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The strengths and weaknesses of L2 approximable regressors

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  • Mynbaev, Kairat

Abstract

The most part of the paper is about modeling (or approximating) nonstochastic regressors. Examples of regressors which are (not) L2-approximable are given. Applications to central limit theory and OLS estimator asymptotics are provided.

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File URL: http://mpra.ub.uni-muenchen.de/9056/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 9056.

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Date of creation: 2001
Date of revision:
Handle: RePEc:pra:mprapa:9056

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Related research

Keywords: L2-approximable regressors; linear regression; OLS estimator; central limit theorem; asymptotic theory;

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References

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  1. Eugene Canjels & Mark W. Watson, 1994. "Estimating deterministic trends in the presence of serially correlated errors," Working Paper Series, Macroeconomic Issues 94-19, Federal Reserve Bank of Chicago.
  2. Bai, Jushan & Lumsdaine, Robin L & Stock, James H, 1998. "Testing for and Dating Common Breaks in Multivariate Time Series," Review of Economic Studies, Wiley Blackwell, vol. 65(3), pages 395-432, July.
  3. Timothy J. Vogelsang, 1998. "Trend Function Hypothesis Testing in the Presence of Serial Correlation," Econometrica, Econometric Society, vol. 66(1), pages 123-148, January.
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Cited by:
  1. Mynbaev, Kairat, 2003. "Asymptotic properties of OLS estimates in autoregressions with bounded or slowly growing deterministic trends," MPRA Paper 18448, University Library of Munich, Germany, revised 2005.
  2. Mynbaev, Kairat, 2006. "Asymptotic Distribution of the OLS Estimator for a Mixed Regressive, Spatial Autoregressive Model," MPRA Paper 4411, University Library of Munich, Germany.

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