Local spillovers, production technology and the choice to make and/or buy. Empirical evidence from Emilia Romagna

By exploiting a new rich firm-level dataset, this paper investigates the decision to subcontract production activities (outsourcing) with respect to vertically integrate them. In particular, we aim at identifying the main factors underlying the decision to either fully or partially decentralise production activities by mechanical firms located in Emilia Romagna (Italy). In so doing, we first account for firm characteristics, such as size, age and the skill composition of the labour force, then we focus on labour costs per employee, product diversity and the presence of the firm on international markets. Finally, and differently from previous research, we include in the analysis both the qualitative composition of the production process, as given by the stages of production potentially developed by the firm, and the industrial composition of the local market. On this last purpose, we estimate the relationship between the propensity and the intensity of concurrent and total sourcing and the main sources of agglomeration economies identified in the literature: specialisation economies, variety and urbanisation economies. Our estimates show a particularly strong and positive relation between the intensity of 'pure' outsourcing and our measure of variety, workforce skill intensity and the internal composition of production, while a negative relation emerges with respect to firm size, age and labour cost. Results concerning concurrent sourcing, instead, appear weaker, but, differently from the case of full outsourcing, we nd a positive relationship with rm size and product diversity.

Mind the Income Gap: Behavior of Inequality Estimators from Complex Survey Small Samples

Income inequality measures are biased in small samples leading generally to an underestimation. After investigating the nature of the bias, we propose a bias-correction framework for a large class of inequality measures comprising Gini Index, Generalized Entropy and Atkinson families by accounting for complex survey designs. The proposed methodology is based on Taylor's expansions and Generalized Linearization Method, and does not require any parametric assumption on income distribution, being very flexible. Design-based performance evaluation of the suggested correction has been carried out using data taken from EU-SILC survey. Results show a noticeable bias reduction for all measures. A bootstrap variance estimation proposal and a distributional analysis follow in order to provide a comprehensive overview of the behavior of inequality estimators in small samples. Results about estimators distributions show increasing positive skewness and leptokurtosis at decreasing sample sizes, confirming the non-applicability of classical asymptotic results in small samples and suggesting the development of alternative methods of inference.Comment: 29 pages, 5 figures. Submitted for publicatio

Small Area Estimation of Inequality Measures using Mixtures of Betas

Economic inequalities referring to specific regions are crucial in deepening spatial heterogeneity. Income surveys are generally planned to produce reliable estimates at countries or macroregion levels, thus we implement a small area model for a set of inequality measures (Gini, Relative Theil and Atkinson indexes) to obtain microregion estimates. Considering that inequality estimators are unit-interval defined with skewed and heavy-tailed distributions, we propose a Bayesian hierarchical model at area level involving a Beta mixture. An application on EU-SILC data is carried out and a design-based simulation is performed. Our model outperforms in terms of bias, coverage and error the standard Beta regression model. Moreover, we extend the analysis of inequality estimators by deriving their approximate variance functions.Comment: 28 pages, 7 figures, 2 tables, 2 pages of supplementary materia

The Pressing Issue of Micro- and Nanoplastic Contamination: Profiling the Reproductive Alterations Mediated by Oxidative Stress

Micro- and nanoplastics (MPs/NPs) are among the most widely distributed pollutants in the environment. It has been suggested that exposure to MPs/NPs can trigger toxicity pathways among which inflammation and oxidative stress (OS) play a pivotal role. Once absorbed, MPs/NPs may act locally or access the bloodstream and, following the translocation process, reach several organs and tissues, including the gonads. Notably, MPs/NPs can bioaccumulate in human and murine placenta, opening new scenarios for toxicological evaluations. We review recent studies on the effects of MPs/NPs on the reproductive health in aquatic and terrestrial organisms of both sexes, focusing on the role of OS and the antioxidant defence system failure as the main underlying mechanisms. Alterations in gametogenesis, embryonic and offspring development, and survival have been shown in most studies and often related to a broken redox balance. All these detrimental effects are inversely related to particle size, whereas they are closely linked to shape, plastic polymer type, superficial functionalization, concentration, and time of exposure. To date, the studies provide insights into the health impacts, but no conclusions can be drawn for reproduction toxicity. The main implication of the few studies on antioxidant substances reveals their potential role in mitigating MP-induced toxic effects

Mind the income gap: bias correction of inequality estimators in small-sized samples

Income inequality estimators are biased in small samples, leading generally to an underestimation. This aspect deserves particular attention when estimating inequality in small domains. After investigating the nature of the bias, we propose a bias correction framework for a large class of inequality measures comprising Gini Index, Generalized Entropy and Atkinson index families by accounting for complex survey designs. The proposed methodology is based on Taylor’s expansions and does not require any parametric assumption on income distribution, being very flexible. Design-based performance evaluation of our proposal has been carried out using data taken from the EU-SILC survey, showing a noticeable bias reduction for all the measures. Lastly, a small area estimation exercise shows the risks of ignoring prior bias correction in a basic area-level model, determining model misspecification

Small area estimation of inequality measures using mixtures of betas

Economic inequalities referring to specific regions are crucial in deepening spatial heterogeneity. Income surveys are generally planned to produce reliable estimates at countries or macro region levels, thus we implement a small area model for a set of inequality measures (Gini, Relative Theil and Atkinson indexes) to obtain microregion estimates. Considering that inequality estimators are unit-interval defined with skewed and heavy-tailed distributions, we propose a Bayesian hierarchical model at area level involving a Beta mixture. An application on EU-SILC data is carried out and a design-based simulation is performed. Our model outperforms in terms of bias, coverage and error the standard Beta regression model. Moreover, we extend the analysis of inequality estimators by deriving their approximate variance functions