当我64岁时:新西兰人想从退休收入政策中得到什么?

IF 0.1
J. Au, A. Coleman, T. Sullivan
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引用次数: 2

摘要

当人们对结果有不同的偏好,并且有许多可供选择的政策设置时,很难选择政策。要做到这一点,政策制定者必须了解潜在的偏好,并根据这些偏好对政策进行排序。在本文中,我们使用多标准决策分析技术来了解新西兰退休政策改革的相对吸引力。通过一个具有全国代表性的样本,我们估计了个人对退休政策七个方面的偏好,描述了这些偏好的多样性,并对三种不同的政策选择进行了排名。我们发现,提高税收为政府退休收入计划预先提供资金的政策将得到所有年龄和收入群体的大多数人的支持,并且将比1 andrew.coleman@otago.ac.nz的政策更受欢迎,奥塔哥大学经济系;joey.au@mbie.govt.nz,新西兰商业、创新和就业部;Trudy.Sullivan@otago.ac.nz,奥塔哥大学预防和社会医学系。我们要感谢财政能力委员会的Diane Maxwell、Malcolm Menzies、Richard Thompson、Kathryn Maloney和Tania Werder在项目实施期间提供的建议和支持。新西兰财政部的几名工作人员协助了该项目。我们要特别感谢吉罗尔·卡拉考奥卢、加布里埃尔·马赫洛夫、克里斯·鲍尔、马修·贝尔、黛博拉·库赞斯、玛格丽特·高尔特、布莱恩·麦克丹尼尔和保罗·罗德威。我们非常感谢1000Minds的工作人员Paul Hansen和Franz Ombler在整个项目中提供的帮助以及对论文的评论。我们还要感谢Colmar Brunton的工作人员,特别是Leilani Liew,感谢他们对问卷的微调和实施提供的帮助。我们感谢达尼丁、惠灵顿和奥克兰的焦点小组成员,包括Atene Andrews和Petone的Hikoikoi Kaumātua小组,花时间与我们讨论他们的观点。最后,我们要感谢奥塔哥大学、奥克兰大学和西方国际经济学会议的与会者和讨论者,特别感谢Motu的Arthur Grimes。我们还要感谢Matt Benge、Norman Gemmell、Nicola Kirkup、David Law、Trinh Le和Jacques Poot提出的有益意见和建议。该项目得到了惠灵顿的新西兰财政部和奥克兰的财政能力委员会的财政支持。议程,2019年第26卷第1号24提高资格年龄。结果表明,多标准决策分析在帮助决策者制定符合人们偏好的政策方面具有相当大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
When I’m 64: What do New Zealanders want in a retirement income policy?
It is difficult to choose policies when people have diverse preferences over outcomes and many alternative policy settings are available. To do this well, policymakers must understand underlying preferences and rank policies according to these preferences. In this paper, we use multi‐criteria decision analysis techniques to understand the relative attractiveness of retirement policy reforms in New Zealand. Using a nationally representative sample, we estimate individual preferences over seven aspects of retirement policy, characterise the diversity of these preferences, and rank three different policy options. We find that a policy which raises taxes to prefund the government retirement income scheme would be supported by a majority of people of all ages and income groups, and would be much more popular than a policy that 1 andrew.coleman@otago.ac.nz, The Department of Economics, University of Otago; joey.au@mbie.govt.nz, Ministry of Business, Innovation and Employment, New Zealand; Trudy.Sullivan@otago.ac.nz, The Department of Preventative and Social Medicine, University of Otago. We would like to thank Diane Maxwell, Malcolm Menzies, Richard Thompson, Kathryn Maloney and Tania Werder at the Commission for Financial Capability for their advice and support while the project was undertaken. Several staff at the New Zealand Treasury assisted in the project. We would particularly like to thank Girol Karacaoglu, Gabriel Makhlouf, Chris Ball, Matthew Bell, Deborah Cuzens, Margaret Galt, Bryan McDaniel and Paul Rodway. We are indebted for the assistance provided by the staff of 1000Minds, Paul Hansen and Franz Ombler, throughout the project and for comments on the paper. We also wish to thank the staff of Colmar Brunton, particularly Leilani Liew, for their help in fine‐tuning and implementing the questionnaire. We are grateful for the time the members of focus groups in Dunedin, Wellington and Auckland spent with us discussing their views, including Atene Andrews and the Hikoikoi Kaumātua group in Petone. Lastly, we wish to thank seminar participants and discussants at the University of Otago, the University of Auckland and the Western International Economics Conference, with particular thanks to Arthur Grimes from Motu. We also wish to thank Matt Benge, Norman Gemmell, Nicola Kirkup, David Law, Trinh Le and Jacques Poot for their helpful comments and suggestions. This project received financial support from the New Zealand Treasury, Wellington, and the Commission for Financial Capability, Auckland, New Zealand. AgendA, Volume 26, number 1, 2019 24 raises the age of eligibility. The results suggest multi‐criteria decision analysis has considerable potential to help policymakers develop policies that are aligned with people’s preferences.
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