Political Competition in Dual Economies: Clientelism in Latin America

Resumen:Este artículo presenta el proyecto de investigación que intenta iluminar los mecanismos que vinculan el clientelismo con la informalidad. En particular la investigación se concentra en las interacciones que tienen lugar durante la competencia electoral e intenta proporcionar un marco analítico para comprender los mecanismos económicos subyacentes en la competencia electoral en América Latina. Esta competencia está caracterizada por asimetrías entre los políticos (credibilidad y habilidad para movilizar votantes) y asimetrías entre los votantes (ingreso y participación en cierto segmento de la economía) ambos inmersos en un ambiente de baja calidad institucional (débil imperio de la ley). El artículo expone la evidencia empírica que motivó la investigación, discute los conceptos y literatura centrales y presenta un ejercicio exploratorio basado en el modelo de votación probabilística como un punto de partida en la formalización del problema. En esta primera aproximación se muestra que el político clientelista en el poder puede proveer más bienes públicos cuando su maquinaria política es suficientemente rentable y la sociedad es altamente inequitativa. En la medida en que el político entrante tiene su nicho en los votantes ricos quienes demandan bajos impuestos, el político clientelista redistribuye más ingreso aunque a costa de una mayor informalidad.maquinaria política, clientelismo, política redistributiva, dualidad, informalidad, modernización económica, América Latina

Contrasting Views of Complexity and Their Implications For Network-Centric Infrastructures

There exists a widely recognized need to better understand and manage complex “systems of systems,” ranging from biology, ecology, and medicine to network-centric technologies. This is motivating the search for universal laws of highly evolved systems and driving demand for new mathematics and methods that are consistent, integrative, and predictive. However, the theoretical frameworks available today are not merely fragmented but sometimes contradictory and incompatible. We argue that complexity arises in highly evolved biological and technological systems primarily to provide mechanisms to create robustness. However, this complexity itself can be a source of new fragility, leading to “robust yet fragile” tradeoffs in system design. We focus on the role of robustness and architecture in networked infrastructures, and we highlight recent advances in the theory of distributed control driven by network technologies. This view of complexity in highly organized technological and biological systems is fundamentally different from the dominant perspective in the mainstream sciences, which downplays function, constraints, and tradeoffs, and tends to minimize the role of organization and design

Ecological-economic viability as a criterion of strong sustainability under uncertainty

Strong sustainability, according to the common definition, requires that different natural and economic capital stocks have to be maintained as physical quantities separately. Yet, in a world of uncertainty this cannot be guaranteed. To therefore define strong sustainability under uncertainty in an operational manner, we propose to use the concept of viability. Viability means that the dierent components and functions of a dynamic, stochastic system at any time remain in a domain where the future existence of these components and functions is guaranteed with suciently high probability. We develop a unifying and general ecological-economic concept of viability that encompasses the traditional ecological and economic notions of viability as special cases. It provides an operational criterion of strong sustainability under conditions of uncertainty. We illustrate this concept and demonstrate its usefulness by applying it to livestock grazing management in semi-arid rangelands.capital (natural and economic), ecological-economic systems, ecosystem services, funds, stocks, sustainability, uncertainty, viability

Software Watermarking: A Semantics-based Approach

Software watermarking is a defence technique used to prevent software piracy by embedding a signature, i.e., an identifier reliably representing the owner, in the code. When an illegal copy is made, the ownership can be claimed by extracting this identifier. The signature has to be hidden inside the program and it has to be difficult for an attacker to detect, tamper or remove it. In this paper we show how the ability of the attacker to identify the signature can be modelled in the framework of abstract interpretation as a completeness property. We view attackers as abstract interpreters that can precisely observe only the properties for which they are complete. In this setting, hiding a signature in the code corresponds to inserting it in terms of a semantic property that can be retrieved only by attackers that are complete for it. Indeed, any abstract interpreter that is not complete for the property specifying the signature cannot detect, tamper or remove it. The goal of this work is to introduce a formal framework for the modelling, at a semantic level, of software watermarking techniques and their quality features

Resilience of multi-robot systems to physical masquerade attacks

The advent of autonomous mobile multi-robot systems has driven innovation in both the industrial and defense sectors. The integration of such systems in safety-and security-critical applications has raised concern over their resilience to attack. In this work, we investigate the security problem of a stealthy adversary masquerading as a properly functioning agent. We show that conventional multi-agent pathfinding solutions are vulnerable to these physical masquerade attacks. Furthermore, we provide a constraint-based formulation of multi-agent pathfinding that yields multi-agent plans that are provably resilient to physical masquerade attacks. This formalization leverages inter-agent observations to facilitate introspective monitoring to guarantee resilience.Accepted manuscrip

A new data-driven framework to select the optimal replenishment strategy in complex supply chains

- Part of special issue: 10th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2022: Nantes, France, 22-24 June 2022. Edited by Alain Bernard, Alexandre Dolgui, Hichem Haddou Benderbal, Dmitry Ivanov, David Lemoine, Fabio Sgarbossa - Copyright © 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)Motivated by the high variability of markets occurred in the last years, which in turns determined significant uncertainty in lead times and supply chain dynamics, this paper introduces a data-driven framework based on machine learning and metaheuristic optimization to dynamically select the most suitable replenishment strategy for a complex two-echelon (supplier-inventory-factory) supply chain (SC) problem with perishable product and stochastic lead times. Since the supplier dispatches the product (i.e., the raw material) with a fixed expiration date, the product shelf-life strictly depends on the related delivery lead time, which is subject to uncertainty. In addition, a minimum order quantity has to be fulfilled and the time between two consecutive orders cannot be less than one month. The aim of the work is to select the most suitable replenishment strategy able to minimize the average stock level, which is a surrogate cost metric, while respecting a target fill rate. Considering a smoothing order-up-to policy, the data-driven prediction-optimization framework makes use of Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to select the best replenishment parameters (i.e., forecasting factor, proportional controller and safety stock factor) able to dynamically enhance the SC economic performance under the fill rate constraint. The ability of the framework under the predictive and the optimization perspective is assessed and a sensitivity analysis on the influence of replenishment parameters is presented as well

An entrepreneurial model of economic and environmental co-evolution

A basic tenet of ecological economics is that economic growth and development are ultimately constrained by environmental carrying capacities. It is from this basis that notions of a sustainable economy and of sustainable economic development emerge to undergird the ‘standard model’ of ecological economics. However, the belief in ‘hard’ environmental constraints may be obscuring the important role of the entrepreneur in the coevolution of economic and environmental relations, and hence limiting or distorting the analytic focus of ecological economics and the range of policy options that are considered for sustainable economic development. This paper outlines a co-evolutionary model of the dynamics of economic and ecological systems as connected by entrepreneurial behaviour. We then discuss some of the key analytic and policy implications.

From the bitterness of lemons to the sweet taste of lemonade: three essays in entrepreneurship

To critically evaluate the constraints faced by entrepreneurs, scholars have lean on two fundamental research questions. First, why doesn’t everyone who pursues his/her entrepreneurial aspirations actually succeed? Second, what are the most effective strategies entrepreneurs lean on to manage their ventures in such turbulent environments? Answering to the first question provides knowledge about how entrepreneurs react to constraints and what fuels/inhibits their behavior in the face of adversity. Furthermore, getting knowledge about how entrepreneurs act, disentangles the nuances of their activity and helps to explain what management practices foster and/or deters the development of a new business. In three studies, using different samples and methodologies, we highlight the importance of understanding the effect of constraints on entrepreneurial behavior, as well as the implications that the strategies used to manage such demands have for the venture development. Our findings deliver contributions for both research and practice. For scholars, this research provides a more granular view about the impact of constraints in entrepreneurial behavior. For entrepreneurs, we provide evidence about the effectiveness of some management practices for venture high-performance. Our findings also help policy makers to elaborate more effective propositions to stimulate entrepreneurial activity