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Various mathematical frameworks play an essential role in understanding the economic systems and the emergence of crises in them. Understanding the relation between the structure of connections between the system’s constituents and the emergence of a crisis is of great importance. In this paper, we propose a novel method for the inference of economic systems’ structures based on complex networks theory utilizing the time series of prices. Our network is obtained from the correlation matrix between the time series of companies’ prices by imposing a threshold on the values of the correlation coefficients. The optimal value of the threshold is determined by comparing the spectral properties of the threshold network and the correlation matrix. We analyze the community structure of the obtained networks and the relation between communities’ inter and intra-connectivity as indicators of systemic risk. Our results show how an economic system’s behavior is related to its structure and how the crisis is reflected in changes in the structure. We show how regulation and deregulation affect the structure of the system. We demonstrate that our method can identify high systemic risks and measure the impact of the actions taken to increase the system’s stability.

La teoría económica competitiva provee la estructura del mercado ideal. El paradigma neoclásico plantea el supuesto de la información disponible completa y gratuita. No obstante, abundante evidencia empírica demuestra que este supuesto no se cumple en la práctica. Frente a esta problemática, el objetivo del presente trabajo es delinear la circulación de la información de precios en los mercados agrícolas en Argentina en función del tiempo, caracterizar los tipos de mercados y la información de mercado. El trabajo se inicia con la búsqueda de información secundaria, revisión bibliográfica y primaria, de encuestas y entrevistas a integrantes del sector agropecuario, productores agropecuarios, acopios, cooperativas, estudiantes de agronomía, analistas del sistema agroindustrial. A partir del análisis de contenido se exponen las concepciones conceptuales, otra forma de representar la magnitud de los mercados agrícolas y la relevancia de la información en función del tiempo en el mundo actual, comprendiendo y analizando la interacción en profundidad entre información y decisión y la relación entre los agentes. Competitive economic theory provides the structure of the ideal market. the neoclassical paradigm assumes complete and free available information. However, abundant empirical evidence shows that this assumption is not fulfilled in practice. Faced with this problem, the aim of this paper is to delineate the circulation of price information in agricultural markets in argentina as a function of time, to characterize the types of markets and market information. the work begins with the search for secondary information, bibliographic and primary review, surveys and interviews with members of the agricultural sector, agricultural producers, stockpiles, cooperatives, agronomy students, analysts of the agroindustrial system. From the content analysis, conceptual views are presented, another way of illustrating the magnitude of agricultural markets and the relevance of information as a function of time in today's world, understanding and analyzing the in-depth interaction between information and decision and the relationship between agents. EEA Pergamino Fil: Leavy, Sebastián. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Agencia de Extensión Rural Junín; Argentina Fil: Leavy, Sebastián. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Comercialización Agropecuaria; Argentina

How does capitalism hold power in climate emergency? Scholars have conventionally thought of capitalism’s power as a function of its ability to leverage market structures, political institutions, social class composition, technology, and the modes of production that technology dictates. This paper argues that tackling this question also requires investigating the need for capital’s power to be legitimate. It considers a synergistic nexus of financial rating agencies, asset managers, and big business that purport to invest in companies meeting certain environmental, social, and governance (ESG) sustainability standards. With a capacious vision to reorient modern capitalism from the maximisation of shareholder to stakeholder value, proponents of ESG seek to reward sustainable companies with trillions of dollars in cheap capital investments such that they grow faster, and incentivise all other companies to join in for an ever-compounding corporate resistance against climate change. In reality, ESG standards are engineered to have no discernible environmental impact and continue to reward the status quo of growth and profit. As a distinct regime, this insipient emergency capitalism effectively functions as an ideological tool to re-legitimise capitalism as the panacea for the climate emergency. Rather than saving the world from the ravages of climate change, the regime helps its proponents pre-empt political or regulatory backlash to their role as major polluters, and facilitate their position as ‘too big to fail’ when future climate disasters strike.

European Commission via the Horizon 2020-MSCA-RISE-2018 Program, under Project Nº 823967 named “Promoting circular economy in the supply chain” (ProCEedS). -- European Commission’s research program Horizon 2020-SC5-2020-2 scheme, Grant Agreement 101003491 (JUST Transition to the Circular Economy project). The current socio-economic model based on a linear approach is being challenged by resource scarcity, negative environmental impacts and socio-economic constraints. Consequently, cycling approaches or circular economy (CE) paradigm is gaining attention. Business as usual is no longer possible and the model and criteria proposed by circular economy are a sustainable alternative that effectively couples natural with human-made systems. A model in which citizens in each of their social roles have a lot to say and do. However, implementation in Argentina is very slow and it is only applied at some level by companies or in urban residues recycling in a small number of cities. Additionally, social skepticism and lack of information about what circular economy embraces is still perceived. The objective of this exploratory paper is to identify the present level of awareness, the current situation and the expectations regarding the transition towards a circular economy approach within Argentina’s agricultural sectors based on an opinion and perception survey. The aim of the study is to establish a baseline understanding and an interpretative framework to aid researchers and policymakers in promoting and increasingly implementing circular economy criteria in specific sectors. The study analyzes by a descriptive statistic a survey (n=534) of selected actors related to the agricultural sector, i.e., farmers, agronomists (including agricultural engineers, veterinarians, and biologists), agrifood companies, and also directly related sectors, such as education and public administration. The anonymous questionnaire was divided into three parts: i) demographic characterization, ii) general awareness about transition towards circular economy (concept, current situation, features, advantages, drivers, obstacles and governance) within the region where the respondent operates, and iii) specific aspects within each selected sector. Results showed that the selected sectors perceived a common vision about the concept of CE “as a more sustainable production and consumption model”, and with some differences, they have mainly sensed that the transformation process is still both not initiated and at its initial steps. Respondents selected to focus on recycling/reusing as well as on the integration between productive units. Political, economic and environmental awareness as well as technological skills have been chosen as barriers. Consequently, they chose to invest on education and research, noticing the citizens/society as the main agent of transformation. Since the challenge is to find organized and progressive steps to build interactions, programs, actions and legislation to favor the integral (between sectors) and internal (within a sector) transition, indicators for monitoring as well as policies, priorities and perspectives have been highlighted to contribute to boost the transformation towards a circularity approach. EEA Oliveros Fil: Rotolo, Gloria Claudia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina Fil: Vassillo, C. University of Naples Federico II. Department of Agriculture; Italia Fil: Rodriguez Aranza, Ailén. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina Fil: Rodriguez, A.A. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Magnano, Luciana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina Fil: Milo Vaccaro, Marcelo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina Fil: Civit, Bárbara. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Civit, Bárbara. Universidad Tecnológica Nacional. Sede Mendoza; Argentina Fil: Covacevich, Melina Soledad. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina Fil: Arena, Alejandro Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Arena, Alejandro Pablo. Universidad Tecnológica Nacional. Sede Mendoza; Argentina Fil: Ulgiati, Sergio. Parthenope University of Naples. Department of Science and Technology; Italia

The outburst of the COVID-19 pandemic and its rapid spread throughout the world in 2020 shed a new light on mathematic models describing the nature of epidemics. However, as the pandemic shocked economies to a much greater extent than earlier epidemics, the recovery potential of economies was emphasized and its inclusion in epidemic models is becoming more important. The present paper deals with the issues of modeling the recovery of economic systems that have undergone severe medical shocks, such as COVID-19. The proposed mathematical model considers the close relationship between the dynamics of pandemics and economic development. This distinguishes it from purely “medical” models, which are used exclusively to study the dynamics of the spread of the COVID-19 pandemic. Unlike standard SIR models, the present approach involves the introduction of the “vaccine” equation to the SIR model and introduces correction components that include the possibility of re-infection and other nuances such as the number of people at risk of infection (not sick with COVID but not vaccinated); sick with COVID; recovered; fully vaccinated (two doses) citizens; the rate of COVID infection; the rate of recovery of infected individuals; the vaccination coefficients, respectively, for those who have not been ill and recovered from COVID; the coefficient of revaccination; the COVID re-infection rate; and the population fluctuation coefficient, which takes into account the effect of population change as a result of births and deaths and due to the departure and return of citizens. The present model contains governance so that it not only generates scenario projections but also models specific governance measures as well to include the pandemic and restore economic growth. The model also adds management issues, so that it not only generates scenario forecasts but simultaneously models specific management measures as well, aiming to suppress the pandemic and restoring economic growth. The model was implemented on specific data on the dynamics of the spread of the COVID-19 pandemic in selected developing economies.