招聘和留住高质量的州和地方工人:养老金重要吗?

Q3 Social Sciences
A. Munnell, J. Aubry, Geoffrey T. Sanzenbacher
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引用次数: 13

摘要

许多州和地方政府通过削减福利来应对养老金计划面临的挑战。这些削减会使州和地方政府更难招募和留住高素质的工人吗?迄今为止,很难得到答案;大多数微观层面的数据集包含养老金存在的信息,但不包含养老金慷慨程度的信息。为了绕过这一限制,本研究使用了一个独特的来源,即公共计划数据库,来获取有关州和地方工人养老金慷慨程度的数据。这些数据与当前人口调查(Current Population Survey)合并,以调查养老金慷慨程度如何影响各州和地方政府从私营部门招聘的工人的工资与从私营部门流失的工人之间的差距。研究结果表明,相对慷慨的养老金有助于缩小这种“质量差距”,使州和地方雇主更容易从私营部门招聘高收入工人并留住这些工人。无论雇主或雇员是否为福利提供资金,其效果都是相似的。该研究建议,各州在削减养老金福利时应谨慎,通过将部分成本转嫁给雇员来维持福利的策略,可能有助于维持各州招聘和留住高素质工人的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recruiting and Retaining High-Quality State and Local Workers: Do Pensions Matter?
Many state and local governments have responded to challenges facing their pension plans by cutting benefits. Will these cuts make it harder for state and local governments to recruit and retain high-quality workers? To date, the answer has been difficult to obtain; most micro-level datasets contain information on the existence of pensions but not on pension generosity. To get around this constraint, this study uses a unique source, the Public Plans Database, to obtain data on the pension generosity of state and local workers’ pensions. These data are merged with the Current Population Survey to investigate how pension generosity affects the gap between the private sector wage of workers that states and localities recruit from the private sector relative to the workers that they lose to it. The findings suggest relatively generous pensions help reduce this “quality gap,” making it easier for state and local employers to recruit high-earning workers from the private sector and retain those workers. The effect is similar regardless of whether employer or employee contributions finance the benefits. The study suggests states should be cautious as they cut their pension benefits and that a strategy to maintain benefits by shifting some costs onto employees may help maintain states’ ability to recruit and retain high-quality workers.
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来源期刊
Social Security Bulletin
Social Security Bulletin Social Sciences-Social Sciences (miscellaneous)
CiteScore
0.70
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0.00%
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