arXiv subjects

Salvador Pueyo

Publications and source records attributed to Salvador Pueyo.

5 recordsLinked to original sources

arXiv2019

Limits to green growth and the dynamics of innovation

Central to the official "green growth" discourse is the conjecture that absolute decoupling can be achieved with certain market instruments. This paper evaluates this claim focusing on the role of technology, while changes in GDP composition are treated elsewhere. Some fundamental difficulties for absolute decoupling, referring specifically to thermodynamic costs, are identified through a stylized model based on empirical knowledge on innovation and learning. Normally, monetary costs decrease more slowly than production grows, and this is unlikely to change should monetary costs align with thermodynamic costs, except, potentially, in the transition after the price reform. Furthermore, thermodynamic efficiency must eventually saturate for physical reasons. While this model, as usual, introduces technological innovation just as a source of efficiency, innovation also creates challenges: therefore, attempts to sustain growth by ever-accelerating innovation collide also with the limited reaction capacity of people and institutions. Information technology could disrupt innovation dynamics in the future, permitting quicker gains in eco-efficiency, but only up to saturation and exacerbating the downsides of innovation. These observations suggest that long-term sustainability requires much deeper transformations than the green growth discourse presumes, exposing the need to rethink scales, tempos and institutions, in line with ecological economics and the degrowth literature.

econ.TH↗

arXiv2019

Growth, degrowth, and the challenge of artificial superintelligence

The implications of technological innovation for sustainability are becoming increasingly complex with information technology moving machines from being mere tools for production or objects of consumption to playing a role in economic decision making. This emerging role will acquire overwhelming importance if, as a growing body of literature suggests, artificial intelligence is underway to outperform human intelligence in most of its dimensions, thus becoming "superintelligence". Hitherto, the risks posed by this technology have been framed as a technical rather than a political challenge. With the help of a thought experiment, this paper explores the environmental and social implications of superintelligence emerging in an economy shaped by neoliberal policies. It is argued that such policies exacerbate the risk of extremely adverse impacts. The experiment also serves to highlight some serious flaws in the pursuit of economic efficiency and growth per se, and suggests that the challenge of superintelligence cannot be separated from the other major environmental and social challenges, demanding a fundamental transformation along the lines of degrowth. Crucially, with machines outperforming them in their functions, there is little reason to expect economic elites to be exempt from the threats that superintelligence would pose in a neoliberal context, which opens a door to overcoming vested interests that stand in the way of social change toward sustainability and equity.

cs.CY↗

arXiv2014

Algorithm for the maximum likelihood estimation of the parameters of the truncated normal and lognormal distributions

This paper describes a simple procedure to estimate the parameters of the univariate truncated normal and lognormal distributions by maximum likelihood. It starts from a reparameterization of the lognormal that was previously introduced by the author and is especially useful when the lognormal is close to a power law, which is a limiting case of the first distribution. One of the new parameters quantifies the distance from the power law, and vanishes when the power law gives a sufficient description of the data. At this point, the other parameter equals the exponent of the power law. In contrast, when using the standard parameterization, the parameters of the lognormal diverge in the neighborhood of the power law. Whether or not we are in this neighborhood, the new parameters have properties that ease the process of estimation.

stat.CO↗

arXiv2013

Idiosyncrasy as an explanation for power laws in nature

Complex systems theory pays much attention to simple mechanisms producing nontrivial patterns, especially power laws. However, power laws with exponent close to one also result from complex mixtures of mechanisms that, in isolation, would not necessarily give this type of distribution. Probably, both paths to the power law are relevant in nature. The second gives a plausible explanation for some instances of power laws emerging in extremely complex systems, such as ecosystems.

nlin.AO↗

arXiv2013

Is it a power law distribution? The case of economic contractions

One of the first steps to understand and forecast economic downturns is identifying their frequency distribution, but it remains uncertain. This problem is common in phenomena displaying power-law-like distributions. Power laws play a central role in complex systems theory; therefore, the current limitations in the identification of this distribution in empirical data are a major obstacle to pursue the insights that the complexity approach offers in many fields. This paper addresses this issue by introducing a reliable methodology with a solid theoretical foundation, the Taylor Series-Based Power Law Range Identification Method. When applied to time series from 39 countries, this method reveals a well-defined power law in the relative per capita GDP contractions that span from 5.53% to 50%, comprising 263 events. However, this observation does not suffice to attribute recessions to some specific mechanism, such as self-organized criticality. The paper highlights a set of points requiring more study so as to discriminate among models compatible with the power law, as needed to develop sound tools for the management of recessions.

nlin.AO↗