The Benefits Cliff and Labor Supply: Lessons from Behavioral Economics

This post and research paper were written by 2017–18 Values & Capitalism Young Scholar Award recipient, Emma Nyhof, a recent graduate of Hope College, class of 2018.

Standard economic theory relies on the assumption that we make choices rationally. Besides the disagreement surrounding the definition of rationality itself, there is growing evidence that suggests our behavior actually is not always rational. While it seems reasonable to assume that we seek to maximize our satisfaction or utility when making decisions, it may be worthwhile to consider the possibility that emotions, distractions, biases, and a number of other factors could lead to behavior that rational choice theory might consider to be sub-optimal.

Behavioral economics seeks to explain this seemingly irrational behavior by incorporating insights from psychology. A framework that utilizes behavioral economics is potentially relevant in a variety of contexts, many of them policy-related. My paper attempts to incorporate psychological principles into our understanding of labor supply behavior as it relates to the benefits cliff. The benefits cliff refers to the high effective marginal tax rates experienced by households nearing ineligibility or phase-out from multiple government income assistance programs. While there are a variety of psychological concepts that may contribute to our understanding of this issue, this study focuses on three in particular: reference dependence, present bias, and limited attention.

Reference dependence refers to our tendency to evaluate a given outcome relative to a reference point or baseline, which influences our perception of losses and gains. Ultimately, it suggests that we are loss averse because we are more sensitive to losses than we are gains. In the context of labor supply decisions surrounding the benefits cliff, reference dependence and loss aversion suggest that the presence of a benefits cliff should act as a large disincentive to increasing labor supply or earnings if participants are using their current level of benefits as a reference point.

The idea of present bias suggests that we are prone to weighing rewards that will be received closer to the immediate future more heavily than those that will be received in the more distant future. In other words, preferences that are present-biased may lead to procrastination and self-control issues. These tendencies are also likely to show up in decisions regarding labor supply. Assuming that wages are a function of human capital and working develops human capital, the reward of higher wages is not received until the distant future. This being said, this may suggest that individuals are prone to put off increasing labor supply in the present in favor of engaging in non-work activities that are more immediately urgent or gratifying.

The final behavioral concept discussed in my paper has two parts: scarcity and limited attention. Our ability to pay attention has limits within any context; therefore, we are forced to allocate attention to what we deem most important or urgent. Furthermore, there is evidence that the effects of these limits are especially apparent when resources are scarce, suggesting that this concept has important implications for decision-making within the context of poverty. The circumstances associated with poverty imply increased scarcity, which results in the need to allocate attention to the issues that are most urgent while neglecting less pressing issues.

These concepts from behavioral economics may have a variety of implications for policy, many that are related to labor supply responses to the benefits cliff.  Reference dependence and loss aversion may suggest that ideally “cliff-like” program structures should be avoided, both in individual programs and when the programs are combined. Gradual phase-outs, clustering phase-outs, and cutoffs from multiple programs near the same income level may work to mitigate some of these effects. Present-biased preferences could be addressed by continuing to make education and training programs more accessible. This is especially true in the case that low-skill jobs exhibit little return in the form of human capital. Providing training and education could potentially increase the opportunity for investment in careers that have a higher potential for future returns. Based on our understanding of scarcity and limited attention, policymakers should keep these constraints in mind, especially when designing policy that is intended for low-income populations.

There are also implications specific to the benefits cliff. For example, it is possible that outcomes would improve if the programs were less complex. Streamlining the programs themselves, or at least making information more easily understandable and accessible, could allow program participants to allocate more attention to decision-making in a variety of areas, including labor supply. These concepts may also suggest that community-based interventions are especially valuable, considering the specific sources of stress may vary from community to community.

Overall, this study suggests that incorporating concepts from behavioral economics and psychology into our understanding of choice has the potential to contribute to a more realistic framework for evaluating human behavior. This may be especially relevant when discussing choice in the context of poverty, as scarcity may increase tendencies toward behavior that is seemingly irrational within the standard framework.

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