Instrumental variables estimation of stationary and nonstationary cointegrating regressions

Peter M. Robinson and Margherita Gerolimetto ()

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: Instrumental variables estimation is classically employed to avoid simultaneous equations bias in a stable environment. Here we use it to improve upon ordinary least squares estimation of cointegrating regressions between nonstationary and/or long memory stationary variables where the integration orders of regressor and disturbance sum to less than 1, as happens always for stationary regressors, and sometimes for mean-reverting nonstationary ones. Unlike in the classical situation, instruments can be correlated with disturbances and/or uncorrelated with regressors. The approach can also be used in traditional non-fractional cointegrating relations. Various choices of instrument are proposed. Finite sample performance is examined.

Keywords: Cointegration; Instrumental variables estimation; I (d) processes (search for similar items in EconPapers)
JEL-codes: C32 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2006-04
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Citations: View citations in EconPapers (4)

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http://eprints.lse.ac.uk/4539/ Open access version. (application/pdf)

Related works:
Journal Article: Instrumental variables estimation of stationary and non-stationary cointegrating regressions (2006)
Working Paper: Instrumental Variables Estimation of Stationaryand Nonstationary Cointegrating Regressions (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:4539

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