird-order biasthird-order variance

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (12)

Exact and higher-order properties of the MLE in spatial autoregressive models, with applications to inference ⋮ Unified \(M\)-estimation of fixed-effects spatial dynamic models with short panels ⋮ Spatial dynamic panel data models with correlated random effects ⋮ Improved likelihood inferences for Weibull regression model ⋮ Indirect inference estimation of higher-order spatial autoregressive models ⋮ The asymptotic distribution of robust maximum likelihood estimator with Huber function for the mixed spatial autoregressive model with outliers ⋮ Saddlepoint Approximations for Spatial Panel Data Models ⋮ Adjusted QMLE for the spatial autoregressive parameter ⋮ Diagnostic tests for homoskedasticity in spatial cross-sectional or panel models ⋮ Approximate least squares estimation for spatial autoregressive models with covariates ⋮ Bias-correction for Weibull common shape estimation ⋮ Higher-order least squares inference for spatial autoregressions

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