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Handbook on social protection systems / / edited by Esther Schüring, Markus Loewe
| Handbook on social protection systems / / edited by Esther Schüring, Markus Loewe |
| Autore | Schüring Esther |
| Pubbl/distr/stampa | Northampton : , : Edward Elgar Publishing, , 2021 |
| Descrizione fisica | 1 online resource (776 pages) |
| Disciplina | 361.6 |
| Collana | Elgar Handbooks in Social Policy and Welfare |
| Soggetto topico |
Political planning
Public welfare |
| Soggetto non controllato |
Social protection
welfare state coordination system poverty risk management |
| ISBN | 1-83910-911-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Matter -- Copyright -- Contents -- Figures -- Tables -- Boxes -- Contributors -- Foreword -- Acknowledgements -- Abbreviations -- 1. Introduction to the Handbook on Social Protection Systems -- PART I INSTRUMENTS -- Introduction: Instruments -- 2. Social transfers -- Case study A: Non-contributory social cash transfers in Zambia -- Case study B: Universal basic income grant in theory and practice -- 3. Social insurance -- Case study C: Transforming healthcare financing in Central and Eastern European countries -- Case study D: Challenges of pension funds in Iran -- 4. Labour market policies -- Case study E: Labour market policies in MENA countries -- 5. Social services -- 6. Micro-insurance -- PART II SYSTEM DESIGN -- Introduction: System design -- 7. Financing -- 8. Targeting -- 9. Human rights approaches -- 10. Actors -- 11. Systematic approaches to social protection -- Case study F: The challenges of moving towards universal social protection in Bolivia -- Case study G: Comprehensive social protection reform in South Africa -- PART III POLICY COORDINATION -- Introduction: Policy coordination -- 12. Harmonization of similar instruments -- 13. Coordination of different instruments -- Case study H: Poverty and social transfer coverage in the Kingdom of Eswatini -- 14. Graduation -- 15. Taxation and social protection -- Case study I: Simplified tax regimes and their impact on social insurance in Uruguay -- 16. The humanitarian-development nexus -- Case study J: Emergency cash transfers in Yemen -- Case study K: Palestine's national cash transfer programme: An example of cash transfer programming in a humanitarian setting -- 17. Social budgeting -- PART IV GROUPS IN FOCUS -- Introduction: Groups in focus -- 18. Gender and social protection -- Case study L: Gender analysis of social protection in Iran.
19. Disability inclusion and social protection -- 20. Child-sensitive social protection -- 21. The elderly and social protection -- 22. The informal sector and social protection -- Case study M: Extension of the contributory pension scheme to small-scale farmers in Zambia -- 23. Refugees and social protection -- PART V ADMINISTRATION -- Introduction: Administration -- 24. Delivering social transfers -- 25. Delivering social insurance -- 26. Integrated information management -- 27. Portability -- 28. Decentralization -- Case study N: Capacity development for social protection in Zambia -- PART VI POLITICAL ECONOMY -- Introduction: Political economy -- 29. International actors and social protection -- 30. Public preferences -- 31. The political economy of social protection adoption -- Case study O: Political economy of social protection in Kenya -- Case study P: Political economy of the basic income grant in South Africa -- 32. Acceptability of social protection reforms -- PART VII EFFECTS -- Introduction: Effects -- 33. Data and analysis in social protection -- Case study Q: An evidence and gap map of effectiveness studies: social protection interventions in low- and middle-income countries -- 34. Effects of social protection on poverty and inequality -- 35. Effects of social protection on food consumption and nutrition -- 36. Effects of social protection on health -- 37. The effects of social protection on economic development -- 38. Effects of social protection on social inclusion, social cohesion and nation building -- PART VIII MAJOR CHALLENGES AND REFORM OPTIONS -- Introduction: Major challenges and reform options -- 39. Demographic change -- 40. Globalization -- 41. The future of work -- 42. Climate change -- 43. Pandemics and other macro crises -- Case study R: A humanitarian social protection response to COVID-19 in Kenya -- Index. |
| Record Nr. | UNINA-9910557591703321 |
Schüring Esther
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| Northampton : , : Edward Elgar Publishing, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Pandemics : insurance and social protection / / editors, María del Carmen Boado-Penas, Julia Eisenberg, Şule Şahin
| 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 |
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Boado-Penas María del Carmen
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||
| 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
| 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 | ||
| ||
Pandemics: Insurance and Social Protection / María del Carmen Boado-Penas, Julia Eisenberg, Şule Şahin editors
| Pandemics: Insurance and Social Protection / María del Carmen Boado-Penas, Julia Eisenberg, Şule Şahin editors |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xx, 298 p. : ill. ; 24 cm |
| Soggetto non controllato |
Actuarial modelling
Epidemics Insurance Risk Social protection |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0277982 |
| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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