Second-Order Approximation For Adaptive Regression Estimators
AbstractWe derive asymptotic expansions for semiparametric adaptive regression estimators. In particular, we derive the asymptotic distribution of the second-order effect of an adaptive estimator in a linear regression whose error density is of unknown functional form. We then show how the choice of smoothing parameters influences the estimator through higher order terms. A method of bandwidth selection is defined by minimizing the second-order mean squared error. We examine both independent and time series regressors; we also extend our results to a t-statistic. Monte Carlo simulations confirm the second order theory and the usefulness of the bandwidth selection method.
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Bibliographic InfoArticle provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 17 (2001)
Issue (Month): 05 (October)
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Other versions of this item:
- Oliver Linton & Zhijie Xiao, 2001. "Second-order approximation for adaptive regression estimators," LSE Research Online Documents on Economics 317, London School of Economics and Political Science, LSE Library.
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
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- Cattaneo, Matias D. & Crump, Richard K. & Jansson, Michael, 2012.
"Optimal inference for instrumental variables regression with non-Gaussian errors,"
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- Hidehiko Ichimura & Oliver Linton, 2003.
"Asymptotic Expansions for Some Semiparametric Program Evaluation Estimators,"
STICERD - Econometrics Paper Series
/2003/451, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Hidehiko Ichimura & Oliver Linton, 2001. "Asymptotic expansions for some semiparametric program evaluation estimators," CeMMAP working papers CWP04/01, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Tamaki, Kenichiro, 2007. "Second order optimality for estimators in time series regression models," Journal of Multivariate Analysis, Elsevier, vol. 98(3), pages 638-659, March.
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