An Evolutionary Algorithm for the Estimation of Threshold Vector Error Correction Models

Makram El-Shagi

No 1/2010, IWH Discussion Papers from Halle Institute for Economic Research (IWH)

Abstract: We develop an evolutionary algorithm to estimate Threshold Vector Error Correction models (TVECM) with more than two cointegrated variables. Since disregarding a threshold in cointegration models renders standard approaches to the estimation of the cointegration vectors inefficient, TVECM necessitate a simultaneous estimation of the cointegration vector(s) and the threshold. As far as two cointegrated variables are considered this is commonly achieved by a grid search. However, grid search quickly becomes computationally unfeasible if more than two variables are cointegrated. Therefore, the likelihood function has to be maximized using heuristic approaches. Depending on the precise problem structure the evolutionary approach developed in the present paper for this purpose saves 90 to 99 per cent of the computation time of a grid search.

Keywords: Strategy; Genetic Algorithm; TVECM; Strategie; Genetischer Algorithmus; Vektorfehlerkorrekturmodelle (search for similar items in EconPapers)
JEL-codes: C32 C61 (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: An evolutionary algorithm for the estimation of threshold vector error correction models (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:iwhdps:iwh-1-10

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