Numerical estimates of risk factors contingent on credit ratings

AbstractAssuming a favorable or an adverse outcome for every combination of a credit class and an industry sector, a binary string, termed as a macroeconomic scenario, is considered. Given historical transition counts and a model for dependence among credit-rating migrations, a probability is assigned to each of the scenarios by maximizing a likelihood function. Applications of this distribution in financial risk analysis are suggested. Two classifications are considered: 7 non-default credit classes with 6 industry sectors and 2 non-default credit classes with 12 industry sectors. We propose a heuristic algorithm for solving the corresponding maximization problems of combinatorial complexity. Probabilities and correlations characterizing riskiness of random events involving several industry sectors and credit classes are reported

Analysis of the historical structural change in the German hard coal mining Ruhr area (case study)

This case study examined the structural change in the Ruhr area caused by the low international competitiveness of German hard coal mining over the period from the late 1950s to 2015. It analysed the structural change process and the structural policies implemented as a reaction to this process with the objective to make this knowledge available for future structural change processes in other (coal) regions by deploying various qualitative and quantitative methods of empirical social and economic research. A discourse analysis helped to recognise who supported which structural policy approaches and why - and thus gives indications of the possible relevance of experiences for other regions

Analyse des historischen Strukturwandels im Ruhrgebiet (Fallstudie)

Diese Fallstudie untersuchte den durch die geringe Wettbewerbsfähigkeit des Steinkohlebergbaus ausgelösten Strukturwandel im Ruhrgebiet vom Ende der 1950er Jahre bis 2015. Mit Hilfe verschiedener qualitativer und quantitativer Methoden der empirischen Sozial- und Wirtschaftsforschung analysierte sie den Strukturwandelprozess und die in Reaktion auf diesen Prozess umgesetzte Strukturpolitik mit dem Ziel, dieses Wissen für zukünftige Strukturwandelprozesse in anderen (Kohle-)Regionen zur Verfügung zu stellen. Eine Diskursanalyse half zu erkennen, wer warum welche strukturpolitischen Ansätze unterstützte - und gibt damit Hinweise auf die mögliche Relevanz von Erfahrungen für andere Regionen

Relationship between depression, anxiety, stress, and SARS-CoV-2 infection: a longitudinal study

ObjectivesWe aimed to (1) describe the course of the emotional burden (i.e., depression, anxiety, and stress) in a general population sample during the coronavirus pandemic in 2020 and 2021 and (2) explore the association between emotional burden and a serologically proven infection with SARS-CoV-2.Study designThis longitudinal study involved a sample of community-dwelling persons aged ≥14 years from the general population of South Tyrol (Province of Bolzano-Bozen, Northern Italy). Data were collected at two stages over a 1-year period in 2020 and 2021.MethodsPersons were invited to participate in a survey on socio-demographic, health-related and psychosocial variables (e.g., age, chronic diseases, Depression Anxiety Stress Scale, DASS-21), as well as in the serological testing for of SARS-CoV-2-specific immunoglobulins.ResultsIn 2020, 855 (23.8%) out of 3,600 persons participated; in 2021, 305 (35.7%) out of 855 were tested again. We observed a statistically significant decrease in mean DASS-21 scores for depression, stress, and total scores between 2020 and 2021, yet not for anxiety. Persons with a confirmed SARS-CoV-2-infection between the first and second data collection exhibited increased emotional burden compared to those without SARS-CoV-2-infection. The odds of participants with a self-reported diagnosis of mental disorder for future infection with SARS-CoV-2 was almost four times higher than that of participants without mental disorders (OR:3.75; 95%CI:1.79-7.83).ConclusionOur findings support to the hypothesis of a psycho-neuroendocrine-immune interplay in COVID-19. Further research is necessary to explore the mechanisms underlying the interplay between mental health and SARS-CoV-2 infections

Vaccine Hesitancy and Public Mistrust during Pandemic Decline: Findings from 2021 and 2023 Cross-Sectional Surveys in Northern Italy

This study examines vaccine agreements in South Tyrol, Italy, within distinct socio-cultural and linguistic contexts. Using data from the 2021 and 2023 “COVID-19 Snapshot Monitoring” extended surveys, we assessed changes in attitudes towards COVID-19 and other vaccinations during the second and final years of the pandemic. Multivariate logistic regression analysis was used to examine factors such as trust in institutions, language groups, and the use of complementary and alternative medicine. The representativeness of the study is supported by good participation rates, ensuring a comprehensive view of attitudes towards vaccination in the region. The results show a shift in public agreement with the national vaccination plan to 64% by 2023, from a rate of about 73% agreement in 2021 (p < 0.001). A significant decrease in trust in health authorities and a negative correlation with complementary and alternative medicine consultations were observed. The results highlight the complex nature of vaccine hesitancy in diverse regions such as South Tyrol and underline the need for targeted communication strategies and trust-building initiatives to effectively reduce hesitancy. This study provides critical insights for the formulation of public health strategies in diverse sociocultural settings

Age-Related Associations of Altruism with Attitudes towards COVID-19 and Vaccination: A Representative Survey in the North of Italy

Background: During the coronavirus pandemic, altruism has been linked to personal protective behavior, vaccine development, and vaccination intention. Studies of the moderating effects of age on altruism in pandemic preparedness have not yet been conducted. Methods: A representative cross-sectional survey of residents of South Tyrol, Italy, was conducted in March 2021. Among the participants, 1169 were aged 18–69 years, and 257 were aged ≥ 70 years. The questionnaire collected information on sociodemographic and individual characteristics, including comorbidities, COVID-19-related experiences, trust in information, the likelihood of accepting the national vaccination plan, and altruism. A linear regression analysis was performed. Results: Among 1426 participants, the median altruism sum score was 24 (interquartile range, 20–26). In the participant group aged ≥ 70 years, the median altruism score was significantly higher than that in the younger group. Participants living in a single household were significantly less altruistic than other participants, while participants working in the health sector, living in a household at risk from coronavirus disease 2019, or suffering from a chronic disease were found to be more altruistic. Altruism showed significant positive correlations with age and agreement with the national vaccination plan and was negatively correlated with well-being. Trust in institutions was positively correlated with altruism only in the younger age group but not in the elderly. Linear regression models confirmed female gender and identified trust in institutions as a positive predictor of altruism. In the younger age group, increased well-being and restricted individual sports activities were associated with reduced altruism, whereas support of compulsory self-isolation after contact with a SARS-CoV-2-positive person and handwashing as a personal protective measure were positively associated. Conclusion: Altruism is associated with various predictors of pandemic behavior and traits. The strengths of the identified positive and negative correlations support the modifying role of age in the effects of altruism on pandemic attitudes. Interventions that are likely to enhance altruism to improve pandemic preparedness in certain age groups require further study

Rural-Urban Disparities in Vaccine Hesitancy among Adults in South Tyrol, Italy

Background: The demographic determinants of hesitancy in Coronavirus Disease&mdash;2019 (COVID-19) vaccination include rurality, particularly in low- and middle-income countries. In the second year of the pandemic, in South Tyrol, Italy, 15.6 percent of a representative adult sample reported hesitancy. Individual factors responsible for greater vaccination hesitancy in rural areas of central Europe are poorly understood. Methods: A cross-sectional survey on a probability-based sample of South Tyrol residents in March 2021 was analyzed. The questionnaire collected information on sociodemographic characteristics, comorbidities, COVID-19-related experiences, conspiracy thinking, and the likelihood of accepting the national vaccination plan. A logistic regression analysis was performed. Results: Among 1426 survey participants, 17.6% of the rural sample (n = 145/824) reported hesitancy with COVID-19 vaccination versus 12.8% (n = 77/602) in urban residents (p = 0.013). Rural residents were less likely to have post-secondary education, lived more frequently in households with children under six years of age, and their economic situation was worse than before the pandemic. Chronic diseases and deaths due to COVID-19 among close relatives were less frequently reported, and trust in pandemic management by national public health institutions was lower, as was trust in local authorities, civil protection, and local health services. Logistic regression models confirmed the most well-known predictors of hesitancy in both urban and rural populations; overall, residency was not an independent predictor. Conclusion: Several predictors of COVID-19 vaccine hesitancy were more prevalent in rural areas than in urban areas, which may explain the lower vaccine uptake in rural areas. Rurality is not a determinant of vaccine hesitancy in the economically well-developed North of Italy

Vaccine Hesitancy during the Coronavirus Pandemic in South Tyrol, Italy: Linguistic Correlates in a Representative Cross-Sectional Survey

Background: German is a minority language in Italy and is spoken by the majority of the inhabitants of the Autonomous Province of Bolzano, South Tyrol. Linguistic group membership in South Tyrol is an established determinant of health information-seeking behavior. Because the COVID-19 incidence and vaccination coverage in the second year of the pandemic in Italy was the worst in South Tyrol, we investigated whether linguistic group membership is related to COVID-19 vaccine hesitancy. Methods: A cross-sectional survey was conducted on a probability-based sample of 1425 citizens from South Tyrol in March 2021. The questionnaire collected information on socio-demographics, including linguistic group membership, comorbidities, COVID-19-related experiences, conspiracy thinking, well-being, altruism, and likelihood of accepting the national vaccination plan. Multiple logistic regression analyses were performed to identify the significant predictors of vaccine hesitancy. Results: Overall, 15.6 percent of the sample reported vaccine hesitancy, which was significantly higher among German speakers than among other linguistic groups. Increased hesitancy was mostly observed in young age, the absence of chronic disease, rural residence, a worsened economic situation, mistrust in institutions, and conspiracy thinking. In the multiple logistic regression analyses, linguistic group membership was not an independent predictor of vaccine hesitancy. Conclusion: Although German is a minority language in Italy and COVID-19 vaccine hesitancy was higher in the German native language group than in the Italian, linguistic group membership was not an independent predictor of hesitancy in the autonomous province. Known predictors of vaccine hesitancy are distributed unevenly across language groups. Whether language group-specific intervention strategies to promote vaccine hesitancy are useful requires further study