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Alternative asymptotics and the partially linear model with many regressors

Author(s): Cattaneo, MD; Jansson, M; Newey, WK

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Abstract: © Cambridge University Press 2016. Many empirical studies estimate the structural effect of some variable on an outcome of interest while allowing for many covariates. We present inference methods that account for many covariates. The methods are based on asymptotics where the number of covariates grows as fast as the sample size. We find a limiting normal distribution with variance that is larger than the standard one. We also find that with homoskedasticity this larger variance can be accounted for by using degrees-of-freedom-adjusted standard errors. We link this asymptotic theory to previous results for many instruments and for small bandwidth(s) distributional approximations.
Publication Date: 1-Apr-2018
Citation: Cattaneo, MD, Jansson, M, Newey, WK. (2018). Alternative asymptotics and the partially linear model with many regressors. Econometric Theory, 34 (2), 277 - 301. doi:10.1017/S026646661600013X
DOI: doi:10.1017/S026646661600013X
ISSN: 0266-4666
EISSN: 1469-4360
Pages: 277 - 301
Type of Material: Journal Article
Journal/Proceeding Title: Econometric Theory

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