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The milk addiction paradox refers to an empirical finding in which commodities that are typically considered to be non addictive, such as milk, appear instead to be addictive. This result seems more likely when there is persistence in consumption and when using aggregate data, and it suggests that the AR(2) model typically used in the addiction literature is prone to produce spurious result in favor of rational addiction. Using both simulated and real data, we show that the milk addiction paradox disappears when estimating the data using an AR(1) linear specification that describes the saddle-path solution of the rational addiction model. The AR(1) specification is able to correctly discriminate between rational addiction and simple persistence in the data, to test for the main features of rational addiction, and to produce unbiased estimates of the short and long-run elasticity of demand. These results hold both with individual and aggregated data, and they suggest that, for testing rational addiction, the AR(1) model is a better empirical alternative than the canonical AR(2) model.

Organizations play a key role in reducing anthropogenic pressure on the natural environment. The first step towards improving their sustainability performances is the implementation of methodologies that take into consideration multiple environmental impact categories, as well as the entire value chain. The attention of scholars and practitioners was initially addressed to the analysis of products and processes, yet in a few cases in which they were addressed, the approaches used for organizations had a limited scope and range of use. Only in recent years have they been framed in a life cycle perspective. This article analyzes two recent life cycle-based methodologies that have their focus on the organization, namely Organization Environmental Footprint (OEF) and Organizational Life Cycle Assessment (O-LCA). The goal is to define the state of the art of their methodological and current application developments and consider the relevance that these methodologies can have, both in terms of internal and external commitment (e.g., for the supply chain actors) and of reporting and communication requirements. The research was carried out starting from scientific databases, integrating technical legislation and secondary literature. The results obtained allowed tracing the first evolutionary trends, identifying the main authors and scientific journals and highlighting the relevant issues according to the researchers. A content and bibliometric analysis was performed that included all the contributions published so far. Projects and case studies that practically applied the two methodologies were also identified and analyzed. Finally, the main differences between the two methodologies were highlighted and future developments were hypothesized.

The rational addiction model is usually tested by estimating a linear second-order difference Euler equation, which may produce unreliable estimates. We show that a linear first-order difference equation is a better alternative. This empirical specification is appropriate under the reasonable assumption that people are uncertain about the time of their death, it is based on the same structural assumptions used in the literature, and it retains all policy implications of the deterministic rational addiction model. It is also empirically convenient because it is simple, it allows using efficient estimation strategies that do not require instrumental variables, and it is robust to the possible non-stationarity of the data. As an application we estimate the demand for smoking in the US from 1970 to 2016, and we show that it is consistent with the rational addiction model.

Xavier Vigna, spécialiste de l'histoire du travail, des ouvriers et des ouvrières au XXe siècle répond aux questions des coordonnateurs du numéro. Il apporte des éclairages sur les enjeux actuels du travail hors de l'usine concentrée. Il propose aussi des réflexions sur l'histoire orale du travail et sur l'historiographie récente du sujet.

Penser et étudier le travail en histoire, entraine souvent une investigation au cœur de l'usine concentrée. Or, l'usine concentrée urbaine n'est pas le seul lieu du travail. Les mondes ruraux connaissent le travail agricole depuis le Néolithique, et si l'on resserre la focale au travail industriel, il existe autant à la campagne qu'en ville, autant au champ, à l'atelier qu'à la mine. C'est ce travail hors l'usine qui nous intéresse dans ce dossier.

The decomposition of the overall effect of a treatment into direct and indirect effects is here investigated with reference to a recursive system of binary random variables. We show how, for the single mediator context, the marginal effect measured on the log odds scale can be written as the sum of the indirect and direct effects plus a residual term that vanishes under some specific conditions. We then extend our definitions to situations involving multiple mediators and address research questions concerning the decomposition of the total effect when some mediators on the pathway from the treatment to the outcome are marginalized over. Connections to the counterfactual definitions of the effects are also made. Data coming from an encouragement design on students' attitude to visit museums in Florence, Italy, are reanalyzed. The estimates of the defined quantities are reported together with their standard errors to compute p values and form confidence intervals.

Life Cycle Assessment (LCA) has been increasingly used for the improvement of the environmental performance of products and services, including food systems. Amongst them, however, honey appears to have been rarely analysed. Furthermore, the pollination by honeybees can be regarded as one of the functions of an apiculture system and is of utmost importance both for natural ecosystems and agriculture. When implementing an LCA of an apiculture system, the pollination service can and should be considered as one of the functions of a multifunctional system and the issue of how to deal with this multifunctionality in the modelling of that system should be considered carefully. The aim of this paper is to explore the economic value of pollination as a potential basis for managing multifunctionality in LCA modelling as well as its implementation in a case study. Economic allocation was performed between the pollination service and honey production. The results demonstrated that the production phase is the most impactful one for most of the environmental categories (due to the use of glass for the honey jars and electricity consumption during the storage of supers in refrigerator rooms), followed by the distribution phase. Finally, the most affected environmental impact category appeared to be natural land transformation, followed by marine ecotoxicity, freshwater eutrophication and human toxicity.