Social Interactions and Disability Benefits: What Can We Learn from Layoffs?

1984年至2001年，美国社会保障残疾保险计划（DI）下领取现金福利的非老年人比例上升了60%，达到530万受益人。因此，2002年直接投资的总支出超过650亿美元，几乎占美国联邦预算的3.4%。 本研究实证调查在何种程度上社会互动影响残疾人参与计划，如DI使用一个独特的挪威数据集。 社会互动效应有助于解释不同地区和不同时期直接投资参与率的巨大差异。这种影响的程度对于预测直接投资政策和经济冲击对直接投资参与率的影响至关重要。 社会互动效应是指一个人的行为对另一个人的行为产生的影响。在直接投资的背景下，这种相互依赖性可能是由于社会规范而产生的。反对直接投资使用的社会规范可能会通过对接受者施加效用成本或污名来降低参与率。 随着一个人的同龄人中DI使用的增加，这种耻辱感预计会下降，从而增加了高利用率同龄人群体成员申请DI福利的倾向。众所周知，在观测数据中识别社会互动效应是非常困难的，因为人们怀疑忽略了变量偏差。这一问题将使用一个包含挪威每个人残疾参与记录的丰富的11年小组数据集来解决。 一个新的工具变量（IV）的战略将采用，使用前几年的同行群体裁员作为一种工具，组内参与率的变化。这种方法背后的直觉是，如果存在社会互动效应，那么不成比例地受到裁员打击的同龄人群体应该表现出残疾申请的相对增加，即使在那些自己没有被解雇的成员中也是如此。本研究的结果可以为美国社会安全网计划的制定提供重要的启示。

Between 1984 and 2001, the share of non-elderly adults receiving cash benefits under the Social Security Disability Insurance program (DI) in the US rose by 60 percent to 5.3 million beneficiaries. As a result, total outlays under DI exceeded $65 billion in 2002, comprising almost 3.4% of the U.S. federal budget. This research empirically investigates the extent to which social interactions affect participation in disability programs such as DI using a unique Norwegian data set. Social interaction effects could help explain the wide variation in DI participation across regions and over time. The magnitude of such effects is critically important for predicting the impact of DI policy and economic shocks on DI participation rates. Social interaction effects refer to the impact that the behavior of one individual has on the behavior of another. In the context of DI, this interdependence could, for example, arise because of social norms. Social norms against DI utilization can reduce participation rates by imposing a utility cost or stigma on recipients. As DI use increases among one's peers, this stigma is expected to decline, thereby increasing the propensity to apply for DI benefits for members of high-utilization peer groups. Identifying social interaction effects in observational data is notoriously difficult due to suspicions of omitted variable bias. This problem will be addressed using a rich 11-year panel dataset containing disability participation records for every person in Norway. A novel instrumental variable (IV) strategy will be employed, using previous years peer groups layoffs as an instrument for changes in-group participation rates. Theintuition behind this approach is that f social interaction effects exist, peer groups disproportionately hit by layoffs should exhibit a relative increase in disability applications even among members who were not themselves laid off. The results of this research could provide important insights into the formulation of social safety net programs in the US.