The National Disability Insurance Scheme : an Australian public policy experiment / / Mhairi Cowden, Claire McCullagh, editors |
Edizione | [First edition.] |
Pubbl/distr/stampa | Singapore : , : Palgrave Macmillan, , [2021] |
Descrizione fisica | 1 online resource (XXIII, 451 p. 6 illus., 4 illus. in color.) |
Disciplina | 362.40994 |
Soggetto topico |
Disability insurance - Government policy - Australia
Social security - Australia Assegurances d'invalidesa Seguretat social Política governamental |
Soggetto genere / forma | Llibres electrònics |
ISBN | 981-16-2244-2 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Part I -- Chapter 1: Introduction -- 2. History of disability services -- 3. What is the National Disability Insurance Scheme? -- 4. The NDIS and Philosophy -- 5. The NDIS today -- 6. The Future of the NDIS -- 7. NDIS and children (possible author Mhairi Cowden) -- 8. NDIS and Indigenous Australians -- 9. NDIS and the Aged Care system -- 10. NDIS and housing -- 11. NDIS and mental health services -- 12. the role of actuaries in the NDIS -- 13. NDIS and the not-for-profit service delivery sector and private providers -- 14. Lessons from implementation (possible authors Mhairi Cowden and Claire McCullagh) -- 15. Individual stories. |
Record Nr. | UNINA-9910495226603321 |
Singapore : , : Palgrave Macmillan, , [2021] | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Pandemics : insurance and social protection / / editors, María del Carmen Boado-Penas, Julia Eisenberg, Şule Şahin |
Autore | Boado-Penas María del Carmen |
Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2021 |
Descrizione fisica | 1 online resource (xx, 298 pages) : illustrations (some color) |
Altri autori (Persone) |
Boado-PenasMaría del Carmen
EisenbergJulia ŞahinŞule |
Collana | Springer Actuarial |
Soggetto topico |
Epidemics
Insurance - Mathematical models Insurance - Statistical methods Social security Assegurances Models matemàtics Estadística matemática Seguretat social Epidèmies |
Soggetto genere / forma | Llibres electrònics |
Soggetto non controllato |
Epidemics
Risk Insurance Social protection Actuarial modelling Open Access |
ISBN | 3-030-78334-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- Contributors -- 1 COVID-19: A Trigger for Innovations in Insurance? -- 1.1 Introduction -- 1.2 Discussions from the Perspective of Insurance and Social Protection -- 1.2.1 Commercial Insurance -- 1.2.2 The Role of the Governments and Social Protection -- 1.3 Listening to the Wind of Change -- References -- 2 Epidemic Compartmental Models and Their Insurance Applications -- 2.1 Introduction -- 2.2 Compartmental Models in Epidemiology -- 2.2.1 SIR Model -- 2.2.2 Other Compartmental Models -- 2.3 Epidemic Insurance
2.3.1 Annuities and Insurance Benefits -- 2.3.2 Reserves -- 2.3.3 Further Extensions -- 2.3.4 Case Studies: COVID-19 -- 2.4 Resource Management -- 2.4.1 Pillar I: Regional and Aggregate Resources Demand Forecast -- 2.4.2 Pillar II: Centralised Stockpiling and Distribution -- 2.4.3 Pillar III: Centralised Resources Allocation -- 2.5 Conclusion -- References -- 3 Some Investigations with a Simple Actuarial Model for Infections Such as COVID-19 -- 3.1 Introduction -- 3.2 Multiple State Actuarial Models -- 3.3 A Simple Daily Model for Infection -- 3.4 Comparisons with the SIR Model 3.5 Enhancements for COVID-19 and Initial Assumptions -- 3.6 Estimating Parameters Model 1 -- 3.7 Estimating Parameters Model 2 -- 3.8 Comments on Results of Models 1 and 2 -- 3.9 Further Extensions: Models 3 and 4 -- 3.10 Comments on Results of Models 3 and 4 -- 3.11 Projection Models -- 3.12 Problems and Unknowns -- 3.13 Other Countries -- 3.14 Conclusions -- References -- 4 Stochastic Mortality Models and Pandemic Shocks -- 4.1 Stochastic Mortality Models and the COVID-19 Shock -- 4.2 The Impact of COVID-19 on Mortality Rates 4.3 Stochastic Mortality Models and Pandemics: Single-Population Models -- 4.3.1 Discrete-Time Single Population Models -- 4.3.2 Continuous-Time Single-Population Models -- 4.4 Stochastic Mortality Models and Pandemics: Multi-population -- 4.4.1 Discrete-Time Models -- 4.4.2 Continuous-Time Models -- 4.5 A Continuous-Time Multi-population Model with Jumps -- 4.6 Conclusions -- References -- 5 A Mortality Model for Pandemics and Other Contagion Events -- 5.1 Introduction -- 5.2 Highlights of Methodology and Findings -- 5.2.1 Summary of Methodology -- 5.2.2 Summary of Findings 5.3 Semiparametric Regression in MCMC -- 5.3.1 MCMC Parameter Shrinkage -- 5.3.2 Spline Regressions -- 5.3.3 Why Shrinkage? -- 5.3.4 Cross Validation in MCMC -- 5.4 Model Details -- 5.4.1 Formulas -- 5.4.2 Fitting Process -- 5.5 Results -- 5.5.1 Extensions: Generalisation, Projections and R Coding -- 5.6 Conclusions -- References -- 6 Risk-Sharing and Contingent Premia in the Presence of Systematic Risk: The Case Study of the UK COVID-19 Economic Losses -- 6.1 Introduction -- 6.2 Risk Levels and Systematic Risk in Insurance -- 6.3 Mathematical Setup -- 6.3.1 Probability Space 6.3.2 Insurance Preliminaries |
Altri titoli varianti | Pandemics |
Record Nr. | UNISA-996466419903316 |
Boado-Penas María del Carmen | ||
Cham, : Springer International Publishing AG, 2021 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Pandemics : insurance and social protection / / editors, María del Carmen Boado-Penas, Julia Eisenberg, Şule Şahin |
Autore | Boado-Penas María del Carmen |
Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2021 |
Descrizione fisica | 1 online resource (xx, 298 pages) : illustrations (some color) |
Altri autori (Persone) |
Boado-PenasMaría del Carmen
EisenbergJulia ŞahinŞule |
Collana | Springer Actuarial |
Soggetto topico |
Epidemics
Insurance - Mathematical models Insurance - Statistical methods Social security Assegurances Models matemàtics Estadística matemática Seguretat social Epidèmies |
Soggetto genere / forma | Llibres electrònics |
Soggetto non controllato |
Epidemics
Risk Insurance Social protection Actuarial modelling Open Access |
ISBN | 3-030-78334-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- Contributors -- 1 COVID-19: A Trigger for Innovations in Insurance? -- 1.1 Introduction -- 1.2 Discussions from the Perspective of Insurance and Social Protection -- 1.2.1 Commercial Insurance -- 1.2.2 The Role of the Governments and Social Protection -- 1.3 Listening to the Wind of Change -- References -- 2 Epidemic Compartmental Models and Their Insurance Applications -- 2.1 Introduction -- 2.2 Compartmental Models in Epidemiology -- 2.2.1 SIR Model -- 2.2.2 Other Compartmental Models -- 2.3 Epidemic Insurance
2.3.1 Annuities and Insurance Benefits -- 2.3.2 Reserves -- 2.3.3 Further Extensions -- 2.3.4 Case Studies: COVID-19 -- 2.4 Resource Management -- 2.4.1 Pillar I: Regional and Aggregate Resources Demand Forecast -- 2.4.2 Pillar II: Centralised Stockpiling and Distribution -- 2.4.3 Pillar III: Centralised Resources Allocation -- 2.5 Conclusion -- References -- 3 Some Investigations with a Simple Actuarial Model for Infections Such as COVID-19 -- 3.1 Introduction -- 3.2 Multiple State Actuarial Models -- 3.3 A Simple Daily Model for Infection -- 3.4 Comparisons with the SIR Model 3.5 Enhancements for COVID-19 and Initial Assumptions -- 3.6 Estimating Parameters Model 1 -- 3.7 Estimating Parameters Model 2 -- 3.8 Comments on Results of Models 1 and 2 -- 3.9 Further Extensions: Models 3 and 4 -- 3.10 Comments on Results of Models 3 and 4 -- 3.11 Projection Models -- 3.12 Problems and Unknowns -- 3.13 Other Countries -- 3.14 Conclusions -- References -- 4 Stochastic Mortality Models and Pandemic Shocks -- 4.1 Stochastic Mortality Models and the COVID-19 Shock -- 4.2 The Impact of COVID-19 on Mortality Rates 4.3 Stochastic Mortality Models and Pandemics: Single-Population Models -- 4.3.1 Discrete-Time Single Population Models -- 4.3.2 Continuous-Time Single-Population Models -- 4.4 Stochastic Mortality Models and Pandemics: Multi-population -- 4.4.1 Discrete-Time Models -- 4.4.2 Continuous-Time Models -- 4.5 A Continuous-Time Multi-population Model with Jumps -- 4.6 Conclusions -- References -- 5 A Mortality Model for Pandemics and Other Contagion Events -- 5.1 Introduction -- 5.2 Highlights of Methodology and Findings -- 5.2.1 Summary of Methodology -- 5.2.2 Summary of Findings 5.3 Semiparametric Regression in MCMC -- 5.3.1 MCMC Parameter Shrinkage -- 5.3.2 Spline Regressions -- 5.3.3 Why Shrinkage? -- 5.3.4 Cross Validation in MCMC -- 5.4 Model Details -- 5.4.1 Formulas -- 5.4.2 Fitting Process -- 5.5 Results -- 5.5.1 Extensions: Generalisation, Projections and R Coding -- 5.6 Conclusions -- References -- 6 Risk-Sharing and Contingent Premia in the Presence of Systematic Risk: The Case Study of the UK COVID-19 Economic Losses -- 6.1 Introduction -- 6.2 Risk Levels and Systematic Risk in Insurance -- 6.3 Mathematical Setup -- 6.3.1 Probability Space 6.3.2 Insurance Preliminaries |
Altri titoli varianti | Pandemics |
Record Nr. | UNINA-9910504284203321 |
Boado-Penas María del Carmen | ||
Cham, : Springer International Publishing AG, 2021 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|