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Tomislava Pavić Kramarić, Marko Miletić and Renata Kožul Blaževski
Background: Financial stability or soundness of insurance companies has gained importance over the years, especially after the financial crisis of 2008. Various stakeholders such as policy makers, regulators, the insured, etc. are interested in keeping the insurance sector stable since it contributes to overall financial stability.
Objectives: The authors explore the determinants of insurers’ soundness in selected countries in Central and Eastern Europe. The analysis covers life, non-life and composite insurers that operated in Croatia, Hungary, and Poland in the period 2013 – 2017.
Methods/Approach: A set of insurer – specific, industry – specific and macroeconomic variables are taken into consideration for having a potential influence on soundness measured by the Z-score. The variables include the size based on total assets, the share of premium ceded to reinsurance, claims growth, gross written premium growth, the premium to surplus ratio, market shares held by the five largest insurers, the share of gross written premium in the gross domestic product (GDP) and the GDP per capita growth.
Results: The findings reveal that soundness of Croatian insurers is positively influenced by the size of an insurer. Both in Hungary and Poland reinsurance plays an important factor positively affecting soundness.
Conclusions: Each of the insurance markets covered by the analysis reveals its characteristics and offers guidelines on factors influencing financial stability.
omitted variable bias in the estimated effects of parental migration.
The results suggest that whether parental migration is beneficial or deleterious to child health depends on which parent moved. Migration of the mother has an adverse effect on child height-for-age, whereas migration of the father has no effect. This finding is important because of the long temporal reach of health in childhood; a plethora of empirical evidence shows that poorer health in early life leads to lower educational attainment ( Almond, 2006 ; Case et al., 2005 ), lower scores in high
The humankind is ageing rapidly, and as a result, there is an increasing need for old people’s homes. The nursing homes face different problems in financing and recruiting the labour force and management. Lack of resources causes the situation, when managers have to find possibilities to accomplish services and to provide quality care with the limited funds. This situation has an additional impact on the nursing professionals, who have to deal with many psychosocial risk factors in their work. The aim of the paper is to explore the work-related psychosocial risk factors and their relationships with mental health problems (MHPs) amongst care workers. A cross-sectional survey was undertaken amongst the care workers in nine Estonian nursing homes. Psychosocial work factors and MHPs (stress, somatic symptoms, depressive symptoms, burnout, cognitive symptoms, and sleep disorders) were analysed using the second version of the Copenhagen Psychosocial Questionnaire (COPSOQ II). Descriptive statistics and Pearson’s r correlation were used to analyse the data. The analysis was based on 340 care worker surveys. The highest mean scores for the studied work-related psychosocial factors were recorded for the quantitative demands, influence, rewards, role conflicts, trust, insecurity and work-family balance. Low mean scores were recorded for the meaning of work, role clarity, social relationships at work. The lowest score was followed by burnout and the highest - by cognitive symptoms.
Pablo de Pedraza, Marcos Álvarez-Díaz and Marcos Domínguez-Torreiro
followed to combine the individual variables into flexicurity drivers. We use the EMCO list of flexicurity and job quality indicators ( EMCO, 2009 ) to populate the different flexibility/security components, types, and drivers. Following the logic outlined in the previous section, we tentatively assign each indicator to the relevant driver and flexibility and security category. The expected sign of the contribution of each variable to flexibility and security is defined as the “direction” of the variable. For example, a higher score on the variable “EPL regular contracts
Note: Luxembourg, Slovak Republic, Estonia, and Slovenia are not presented in the graph because data are not available at the beginning of the period.
Source : OECD. PMR, product market regulation.
In recent years, liberalization of the product market has slowed down in European countries. Between 1998 and 2003, the average PMR score fell by 0.46 compared to 0.26 between 2003 and 2008 and 0.14 between 2008 and 2013. The pace of reforms may have slowed down, because most countries have already reached a low level of regulation. The potential
empirical and theoretical findings by Rauch and Trindade (2002) and Rauch and Casella (2003) , the authors find weaker effects for entrepreneurs and business-class immigrants. The authors explain this result with the selection of immigrants in these classes. Business immigrants are admitted to Canada primarily because of capital (investors) or because they are artists (self-employed) and therefore do not bring trade knowledge or connections to Canada. Entrepreneur-class immigrants receive a 45-point (out of 70) bonus which may allow many to enter despite low scores on
years of education and educational degree, they found that foreign-acquired education is valued less than education acquired in Canada. In their recent study, Fortin et al. (2016) found that controlling for source of human capital helps to account for a large share of the immigrant–native-born wage gap. Li and Sweetman (2014) used international test scores as a proxy for the quality of source country educational outcomes and found that there is a strong and positive association between returns to prearrival schooling in the host country and the quality of
limits (and hence potentially weaker protection). The output of AI tools (for instance, creative works) are, so far, not protected. Similarly, individual data are not being protected (but rather are considered confidential), including against false information ( Scassa, 2018 ). This is a particular challenge when workers, customers, or debtors are shunned from market opportunities because of false information recorded in the databases on which AI algorithms base their assessment. Accounts of credit scoring systems shunning potential debtors from financial services