Building Factories Without Bosses: The Movement of Worker-Managed Factories in Argentina

In the 1990s and 2000s, Argentina suffered one of the quickest and most extreme processes of neoliberal state reforms in the world, leading to the closure of numerous factories. To resist the increased unemployment produced by neoliberalism, workers started to organize in a movement aimed at defending their only source of income: their labor. In this article, I analyze the main characteristics of the movement of worker-managed factories in Argentina by exploring how factories were occupied, what motivated the workers' decision to create co-operatives, what made the factories economically viable, how they were legitimated by the community, which legal reforms workers achieved to support their struggle, and how they manage their factories.     

Savage in the Market

We develop a behavioral axiomatic characterization of subjective expected utility (SEU) under risk aversion. Given is an individual agent's behavior in the market: assume a finite collection of asset purchases with corresponding prices. We show that such behavior satisfies a “revealed preference axiom” if and only if there exists a SEU model (a subjective probability over states and a concave utility function over money) that accounts for the given asset purchases.     

A pseudo-values regression model for non-fatal event free survival in the presence of semi-competing risks

Statistical Methods & Applications - During follow-up patients may experience non-fatal events related to disease progression and death. This is a “semi-competing risks” setting, as...     

Efficient algorithms for the max k -vertex cover problem

Given a graph  \(G(V,E)\) of order  \(n\) and a constant \(k \leqslant n\) , the max  \(k\) -vertex cover problem consists of determining  \(k\) vertices that cover the maximum number of edges in  \(G\) . In its (standard) parameterized version, max  \(k\) -vertex cover can be stated as follows: “given  \(G,\) \(k\) and parameter  \(\ell ,\) does  \(G\) contain  \(k\) vertices that cover at least  \(\ell \) edges?”. We first devise moderately exponential exact algorithms for max  \(k\) -vertex cover, with time-complexity exponential in  \(n\) but with polynomial space-complexity by developing a branch and reduce method based upon the measure-and-conquer technique. We then prove that, there exists an exact algorithm for max  \(k\) -vertex cover with complexity bounded above by the maximum among  \(c^k\) and  \(\gamma ^{\tau },\) for some \(\gamma < 2,\) where  \(\tau \) is the cardinality of a minimum vertex cover of  \(G\) (note that \({\textsc {max}}\,\) k \({\textsc {\!-vertex cover}}{} \notin \mathbf{FPT}\) with respect to parameter  \(k\) unless \(\mathbf{FPT} = \mathbf{W[1]}\) ), using polynomial space. We finally study approximation of max  \(k\) -vertex cover by moderately exponential algorithms. The general goal of the issue of moderately exponential approximation is to catch-up on polynomial inapproximability, by providing algorithms achieving, with worst-case running times importantly smaller than those needed for exact computation, approximation ratios unachievable in polynomial time.     

Hedging against disruptions with ripple effects in location analysis

Supply systems are subject to disruptions whose impact may not remain confined, but might actually propagate across the network. We consider the problem of optimally protecting a capacitated median system with a limited amount of protective resources subject to disruptions. Specifically, the type of disruption studied is characterized by correlation effects between the facilities, and may result in partial or complete disruption of the facilities involved. The model optimizes protection plans in the face of large area disruptions; i.e., disruptions that affect regions rather than single elements of the system. Examples may be earthquakes, storms, floods, fires, hurricanes, droughts, the spread of diseases, the spread of chemical agents, and cascading failures. The model is also a general framework for the family of fortification problems in the context of location analysis, as it includes uncapacitated facilities and single-target disruptions as special cases. We provide a tri-level formulation of the problem, and we propose an exact solution algorithm which makes use of a tree-search procedure to identify which facilities to protect. The procedure is enhanced by a dual-based pruning rule. The underlying disruption problem is reformulated as a single-level mixed-integer program. The algorithm has been tested on a dataset based on the 2009 L’Aquila earthquake. We verify empirically the efficiency of the pruning rule, and we provide an evaluation of the importance of considering propagation effects in the disruptions.     

Afghanistan: A Change of Course?

The situation in Afghanistan today is not what the international community was planning it to be, 7 years ago when the Bonn Agreement was signed. Deterioration of security, weak governance, corruption, high narcotic production and trade, slow reconstruction process and consequent people’s disappointment are some of the features of that situation. Kabul and its international partners had a very little success in restoring peace and security, and a new phase of strategic re-thinking is in process. This article analyzes the different aspects of Afghan reconstruction and military intervention, their strengths and weaknesses, and outlines some urgent actions to be taken by all concerned actors.

Fiducial distribution in a power series family

Abstract

In this article the interest is on finding the fiducial distribution of the parameter, when the probability distribution belongs to the power series family, as in Johnson et al. (1992 Johnson, N. L., S. Kotz, and A. W. Kemp. 1992. Univariate discrete distributions. New York, NY: John Wiley and Sons. [Google Scholar]). Recently in Nájera and O’Reilly (2017 Nájera, E., and F. O’Reilly. 2017. On fiducial generators. Communications Statistics - Theory Methods 46 (5):2232–2248. doi:10.1080/03610926.2015.1040505.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) an argument is given to obtain a unique fiducial in the Bernoulli case. An attempt is made here to define some sort of invariance in a power series distribution so that, as was done in the Bernoulli case, one may find a unique invariant fiducial for the parameter. The Bernoulli case is reviewed in detail and the Poisson and negative binomial cases are addressed.     

Using High-Frequency Data in Dynamic Portfolio Choice

This article evaluates the economic benefit of methods that have been suggested to optimally sample (in an MSE sense) high-frequency return data for the purpose of realized variance/covariance estimation in the presence of market microstructure noise (Bandi and Russell, 2005a Bandi , F. M. , Russell , J. R. ( 2005a ). Realized covariation, realized beta, and microstructure noise . Working paper . [Google Scholar], 2008 Bandi , F. M. , Russell , J. R. ( 2008 ). Microstructure noise, realized variance, and optimal sampling . Review of Economic Studies , forthcoming . [Google Scholar]). We compare certainty equivalents derived from volatility-timing trading strategies relying on optimally-sampled realized variances and covariances, on realized variances and covariances obtained by sampling every 5 minutes, and on realized variances and covariances obtained by sampling every 15 minutes. In our sample, we show that a risk-averse investor who is given the option of choosing variance/covariance forecasts derived from MSE-based optimal sampling methods versus forecasts obtained from 5- and 15-minute intervals (as generally proposed in the literature) would be willing to pay up to about 80 basis points per year to achieve the level of utility that is guaranteed by optimal sampling. We find that the gains yielded by optimal sampling are economically large, statistically significant, and robust to realistic transaction costs.     

Measuring residential segregation in multi-ethnic and unequal European cities

Immigration flows and social inequalities reflect increased social and multi-ethnic segregation in contemporary urban Europe. For a better understanding of these processes, the present study investigates the main strengths of the multi-group residential indices, testing sensitivity and reliability under different metropolitan contexts in five European countries. These indices focus on different research dimensions and approach multi-group residential segregation conceptually and mathematically in a different way. A multivariate exploratory data analysis was adopted to classify the observed segregation patterns into a few homogeneous types and to delineate the multivariate relationship between the indices. The results of principal component analysis demonstrate that the indices assessing uniformity and disproportionality of the social groups analysed (H and D) contribute largely to the diversification in today's multi-ethnic communities, clarifying the importance of the dimension of evenness. Our results highlight how segregation is more evident in economically disadvantaged metropolitan regions with high levels of social vulnerability.