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The Asymptotic Efficiency Of Cointegration Estimators Under Temporal Aggregation

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Chambers, Marcus J.

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Abstract

This paper examines the effects of temporal aggregation on the asymptotic variances of estimators in cointegrated systems. Two important findings are obtained. First, estimators based on flow data alone are more efficient than when the data are all stocks or a mixture of stocks and flows. Second, estimators based on flow data are as efficient as when the data are recorded continuously. A method of improving efficiency with stock variables is also proposed, and an empirical illustration of the method is provided in the context of long-run money demand regressions.I thank Roy Bailey, Rex Bergstrom, Roderick McCrorie, a co-editor, and two anonymous referees for helpful comments. I also thank Katsumi Shimotsu for help with some data issues. None of these individuals are implicated, however, in any possible shortcomings of this paper. The financial support provided by the ESRC under grant R000221818 is gratefully acknowledged.

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File URL: http://journals.cambridge.org/abstract_S0266466603191037
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Publisher Info
Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 19 (2003)
Issue (Month): 01 (February)
Pages: 49-77
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Handle: RePEc:cup:etheor:v:19:y:2003:i:01:p:49-77_19

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  1. Marcus J. Chambers, 2001. "Cointegration and Sampling Frequency," Economics Discussion Papers 531, University of Essex, Department of Economics. [Downloadable!]
  2. Chambers, M.J. & McCrorie, J.R., 2004. "Frequency domain gaussian estimation of temporally aggregated cointegrated systems," Discussion Paper 40, Tilburg University, Center for Economic Research. [Downloadable!]
  3. Enrique Sentana & Antonio Diez de los Rios, 2007. "Testing Uncovered Interest Parity: A Continuous-Time Approach," Working Papers wp2007_0714, CEMFI. [Downloadable!]
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This page was last updated on 2009-12-20.


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