Dynamics in private pension saving across the income distribution

收入分配中私人养老金储蓄的动态

基本信息

  • 批准号:
    ES/X000362/1
  • 负责人:
  • 金额:
    $ 19.84万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2023
  • 资助国家:
    英国
  • 起止时间:
    2023 至 无数据
  • 项目状态:
    未结题

项目摘要

How much people save for their retirement is extremely important. It matters not only for individuals' wellbeing but also for society in general because those with insufficient private savings are more reliant on government benefits. It is increasingly important because people are living longer. Various policy levers are used to encourage retirement saving. Most notably, there are large tax advantages to pension saving that have been changed in various ways in recent years. In 2012, the government began to roll out pension auto-enrolment, a policy through which employers are required to put most of their employees into a workplace pension scheme and contribute towards it. This has led to almost 90% of eligible employees saving in a pension. Despite policy action, there are ongoing concerns that some groups are not saving enough for their retirement. The self-employed are a particular concern because they are much less likely to invest in a pension and, when they do, they save less than employees. There is no equivalent to auto-enrolment for the self-employed but government are actively looking at policy options. It is important to understand the patterns of pension saving across different groups in society and the role of various policies in shaping decisions. This project will provide insights in this area by using comprehensive information on pension contributions held by HMRC, the tax authority. Specifically, we will use data on all pension contributions made either by individuals or their employers to personal pensions, and link this to individuals' (anonymised) tax records. The later provides information on how much income a person has and how that income is generated. We will be able to track people over time, thereby observing, for example, how pension saving changes as income and the policy environment changes. We will be creating the first and only dataset that provides a comprehensive picture of how much money people are putting into personal pensions. The best available survey data are incomplete because they: cover only employees (not the self-employed or those not in paid work); has limited information on people over time; does not cover pension contributions made outside of a workplace; records people's earnings but not their total income (which is particularly important for many of those on the highest incomes). The data we will create will include employees as well as the self-employed, people working for their own companies and those not working. We will capture all contributions to personal pensions and have detailed information on total income. We will use the data to document the pension savings of employees and the self-employed, including how pension contributions change as people move from employment to self-employment. The self-employed have been the fastest growing part of the UK labour force since the early 2000s. Around 15% of the UK workforce is now self-employed but there is much churn in this population -many enter leave self-employment each year. We will study whether auto-enrolment has changed the saving habits of people who were auto-enrolled as an employee and went on to be self-employed. This will provide important evidence on the channels through which auto-enrolment operates and will inform the design of policies to encourage saving among the self-employed. With the new dataset established for research, there will be opportunities to address many other important policy questions, including, for example, how various aspect of tax policy affect how much different types of people chose to save in a pension and their wider investment and economic choices.
人们为退休存多少钱是非常重要的。这不仅关系到个人的福祉,也关系到整个社会,因为那些私人储蓄不足的人更依赖于政府福利。它越来越重要,因为人们的寿命越来越长。各种政策杠杆被用来鼓励退休储蓄。最值得注意的是,养老金储蓄有很大的税收优势,近年来已经以各种方式发生了变化。2012年,政府开始推出养老金自动登记政策,通过该政策,雇主必须将大多数员工纳入工作场所养老金计划并为其缴费。这使得近90%符合条件的员工储蓄养老金。尽管采取了政策行动,但人们仍担心一些群体没有为退休储蓄足够的钱。自营职业者尤其令人担忧,因为他们投资养老金的可能性要小得多,而且即使投资养老金,他们的储蓄也比员工少。对于自营职业者来说,没有相当于自动登记的办法,但政府正在积极研究政策选择。重要的是要了解不同社会群体的养老金储蓄模式以及各种政策在决策中的作用。该项目将利用税务当局HMRC掌握的养老金缴款综合信息,提供这方面的见解。具体而言,我们将使用个人或其雇主对个人养老金的所有养老金缴款数据,并将其与个人(匿名)纳税记录相关联。后者提供了关于一个人有多少收入以及收入是如何产生的信息。我们将能够随着时间的推移跟踪人们,从而观察养老金储蓄如何随着收入和政策环境的变化而变化。我们将创建第一个也是唯一一个数据集,全面了解人们在个人养老金上投入了多少钱。现有最好的调查数据是不完整的,因为它们:只涵盖雇员(不包括自营职业者或无报酬工作的人);关于人们的长期信息有限;不包括工作场所以外的养老金缴款;记录人们的收入,但不记录他们的总收入(这对许多收入最高的人特别重要)。我们将创建的数据将包括员工以及自雇人士,为自己的公司工作的人和那些没有工作的人。我们将收集个人养老金的所有缴款,并获得有关总收入的详细信息。我们将使用这些数据来记录雇员和自营职业者的养老金储蓄,包括随着人们从就业转向自营职业,养老金缴款如何变化。自21世纪初以来,自雇人士一直是英国劳动力增长最快的部分。目前,英国约有15%的劳动力是自雇人士,但这一人群的流动性很大--每年都有许多人进入自雇行业。我们将研究自动登记是否改变了那些自动登记为雇员并继续从事自雇工作的人的储蓄习惯。这将为自动登记的运作渠道提供重要证据,并将为制定鼓励自营职业者储蓄的政策提供信息。随着新数据集的建立,将有机会解决许多其他重要的政策问题,包括税收政策的各个方面如何影响不同类型的人选择在养老金中储蓄多少以及他们更广泛的投资和经济选择。

项目成果

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Helen Miller其他文献

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini 1.5:解锁跨数百万个上下文标记的多模式理解
  • DOI:
    10.48550/arxiv.2403.05530
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Machel Reid;Nikolay Savinov;Denis Teplyashin;Dmitry Lepikhin;T. Lillicrap;Jean;Radu Soricut;Angeliki Lazaridou;Orhan Firat;Julian Schrittwieser;Ioannis Antonoglou;Rohan Anil;Sebastian Borgeaud;Andrew M. Dai;Katie Millican;Ethan Dyer;Mia Glaese;Thibault Sottiaux;Benjamin Lee;Fabio Viola;Malcolm Reynolds;Yuanzhong Xu;James Molloy;Jilin Chen;M. Isard;Paul Barham;Tom Hennigan;Ross McIlroy;Melvin Johnson;J. Schalkwyk;Eli Collins;Eliza Rutherford;Erica Moreira;Kareem W. Ayoub;Megha Goel;Clemens Meyer;Gregory Thornton;Zhen Yang;H. Michalewski;Zaheer Abbas;Nathan Schucher;Ankesh Anand;Richard Ives;James Keeling;Karel Lenc;Salem Haykal;Siamak Shakeri;Pranav Shyam;Aakanksha Chowdhery;Roman Ring;Stephen Spencer;Eren Sezener;Luke Vilnis;Oscar Chang;Nobuyuki Morioka;George Tucker;Ce Zheng;Oliver Woodman;Nithya Attaluri;Tomás Kociský;Evgenii Eltyshev;Xi Chen;Timothy Chung;Vittorio Selo;Siddhartha Brahma;Petko Georgiev;Ambrose Slone;Zhenkai Zhu;James Lottes;Siyuan Qiao;Ben Caine;Sebastian Riedel;Alex Tomala;Martin Chadwick;J Christopher Love;Peter Choy;Sid Mittal;N. Houlsby;Yunhao Tang;Matthew Lamm;Libin Bai;Qiao Zhang;Luheng He;Yong Cheng;Peter Humphreys;Yujia Li;Sergey Brin;Albin Cassirer;Ying;Lukás Zilka;Taylor Tobin;Kelvin Xu;Lev Proleev;Daniel Sohn;Alberto Magni;Lisa Anne Hendricks;Isabel Gao;Santiago Ontan'on;Oskar Bunyan;Nathan Byrd;Abhanshu Sharma;Biao Zhang;Mario Pinto;Rishika Sinha;Harsh Mehta;Dawei Jia;Sergi Caelles;Albert Webson;Alex Morris;Becca Roelofs;Yifan Ding;Robin Strudel;Xuehan Xiong;Marvin Ritter;Mostafa Dehghani;Rahma Chaabouni;Abhijit Karmarkar;Guangda Lai;Fabian Mentzer;Bibo Xu;YaGuang Li;Yujing Zhang;T. Paine;Alex Goldin;Behnam Neyshabur;Kate Baumli;Anselm Levskaya;Michael Laskin;Wenhao Jia;Jack W. Rae;Kefan Xiao;Antoine He;Skye Giordano;Lakshman Yagati;Jean;Paul Natsev;Sanjay Ganapathy;Fangyu Liu;Danilo Martins;Nanxin Chen;Yunhan Xu;Megan Barnes;Rhys May;Arpi Vezer;Junhyuk Oh;Ken Franko;Sophie Bridgers;Ruizhe Zhao;Boxi Wu;Basil Mustafa;Sean Sechrist;Emilio Parisotto;Thanumalayan Sankaranarayana Pillai;Chris Larkin;Chenjie Gu;Christina Sorokin;M. Krikun;Alexey Guseynov;Jessica Landon;Romina Datta;A. Pritzel;Phoebe Thacker;Fan Yang;Kevin Hui;A.E. Hauth;Chih;David Barker;J. Mao;Sophia Austin;Hannah Sheahan;Parker Schuh;James Svensson;Rohan Jain;V. Ramasesh;Anton Briukhov;Da;Tamara von Glehn;Christina Butterfield;Priya Jhakra;Matt Wiethoff;Justin Frye;Jordan Grimstad;Beer Changpinyo;Charline Le Lan;Anna Bortsova;Yonghui Wu;P. Voigtlaender;Tara N. Sainath;Charlotte Smith;Will Hawkins;Kris Cao;James Besley;S. Srinivasan;Mark Omernick;Colin Gaffney;G. Surita;Ryan Burnell;Bogdan Damoc;Junwhan Ahn;Andrew Brock;Mantas Pajarskas;Anastasia Petrushkina;Seb Noury;Lorenzo Blanco;Kevin Swersky;Arun Ahuja;Thi Avrahami;Vedant Misra;Raoul de Liedekerke;Mariko Iinuma;A. Polozov;Sarah York;George van den Driessche;Paul Michel;Justin Chiu;Rory Blevins;Zach Gleicher;Adrià Recasens;Alban Rrustemi;E. Gribovskaya;Aurko Roy;Wiktor Gworek;S'ebastien M. R. Arnold;Lisa Lee;James Lee;Marcello Maggioni;Enrique Piqueras;Kartikeya Badola;S. Vikram;Lucas Gonzalez;Anirudh Baddepudi;Evan Senter;J. Devlin;James Qin;Michael Azzam;Maja Trebacz;M. Polacek;Kashyap Krishnakumar;Shuo;Matthew Tung;Ivo Penchev;Rishabh Joshi;Kate Olszewska;Carrie Muir;Mateo Wirth;Ale Jakse Hartman;Joshua Newlan;S. Kashem;Vijay Bolina;Elahe Dabir;Joost R. van Amersfoort;Zafarali Ahmed;James Cobon;Aishwarya B Kamath;A. M. Hrafnkelsson;Le Hou;Ian Mackinnon;Alexandre Frechette;Eric Noland;Xiance Si;E. Taropa;Dong Li;Phil Crone;Anmol Gulati;S'ebastien Cevey;Jonas Adler;Ada Ma;David Silver;Simon Tokumine;Richard Powell;Stephan Lee;Michael B. Chang;Samer Hassan;Diana Mincu;Antoine Yang;Nir Levine;Jenny Brennan;Mingqiu Wang;Sarah Hodkinson;Jeffrey Zhao;Josh Lipschultz;Aedan Pope;Michael B. Chang;Cheng Li;Laurent El Shafey;M. Paganini;Sholto Douglas;Bernd Bohnet;Fabio Pardo;Seth Odoom;Mihaela Rosca;Cicero Nogueira dos Santos;Kedar Soparkar;A. Guez;Tom Hudson;Steven Hansen;Chulayuth Asawaroengchai;Ravichandra Addanki;Tianhe Yu;Wojciech Stokowiec;Mina Khan;Justin Gilmer;Jaehoon Lee;Carrie Grimes Bostock;Keran Rong;Jonathan Caton;Pedram Pejman;Filip Pavetic;Geoff Brown;Vivek Sharma;Mario Luvci'c;Rajkumar Samuel;Josip Djolonga;Amol Mandhane;Lars Lowe Sjosund;Elena Buchatskaya;Elspeth White;Natalie Clay;Jiepu Jiang;Hyeontaek Lim;Ross Hemsley;Jane Labanowski;Nicola De Cao;David Steiner;Sayed Hadi Hashemi;Jacob Austin;Anita Gergely;Tim Blyth;Joe Stanton;K. Shivakumar;Aditya Siddhant;Anders Andreassen;Carlos L. Araya;Nikhil Sethi;Rakesh Shivanna;Steven Hand;Ankur Bapna;A. Khodaei;Antoine Miech;Garrett Tanzer;Andy Swing;S. Thakoor;Zhufeng Pan;Zachary Nado;Stephanie Winkler;Dian Yu;Mohammad Saleh;Lorenzo Maggiore;Iain Barr;Minh Giang;Thais Kagohara;Ivo Danihelka;Amit Marathe;Vladimir Feinberg;Mohamed Elhawaty;Nimesh Ghelani;Dan Horgan;Helen Miller;Lexi Walker;Richard Tanburn;Mukarram Tariq;Disha Shrivastava;Fei Xia;Chung;Zoe C. Ashwood;Khuslen Baatarsukh;Sina Samangooei;Fred Alcober;Axel Stjerngren;P. Komarek;Katerina Tsihlas;Anudhyan Boral;Ramona Comanescu;Jeremy Chen;Ruibo Liu;Dawn Bloxwich;Charlie Chen;Yanhua Sun;Fangxiaoyu Feng;M. Mauger;Xerxes Dotiwalla;V. Hellendoorn;Michael Sharman;Ivy Zheng;Krishna Haridasan;Gabriel Barth;Craig Swanson;Dominika Rogozi'nska;Alek Andreev;P. Rubenstein;Ruoxin Sang;Dan Hurt;Gamaleldin Elsayed;Ren;Dave Lacey;Anastasija Ili'c;Yao Zhao;Lora Aroyo;Chimezie Iwuanyanwu;Vitaly Nikolaev;Balaji Lakshminarayanan;Sadegh Jazayeri;Raphael Lopez Kaufman;Mani Varadarajan;Chetan Tekur;Doug Fritz;Misha Khalman;David Reitter;Kingshuk Dasgupta;Shourya Sarcar;T. Ornduff;Javier Snaider;Fantine Huot;Johnson Jia;Rupert Kemp;Nejc Trdin;Anitha Vijayakumar;Lucy Kim;Christof Angermueller;Li Lao;Tianqi Liu;Haibin Zhang;David Engel;Somer Greene;Anais White;Jessica Austin;Lilly Taylor;Shereen Ashraf;Dangyi Liu;Maria Georgaki;Irene Cai;Yana Kulizhskaya;Sonam Goenka;Brennan Saeta;Kiran Vodrahalli;Christian Frank;D. Cesare;Brona Robenek;Harry Richardson;Mahmoud Alnahlawi;Christopher Yew;Priya Ponnapalli;M. Tagliasacchi;Alex Korchemniy;Yelin Kim;Dinghua Li;B. Rosgen;Kyle Levin;Jeremy Wiesner;Praseem Banzal;Praveen Srinivasan;Hongkun Yu;cCauglar Unlu;David Reid;Zora Tung;D. Finchelstein;Ravin Kumar;A. Elisseeff;Jin Huang;Ming Zhang;Rui Zhu;Ricardo Aguilar;Mai Gim'enez;Jiawei Xia;Olivier Dousse;W. Gierke;S. Yeganeh;Damion Yates;Komal Jalan;Lu Li;Eri Latorre;Duc Dung Nguyen;Ken Durden;Praveen Kallakuri;Yaxin Liu;Matthew Johnson;Tomy Tsai;Alice Talbert;Jasmine Liu;Alexander Neitz;Chen Elkind;Marco Selvi;Mimi Jasarevic;Livio Baldini Soares;Albert Cui;Pidong Wang;Alek Wenjiao Wang;Xinyu Ye;Krystal Kallarackal;Lucia Loher;Hoi Lam;Josef Broder;D. Holtmann;Nina Martin;Bramandia Ramadhana;Daniel Toyama;Mrinal Shukla;Sujoy Basu;Abhi Mohan;Nicholas Fernando;Noah Fiedel;Kim Paterson;Hui Li;Ankush Garg;Jane Park;Donghyun Choi;Diane Wu;Sankalp Singh;Zhishuai Zhang;Amir Globerson;Lily Yu;John Carpenter;F. D. C. Quitry;Carey Radebaugh;Chu;Alex Tudor;Prakash Shroff;Drew Garmon;Dayou Du;Neera Vats;Han Lu;Shariq Iqbal;A. Yakubovich;Nilesh Tripuraneni;James Manyika;Haroon Qureshi;Nan Hua;Christel Ngani;Maria Abi Raad;Hannah Forbes;Anna Bulanova;Jeff Stanway;Mukund Sundararajan;Victor Ungureanu;Colton Bishop;Yunjie Li;Balaji Venkatraman;Bo Li;Chloe Thornton;Salvatore Scellato;Nishesh Gupta;Yicheng Wang;Ian Tenney;Xihui Wu;Ashish Shenoy;Gabriel Carvajal;Diana Gage Wright;Ben Bariach;Zhuyun Xiao;Peter Hawkins;Sid Dalmia;Cl'ement Farabet;Pedro Valenzuela;Quan Yuan;Christoper A. Welty;Ananth Agarwal;Mianna Chen;Wooyeol Kim;Brice Hulse;Nandita Dukkipati;Adam Paszke;Andrew Bolt;Elnaz Davoodi;Kiam Choo;Jennifer Beattie;J. Prendki;Harsha Vashisht;Rebeca Santamaria;Luis C. Cobo;Jarek Wilkiewicz;David Madras;Ali Elqursh;Grant Uy;Kevin Ramirez;Matt Harvey;Tyler Liechty;H. Zen;Jeff Seibert;Clara Huiyi Hu;A. Ya. Khorlin;Maigo Le;A. Aharoni;Megan Li;Lily Wang;Sandeep Kumar;Alejandro Lince;Norman Casagrande;Jay Hoover;Dalia El Badawy;David Soergel;Denis Vnukov;Matt Miecnikowski;Jiří Šimša;Anna Koop;Praveen Kumar;Thibault Sellam;Daniel Vlasic;Samira Daruki;Nir Shabat;John Zhang;Guolong Su;Kalpesh Krishna;Jiageng Zhang;Jeremiah Liu;Yi Sun;Evan Palmer;Alireza Ghaffarkhah;Xi Xiong;Victor Cotruta;Michael Fink;Lucas Dixon;Ashwin Sreevatsa;Adrian Goedeckemeyer;Alek Dimitriev;Mohsen Jafari;Remi Crocker;Nicholas A Fitzgerald;Aviral Kumar;Sanjay Ghemawat;Ivan Philips;Frederick Liu;Yannie Liang;Rachel Sterneck;Alena Repina;Marcus Wu;Laura Knight;Marin Georgiev;Hyo Lee;Harry Askham;A. Chakladar;Annie Louis;C. Crous;Hardie Cate;Dessie Petrova;Michael Quinn;Denese Owusu;Achintya Singhal;Nan Wei;Solomon Kim;Damien Vincent;Milad Nasr;Christopher A. Choquette;Reiko Tojo;Shawn Lu;Diego de Las Casas;Yuchung Cheng;Tolga Bolukbasi;Katherine Lee;Saaber Fatehi;R. Ananthanarayanan;Miteyan Patel;C. Kaed;Jing Li;Jakub Sygnowski;S. Belle;Zhe Chen;Jaclyn Konzelmann;Siim Poder;Roopal Garg;Vinod Koverkathu;Adam Brown;Chris Dyer;Rosanne Liu;Azade Nova;Jun Xu;Slav Petrov;D. Hassabis;K. Kavukcuoglu;Jeffrey Dean;O. Vinyals
  • 通讯作者:
    O. Vinyals
Structural social capital and mental health in Australia: an analysis of the 2007 Household Income and Labour Dynamics (HILDA) Survey
澳大利亚的结构性社会资本和心理健康:2007 年家庭收入和劳动力动态 (HILDA) 调查分析
  • DOI:
  • 发表时间:
    2009
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Helen Miller
  • 通讯作者:
    Helen Miller
Tax and public finances: the fundamentals
税收和公共财政:基础知识
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Isaac Delestre;Helen Miller
  • 通讯作者:
    Helen Miller
Variation in thromboxane B2 concentrations in serum and plasma in patients taking regular aspirin before and after clopidogrel therapy
服用常规阿司匹林的患者氯吡格雷治疗前后血清和血浆中血栓素 B2 浓度的变化
  • DOI:
  • 发表时间:
    2015
  • 期刊:
  • 影响因子:
    3.3
  • 作者:
    R. Good;A. McGarrity;R. Sheehan;T. E. James;Helen Miller;J. Stephens;S. Watkins;A. McConnachie;A. Goodall;K. Oldroyd
  • 通讯作者:
    K. Oldroyd
45. Impact of red beetroot supplemented diets on the gut bacterial composition of weaned pigs
  • DOI:
    10.1016/j.anscip.2021.03.046
  • 发表时间:
    2021-04-01
  • 期刊:
  • 影响因子:
  • 作者:
    Opeyemi Adekolurejo;Katie McDermott;Helen Miller;Alan Mackie;Christine Boesch
  • 通讯作者:
    Christine Boesch

Helen Miller的其他文献

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{{ truncateString('Helen Miller', 18)}}的其他基金

Productivity and the allocation of capital following the great recession
大衰退后的生产力和资本配置
  • 批准号:
    ES/L013517/1
  • 财政年份:
    2014
  • 资助金额:
    $ 19.84万
  • 项目类别:
    Research Grant
ARFMP: Renovation of Botanical Research Facilities
ARFMP:植物研究设施的翻新
  • 批准号:
    9021875
  • 财政年份:
    1991
  • 资助金额:
    $ 19.84万
  • 项目类别:
    Standard Grant
Improving the Visual Components of Sections of a Non-Major Biology Course
改进非专业生物学课程各部分的视觉成分
  • 批准号:
    7900219
  • 财政年份:
    1979
  • 资助金额:
    $ 19.84万
  • 项目类别:
    Standard Grant

相似国自然基金

基于VFM视角的公共基础设施项目PPP模式选择模型及应用研究
  • 批准号:
    71102091
  • 批准年份:
    2011
  • 资助金额:
    22.0 万元
  • 项目类别:
    青年科学基金项目

相似海外基金

The impacts of climate change on the long-term viability of public and private pension plans
气候变化对公共和私人养老金计划长期可行性的影响
  • 批准号:
    576616-2022
  • 财政年份:
    2022
  • 资助金额:
    $ 19.84万
  • 项目类别:
    Alliance Grants
Partnership between Public and Private Pension Insurance for a Sustainable Retirement Security System
公共和私人养老保险之间的合作,建立可持续的退休保障体系
  • 批准号:
    17K04018
  • 财政年份:
    2017
  • 资助金额:
    $ 19.84万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Development of a model for post-retirement cost of living for the junior baby boomers : A study of the role of the pension system in dividing public and private sector
婴儿潮一代退休后生活成本模型的开发:养老金制度在公共和私营部门划分中的作用研究
  • 批准号:
    17K04303
  • 财政年份:
    2017
  • 资助金额:
    $ 19.84万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Optimal Portfolio of Private Defined Contribution Plan Complementing Public Pension Under Macroeconmic Slide
宏观经济下滑下私人设定缴费计划补充公共养老金的最优组合
  • 批准号:
    16K03744
  • 财政年份:
    2016
  • 资助金额:
    $ 19.84万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Policy Transformations of 'Public-Private' Sphere and Pension Regimes in the Retrenchment Politics: Comparative Perspectives
紧缩政治中“公私”领域和养老金制度的政策转型:比较视角
  • 批准号:
    15K03282
  • 财政年份:
    2015
  • 资助金额:
    $ 19.84万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Total Reward, the Great Recession and the Proposed Public Sector Pension Reforms: Evidence from the Public vs. Private Sectors in the UK
总报酬、大衰退和拟议的公共部门养老金改革:来自英国公共部门与私营部门的证据
  • 批准号:
    ES/L014920/1
  • 财政年份:
    2015
  • 资助金额:
    $ 19.84万
  • 项目类别:
    Research Grant
Emerging "Property Rights" in the World Pension Systems: Focusing the U.S. Private Pension Plans
世界养老金体系中新兴的“产权”:聚焦美国私人养老金计划
  • 批准号:
    15K11979
  • 财政年份:
    2015
  • 资助金额:
    $ 19.84万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Theorizing the Accountability in the Policy Transformation of 'Public - Private' Sphere: The Case of Pension and Healthcare Reform
“公私”领域政策转型中的问责理论:以养老金和医疗改革为例
  • 批准号:
    22530133
  • 财政年份:
    2010
  • 资助金额:
    $ 19.84万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Private Responses to Demographic Change and Pension Reform in Urban China
私营部门对中国城市人口变化和养老金改革的反应
  • 批准号:
    DP0558510
  • 财政年份:
    2005
  • 资助金额:
    $ 19.84万
  • 项目类别:
    Discovery Projects
INTERGENERATIONAL INDEPENDENCE, COOPERATION AND JUSTICE IN AGEING SOCIETY
老龄化社会中的代际独立、合作与正义
  • 批准号:
    16530196
  • 财政年份:
    2004
  • 资助金额:
    $ 19.84万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
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