Contingency Planning and Early Crisis Management: Italy and the COVID-19 Pandemic

Public Organization Review - This study examines the level of preparedness exhibited through strategy, planning and organization to deal with the COVID-19 pandemic in Italy. A comparative analysis...     

Assessing the effect of the amount of financial aids to Piedmont firms using the generalized propensity score

Regional and national development policies play an important role to support local enterprises in Italy. The amount of financial aid may be a key feature for firms’ employment policies. We study the impact on employment of the amount of financial aid attributed to enterprises located in Piedmont, a region in northern Italy, analysing small-sized firms and medium- or large-sized firms separately. We apply generalized propensity score methods under the unconfoundedness assumption that adjusting for differences in a set of observed pre-treatment variables removes all biases in comparisons by different amounts of financial aid. We find that the estimated effects are increasing with amount of financial aid for both small-sized and medium- or large-sized firms, whereas the marginal effects of additional incentives are decreasing with amount of financial aid for small-sized firms, and have an inverse J-shape for medium- or large-sized firms.     

Estimating and using propensity score in presence of missing background data: an application to assess the impact of childbearing on wellbeing

Propensity score methods are an increasingly popular technique for causal inference. To estimate propensity scores, we must model the distribution of the treatment indicator given a vector of covariates. Much work has been done in the case where the covariates are fully observed. Unfortunately, many large scale and complex surveys, such as longitudinal surveys, suffer from missing covariate values. In this paper, we compare three different approaches and their underlying assumptions of handling missing background data in the estimation and use of propensity scores: a complete-case analysis, a pattern-mixture model based approach developed by Rosenbaum and Rubin (J Am Stat Assoc79:516–524, 1984), and a multiple imputation approach. We apply these methods to assess the impact of childbearing events on individuals’ wellbeing in Indonesia, using a sample of women from the Indonesia Family Life Survey. I am grateful to all the participants at the project “Poverty Dynamics and Fertility in Developing Countries” for their support and encouragement. Special thanks are due to Fabrizia Mealli for her insightful suggestions and discussions. I also thank Jungho Kim, who is the main author of the STATA code to produce Indonesia consumption expenditure. Finally, I thank Arnstein Aassve, and Letizia Mencarini for help working with the data and their very useful discussions, and Alexia Fuernkranz-Prskawetz, and Henriette Engelhardt for detailed comments and suggestions which have improved the paper. Financial support from CNR-EFS and COFIN 2005 is gratefully acknowledged.     

Childhood Victimization,Cognitive Schemas,and Unwanted Consensual Sex Among College Students

Objective: Unwanted consensual sex (UCS)—freely consenting to sex that is neither wanted nor desired—is largely excluded from campus programming and the literature on sexual behavior. The present study expands on previous research to examine the relation between childhood victimization experiences and UCS.

Methods: Data were gathered using an online survey of college students.

Results: In the past year, 43% percent of 587 college students who engaged in sexual activity also engaged in UCS at least once. Childhood victimization was modestly related to frequency of UCS. The relation between childhood victimization and UCS was mediated by disconnection/rejection schemas (e.g., beliefs that one’s needs will not be met by others).

Conclusions: Results suggest that altering cognitive schemas through evidence-based psychotherapy may interrupt the relation between childhood victimization and engagement in UCS.     

全球法与掠夺:法治的阴暗面

"法治"(rule of law),习惯上已被当作一个具有积极本质、政治中立的"工具",且效力普适,放之四海而皆准.作为Ugo Mattei与Laura Nadar教授合著的Plunder:When the Ruleof Law is Illegal (Blackwell Publishing,Oxford 2008)一书观点的综述,本文认为,作为一个歧义丛生的概念,"法治"具有光明与阴暗的两面性,而"法治"的阴暗面长期以来一直被排除在公众讨论的范围之外."法治"作为一个华丽辞藻,已被西方强势者所挟持,用来论证其(主要)对"发展中"国家的干涉及其最终演变成的掠夺(plunder)实践的合法性,并使西方经济势力对"非西方世界"(the rest)的扩张成为可能.基于此,我们得出了这样的结论:"法治"已被"非法地"(illegally)利用.目前国际金融机构--当今的全球立法者--在用"法治"观念包裹着其提供给"发展中世界"的各种改革方案的背后,隐藏着智识短视、种族中心主义和帝国主义立场."技术性"概念对"法"概念的偷换,美国法所独享的全球性支配地位以及当今西方跨国公司的帝国主义态度等作为其中的一些指标,向我们展示了殖民主义与当今新自由主义政策之间的沆瀣一气.     

The Politics of ‘Social Accountability’ in England and Germany: Democratic Control and Moral Imperatives

This article investigates how politicians in England and Germany approach social accountability during the introduction of markets in the national health care systems. It analyses the discourse among members of parliament during the law making process of the 2012 NHS Health Care Act in England and the 2011 Act for Financing of Statutory Health Insurance in Germany. Generally, the new social accountability reform agenda is attractive to policy makers as it foregrounds public engagement and bottom-up participation (Peters 2001). Social accountability refers to institutional practices that favour participatory and horizontal mechanisms that depart from traditional hierarchical Principal-Agent forms.     

Exact dimensionality selection for Bayesian PCA

We present a Bayesian model selection approach to estimate the intrinsic dimensionality of a high-dimensional dataset. To this end, we introduce a novel formulation of the probabilisitic principal component analysis model based on a normal-gamma prior distribution. In this context, we exhibit a closed-form expression of the marginal likelihood which allows to infer an optimal number of components. We also propose a heuristic based on the expected shape of the marginal likelihood curve in order to choose the hyperparameters. In nonasymptotic frameworks, we show on simulated data that this exact dimensionality selection approach is competitive with both Bayesian and frequentist state-of-the-art methods.     

Identification of Local Causal Effects with Missing Outcome Values and an Instrument for Non Response

Even in randomized experiments the identification of causal effects is often threatened by the presence of missing outcome values, with missingness possibly being non ignorable. We provide sufficient conditions under which the availability of a binary instrument for non response allows us to non parametrically point identify average causal effects in some latent subgroups of units, named Principal Strata, defined by their non response behavior in all possible combinations of treatment and instrument. Examples are provided as possible scenarios where our assumptions may be plausible.