Existing explanations of systematic undersupply of policy (e.g., institutional frictions, policy drift, and loss aversion) highlight the role of institutional and cognitive factors in the policy process while paying little attention to the role of emotions and emotional sentiments (e.g., policy mood). To bridge this gap, this article conceptualizes the role of negative emotions (e.g., fear, anger, hatred, disgust) and emotional sentiments in driving systematic policy underreaction (or what I have termed a negative policy bubble). Regarding the birth of emotion-driven negative policy bubbles, the behavioral understanding advanced here points to (1) an endogenous process that affects opinion formation, attention, learning, behavior, and attitudes; (2) an exogenous shock that “turns on” an endogenous process; (3) emotional manipulation by emotional entrepreneurs, or (4) a process by which the psychological context within which the policy process takes place conditions policy dynamics. Self-reinforcing processes interact with the contagion of emotions, imitation, and herd behavior to reinforce the lack of confidence in the policy, thereby creating a lock-in effect of systematic undersupply of policy. This process may be interrupted following modest endogenous or exogenous perturbations; a decrease in the intensity and duration of negative emotions and/or an increase in their speed of decline by emotional entrepreneurs, as well as following the reduction in negativity bias when the information environment becomes predominantly negative. The paper also provides guidance on productive directions for future research.
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The term negative bubble is imported from the area of finance where it commonly refers to a process characterized by pressures toward panic accompanied by strong herding leading to disproportionate selling (e.g., Sornette and Cauwels 2014). The term negative policy bubbles is therefore not derived from the term negative emotions.
The term negative emotion is a coherent scientific term only when it includes emotions which have array of negative (read, destructive) consequences (e.g., fear, anger, hatred and disgust). It is not coherent when anxiety enters into the fray, because the range of consequences include abandoning extant convictions, learning, attention to new solutions, and willingness to entertain new coalitions, or aversion, whose consequences include a fight to preserve and defend valued goals (e.g., Marcus and MacKuen 1993; Valentino et al. 2011).
Emotional entrepreneurs refer to “individual and collective actors that attempt to advance a political and/or policy agenda by regulating expected or actual emotions generated during political and policy processes” (Maor and Gross 2015: 3).
For a concise list of policies enacted in 1987, see: https://www.aids.gov/hiv-aids-basics/hiv-aids-101/aids-timeline/. Accessed 16 August 2015.
According to Finucane et al. (2003: 328), affect refers to ““goodness” or “badness” (1) experienced as a feeling state […] (2) demarcating a positive or negative quality of a specific stimulus. “Affect is thus critical to identifying stimuli as either rewarding, hence justifying approach, or punishing, thus justifying avoidance” (Brader and Marcus 2013: 167; see also Lodge and Taber 2013).
A recent advance posits affect-driven, dual-process modes of thinking and reasoning, that is, that “[…] all thinking is suffused with feeling, and these feeling arise automatically within a few milliseconds […] of exposure to a sociopolitical object or event” (Lodge and Taber 2013: 19).
It is important to recognize that “[…] from affect-as-information perspective, the critical factor is not affect itself, but its information value” (Clore and Palmer 2009: 26). This, in turn, depends on tacit attributions about the source and apparent meaning of the effect (Schwartz and Clore 1983; Clore and Storbeck 2006), as well as on contextual factors (Martin 2001).
I thank Ezra Zuckerman for raising this important point.
I thank Frank Baumgartner for raising this important point.
Doing so may also raise an important question: How do we know whether a change in the level of true policy valuation will bring it back to an appropriate level of policy response or to an overreaction level. It is reasonable to suggest that when the effects of the policy response on different segments of society are widely disproportionate, the response could be classified as a policy overreaction. An example that springs to mind is the dramatic rise in the arrest rate in New York City for lower-level crimes—the brunt of which fell on young black and Hispanic men—which eclipsed arrests for more serious offenses. The arrest rate for these more minor crimes had risen 190 percent by 2013, when the police made 225,684 such arrests (Chauhan et al. 2014).
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Earlier versions of this article—including the first version, entitled “Policy Anti-Bubbles”—were presented at the workshop on “Financial, Technological, Social and Political Bubbles,” ETH Risk Center, Zurich, 2015; the Biennial ECPR Standing Group for Regulatory Governance Conference, 2014; the Annual Meeting of the Midwest Political Science Association, 2014; the Institute of Political Science, University of Heidelberg, 2014, and the International Workshop on “Policy Design and Governance Failures,” Lee Kuan Yew School of Public Policy, National University of Singapore, 2014. I thank the audiences of these events for useful comments and suggestions. I also thank the anonymous reviewers for their comments on the manuscript. All remaining errors are my own.
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Maor, M. Emotion-driven negative policy bubbles. Policy Sci 49, 191–210 (2016). https://doi.org/10.1007/s11077-015-9228-7
- Policy change
- Emotional entrepreneurs
- Policy mood