Persistent mutual information

We study Persistent Mutual Information (PMI), the information about the past that persists into the future as a function of the length of an intervening time interval. Particularly relevant is the limit of an infinite intervening interval, which we call Permanently Persistent MI. In the logistic and tent maps PPMI is found to be the logarithm of the global periodicity for both the cases of periodic attractor and multi-band chaos. This leads us to suggest that PPMI can be a good candidate for a measure of strong emergence, by which we mean behaviour that can be forecast only by examining a specific realisation. We develop the phenomenology to interpret PMI in systems where it increases indefinitely with resolution. Among those are area-preserving maps. The scaling factor r for how PMI grows with resolution can be written in terms of the combination of information dimensions of the underlying spaces. We identify r with the extent of causality recoverable at a certain resolution, and compute it numerically for the standard map, where it is found to reflect a variety of map features, such as the number of degrees of freedom, the scaling related to existence of different types of trajectories, or even the apparent peak which we conjecture to be a direct consequence of the stickiness phenomenon. We show that in general only a certain degree of mixing between regular and chaotic orbits can result in the observed values of r. Using the same techniques we also develop a method to compute PMI through local sampling of the joint distribution of past and future. Preliminary results indicate that PMI of the Double Pendulum shows some similar features, and that in area-preserving dynamical systems there might be regimes where the joint distribution is multifractal

Absorbing and Shattered Fragmentation Transitions in Multilayer Coevolution

We introduce a coevolution voter model in a multilayer, by coupling a fraction of nodes across two network layers and allowing each layer to evolve according to its own topological temporal scale. When these time scales are the same the dynamics preserve the absorbing-fragmentation transition observed in a monolayer network at a critical value of the temporal scale that depends on interlayer connectivity. The time evolution equations obtained by pair approximation can be mapped to a coevolution voter model in a single layer with an effective average degree. When the two layers have different topological time scales we find an anomalous transition, named shattered fragmentation, in which the network in one layer splits into two large components in opposite states and a multiplicity of isolated nodes. We identify the growth of the number of components as a signature of this anomalous transition. We also find a critical level of interlayer coupling needed to prevent the fragmentation in a layer connected to a layer that does not fragment.Comment: 7 pages, 6 figures, last figure caption includes link to animation

Noise in Coevolving Networks

Coupling dynamics of the states of the nodes of a network to the dynamics of the network topology leads to generic absorbing and fragmentation transitions. The coevolving voter model is a typical system that exhibits such transitions at some critical rewiring. We study the robustness of these transitions under two distinct ways of introducing noise. Noise affecting all the nodes destroys the absorbing-fragmentation transition, giving rise in finite-size systems to two regimes: bimodal magnetisation and dynamic fragmentation. Noise Targeting a fraction of nodes preserves the transitions but introduces shattered fragmentation with its characteristic fraction of isolated nodes and one or two giant components. Both the lack of absorbing state for homogenous noise and the shift in the absorbing transition to higher rewiring for targeted noise are supported by analytical approximations.Comment: 20 page

Dynamical origins of the community structure of multi-layer societies

Social structures emerge as a result of individuals managing a variety of different of social relationships. Societies can be represented as highly structured dynamic multiplex networks. Here we study the dynamical origins of the specific community structures of a large-scale social multiplex network of a human society that interacts in a virtual world of a massive multiplayer online game. There we find substantial differences in the community structures of different social actions, represented by the various network layers in the multiplex. Community size distributions are either similar to a power-law or appear to be centered around a size of 50 individuals. To understand these observations we propose a voter model that is built around the principle of triadic closure. It explicitly models the co-evolution of node- and link-dynamics across different layers of the multiplex. Depending on link- and node fluctuation rates, the model exhibits an anomalous shattered fragmentation transition, where one layer fragments from one large component into many small components. The observed community size distributions are in good agreement with the predicted fragmentation in the model. We show that the empirical pairwise similarities of network layers, in terms of link overlap and degree correlations, practically coincide with the model. This suggests that several detailed features of the fragmentation in societies can be traced back to the triadic closure processes.Comment: 8 pages, 6 figure

The economic impact of conflict-related and policy uncertainty shocks: the case of Russia

En el presente artículo se muestra como la incertidumbre política y las variables que miden el conflicto impactan sobre la actividad económica en Rusia (y en concreto sobre el PIB). Para ello se utilizan diversos indicadores que miden el conflicto, referidos a aspectos específicos de este concepto general: riesgo geopolítico, malestar social, brotes de violencia y conflicto armado interno. Para la incertidumbre sobre el curso de la política económica se emplea el habitual EPU (indicador de incertidumbre de política económica). En el artículo se utilizan dos enfoques empíricos distintos pero complementarios. El primero se basa en un modelo de predicción de frecuencia mixta de series de tiempo (MIDAS), en el que se muestra que los indicadores de conflicto aportan información útil para pronosticar el PIB a corto plazo, incluso controlando por un conjunto amplio de variables macrofinancieras. El segundo enfoque es un modelo de vectores autorregresivos estructural (SVAR), en el que se muestra que los shocks de los indicadores de conflicto generan una desaceleración de la actividad, con una caída persistente del crecimiento del PIB y un incremento efímero pero sustancial de las primas de riesgo.We show how policy uncertainty and conflict-related shocks impact the dynamics of economic activity (GDP) in Russia. We use alternative indicators of “conflict”, relating to specific aspects of this general concept: geopolitical risk, social unrest, outbreaks of political violence and escalations into internal armed conflict. For policy uncertainty we employ the workhorse economic policy uncertainty (EPU) indicator. We use two distinct but complementary empirical approaches. The first is based on a time series mixed-frequency forecasting model. We show that the indicators provide useful information for forecasting GDP in the short run, even when controlling for a comprehensive set of standard high-frequency macro-financial variables. The second approach, is a SVAR model. We show that negative shocks to the selected indicators lead to economic slowdown, with a persistent drop in GDP growth and a short-lived but large increase in country risk

Sources of economic policy uncertainty in the euro area: a ready-to-use database

Construimos una base de datos de indicadores de incertidumbre de política económica (economic policy indicators: EPU, por sus siglas en inglés) de acceso público basada en la metodología propuesta por Azqueta-Gavaldón, Hirschbühl, Onorante y Saiz (2023), que utiliza técnicas de topic modelling para identificar los distintos componentes de incertidumbre. Esta base de datos se actualiza periódicamente y es accesible a través de la página web del Banco de España. Actualmente, los indicadores abarcan los cuatro países más grandes de la zona euro: España, Italia, Francia y Alemania. Además, agregando los indicadores nacionales de estos cuatro países, calculamos un indicador EPU para la zona euro. Estamos en el proceso de ampliar la cobertura de datos para construir indicadores EPU para más países de la UEM. Este conjunto de datos y los índices derivados para la zona euro proporcionan valiosas herramientas a investigadores, responsables políticos y analistas para evaluar y supervisar la dinámica de la incertidumbre de la política económica en tiempo real.In this paper, we build a publicly-available database of economic policy uncertainty (EPU) indicators based on the methodology proposed by Azqueta-Gavaldón, Hirschbühl, Onorante and Saiz (2023), which uses topic modelling techniques to identify distinct components of EPU. This database is regularly updated and can be accessed on the Banco de España’s website. Currently, the dataset covers the four largest countries in the euro area, namely Spain, Italy, France, and Germany. Our data coverage is continually expanding to include more euro area countries. Additionally, we compute the aggregated EPU indexes for the euro area. This comprehensive dataset and the resulting euro area indexes provide valuable tools for researchers, policymakers and analysts to assess and monitor the dynamics of economic policy uncertainty in real time

The information content of conflict, social unrest and policy uncertainty measures for macroeconomic forecasting

El hecho de que los episodios de disturbios y conflictos sociales, tensiones políticas e incertidumbre sobre las políticas económicas afectan a la evolución de la economía es comúnmente aceptado en Economía. Sin embargo, la dimensión en tiempo real de tales interacciones no ha sido tan estudiada, y en concreto no está claro cómo se incorporarían dichas tensiones en los modelos de predicción al uso. Esto puede explicarse en parte por la división entre las contribuciones de la ciencia económica y la ciencia política en esta área, así como por la tradicional falta de disponibilidad de indicadores de alta frecuencia que midan tales fenómenos. Sin embargo, esta restricción se está volviendo cada vez menos limitante, gracias a la construcción de indicadores basados en análisis textuales. En este trabajo reunimos un conjunto de datos de medidas de lo que llamamos «inestabilidad institucional» para tres economías emergentes representativas: Brasil, Colombia y México. Dichos indicadores se introducen en un modelo estándar de predicciones (MIDAS) para el PIB trimestral. Los resultados muestran que la introducción de los indicadores que captan la inestabilidad institucional mejora el pronóstico del PIB trimestral respecto al uso de un conjunto amplio de indicadores estándar macroeconómicos y financieros de alta frecuencia.It is widely accepted that episodes of social unrest, conflict, political tensions and policy uncertainty affect the economy. Nevertheless, the real-time dimension of such relationships is less studied, and it remains unclear how to incorporate them in a forecasting framework. This can be partly explained by a certain divide between the economic and political science contributions in this area, as well as by the traditional lack of availability of high-frequency indicators measuring such phenomena. The latter constraint, though, is becoming less of a limiting factor through the production of text-based indicators. In this paper we assemble a dataset of such monthly measures of what we call “institutional instability”, for three representative emerging market economies: Brazil, Colombia and Mexico. We then forecast quarterly GDP by adding these new variables to a standard macro-forecasting model in a mixed-frequency MIDAS framework. Our results strongly suggest that capturing institutional instability based on a broad set of standard high-frequency indicators is useful when forecasting quarterly GDP. We also analyse the relative strengths and weaknesses of the approach

Irreducibility of multilayer network dynamics: the case of the voter model

10 pages, 6 figuresThis work has been supported by the Spanish MINECO and FEDER under projects INTENSE@COSYP (FIS2012-30634), and by the EU Commission through the project LASAGNE (FP7-ICT-318132). VL also acknowledges support from EPSRC project GALE (EP/K020633/1

Wildlife law enforcement Report of the Police/DOE Working Group set up following the DOE review of wildlife sales and related controls; annexes

SIGLEAvailable from British Library Document Supply Centre- DSC:GPC/07339 / BLDSC - British Library Document Supply CentreGBUnited Kingdo