Instrumental Variables Estimation of Stationaryand Nonstationary Cointegrating Regressions

Margherita Gerolimetto () and Peter M Robinson

STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE

Abstract: Instrumental variables estimation is classically employed to avoid simultaneousequations bias in a stable environment. Here we use it to improve upon ordinaryleast squares estimation of cointegrating regressions between nonstationaryand/or long memory stationary variables where the integration orders of regressorand disturbance sum to less than 1, as happens always for stationary regressors,and sometimes for mean-reverting nonstationary ones. Unlike in the classicalsituation, instruments can be correlated with disturbances and/or uncorrelated withregressors. The approach can also be used in traditional non-fractionalcointegrating relations. Various choices of instrument are proposed. Finite sampleperformance 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)
Date: 2006-04
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Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Instrumental variables estimation of stationary and non-stationary cointegrating regressions (2006)
Working Paper: Instrumental variables estimation of stationary and nonstationary cointegrating regressions (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:cep:stiecm:500

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