The more you know,the more you give: Influence of online disclosure on European community foundations' donations

Competition is high in the charitable contributions market, and donors demand to know how nonprofit organizations use the money they receive. In scrutinizing the variables that affect the capacity of nonprofits to attract donations, previous research has highlighted the positive influence of the amount of financial and performance information that nonprofits disclose through their websites. This study explored whether the depth of the organizations' online disclosures also affects these donations. In line with existing studies on regression‐based economic models of giving, this study considered community foundations—focusing on the United Kingdom and Italy—and its results indicated that managing the depth of the information provided through financial reports can influence donors' sensitivity and willingness to donate.     

Cost–Benefit Analysis and the Rates of Return of Infrastructure Projects: Evidence from International Organizations

In this paper we analyse data on the rates of return of investment projects sponsored by three international institutions: the European Union (EU), the European Bank for Reconstruction and Development (EBRD), the World Bank (WB). The focus of the paper is on the variability of ex-ante economic rate of returns (ERR), of financial rates of return (FRR, available for EU and EBRD) and ex-post or re-estimated economic rates of return (RERR, available for WB only), along with the co-financing rate (EU). We propose a framework of analysis of FRR and ERR variations across projects, sectors, financing institutions and time, of the wedge between ERR and FRR, and of the gap between ERR and RERR. Our main conclusions are that the informational content of projects’ rates of return is valuable and is needed for cost–benefit analyses, and that sectors, countries, time and funding institutions explain much of the variability of these rates. We advocate the collection of standardized and comparable data since our framework could be used for comparing rates of return variability of development projects across countries, time of approval or completion, or any other relevant sampling criterion.     

Permutation Approaches for Stochastic Ordering

In many application problems, when dealing with comparisons between two or more groups, the classical parametric inferential statistical methods are used, although in real problems the quite stringent assumptions required by such methods are rarely satisfied. In particular a parametric approach to the test on ordering of C > 2 populations is very difficult. In order to tackle this problem two alternative methods are proposed in the present paper. Both the methods consist in permutation combination based tests: the first is supposed to be more powerful and it is suitable when the main goal of the study is related to the global ordering of the populations; the second is useful when the interest is in the pairwise comparisons between the populations.     

RECONSTRUCTING DNA COPY NUMBER BY PENALIZED ESTIMATION AND IMPUTATION

Recent advances in genomics have underscored the surprising ubiquity of DNA copy number variation (CNV). Fortunately, modern genotyping platforms also detect CNVs with fairly high reliability. Hidden Markov models and algorithms have played a dominant role in the interpretation of CNV data. Here we explore CNV reconstruction via estimation with a fused-lasso penalty as suggested by Tibshirani and Wang [Biostatistics 9 (2008) 18-29]. We mount a fresh attack on this difficult optimization problem by the following: (a) changing the penalty terms slightly by substituting a smooth approximation to the absolute value function, (b) designing and implementing a new MM (majorization-minimization) algorithm, and (c) applying a fast version of Newton's method to jointly update all model parameters. Together these changes enable us to minimize the fused-lasso criterion in a highly effective way.We also reframe the reconstruction problem in terms of imputation via discrete optimization. This approach is easier and more accurate than parameter estimation because it relies on the fact that only a handful of possible copy number states exist at each SNP. The dynamic programming framework has the added bonus of exploiting information that the current fused-lasso approach ignores. The accuracy of our imputations is comparable to that of hidden Markov models at a substantially lower computational cost.     

A Smile Enhances 3‐Month‐Olds’ Recognition of an Individual Face

Recent studies demonstrated that in adults and children recognition of face identity and facial expression mutually interact ( Bate, Haslam, & Hodgson, 2009 ; Spangler, Schwarzer, Korell, & Maier‐Karius, 2010 ). Here, using a familiarization paradigm, we explored the relation between these processes in early infancy, investigating whether 3‐month‐old infants’ ability to recognize an individual face is affected by the positive (happiness) or neutral emotional expression displayed. Results indicated that infants’ face recognition appears enhanced when faces display a happy emotional expression, suggesting the presence of a mutual interaction between face identity and emotion recognition as early as 3 months of age.     

Working Conditions and Health Among Italian Ageing Workers

In many European countries requirements for retirement have been tightened, causing an increase in work participation of older workers, in spite their potentially poorer health may limit their work ability. This study aimed at assessing the diffusion of health problems and exposure to unfavorable working conditions among ageing workers in two Italian surveys, as well as comparing them with those observed in the same surveys conducted before the 2011 Italian pension reform tightening the normal retirement age. The 2013 National Health Survey (NHS) and Labour Force Survey (LFS) were employed to assess the prevalence of poor perceived health, health conditions and functional limitations, and of exposure to physical, psychosocial and organization factors at work, among 60–64 years workers. Poisson regression models were used to estimate Prevalence Ratios of health outcomes and unfavorable working conditions in the two surveys, compared to data from the 2005 (NHS) and 2007 (LFS) corresponding surveys, respectively. Among both men and women, approximately one quarter had at least one physical disorder or functional limitations and 15% poor mental health. Exposure to different ergonomic factors (15–30%) and working during unsocial hours (19%) were particularly diffused. A significant increase in the prevalence of functional limitations and of working at night or during unsocial hours was found in 2013, compared to corresponding data from 2005 and 2007, respectively. Our results indicate that exposure to ergonomic and organizational hazards should be reduced among ageing workers, to avoid decreased work ability, health damage or early exit from the labour market.

     

Networks as mediating variables: a Bayesian latent space approach

Statistical Methods & Applications - The use of network analysis to investigate social structures has recently seen a rise due to the high availability of data and the numerous insights it can...