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In the summer of 1938, Italy's Fascist regime announced its new 'racial' policy, soon to be followed by a series of draconian racial laws. The policy was based on the principle that Catholic Italians were of the Aryan race and Jewish Italians belonged to a separate race of non-Aryans. Previously the Vatican had made no such racial distinction. Yet, notwithstanding the frequent claim that the Church has never distinguished between Catholics and Jews on racial grounds, the Vatican quickly began to assimilate to the Fascist state's distinction of Jews as racially marked as non-Aryan. The opening in 2020 of the Vatican archives for the papacy of Pius XII (1939–58) has made available a huge trove of documents bearing on the way the pope and the Vatican secretariat of state dealt with Italy's racial laws and with the subsequent persecution of Italy's Jews during German occupation. As shown in this article, these documents make clear the Vatican's use of racial language and racial concepts as it dealt with the racial laws and the persecution of Italy's Jews from the time the racial laws were introduced in 1938 to the years of the Holocaust. [ABSTRACT FROM AUTHOR]

As the war was going badly in early 1943, Mussolini took the dramatic step of replacing most of his government ministers. Of the men sacked, none drew more attention than Galeazzo Ciano, Mussolini's son-in-law, who had served as minister of foreign affairs since 1936. The announcement that Ciano would immediately be appointed as Italy's ambassador to the Holy See sparked much speculation in the diplomatic community, where it was viewed as a possible move by Mussolini to employ the Vatican to broker an Italian exit from the war. Others saw the appointment as a desperate move by Ciano himself to find a way out of the war. The recently opened Vatican archives for these years, along with archival evidence from Germany, Britain, the U.S., France, and Italy, offer new insight both into Ciano's attempts to ingratiate himself with Pope Pius XII and to how he in fact operated in his role as Italian ambassador to the Holy See in the months preceding the collapse of the Fascist regime. [ABSTRACT FROM AUTHOR]

Balanced sampling is a random method for sample selection, the use of which is preferable when auxiliary information is available for all units of a population. However, implementing balanced sampling can be a challenging task, and this is due in part to the computational efforts required and the necessity to respect balancing constraints and inclusion probabilities. In the present paper, a new algorithm for selecting balanced samples is proposed. This method is inspired by simulated annealing algorithms, as a balanced sample selection can be interpreted as an optimization problem. A set of simulation experiments and an example using real data shows the efficiency and the accuracy of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The adoption of the Sustainable Development Goals in September 2015 by the United Nations General Assembly is calling National Statistics Offices worldwide to underpin a data revolution. Indeed, these organizations should extend both the scope and disaggregation of the data traditionally produced, and measure new economic, social and environmental phenomena, leaving none behind. There is a growing consensus that, in the digital era, earth observation might strengthen traditional data sources and statistics in monitoring sustainable well-being, facilitating the transformative agenda that official statisticians should implement in the forthcoming years. This research analyses how earth observation, under the form of observable nightlights, might help in mapping poverty data, thus filling in existing gaps of official statistics for a core sustainable development indicator. The empirical analyses show that there are indeed considerable advantages from the use of satellite remote sensing information, the so-called 'views from the above', in facing the increasing demand from policy makers and the public at large. The analysis shows that publicly and freely available information from the space might be a key source of information to derive—through an unbalanced fractional panel-data model—spatially disaggregated and continuous-time estimations of poverty gap, headcount, and Gini indices for 20 Latin American and Caribbean countries. [ABSTRACT FROM AUTHOR]

This study provides new insights into the relation between the size of the territorial units for which the provision of waste services is entrusted to external operators and their efficiency. The need for a deeper investigation of this relation arises from the fact that on the one hand, the European Union is pushing its Member States towards the adoption of laws aimed at ensuring competition for the market whenever competition in the market is possible; on the other, both the theoretical and the empirical literature cautions policymakers against the risks associated with contracting out. This problem is addressed here through an efficiency analysis of Italian municipalities in the organization of waste services. The stochastic frontier analysis (SFA) is applied to estimate efficiency scores for the municipalities. Then, a regression analysis is carried out to investigate the relation between the efficiency scores and the size of the municipality. This analysis has been carried out using data on a sample of 6,916 Italian municipalities (87.39% of the entire population) for the year 2019. The method adopted here can also support regulatory authorities in defining the size of the territorial units in which other types of local public service should be outsourced. • The beneficial potential of outsourcing public services may vary with the size of the municipality. • An efficiency analysis of the organization of waste services in Italy is presented. • A stochastic frontier analysis to estimate efficiency scores for municipalities is used. • The relation between efficiency scores and size of the municipality is studied. • The best size for gaining benefits from outsourcing is near 62,000 people. [ABSTRACT FROM AUTHOR]

Building on the idea that different hospitals may operate with different technologies, the objective of this paper is a spatial characterization of the production function of hospital services through the identification of different spatial regimes. We introduce an original methodology to identify spatially constrained regimes, namely spatially constrained portions of territory in which the production units are maximally homogeneous in functional terms. The empirical algorithm can be described as a k -means cluster-wise regression procedure in which the units are belonging to a proximity graph and where distance is assessed in regressive terms. The analysis is implemented, first, on simulated data and, then, on output and input data of Italian hospitals for the year 2010. Our results, besides their methodological value, allow to shed light on the working of the hospital sector in Italy. The heterogeneity of the identified technological regimes can be associated to spatial heterogeneity of relevant aspects, like demand, internal organization, clinical and managerial governance, etc., and consequential policy implications can be, therefore, gathered. • A methodology to identify spatially constrained regimes, with production units maximally homogeneous in functional terms. • A production function is estimated for a large sample (681) Italian hospitals. • Spatial heterogeneity of relevant aspects associated to the heterogeneity of the spatial regimes, for policy implications. [ABSTRACT FROM AUTHOR]

Building on the idea that different hospitals may operate with different technologies, the objective of this paper is a spatial characterization of the production function of hospital services through the identification of different spatial regimes. We introduce an original methodology to identify spatially constrained regimes, namely spatially constrained portions of territory in which the production units are maximally homogeneous in functional terms. The empirical algorithm can be described as a k -means cluster-wise regression procedure in which the units are belonging to a proximity graph and where distance is assessed in regressive terms. The analysis is implemented, first, on simulated data and, then, on output and input data of Italian hospitals for the year 2010. Our results, besides their methodological value, allow to shed light on the working of the hospital sector in Italy. The heterogeneity of the identified technological regimes can be associated to spatial heterogeneity of relevant aspects, like demand, internal organization, clinical and managerial governance, etc., and consequential policy implications can be, therefore, gathered. • A methodology to identify spatially constrained regimes, with production units maximally homogeneous in functional terms. • A production function is estimated for a large sample (681) Italian hospitals. • Spatial heterogeneity of relevant aspects associated to the heterogeneity of the spatial regimes, for policy implications. [ABSTRACT FROM AUTHOR]