We analyse the recurrence (Formula presented.) , where (Formula presented.) is a weighted power mean of (Formula presented.) , which has been proposed to model a class of non-linear forward-looking economic models with bounded rationality. Under suitable hypotheses on weights, we prove the convergence of the sequence (Formula presented.) Then, to simulate a fading memory, we consider exponentially decreasing weights. Since, in this case, the resulting recurrence does not fulfil the hypotheses of the previous convergence theorem, it is studied by reducing it to an equivalent two-dimensional autonomous map, which shares the asymptotic behaviours with a particular one-dimensional map. This allows us to prove that a long memory with sufficiently large weights has a stabilizing effect. Finally, we numerically investigate what happens when the memory ratio is not sufficiently large to provide stability, showing that, depending on the power mean and the memory ratio, either a delayed or early cascade of flip bifurcations occurs.

Bischi, G., CAVALLI, F., & NAIMZADA, A. (2015). Mann iteration with power means. JOURNAL OF DIFFERENCE EQUATIONS AND APPLICATIONS, 21(12), 1212-1233 [10.1080/10236198.2015.1080252].

Mann iteration with power means

CAVALLI, FAUSTO
;
NAIMZADA, AHMAD KABIR
Ultimo
2015

Abstract

We analyse the recurrence (Formula presented.) , where (Formula presented.) is a weighted power mean of (Formula presented.) , which has been proposed to model a class of non-linear forward-looking economic models with bounded rationality. Under suitable hypotheses on weights, we prove the convergence of the sequence (Formula presented.) Then, to simulate a fading memory, we consider exponentially decreasing weights. Since, in this case, the resulting recurrence does not fulfil the hypotheses of the previous convergence theorem, it is studied by reducing it to an equivalent two-dimensional autonomous map, which shares the asymptotic behaviours with a particular one-dimensional map. This allows us to prove that a long memory with sufficiently large weights has a stabilizing effect. Finally, we numerically investigate what happens when the memory ratio is not sufficiently large to provide stability, showing that, depending on the power mean and the memory ratio, either a delayed or early cascade of flip bifurcations occurs.
Articolo in rivista - Articolo scientifico
Forward-looking models; Learning; Mann iterations; Non-autonomous difference equations
English
1212
1233
22
Bischi, G., CAVALLI, F., & NAIMZADA, A. (2015). Mann iteration with power means. JOURNAL OF DIFFERENCE EQUATIONS AND APPLICATIONS, 21(12), 1212-1233 [10.1080/10236198.2015.1080252].
Bischi, G; Cavalli, F; Naimzada, A
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/99657
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