Carregant...
Miniatura

Tipus de document

Article

Versió

Versió publicada

Data de publicació

Llicència de publicació

cc by (c) IOP Publishing Ltd. and SISSA Medialab srl, 2020
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/172554

Statistical analysis and stochastic interest rate modeling for valuing the future with implications in climate change mitigation

Títol de la revista

Director/Tutor

ISSN de la revista

Títol del volum

Resum

High future discounting rates favor inaction on present expend- ing while lower rates advise for a more immediate political action. A possible approach to this key issue in global economy is to take historical time series for nominal interest rates and inflation, and to construct then real interest rates and finally obtaining the resulting discount rate according to a specific stochastic model. Extended periods of negative real interest rates, in which inflation dominates over nominal rates, are commonly observed, occurring in many epochs and in all countries. This feature leads us to choose a well-known model in statistical physics, the Ornstein-Uhlenbeck model, as a basic dynamical tool in which real interest rates randomly fluctuate and can become negative, even if they tend to revert to a positive mean value. By covering 14 countries over hundreds of years we suggest different scenarios and include an error analysis in order to consider the impact of statistical uncertainty in our results. We find that only 4 of the countries have positive long-run discount rates while the other ten coun- tries have negative rates. Even if one rejects the countries where hyperinflation has occurred, our results support the need to consider low discounting rates. The results provided by these fourteen countries significantly increase the prior- ity of confronting global actions such as climate change mitigation. We finally extend the analysis by first allowing for fluctuations of the mean level in the Ornstein-Uhlenbeck model and secondly by considering modified versions of the Feller and lognormal models. In both cases, results remain basically unchanged thus demonstrating the robustness of the results presented.

Citació

Citació

PERELLÓ, Josep, MONTERO TORRALBO, Miquel, MASOLIVER, Jaume, FARMER, J. doyne, GEANAKOPLOS, John. Statistical analysis and stochastic interest rate modeling for valuing the future with implications in climate change mitigation. _Journal of Statistical Mechanics: Theory and Experiment_. 2020. Vol. 2020, núm. 043210-1-043210-22. [consulta: 24 de gener de 2026]. ISSN: 1742-5468. [Disponible a: https://hdl.handle.net/2445/172554]

Exportar metadades

JSON - METS

Compartir registre