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The smoking epidemic across generations, genders, and educational groups: A matter of diffusion of innovations
No full textThis study determines whether the temporal variations in smoking habits across generations and genders and among groups with differing levels of education fit the pattern proposed by the theory of the diffusion of innovations (TDI) (Rogers, 2003). We focus on the Italian case and employ a pseudo-panel derived from repeated cross-sections of the annual household survey, “Aspects of Daily Life,” that was part of the Multipurpose Survey carried out by the Italian National Statistical Office (ISTAT) for the period 1997 to 2012. The results confirm Rogers’ TDI and show that smoking prevalence has declined over time and across age cohorts: Younger men of all educational levels and women with higher education are less likely to smoke than are those in other cohorts, while less-educated women who entered the smoking-diffusion process later than others are more likely to smoke. Hence, socio-economic differences in smoking continue to persist, especially for women. According to Rogers’ TDI, smoking prevalence is expected to continue to decline, particularly among little-educated women
Assembling Reminders for a Particular Purpose: Paolozzi’s Ephemera, Toys and Collectibles
No full text
How grossone can be helpful to iteratively compute negative curvature directions
No full textWe consider an iterative computation of negative curvature directions, in large scale optimization frameworks. We show that to the latter purpose, borrowing the ideas in [1, 3] and [4], we can fruitfully pair the Conjugate Gradient (CG) method with a recently introduced numerical approach involving the use of grossone [5]. In particular, though in principle the CG method is well-posed only on positive definite linear systems, the use of grossone can enhance the performance of the CG, allowing the computation of negative curvature directions, too. The overall method in our proposal significantly generalizes the theory proposed for [1] and [3], and straightforwardly allows the use of a CG-based method on indefinite Newton’s equations
The Social Value of Asymmetric Information Revisited
No full textIn contrary to previous literature, we show in the Grossman-Stiglitz model of noisy rational expectation that the social value of asymmetric information can be improved with more informative prices when being informed is uncertain. Investors always benefit from a privately payoff-relevant information, but they have to pay more to increase the probability of observing the information. In equilibrium, this trade-off can lead to high-risk, high return investments. Consequently the marginal expected utility gain from observing the information is not completely washed out by the cost of information acquisition, which leads to Pareto-optimal equilibrium and improves investors' welfare
Heterogeneity of scaling of the observed global temperature data
No full textWe investigated the scaling properties of two datasets of the observed near-surface global temperature data anomalies: the Met Office and the University of East Anglia Climatic Research Unit HadCRUT4 dataset and the NASA GISS Land-Ocean Temperature Index (LOTI) dataset. We used detrended fluctuation analysis of second-order (DFA2) and wavelet-based spectral (WTS) analysis to investigate and quantify the global pattern of scaling in two datasets and to better understand cyclic behavior as a possible underlying cause of the observed forms of scaling. We found that, excluding polar and parts of subpolar regions because of their substantial data inhomogeneity, the global temperature pattern is long-range autocorrelated. Our results show a remarkable heterogeneity in the long-range dynamics of the global temperature anomalies in both datasets. This finding is in agreement with previous studies. We additionally studied the DFA2 and the WTS behavior of the local station temperature anomalies and satellite-based temperature estimates and found that the observed diversity of global scaling can be attributed both to the intrinsic variability of data and to the methodology-induced variations that arise from deriving the global temperature gridded data from the original local sources. Finally, we found differences in global temperature scaling patterns of the two datasets and showed instances where spurious scaling is introduced in the global datasets through a spatial infilling procedure or the optimization of integrated satellite records
