An Alternative to Stationarization
Michel Juillard ()
No 377, Computing in Economics and Finance 2006 from Society for Computational Economics
For good reasons, it is standard practice to remove trends before linearizing a growth model. This paper explores an alternative strategy that consists in computing local approximations around successive points in the state space. Obviously this is terribly inefficiant it trend removal is feasible, but it makes possible to do local approximation in models that don't allow for trend removal. Among such models one can find models that don't display balanced growth and some models with learning
Keywords: approximation method; growth models (search for similar items in EconPapers)
JEL-codes: C63 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:sce:scecfa:377
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