Statistical analysis and stochastic interest rate modelling for valuing the future with implications in climate change mitigation
Josep Perell\'o, Miquel Montero, Jaume Masoliver, J. Doyne Farmer,, John Geanakoplos

TL;DR
This paper uses stochastic interest rate models based on historical data from 14 countries to assess long-term discount rates, highlighting the importance of low discounting in climate change mitigation.
Contribution
It introduces a stochastic modeling approach with Ornstein-Uhlenbeck and other models to analyze real interest rates across multiple countries, emphasizing the prevalence of negative rates and their implications.
Findings
Majority of countries have negative long-term discount rates.
Results support the need for low discounting in climate policy.
Model robustness confirmed across different stochastic models.
Abstract
High future discounting rates favor inaction on present expending 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…
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