Policy Makers and Inefficient Decisions
Sometimes it is very evident when a policy, although proven to be inefficient, is still implemented by the policymakers. In his article, Dur describes the reasons behind it and suggests different models confirm his assumptions. Dur argues that not the failed policy itself, but the policymaker’s refusal to implement another, more successful variant of the policy is an indication of his or her incompetence (2001, p. 221).We will write a custom Inefficient Decisions and Policy Bubbles specifically for you
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According to him, the sequence of the events is following: the incumbent designs a policy, then observes the signal about the effects of the policy and either continues or repeals the policy; voters revise the competence probability of the incumbent; elections take place, and the winning candidate designs another policy; later, he observes if it was successful or failed and decides whether he should implement or repeal it (Dur, 2001, p. 225). The author solves the model for Perfect Bayesian equilibria. Three types of equilibria are proposed by Dur: non-distortionary equilibrium, equilibrium with distorted policy choice, and equilibria in mixed strategies (2001, p.226).
The first type suggests that no matter how successful or unsuccessful the policy was, the incumbent will nevertheless continue implementing it. The second type suggests that the voters’ belief in policymaker’s competence is not affected by the decision of the policymaker to implement or repeal the policy; so, if the incumbent “cares sufficiently about holding office relative to social welfare, he never repeals a policy” (Dur, 2001, p. 228). The third type suggests that a policymaker will always implement a successful policy and with a certain probability repeal a failed policy (Dur, 2001, p. 230). Using these three equilibria, Dur proves that policymakers choose to implement an insufficient policy to increase the chances of reelection.
The name ‘policy bubble’ is used when a policy overreaction occurs; however, the definition can be found in different scientific branches where its meaning varies from one situation to another. Maor argues that modes of policy overreaction can create different policy bubbles; a policy bubble can emerge only when perceived policy overreaction lasts for a sustained period (2013, p. 474). The image of the policy plays a significant role – its modification can provoke positive feedback and oversupply of this exact policy (Maor, 2013, p. 475).
The author also examines the so-called ‘feedback loops’: these occur when increased support of the policy results in trend-chasers subscribing to it, and, in return, positive feedback increases, granting oversupply of the policy (Maor, 2013, p. 475). Also, policymakers may intentionally create a policy bubble to protect themselves from changes in public opinions (Maor, 2013, p. 476). The main reasons why the policy bubbles grow include overconfidence (that may result in bubble burst), human herding (people observe the choices of others and make similar ones), serial information processing (not all information is available to people), and the lock-in effect (self-reinforcement of the policy allows it to grow) (Maor, 2013, p. 478).
To identify a policy bubble, Maor suggests three methods: attentional perspective (a measure of congressional, media, and public concerns), transmission perspective (measuring social contagion in social networks with formal analysis and data mining), and attitudinal perspective (studying individuals’ confidence and expectations of the policy bubble) (2013, p. 481). Maor stresses out that policy bubbles can bring both great harm and beneficial consequences, so it is necessary to study policy bubbles through social media (2013, p. 482). Understanding policy bubbles will possibly help policymakers create more efficient and rational policies.
Dur, R. A. (2001). Why do policy makers stick to inefficient decisions? Public Choice, 107(3-4), 221-234.Get your
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Maor, M. (2013). Policy bubbles: Policy overreaction and positive feedback. Governance, 27(3), 469-487.