Robinson, Peter M. and Gerolimetto, M. (2006) Instrumental variables estimation of stationary and nonstationary cointegrating regressions. . Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.
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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.
| Item Type: | Monograph (Discussion Paper) |
|---|---|
| Official URL: | http://sticerd.lse.ac.uk |
| Additional Information: | © 2006 the author |
| Divisions: | Economics STICERD |
| Subjects: | H Social Sciences > HB Economic Theory |
| JEL classification: | C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C32 - Time-Series Models |
| Date Deposited: | 28 Apr 2008 15:40 |
| Last Modified: | 11 Dec 2024 18:46 |
| URI: | http://eprints.lse.ac.uk/id/eprint/4539 |
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