Limit Theory for M-Estimates in an Integrated Infinite Variance

Keith Knight

Econometric Theory, 1991, vol. 7, issue 02, pages 200-212

Abstract: We consider the limiting distributions of M-estimates of an parameter when the observations come from an integrated linear process with infinite variance innovations. It is shown that M-estimates are, asymptotically, infinitely more efficient than the least-squares estimator (in the sense that they have a faster rate of convergence) and are conditionally asymptotically normal.

Date: 1991

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Persistent link: http://EconPapers.repec.org/RePEc:cup:etheor:v:7:y:1991:i:02:p:200-212_00

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