Ethical Problems for the Law Firm of a Former Government Attorney: Firm or Individual Disqualification?

In the area of pricing insurances, many statistical tools are used. The number of tools that exist are overwhelming and it is dicult to know which one to choose. In this thesis ve regression models are compared on how good they t the number of reported claims in third party automobile insurance. The models considered are OLS, Poisson, Negative Binomial and two Hurdle models. The Hurdle models are based on Poisson regression and Negative Binomial regression respectively, but with additional number of zeros. The AIC and BIC statistics are considered for all the models and the predicted number of claims are calculated and compared to the observed number of claims. Also, a hypothesis test for the null hypothesis that the Hurdle models are not needed is performed. The OLS regression is not suitable for this kind of data. This can be explained by the fact that the number of claims are not normally distributed. This is the case because many policyholders never report any claims and the data therefore includes an excess number of zeros. Also, the number of claims can never be negative. The other four models are considerably better and all of them t the data satisfactory. The one of them that performs best in one test is inadequate in another. The Negative Binomial model is a bit better than the other models, but the model choice is not obvious. The conclusion is not that a specic model is preferable, but that one need to choose model critically. Keywords: Regression Models, Insurance, Count Data, Regression Analysis, Hurdle RegressionDet finns många statistiska hjälpmedel att använda inom prissättning av forsäkringar. Antalet hjälpmedel är överväldigande och det är svårt att veta vad man ska använda sig av. I den har studentuppsatsen kommer fem regressionsmodeller att jämforas i hur bra de passar for antalet anmälda skador inom trafikförsäkring. De fem modellerna är OLS, Poisson, Negative Binomial och två Hurdle-modeller. Hurdle-modellerna är baserade på Poisson och Negative Binomial respektive, men de är anpassade för ett större antal nollor. Värdena av AIC och BIC jämförs för de olika modellerna och antalet predikterade anmälda skador jämfors med antalet observerade skador. Ett hypotestest är också utfort for att testa nollhypotesen att Hurdle-modellerna inte behövs. Den modell som passar sämst till datan ar OLS. Det kan forklaras av att antalet anmälda skador inte ar normalfordelade som man antar vid OLS. Det kan bero på att många försäkringstagare aldrig anmäler någon skada och att det därfor finns ett överskott av nollor i datan. Det kan även bero på att antalet anmälda skador aldrig kan bli negativt. De andra fyra modellerna är mycket bättre och de kan anpassas till datan på ett acceptabelt sätt. Den av modellerna som är bäst i ett test är sämre i ett annat. Negative Binomial-modellen är aningen bättre än ovriga modeller, men det ar inte självklart vilken modell som bör anvandas. Slutsatsen är att det inte finns någon perfekt modell, utan att man maste välja genom att vara kritisk. Nyckelord: Regressionsmodeller, Forsäkring, Raknedata, Regressionsanalys, Hurdleregressio

NHS reforms and the working lives of midwives and physiotherapists

From 2000 the NHS was subjected to a series of far reaching reforms, the purposes of which were to increase the role of the primary care sector in commissioning and providing services, promote healthier life styles, reduce health inequality, and improve service standards. These were seen as requiring a greater leadership role from health professionals, closer and more cooperative working between health professionals, and between health professionals, social services, and community and other service providers. The project surveyed a random sample of midwives and physiotherapists to investigate their perceptions of the effectiveness of the reforms, and their effects on working lives. The predominant perception was that NHS reforms had negatively affected the funding of their services; and had done little to improve service quality, delivery or organisation. Although the potential existed for the reforms to improve services, the necessary resources and required staffing were not made available and the objectives of the reforms were only partially secured by intensifying of work. The downside of this was a deterioration of the sociopsychological wellbeing of midwives and physiotherapists, especially the former, exacerbating the shortage of skilled and experienced. Shortage of staff and the associated increased work burdens were demoralising and demotivating; morale and job satisfaction declined, and job insecurity and labour turnover increased