Konkursprediksjon gjennom ulike konjunkturfaser : en studie om hvordan en empirisk konkursprediksjonsmodell endrer seg gjennom ulike konjunkturfaser, i tidsperioden 2001 til 2009

Hensikten med denne studien er å analysere hvordan en empirisk konkursprediksjonsmodell endres gjennom ulike konjunkturfaser, og med dette som utgangspunkt undersøke hvorvidt seleksjonskriterier endres i nedgangsperioder. For å gjøre dette har vi på bakgrunn av eksisterende teori og litteratur utviklet en konkursprediksjonsmodell, med utgangspunkt i foretaks- og regnskapsinformasjon for norske bedrifter. Vi har tatt utgangspunkt i tall fra perioden 1999 til 2007, der vi predikerer konkurs to år frem i tid, og følgelig er vår analyseperiode fra 2001 til 2009. De empiriske resultatene viser at konkursprediksjonsmodellens prediksjonsevner endres gjennom ulike konjunkturfaser. Samtidig viser resultatene at parameterverdiene på inkluderte uavhengige variabler også endres. Dette indikerer at seleksjonen av bedrifter i markedet endres i ulike konjunkturfaser, da man ser at ulike bedriftsforhold har ulike effekter på konkurssannsynlighet på tvers av konjunkturfasene. Vi presenterer også forslag til videre forskning på teamet konkursprediksjon, og konkluderer med at det vil være interessant å se på interaksjonseffekter mellom de uavhengige variablene i konkursprediksjonsmodellen, og hvordan deres samspill påvirker bedrifters prestasjoner og overlevelsesevne. Videre vil det være interessant å se hvordan ulike nedgangsperioder kjennetegnes av ulike karakteristikker, og hvordan dette påvirker bedrifters konkurssannsynlighet

Unemployment and Causes of Hospital Admission Considering Different Analytical Approaches

The association between unemployment and hospital admission is known, but the causal relationship is still under discussion. The aim of the present analysis is to compare results of a cross-sectional and a cohort approach considering overall hospital admission and hospital admission due to cancer and circulatory disease. Register-based data were analysed for the period of 2006–2009. In the cross-sectional analysis, a multiple logistic regression model was conducted based on the year 2006, and cohort information from the same year onward up to 2009 was available for a Cox regression model. Social welfare compensated unemployment and both types of disease-specific hospital admission were associated to be statistically significant in the cross-sectional analysis. With regard to circulatory disease, the cohort approach suggests that social welfare compensated unemployment might lead to hospital admission due to the disease. Given the significant results in the cross-sectional analysis for hospital admission due to cancer, the unfound cohort effect might indicate a reverse causation suggesting that the disease caused joblessness, and finally social welfare compensated unemployment and not vice versa. Comparing different study designs allows for a better causal interpretation, which should be recommended in future quantitative social welfare analysis

Health-risk behaviour in deprived neighbourhoods compared with non-deprived neighbourhoods:a systematic literature review of quantitative observational studies

There has been increasing interest in neighbourhoods' influence on individuals' health-risk behaviours, such as smoking, alcohol consumption, physical activity and diet. The aim of this review was to systematically review recent studies on health-risk behaviour among adults who live in deprived neighbourhoods compared with those who live in non-deprived neighbourhoods and to summarise what kind of operationalisations of neighbourhood deprivation that were used in the studies.PRISMA guidelines for systematic reviews were followed. Systematic searches were performed in PubMed, Embase, Web of Science and Sociological Abstracts using relevant search terms, Boolean operators, and truncation, and reference lists were scanned. Quantitative observational studies that examined health-risk behaviour in deprived neighbourhoods compared with non-deprived neighbourhoods were eligible for inclusion.The inclusion criteria were met by 22 studies. The available literature showed a positive association between smoking and physical inactivity and living in deprived neighbourhoods compared with non-deprived neighbourhoods. In regard to low fruit and vegetable consumption and alcohol consumption, the results were ambiguous, and no clear differences were found. Numerous different operationalisations of neighbourhood deprivation were used in the studies.Substantial evidence indicates that future health interventions in deprived neighbourhoods should focus on smoking and physical inactivity. We suggest that alcohol interventions should be population based rather than based on the specific needs of deprived neighbourhoods. More research is needed on fruit and vegetable consumption. In future studies, the lack of a uniform operationalisation of neighbourhood deprivation must be addressed

Widening the Understanding of Risk Approaches by Comparing Definitions from Different Disciplines

The aim of this chapter is to critically reflect definitions of hazard, risk, and risk perception and their assessments used in different scientific disciplines and give examples of the potential implications for scientific discussions, knowledge management, and risk communication. Scientists with backgrounds in public health, psychology, environmental health, occupational health, engineering, sociology, and medicine were asked for a definition of hazard, risk, risk assessment, and risk perception seen from their specific scientific disciplines. Hazard is generally seen as an adverse event or condition. For most risk definitions, probability and severity are important aspects. Often a quantification of risk is desired, whereas risk perception is seen as a subjective appraisal and a cognitive construct. As risk perceptions are based on a combination of knowledge and individual values and affects, it may not provide a reliable guidance for risk management decisions on a societal level. Discipline differences are mainly connected to terminology and interpretation of key concepts, but the differences are based on different tasks and perspectives. For dealing with controversies in science across disciplines, an acceptance and appreciation of terminology and perspectives from different scientific disciplines are needed to ensure a transparent risk assessment process