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Introduction: Several countries imposed nationwide or partial lockdowns to limit the spread of COVID-19 and avoid overwhelming hospitals and intensive care units. Lockdown may involve restriction of movement, stay-at-home orders and self-isolation, which may have dramatic consequences on mental health. Recent studies demonstrated that the negative impact of lockdown restrictions depends on a wide range of psychological and socio-demographic factors. Aims: This longitudinal study aimed to understand how internal factors such as personality and mindfulness traits, and external factors, such as daily habits and house features, affect anxiety, depression and general wellbeing indicators, as well as cognitive functions, during the course of a lockdown. Methods: To address these questions, 96 participants in Italy and the United Kingdom filled out a survey, once a week for 4 weeks, during the first-wave lockdowns. The survey included questions related to their habits and features of the house, as well as validated questionnaires to measure personality traits, mindful attitude and post-traumatic symptoms. Indicators of wellbeing were the affective state, anxiety, stress and psychopathological indices. We also measured the emotional impact of the pandemic on cognitive ability by using two online behavioral tasks [emotional Stroop task (EST) and visual search]. Results: We found that internal factors influenced participants' wellbeing during the first week of the study, while external factors affected participants in the last weeks. In the first week, internal variables such as openness, conscientiousness and being non-judgmental toward one's own thoughts and emotions were positively associated with wellbeing; instead, neuroticism and the tendency to observe and describe one's own thoughts and emotions had detrimental effects on wellbeing. Toward the end of the study, external variables such as watching television and movies, browsing the internet, walking the dog, and having a balcony showed a protective value, while social networking and engaging in video calls predicted lower values of wellbeing. We did not find any effects of wellbeing on cognitive functioning. Conclusion: Recognizing specific traits and habits affecting individuals' wellbeing (in both short and long terms) during social isolation is crucial to identify people at risk of developing psychological distress and help refine current guidelines to alleviate the psychological consequences of prolonged lockdowns. [ABSTRACT FROM AUTHOR]

This paper analyzes the impact of the Italian Start Up Act which entered into force in October 2012. This public policy provides a unique bundle of benefits, such as tax incentives, public loan guarantees, and a more flexible labor law, for firms registered as "innovative startups" in Italy. This legislation has been implemented by the Italian government to increase innovativeness of small and young enterprises by facilitating access to (external) capital and (high-skilled) labor. Consequently, the goal of our evaluation is to assess the impact of the policy on equity, debt, and employment. Using various conditional difference-in-difference models, we find that the Italian innovative startup policy has met its primary objectives. The econometric results strongly suggest that Italian innovative startups are more successful in obtaining equity and debt capital and they also hire more employees because of the program participation. [ABSTRACT FROM AUTHOR]

This work analyses the properties of corporate growth in a large longitudinal sample of Italian manufacturing firms. In particular, it focuses on the statistical properties of growth rates and on the influence of proxies for relative efficiency upon relative growth. In line with previous work, the emergence of 'fat tails' in growth rate distributions and the idiosyncratic nature of autocorrelation coefficients confirm the existence of a structure in the growth process richer than the one normally assumed by the 'Gibrat Law' hypothesis and suggest the presence of firm-specific drivers of growth. At the same time, there is a remarkable puzzle concerning the absence of any negative relationship between size and growth variance and only weak influences of relative efficiencies upon growth dynamics. [ABSTRACT FROM AUTHOR]

In this paper we present an analysis of the behavior of Italian Twitter users during national political elections. We monitor the volumes of the tweets related to the leaders of the various political parties and we compare them to the elections results. Furthermore, we study the topics that are associated with the co-occurrence of two politicians in the same tweet. We cannot conclude, from a simple statistical analysis of tweet volume and their time evolution, that it is possible to precisely predict the election outcome (or at least not in our case of study that was characterized by a “too-close-to-call” scenario). On the other hand, we found that the volume of tweets and their change in time provide a very good proxy of the final results. We present this analysis both at a national level and at smaller levels, ranging from the regions composing the country to macro-areas (North, Center, South). [ABSTRACT FROM AUTHOR]