Learning Self-Control *

Ali, S. Nageeb

doi:10.1093/qje/qjr014

Cited by 110 publications

(51 citation statements)

References 63 publications

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“…28 Ali (2011) gives a condition under which individuals will learn about their self-control problems over time. That students who have not paid for a gym membership have de facto committed not to attend the gym in the current period places a significant limit on the potential for such learning in our environment.…”

Section: Setupmentioning

confidence: 99%

Naiveté, Projection Bias, and Habit Formation in Gym Attendance

2015

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We develop a model capturing habit formation, projection bias, and present bias in an intertemporal-choice setting, and conduct a field experiment to identify its main parameters. We elicit subjects' pre-and post-treatment predictions of post-treatment gym attendance, using a habit-formation intervention based on Charness and Gneezy (2009) as an exogenous shock to treated subjects' gym preferences. Projection-biased subjects, projecting their current habit state onto their future expectations, will, ex-ante, under-estimate any habit-formation effect of our treatment. Naive present-biased subjects in both groups will overestimate their future attendance. Like Charness and Gneezy, we find subjects do form a significant short-run habit, though we find substantial decay caused by the semester break. Subjects appear not to embed this habit formation into their ex-ante predictions. Approximately one-third of subjects formed a habit equivalent to the effect of a $2.60 per-visit subsidy, while their predictions correspond to 90% projection bias over this habit formation. Moreover, subjects greatly over-predict future attendance, which we interpret as evidence of partial naiveté with respect to present bias: they appear to expect their future selves to be two-thirds less "present biased" than they currently are.

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Section: Setupmentioning

confidence: 99%

Naiveté, Projection Bias, and Habit Formation in Gym Attendance

2015

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“…Observing the propensity for judgment biases in the decision-making process (Kahneman & Riepe, 1998), investors anticipating the occurrence of these problems can be termed as sophisticated (Ali, 2011), as well as managers looking for mechanisms to protect their strategies against unexpected redeeming.…”

Section: Resultsmentioning

confidence: 99%

“…If self-control problems are argued in the light of behavioral biases, Investors who anticipate these problems can be termed as sophisticated (Ali, 2011), as well as fund managers seeking mechanisms in order for their strategies not to be negatively affected by unexpected behaviors. Nunes et al (2015) affirm that individuals perceived as sophisticated opt for commitments that refrain from situations which may lead them to self-control problems: "[...]For example, sophisticated savers demand financial products that provide penalties and liquidity restrictions, such as investment funds and pension plans, to help them overcome self-control problems" (Nunes et al, 2015, p. 190).…”

Section: Behavioral Biases and Lock-up Periodsmentioning

confidence: 99%

Liquidity Restrictions on Investment Funds: Are they a Response to Behavioral Bias?

Malaquias¹,

Pontes²

2018

BBR

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“…From a conceptual viewpoint, the paper is related to the behavioral economics liter-ature that studies decision-making when individuals have imperfect self-knowledge (see e.g, Carrillo Ali, 2011). Our model focuses on a novel set of issues, namely performance in a multi-tasking environment.…”

Section: Related Literature In Economicsmentioning

confidence: 99%

“…The fundamental features of brain processes that will constitute the building blocks of our theory are briefly introduced here (the supporting evidence is reviewed more thoroughly in section 2.1). 1 First, there is brain specialization. Different brain systems are recruited to perform different tasks and neurons in a given system respond exclusively to features of that particular task.…”

Section: Introductionmentioning

confidence: 99%

Resource Allocation in the Brain

Alonso

Brocas

Carrillo

2013

The Review of Economic Studies

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When an individual performs several tasks simultaneously, processing resources must be allocated to different brain systems to produce energy for neurons to fire. Following the evidence from neuroscience, we model the brain as an organization in which a coordinator allocates limited resources to the brain systems responsible for the different tasks. Systems are privately informed about the amount of resources necessary to perform their task and compete to obtain the resources. The coordinator arbitrates the demands while satisfying the resource constraint. We show that the optimal mechanism is to impose to each system with privately known needs a cap in resources that depends negatively on the amount of resources requested by the other system. This allocation can be implemented using a biologically plausible mechanism. Finally, we provide some implications of our theory: (i) performance is inversely related to the difficulty of the task and can be flawless for sufficiently simple tasks, (ii) the dynamic allocation rule exhibits inertia (current allocations are increasing in past needs), and (iii) different cognitive tasks are performed by different systems only if the tasks are sufficiently important.

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Learning Self-Control *

Cited by 110 publications

References 63 publications

Naiveté, Projection Bias, and Habit Formation in Gym Attendance

Naiveté, Projection Bias, and Habit Formation in Gym Attendance

Liquidity Restrictions on Investment Funds: Are they a Response to Behavioral Bias?

Resource Allocation in the Brain

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