John Monterosso and George Ainslie, “The Behavioral Economics of Will in Recovery from Addiction.” Drug and Alcohol Dependence 90(Supplement 1): S100-S111, September 2007.
• Addicts have severe self-control issues with respect to the object of their ardor.
• The goal of this article is to suggest that behavioral economics ideas are fruitful not only in thinking about the process of building an addiction, but also in understanding recoveries from addiction.
• Dynamic inconsistency seems to be tied up in addiction: addicts often express (quite credibly) desires to quit or cut down, but do not follow through on those desires.
• But dynamic inconsistency might also suggest pathways out of addiction – and many treatment programs look to develop these pathways, which involve internal, not external, commitment devices (“private side-betting”).
• Drug use would not be a problem if the pain arose immediately, and the gratification arrived after a delay.
• “Hyperbolic discounting implies that the increase in valuation that occurs when moving a fixed unit of time closer to an expected outcome is proportionately greater the closer one is to that outcome. Think of the experience of waiting for an additional day for an important event that is a year off, versus for one that is imminent [p. 3].”
• Hyperbolic discounting sets one up for dynamic inconsistency of the immediate gratification variety; further, addicts tend to display higher discount rates than non-addicted people (though causality might go both ways). How is it that people with this sort of discounting ever recover, and become dynamically consistent with respect to their intentions to indulge in drugs, say?
• A hyperbolic discounter has a multitude of different (time-based) “interests” – it is Jekyll and Hyde and the rest of the London population, too.
• How does one “interest” protect itself against foreseeable future “interests”? One approach is to make the tempting act unavailable, or raise its cost – perhaps by announcing to your social circle that you are on a diet, for instance, or are having a Dryuary. Or maybe you can deflect your attention (subconsciously) from activities that lead to your problem activity, or develop a repugnance towards them.
• These approaches are not really about willpower; rather, they signal a sophisticated understanding of your own future lack of willpower. And yet many treatment programs harp on building willpower.
• Another method to bolster willpower is a form of mental accounting: you bundle current choices with a string of future choices. In this way, a choice to drink today isn’t just about drinking or not drinking today: a choice to drink means that you will make a similar choice in future days – and that prospect might be sufficiently harrowing to keep you from drinking today.
• Experiments show that humans and non-human animals do choose less impulsively when they know that the current choice will bind similar choices down the road.
• What if you knew that having a drink today would have no effect on your future behavior, that you were pre-determined to drink every future day? What if you were told that you were pre-determined to never drink again, whether or not you drink today? It looks like current abstention is bolstered by the notion that it can influence future choices! But people do abstain, so they must see a link between today’s choice and future choices.
• Bundling can arise when someone sees that “I’ll smoke today and quit tomorrow” will also apply tomorrow, ad infinitum. Then, the actual choices today are “I’ll smoke today and forever” or “I’ll stop today and not relapse.” The personal “rule” becomes “never smoke.”
• The situation is like an intrapersonal repeated prisoners’ dilemma: the only reason you choose to “cooperate” today is if you can thereby make it more likely that your future selves also will choose to cooperate.
• But recall: in iterated prisoners’ dilemmas, it is hard to restore cooperation after a single defection. Likewise, a single lapse from abstinence by a recovering addict can lead to a binge. This sort of behavior looks like it is better described by the “bundling” model or willpower, not a story of binding commitments.
• Why would an addict fall off the wagon?: “[T]o the extent that her abstinence is based on a bundling effect, the primary danger comes from factors that reduce her differential expectation of future abstinence as a function of current abstinence [p. 9].”
• This reduction of perceived danger can derive from overconfidence, underconfidence, or rationalization.
• Twelve-step programs emphasize that willpower is unreliable, yet their adherents seem to do better (than those in other treatment forms) in overcoming cravings.
• Twelve-step treatments seem to respond to the threats created by overconfidence, underconfidence, and rationalization. How? (1) powerlessness and its related credos; (2) the focus on abstinence and the permanence of addiction; and (3) the adoption of doable goals, such as “one day at a time,” while tracking the abstinence streak.
• “When a person structures her choices with personal rules she can be expected to express different preferences than she would if she were making a choice just on the basis of its own merits, and these preferences are apt to differ as well among categories of reward, according to their temporal distribution, emotional relevance, dangerousness, impulse control history, and doubtless many other factors [p. 12].”
• There is a possibility for a deleterious positive feedback loop, where proximity to the temptation good (or a cue) increases the probability of consumption which increases appetite which leads to increased probability of consumption…
Sunday, September 23, 2018
Wednesday, August 22, 2018
Banker et al. (2017) on Sticky Anchors
Sachin Banker, Sarah E. Ainsworth, Roy F. Baumeister, Dan Ariely, and
Kathleen D. Voh, “The Sticky Anchor Hypothesis: Ego Depletion Increases Susceptibility to Situational Cues.” Journal of Behavioral Decision Making 30(5): 1027-1040, December 2017 [pdf here].
• “Ego Depletion”: Exerting self-control undermines self-control in slightly later situations.
• Is ego depletion a thing? Maybe, maybe not (pdf here); like many behavioral concepts (for example, grit [pdf here]), ego depletion has its detractors.
• In a dictator game-type setting, does less altruistic behavior (from ego depletion) come about because self-controls over selfishness are undermined, or because people are more inclined to follow salient situational cues? This latter possibility is the sticky anchor hypothesis: depleted people are more suggestible or manipulable.
• Some dictator game experiments show that depleted people do indeed keep more of the monetary stake for themselves.
• Are the dictator game findings due to unleashed selfishness or to sticking with the default? To test between the two mechanisms, the authors switch the default: they conduct reverse dictator games. The other (anonymous) party is endowed with the full stake, but you, as the dictator, can choose to take some or all of it. The default, now, is the unselfish setting, so if depleted people have a hard time overcoming defaults, they will leave more of the cash with the other player (relative to the amount left by undepleted folks). Alternatively, if depletion makes you selfish, depleted folks will take more of the endowment from the other player.
• The depletion manipulation (in Experiment 1, with overall N=54) involves writing some text without using the letters A or N. (Those in the “undepleted” camp write without using the letters X and Z. Incidentally, this reminds me of the singular novel Ella Minnow Pea.) That is, it is attention control that is the source of ego depletion within this experiment.
• On average, those in the depleted condition take less money for themselves ($2.62) than do those in the undepleted condition ($3.69). So, ego depletion does not seem to increase selfishness; rather, it makes it harder to overcome the influence of environmental cues: defaults become more sticky. Notice that neither group is particularly generous.
• But maybe the attention control manipulation means that the depleted also feel like failures, because they perform poorly at writing without A’s or N’s: they don’t deserve the money in the reverse dictator game. Vicarious depletion [pdf here] to the rescue! A waiter is really hungry…(alternatively, not so hungry…)
• Once again, the depleted folks (that is, the now vicariously depleted folks, who feel no shame) stick more closely to the anchor: it doesn’t seem to be a lack of desert that causes them to take less money (or fewer lottery tickets) for themselves.
• But maybe it isn’t general environmental cues at work, maybe it is just our old friend, the status quo effect. So now (Experiment 3) the authors offer either a high or a low anchor before subjects decide how much money to take. Note that the default (the anonymous other gets all the cash) is unchanged, but there is a new situational cue, the anchor. (Subjects are first asked whether they want to take more or less than the anchor; only then are they asked for the precise amount they want to take.) Will depleted people respond to the anchor (more than non-depleted people do), or just to the default?
• Both depleted and non-depleted subjects respond to the anchor. But the depleted respond more, particularly in the low-anchor treatment. The influence of environmental cues, and not the status quo per se, is what leads to different behavior by depleted folk relative to the undepleted.
• “Ego Depletion”: Exerting self-control undermines self-control in slightly later situations.
• Is ego depletion a thing? Maybe, maybe not (pdf here); like many behavioral concepts (for example, grit [pdf here]), ego depletion has its detractors.
• In a dictator game-type setting, does less altruistic behavior (from ego depletion) come about because self-controls over selfishness are undermined, or because people are more inclined to follow salient situational cues? This latter possibility is the sticky anchor hypothesis: depleted people are more suggestible or manipulable.
• Some dictator game experiments show that depleted people do indeed keep more of the monetary stake for themselves.
• Are the dictator game findings due to unleashed selfishness or to sticking with the default? To test between the two mechanisms, the authors switch the default: they conduct reverse dictator games. The other (anonymous) party is endowed with the full stake, but you, as the dictator, can choose to take some or all of it. The default, now, is the unselfish setting, so if depleted people have a hard time overcoming defaults, they will leave more of the cash with the other player (relative to the amount left by undepleted folks). Alternatively, if depletion makes you selfish, depleted folks will take more of the endowment from the other player.
• The depletion manipulation (in Experiment 1, with overall N=54) involves writing some text without using the letters A or N. (Those in the “undepleted” camp write without using the letters X and Z. Incidentally, this reminds me of the singular novel Ella Minnow Pea.) That is, it is attention control that is the source of ego depletion within this experiment.
• On average, those in the depleted condition take less money for themselves ($2.62) than do those in the undepleted condition ($3.69). So, ego depletion does not seem to increase selfishness; rather, it makes it harder to overcome the influence of environmental cues: defaults become more sticky. Notice that neither group is particularly generous.
• But maybe the attention control manipulation means that the depleted also feel like failures, because they perform poorly at writing without A’s or N’s: they don’t deserve the money in the reverse dictator game. Vicarious depletion [pdf here] to the rescue! A waiter is really hungry…(alternatively, not so hungry…)
• Once again, the depleted folks (that is, the now vicariously depleted folks, who feel no shame) stick more closely to the anchor: it doesn’t seem to be a lack of desert that causes them to take less money (or fewer lottery tickets) for themselves.
• But maybe it isn’t general environmental cues at work, maybe it is just our old friend, the status quo effect. So now (Experiment 3) the authors offer either a high or a low anchor before subjects decide how much money to take. Note that the default (the anonymous other gets all the cash) is unchanged, but there is a new situational cue, the anchor. (Subjects are first asked whether they want to take more or less than the anchor; only then are they asked for the precise amount they want to take.) Will depleted people respond to the anchor (more than non-depleted people do), or just to the default?
• Both depleted and non-depleted subjects respond to the anchor. But the depleted respond more, particularly in the low-anchor treatment. The influence of environmental cues, and not the status quo per se, is what leads to different behavior by depleted folk relative to the undepleted.
Sunday, August 12, 2018
Shrader, Wooten, White, et al. (2017) on Using Loss Aversion to Motivate Students
Rebekah Shrader, Jadrian James Wooten, Dustin R. White, et al.,
“Improving Student Performance through Loss Aversion.” December 12,
2017; updated version available here.
• Pairs of nearly identical courses are offered, where one element of each pair calculates student points as losses from a perfect base: a score of 50 means the student has lost 50 points, as opposed to the usual (control) case where points accumulate with correct assignments. • The idea is to see if the “loss framing” triggers greater student effort in a bid to avoid or minimize losses (as opposed to hoping to acquire gains); that is, the authors are testing to see if enlisting aversion towards losses via the grading framework leads to better student performance.
• Students were not informed when they signed up for their classes that they were part of a field experiment.
• The loss framing (“counting down”) was associated with higher grades – some 2.6 to 4.2 percentage points higher.
• Did students perform better in the loss framework simply because it was unusual?
• A couple of related papers. not (yet?) covered by Behavioral Economics Outlines, are Roland G. Fryer, Jr, Steven D. Levitt, John List, and Sally Sadoff, “Enhancing the Efficacy of Teacher Incentives Through Framing: A Field Experiment," April 2018, pdf here) and Steven D. Levitt, John A. List, Susanne Neckermann, and Sally Sadoff, “The Behavioralist Goes to School: Leveraging Behavioral Economics to Improve Educational Performance,” American Economic Journal: Economic Policy 8(4): 183-219, November 2016.
Clark and Lisowski (2017) on Prospect Theory and Moving
William A. V. Clark and William Lisowski, “Prospect Theory and the Decision to Move or Stay.” Proceedings of the National Academy of
Sciences of the United States of America 114(36): E7432–E7440,
September 5, 2017.
• Clark and Lisowski examine residential moves (of 70 kilometers or more) in Australia between 2010 and 2014.
• The analysis assumes that the status quo residence represents the reference point.
• The authors argue that the endowment effect in housing occurs because residents learn more about advantages and disadvantages of their housing, and that this raises “use values” relative to “exchange values.”
• Previous empirical evidence indicates that the probability of moving decreases with the duration of living in the current residence; the authors, therefore, include a duration variable, as well as an indicator for owning versus renting, among their independent variables.
• Clark and Lisowski also possess a variable that captures the extent of self-reported risk aversion on the part of the surveyed individual. It turns out that people who don’t move are quite likely to be in the top half of the population in terms of this measure of risk aversion.
• Movers tend to be younger, and they tend to be renters in their initial residence. Couples with kids are less likely to move.
• Both duration and home ownership are associated with decreased re-location, which the authors interpret as an endowment effect -- but are these endowment effects?
• Clark and Lisowski examine residential moves (of 70 kilometers or more) in Australia between 2010 and 2014.
• The analysis assumes that the status quo residence represents the reference point.
• The authors argue that the endowment effect in housing occurs because residents learn more about advantages and disadvantages of their housing, and that this raises “use values” relative to “exchange values.”
• Previous empirical evidence indicates that the probability of moving decreases with the duration of living in the current residence; the authors, therefore, include a duration variable, as well as an indicator for owning versus renting, among their independent variables.
• Clark and Lisowski also possess a variable that captures the extent of self-reported risk aversion on the part of the surveyed individual. It turns out that people who don’t move are quite likely to be in the top half of the population in terms of this measure of risk aversion.
• Movers tend to be younger, and they tend to be renters in their initial residence. Couples with kids are less likely to move.
• Both duration and home ownership are associated with decreased re-location, which the authors interpret as an endowment effect -- but are these endowment effects?
Friday, August 10, 2018
Chen and Schonger (2016) on Ambiguity Aversion
Daniel L. Chen and Martin Schonger, “Is Ambiguity Aversion a
Preference?” TSE Working Paper No. 16-703, December 2016.
• Ambiguity aversion has been implicated in many real world phenomena, including the equity premium puzzle: the stock market operates under Knightian uncertainty (ambiguity), not risk, and so ambiguity-averse investors need compensation to buy stocks. Overly punitive plea bargains are acceptable to ambiguity-averse defendants…
• But perhaps the sort of behavior exhibited by the Ellsberg paradox is not really indicative of underlying preferences – perhaps it is mistake, the use of a decision heuristic in inappropriate circumstances. Perhaps people are not actually ambiguity averse.
• Maybe people (rightly) shy away from unfamiliar offers, especially when the person making the offer possesses superior information – and this is the situation when experimental participants are presented with the Ellsberg game. Subjects suspect that the experimenter actually knows how many red and blue balls are in the urn.
• Chen and Schonger set up an Ellsberg experiment where the experimenter is not the party responsible for the contents of the ambiguous urn; rather, the choices of other subjects determine the contents.
• Every subject decides which of two symbols to send to the others. In experiment 1, the symbol that gets the most “votes” is the symbol that will appear in the “ambiguous” urn for other participants (which need not be the same for all participants, incidentally).
• All experiments involve a toss of a fair coin, where the subjects can choose to bet on either heads or tails, along with the two ambiguous options. A correct outcome yields 4€. The choice of the bet is determined by taking the maximum of the valuations provided by each participant for each of the four bets.
• People turn out to prefer the ambiguous bets! “For each of the 16 sessions, individuals were more likely to bet on a symbol with subjective uncertainty, and in all but 2 of the 16 sessions, both bets with subjective uncertainty were more popular than the bets with objective uncertainty [p. 15].” This remains true in design 2, where there is a full-on urn and not just a specific symbol chosen by others.
• Ambiguity aversion has been implicated in many real world phenomena, including the equity premium puzzle: the stock market operates under Knightian uncertainty (ambiguity), not risk, and so ambiguity-averse investors need compensation to buy stocks. Overly punitive plea bargains are acceptable to ambiguity-averse defendants…
• But perhaps the sort of behavior exhibited by the Ellsberg paradox is not really indicative of underlying preferences – perhaps it is mistake, the use of a decision heuristic in inappropriate circumstances. Perhaps people are not actually ambiguity averse.
• Maybe people (rightly) shy away from unfamiliar offers, especially when the person making the offer possesses superior information – and this is the situation when experimental participants are presented with the Ellsberg game. Subjects suspect that the experimenter actually knows how many red and blue balls are in the urn.
• Chen and Schonger set up an Ellsberg experiment where the experimenter is not the party responsible for the contents of the ambiguous urn; rather, the choices of other subjects determine the contents.
• Every subject decides which of two symbols to send to the others. In experiment 1, the symbol that gets the most “votes” is the symbol that will appear in the “ambiguous” urn for other participants (which need not be the same for all participants, incidentally).
• All experiments involve a toss of a fair coin, where the subjects can choose to bet on either heads or tails, along with the two ambiguous options. A correct outcome yields 4€. The choice of the bet is determined by taking the maximum of the valuations provided by each participant for each of the four bets.
• People turn out to prefer the ambiguous bets! “For each of the 16 sessions, individuals were more likely to bet on a symbol with subjective uncertainty, and in all but 2 of the 16 sessions, both bets with subjective uncertainty were more popular than the bets with objective uncertainty [p. 15].” This remains true in design 2, where there is a full-on urn and not just a specific symbol chosen by others.
Monday, July 30, 2018
Golman, Loewenstein, Moene, and Zarri (2016) on Belief Consonance
Russell Golman, George Loewenstein, Karl Ove Moene, and Luca Zarri, “The Preference for Belief Consonance.” Journal of Economic Perspectives 30(3): 165-188, Summer 2016 [pdf].
• People like to have beliefs that accord with the beliefs of others. Sharing beliefs enhances our connection to our group.
• Much of world conflict is about beliefs – often about rather subtle differences in beliefs. Recall that people protect beliefs in which they have invested heavily.
• Conflict over small differences in beliefs might arise because our beliefs are most threatened by those who are otherwise similar to us.
• People do not like to have their beliefs challenged, so media have incentives not to challenge beliefs.
• Beliefs might come first, and only then do we develop the “rational” reasons that we hold them; see Jonathan Haidt, The Righteous Mind: Why Good People Are Divided by Politics and Religion, Pantheon, 2012.
• Belief consonance can be self-reinforcing: when someone stubbornly refuses to agree with me, I can attribute her stubbornness to her own interest in protecting her initial beliefs – and therefore I do not have to reconsider my own beliefs.
• In the interest of possessing consonant beliefs, all people might believe X, but believe that everyone else believes “not X”: “pluralistic ignorance”. See Timur Kuran, Private Truths, Public Lies: The Social Consequences of Preference Falsification, Harvard, 1998.
• In trust and dictator games, people are more generous when paired with members of their own political party.
• Two (complementary?) approaches to the enticements of belief consonance: (1) desire to match beliefs with a group that you are in, or want to join; and (2) desire to maintain desirable beliefs about yourself.
• On the whole, belief consonance probably is detrimental to society.
• People like to have beliefs that accord with the beliefs of others. Sharing beliefs enhances our connection to our group.
• Much of world conflict is about beliefs – often about rather subtle differences in beliefs. Recall that people protect beliefs in which they have invested heavily.
• Conflict over small differences in beliefs might arise because our beliefs are most threatened by those who are otherwise similar to us.
• People do not like to have their beliefs challenged, so media have incentives not to challenge beliefs.
• Beliefs might come first, and only then do we develop the “rational” reasons that we hold them; see Jonathan Haidt, The Righteous Mind: Why Good People Are Divided by Politics and Religion, Pantheon, 2012.
• Belief consonance can be self-reinforcing: when someone stubbornly refuses to agree with me, I can attribute her stubbornness to her own interest in protecting her initial beliefs – and therefore I do not have to reconsider my own beliefs.
• In the interest of possessing consonant beliefs, all people might believe X, but believe that everyone else believes “not X”: “pluralistic ignorance”. See Timur Kuran, Private Truths, Public Lies: The Social Consequences of Preference Falsification, Harvard, 1998.
• In trust and dictator games, people are more generous when paired with members of their own political party.
• Two (complementary?) approaches to the enticements of belief consonance: (1) desire to match beliefs with a group that you are in, or want to join; and (2) desire to maintain desirable beliefs about yourself.
• On the whole, belief consonance probably is detrimental to society.
Friday, July 20, 2018
Bénabou and Tirole (2016) on Motivated Beliefs
Roland Bénabou and Jean Tirole, “Mindful Economics: The Production,
Consumption, and Value of Beliefs.” Journal of Economic Perspectives 30(3): 141-164, Summer 2016.
• People value their beliefs, both directly and for instrumental reasons; therefore, beliefs can withstand counter-evidence, and people may prefer to steer clear of evidence.
• Positive beliefs can be nurtured by responding asymmetrically to good and bad news.
• Shared beliefs also can be resistant to evidence, possibly with dreadful consequences.
• Bénabou et Tirole treat beliefs as if they were standard economic goods or assets, which people consume, invest in, produce, and so on.
• Optimism can serve as a sort of commitment device to stick with long-term projects and to avoid temptation. False beliefs can also influence other people in a way that might serve your interests. Religious beliefs might contribute both to self-discipline and to improve your view of yourself and your future.
• Methods to protect valued beliefs include “strategic ignorance, reality denial, and self-signaling [p. 144].” More educated people are not better shielded from employing these methods.
• Confirmation bias allows people to believe that their previous views have been corroborated. They anticipate this future corroboration, and this allows them to take on risky projects.
• Emotional responses to a challenge to your beliefs are a signal that your beliefs are something you are trying to protect. Standard rationality suggests that challenges should be welcomed -- shades of J. S. Mill.
• There’s a trade-off between accepting bad news and optimizing decisions given reality versus living in blissful ignorance for awhile before the piper must be paid.
• Because it is easier to recall our actions than it is to recall our motives, we might try to self-signal, by choosing actions that will allow us to later have a good (but distorted) view of ourselves.
• In laboratory experiments, subjects have a harder time remembering (accurately) their past failures.
• Self-deception rises with the size of the sunk costs. People persuade themselves of the future value of these investments.
• People are quite good at believing they had sound reasons for their bad behaviors.
• Blind persistence in social projects in the face of bad news might make the situation more tolerable. But if persistence can lead to bigger losses, watch out for “Mutually Assured Delusion.” Unfortunately, it is in this situation that denial becomes contagious.
• Organizational failures might be a result of bad beliefs as much as bad incentives.
• “Just-world” beliefs and the extent of the welfare state are negatively correlated.
• Constitutional guarantees of free speech and a free press might serve as a commitment device to allow dissent even in the future bad states – and reduce the protection of current beliefs, because of the increased likelihood that they will be challenged, anyway.
• People value their beliefs, both directly and for instrumental reasons; therefore, beliefs can withstand counter-evidence, and people may prefer to steer clear of evidence.
• Positive beliefs can be nurtured by responding asymmetrically to good and bad news.
• Shared beliefs also can be resistant to evidence, possibly with dreadful consequences.
• Bénabou et Tirole treat beliefs as if they were standard economic goods or assets, which people consume, invest in, produce, and so on.
• Optimism can serve as a sort of commitment device to stick with long-term projects and to avoid temptation. False beliefs can also influence other people in a way that might serve your interests. Religious beliefs might contribute both to self-discipline and to improve your view of yourself and your future.
• Methods to protect valued beliefs include “strategic ignorance, reality denial, and self-signaling [p. 144].” More educated people are not better shielded from employing these methods.
• Confirmation bias allows people to believe that their previous views have been corroborated. They anticipate this future corroboration, and this allows them to take on risky projects.
• Emotional responses to a challenge to your beliefs are a signal that your beliefs are something you are trying to protect. Standard rationality suggests that challenges should be welcomed -- shades of J. S. Mill.
• There’s a trade-off between accepting bad news and optimizing decisions given reality versus living in blissful ignorance for awhile before the piper must be paid.
• Because it is easier to recall our actions than it is to recall our motives, we might try to self-signal, by choosing actions that will allow us to later have a good (but distorted) view of ourselves.
• In laboratory experiments, subjects have a harder time remembering (accurately) their past failures.
• Self-deception rises with the size of the sunk costs. People persuade themselves of the future value of these investments.
• People are quite good at believing they had sound reasons for their bad behaviors.
• Blind persistence in social projects in the face of bad news might make the situation more tolerable. But if persistence can lead to bigger losses, watch out for “Mutually Assured Delusion.” Unfortunately, it is in this situation that denial becomes contagious.
• Organizational failures might be a result of bad beliefs as much as bad incentives.
• “Just-world” beliefs and the extent of the welfare state are negatively correlated.
• Constitutional guarantees of free speech and a free press might serve as a commitment device to allow dissent even in the future bad states – and reduce the protection of current beliefs, because of the increased likelihood that they will be challenged, anyway.
Sunday, July 15, 2018
WS on Hot States and Cold States (V)
Who can be wise, amazed, temperate and furious,
Loyal and neutral, in a moment? No man:
The expedition my violent love
Outrun the pauser, reason. Here lay Duncan,
His silver skin laced with his golden blood;
And his gash'd stabs look'd like a breach in nature
For ruin's wasteful entrance: there, the murderers,
Steep'd in the colours of their trade, their daggers
Unmannerly breech'd with gore: who could refrain,
That had a heart to love, and in that heart
Courage to make's love known?
(Macbeth, Act 2, Scene 3, lines 896-906)
See also:
WS on Hot States and Cold States (I)
WS on Hot States and Cold States (II)
WS on Hot States and Cold States (III)
WS on Hot States and Cold States (IV)
Loyal and neutral, in a moment? No man:
The expedition my violent love
Outrun the pauser, reason. Here lay Duncan,
His silver skin laced with his golden blood;
And his gash'd stabs look'd like a breach in nature
For ruin's wasteful entrance: there, the murderers,
Steep'd in the colours of their trade, their daggers
Unmannerly breech'd with gore: who could refrain,
That had a heart to love, and in that heart
Courage to make's love known?
(Macbeth, Act 2, Scene 3, lines 896-906)
See also:
WS on Hot States and Cold States (I)
WS on Hot States and Cold States (II)
WS on Hot States and Cold States (III)
WS on Hot States and Cold States (IV)
Flèche and Layard (2017) on Misery
Sarah Flèche and Richard Layard, “Do More of Those in Misery Suffer from Poverty, Unemployment or Mental Illness?” KYKLOS 70(1): 27-41, February 2017 [prior version here].
• The authors define the miserable to be those whose self-report of life satisfaction is among the lowest in their nation -- (slightly) more specifically, in about the lowest ten percent (it varies by country).
• Their main measure of mental illness is an objective one: the person is in treatment or has received a mental health diagnosis.
• The data are drawn from the US, Australia, Britain, and Germany.
• There are many “causes” of misery, but poor mental health is a leading one, more important than poverty or unemployment or poor physical health. In the US, for instance, 27% of the miserable are poor, but 61% have been diagnosed with depression or anxiety.
• Mental illness might be harder to adapt to than physical illness.
• Therapy appears to be able to help people alleviate their misery: perhaps 1 in 3 people who receive cognitive behavioral therapy for their depression/anxiety recover (who without treatment would not recover). In terms of life-satisfaction, there seems to be a huge payoff (many multiples of the cost) to making cognitive behavioral therapy more available.
• Nonetheless, the vast majority of health care spending is aimed at physical health, not mental health.
• The authors define the miserable to be those whose self-report of life satisfaction is among the lowest in their nation -- (slightly) more specifically, in about the lowest ten percent (it varies by country).
• Their main measure of mental illness is an objective one: the person is in treatment or has received a mental health diagnosis.
• The data are drawn from the US, Australia, Britain, and Germany.
• There are many “causes” of misery, but poor mental health is a leading one, more important than poverty or unemployment or poor physical health. In the US, for instance, 27% of the miserable are poor, but 61% have been diagnosed with depression or anxiety.
• Mental illness might be harder to adapt to than physical illness.
• Therapy appears to be able to help people alleviate their misery: perhaps 1 in 3 people who receive cognitive behavioral therapy for their depression/anxiety recover (who without treatment would not recover). In terms of life-satisfaction, there seems to be a huge payoff (many multiples of the cost) to making cognitive behavioral therapy more available.
• Nonetheless, the vast majority of health care spending is aimed at physical health, not mental health.
Chin, Markey, Bhargava, et al. (2017) on Boredom
Alycia Chin, Amanda Markey, Saurabh Bhargava, Karim S. Kassam, and George Loewenstein, “Bored in the USA: Experience Sampling and Boredom in Everyday Life.” Emotion 17(2): 359-368, 2017 [pdf].
• This article is based on experience sampling: more than 3000 adults offer half-hour updates for 7-to-10 days, yielding more than one million observations; about 2.8% of these updates include a claim of boredom. (More than one-third pf participants, however, never report feeling bored.) "[S]ubjects additionally report details about their time-use, including what they were doing, who they were with, and their location, as well as their experience of 16 other emotions [page 360]."
• The data is collected via a custom-made iPhone app; participants without iPhones are loaned a phone dedicated to the app.
• Boredom is much more likely to be accompanied by a negative emotion (such as sadness) than by a positive emotion (such as happiness).
• Men are more likely (one-third more likely) than women to be bored; unmarried people and younger people are more likely to feel bored. High-school drop-outs suffer boredom at higher rates than the more educated.
• Studying and work seem to go along with boredom (and as locations, schools and workplaces are boring); boredom peaks around 2PM. (Neither napping nor exercise is associated with boredom!) Co-workers tend to be boring, but friends and spouses aren't boring. Dining or drinking out is not boring.
• Most of the variation in boredom is due to circumstances, not to the individuals involved.
• The authors cite Kierkegaard on boredom; they don't mention Bertrand Russell, who had lots of non-boring things to say about boredom.
• This article is based on experience sampling: more than 3000 adults offer half-hour updates for 7-to-10 days, yielding more than one million observations; about 2.8% of these updates include a claim of boredom. (More than one-third pf participants, however, never report feeling bored.) "[S]ubjects additionally report details about their time-use, including what they were doing, who they were with, and their location, as well as their experience of 16 other emotions [page 360]."
• The data is collected via a custom-made iPhone app; participants without iPhones are loaned a phone dedicated to the app.
• Boredom is much more likely to be accompanied by a negative emotion (such as sadness) than by a positive emotion (such as happiness).
• Men are more likely (one-third more likely) than women to be bored; unmarried people and younger people are more likely to feel bored. High-school drop-outs suffer boredom at higher rates than the more educated.
• Studying and work seem to go along with boredom (and as locations, schools and workplaces are boring); boredom peaks around 2PM. (Neither napping nor exercise is associated with boredom!) Co-workers tend to be boring, but friends and spouses aren't boring. Dining or drinking out is not boring.
• Most of the variation in boredom is due to circumstances, not to the individuals involved.
• The authors cite Kierkegaard on boredom; they don't mention Bertrand Russell, who had lots of non-boring things to say about boredom.
Wednesday, June 27, 2018
Knabe, Schöb, and Weimann (2017) on the Well-Being of Workfare Participants
Andreas Knabe, Ronnie Schöb, and Joachim Weimann, “The Subjective
Well-Being of Workfare Participants: Insights from a Day Reconstruction
Survey.” Applied Economics 49(13), 2017.
• Workfare involves connecting unemployment benefits to participation in (public) employment.
• Unemployment is very bad for subjective well-being; the authors want to know if workfare is, too.
• The sample (usable n=1055) is drawn from German labor force participants, some working full-time (n=366), and some in long-term unemployment. Of the long-term unemployed, some (n=341) were participating in low-paid workfare jobs.
• The authors find through interviews (conducted in 2008) using the Day Reconstruction Method that self-reported life satisfaction of the workfare population is better than that of unemployed people, but not as high as that of employed people. This life-satisfaction boost is enjoyed both by those who were coerced into workfare jobs by the threat of losing benefits and those who voluntarily entered the workfare scheme.
• The affect (day-to-day happiness) of those on workfare is more positive than that of either the unemployed or the employed: workfare participants enjoy their hours working more than "regular" employees do.
• Workfare involves connecting unemployment benefits to participation in (public) employment.
• Unemployment is very bad for subjective well-being; the authors want to know if workfare is, too.
• The sample (usable n=1055) is drawn from German labor force participants, some working full-time (n=366), and some in long-term unemployment. Of the long-term unemployed, some (n=341) were participating in low-paid workfare jobs.
• The authors find through interviews (conducted in 2008) using the Day Reconstruction Method that self-reported life satisfaction of the workfare population is better than that of unemployed people, but not as high as that of employed people. This life-satisfaction boost is enjoyed both by those who were coerced into workfare jobs by the threat of losing benefits and those who voluntarily entered the workfare scheme.
• The affect (day-to-day happiness) of those on workfare is more positive than that of either the unemployed or the employed: workfare participants enjoy their hours working more than "regular" employees do.
Sunday, June 24, 2018
Silver et al. (2017) on the Berkeley Soda Tax
Lynn D. Silver, Shu Wen Ng, Suzanne Ryan-Ibarra, et al., “Changes in prices, sales, consumer spending, and beverage consumption one year after a tax on sugar-sweetened beverages in Berkeley, California, US: A before-and-after study.” PLoS Med 14(4), April 18, 2017, https://doi.org/10.1371/journal.pmed.1002283.
• Berkeley imposed a 1-cent per ounce tax for sugar-sweetened beverages starting in January, 2015; even before the tax, Berkeley per-capita soda consumption was quite low by US standards.
• The study compares the before-and-after situation in Berkeley stores with comparable stores outside of Berkeley.
• The tax led to higher soda prices in chain-stores, and to a significant fall in soda purchases, as well as a rise in water purchases. Consumers don’t seem to spend more on beverages after the tax is imposed. The overall effect on calories consumed is uncertain.
Popkin and Hawkes (2016) on Sweetening of Diets
Barry M. Popkin and Corinna Hawkes, “Sweetening of the Global Diet, Particularly Beverages: Patterns, Trends, and Policy Responses.” The Lancet Diabetes & Endocrinology 4(2): 174–186, February 2016.
• Added caloric sweeteners in beverages seem to involve special health risks, such as diabetes. (The jury is still out on low-calorie sweeteners and 100% fruit juices.) Chile, Mexico, and the US lead the league table.
• Most food and most beverage calories consumed in the US come from items with added sweeteners. In recent years, the US has seen some movement away from beverages with added caloric sweeteners.
• As incomes rise, much of the rest of the world is adopting US-style added-caloric-sweetener habits.
• Early studies of sweet taxes suggest that they do dissuade consumption, and possibly even lead to changes in the composition of food items.
• Sustained public information campaigns employing multiple channels of dissemination can dissuade unhealthy behaviors. The precise right approach (or approaches) to label information and warnings remains unresolved.
• Many jurisdictions have imposed restrictions on sugar marketing and in-school availability, as well as promoting public awareness and requiring nutritional information and warnings on packaging.
• Added caloric sweeteners in beverages seem to involve special health risks, such as diabetes. (The jury is still out on low-calorie sweeteners and 100% fruit juices.) Chile, Mexico, and the US lead the league table.
• Most food and most beverage calories consumed in the US come from items with added sweeteners. In recent years, the US has seen some movement away from beverages with added caloric sweeteners.
• As incomes rise, much of the rest of the world is adopting US-style added-caloric-sweetener habits.
• Early studies of sweet taxes suggest that they do dissuade consumption, and possibly even lead to changes in the composition of food items.
• Sustained public information campaigns employing multiple channels of dissemination can dissuade unhealthy behaviors. The precise right approach (or approaches) to label information and warnings remains unresolved.
• Many jurisdictions have imposed restrictions on sugar marketing and in-school availability, as well as promoting public awareness and requiring nutritional information and warnings on packaging.
Monday, June 18, 2018
Downs and Loewenstein (2011) on Obesity
Julie S. Downs and George Loewenstein, “Behavioral Economics and Obesity.” In The Oxford Handbook of the Social Science of Obesity, John Cawley, editor, 2011.
• The rise in obesity is hard to explain via rational choice: think of the huge expenditures on failed diets and exercise programs, for instance. “Informational” interventions, such as better calorie information, might be fairly limited in terms of combatting obesity, then.
• One cannot take a zero tolerance approach towards food; also, people have a habit of understating their consumption, or simply forgetting about snacks.
• It doesn’t seem as if an increase in discount rates spurred the obesity rise, because discount rates have not risen, even though obesity is concentrated among those with higher discount rates. And present bias seems more applicable to food than it does to other types of decisions.
• The future health costs of a bad diet are intangible, and for a single meal, negligible. Any one dietary indiscretion is (metaphorically) peanuts, but routinely neglecting these indiscretions – the “peanuts effect” – can lead to obesity and serious harm.
• Field studies don’t show much improvement in calorie reduction from posting calorie counts. A decrease in consumption in one meal can be offset by later meals.
• The rise in obesity tracks the rise in restaurant serving sizes fairly closely.
• The rise in obesity is hard to explain via rational choice: think of the huge expenditures on failed diets and exercise programs, for instance. “Informational” interventions, such as better calorie information, might be fairly limited in terms of combatting obesity, then.
• One cannot take a zero tolerance approach towards food; also, people have a habit of understating their consumption, or simply forgetting about snacks.
• It doesn’t seem as if an increase in discount rates spurred the obesity rise, because discount rates have not risen, even though obesity is concentrated among those with higher discount rates. And present bias seems more applicable to food than it does to other types of decisions.
• The future health costs of a bad diet are intangible, and for a single meal, negligible. Any one dietary indiscretion is (metaphorically) peanuts, but routinely neglecting these indiscretions – the “peanuts effect” – can lead to obesity and serious harm.
• Field studies don’t show much improvement in calorie reduction from posting calorie counts. A decrease in consumption in one meal can be offset by later meals.
• The rise in obesity tracks the rise in restaurant serving sizes fairly closely.
Schall, Doll, and Mohnen (2017) on Useless Warnings
Dominik L. Schall, Dominik Doll, and Alwine Mohnen, “Caution! Warnings as a Useless Countermeasure to Reduce Overconfidence? An Experimental Evaluation in Light of Enhanced and Dynamic Warning Designs.” Journal of Behavioral Decision Making 30(2): 347-358, April 2017.
• Two experiments look at over-precision in guessing the answers to factual questions. People tend to choose 90% confidence intervals that are much, much too narrow: people are overly optimistic about their precision.
• Warning people to be wary of over-precision in itself (even when the warning takes a fairly fancy form) seems useless, but…
• …a dynamic (pop-up) warning significantly reduces over-precision. Effective warning content and the dynamic element seem to both be required.
• Effective warning content is rather involved: it consists of a highlighted signal word ("Caution"); an explanation of the hazard (overconfidence); the consequence of the hazard (the truth lying outside of the chosen confidence interval excessively); and instructions (widen your intervals) about how to overcome the hazard.
• Two experiments look at over-precision in guessing the answers to factual questions. People tend to choose 90% confidence intervals that are much, much too narrow: people are overly optimistic about their precision.
• Warning people to be wary of over-precision in itself (even when the warning takes a fairly fancy form) seems useless, but…
• …a dynamic (pop-up) warning significantly reduces over-precision. Effective warning content and the dynamic element seem to both be required.
• Effective warning content is rather involved: it consists of a highlighted signal word ("Caution"); an explanation of the hazard (overconfidence); the consequence of the hazard (the truth lying outside of the chosen confidence interval excessively); and instructions (widen your intervals) about how to overcome the hazard.
Saturday, April 28, 2018
Grubb (2015) on Overconfident Consumers
Michael D. Grubb, “Overconfident Consumers in the Marketplace.” Journal of Economic Perspectives 29(4): 9-36, Fall 2015.
• Overconfidence encompasses both excessive optimism and flattering views of the precision of beliefs. For instance, people are overconfident about their future ability to exercise self-control or to pay attention to the potential of looming high fees.
• Overconfidence harms consumers, and competitive markets do not necessarily mitigate overconfidence – they may even exacerbate its costs; rebates and gym memberships are canonical instances.
• Complex contract terms can take advantage of overconfident consumers.
• Overconfident consumers can be the source of a subsidy to fully rational consumers.
• Price controls could serve consumer and social welfare in the presence of overconfident consumers.
• Overconfidence encompasses both excessive optimism and flattering views of the precision of beliefs. For instance, people are overconfident about their future ability to exercise self-control or to pay attention to the potential of looming high fees.
• Overconfidence harms consumers, and competitive markets do not necessarily mitigate overconfidence – they may even exacerbate its costs; rebates and gym memberships are canonical instances.
• Complex contract terms can take advantage of overconfident consumers.
• Overconfident consumers can be the source of a subsidy to fully rational consumers.
• Price controls could serve consumer and social welfare in the presence of overconfident consumers.
Arad and Rubinstein (2015) on the People’s Perspective on Nudges
Ayala Arad and Ariel Rubinstein, “The People’s Perspective on Libertarian-Paternalistic Policies,” July 2015. This outline draws on the July, 2015 version of the paper, but a later version (October, 2017) of the paper is available here, as a pdf.
• Two online studies (each n>1000) are conducted with university students in Israel, Germany, and the US.
• In Study 1, subjects either are presented with an opt-in employee savings plan, or a government-mandated opt-out version with an 8% savings default.
• A large percentage (28-53% across the three countries) of subjects have a negative view of the opt-out version (especially if they are aware of the opt-in alternative), even if they intend to save 8% monthly. Indeed, fewer people indicate that they will take up the 8% savings rate when it is presented as the default than would take it up on an opt-in basis.
• Study 2 concerns attempts to decrease the consumption of fatty foods. Some measures (taxes, one-day-per-week ban) are hard paternalism, one is a System 1 nudge (shifting the placement of food items on menus), and two are System 2 nudges involving information provision (media campaign, smartphone app).
• The effectiveness of each of the measures in reducing consumption of fatty foods is presented to the subjects, with seven variations.
• Up to 25% of subjects think that government shouldn’t be in the business of trying to change diets.
• Most subjects (among those who do not object to the government being involved) seem to prefer whatever measure is most effective.
• But 19 to 54% of subjects prefer the info provision, even when it is less effective than the System 1 nudge.
• The “hard” interventions attract little support.
• The October 2017 version of the paper includes these two sentences in the abstract: "The opposition to soft interventions appears to be driven by concerns about manipulation and the fear of a 'slippery slope' to non-consensual interventions. Opposition to soft interventions is reduced when they are carried out by employers rather than the government."
• Two online studies (each n>1000) are conducted with university students in Israel, Germany, and the US.
• In Study 1, subjects either are presented with an opt-in employee savings plan, or a government-mandated opt-out version with an 8% savings default.
• A large percentage (28-53% across the three countries) of subjects have a negative view of the opt-out version (especially if they are aware of the opt-in alternative), even if they intend to save 8% monthly. Indeed, fewer people indicate that they will take up the 8% savings rate when it is presented as the default than would take it up on an opt-in basis.
• Study 2 concerns attempts to decrease the consumption of fatty foods. Some measures (taxes, one-day-per-week ban) are hard paternalism, one is a System 1 nudge (shifting the placement of food items on menus), and two are System 2 nudges involving information provision (media campaign, smartphone app).
• The effectiveness of each of the measures in reducing consumption of fatty foods is presented to the subjects, with seven variations.
• Up to 25% of subjects think that government shouldn’t be in the business of trying to change diets.
• Most subjects (among those who do not object to the government being involved) seem to prefer whatever measure is most effective.
• But 19 to 54% of subjects prefer the info provision, even when it is less effective than the System 1 nudge.
• The “hard” interventions attract little support.
• The October 2017 version of the paper includes these two sentences in the abstract: "The opposition to soft interventions appears to be driven by concerns about manipulation and the fear of a 'slippery slope' to non-consensual interventions. Opposition to soft interventions is reduced when they are carried out by employers rather than the government."
Sunday, April 1, 2018
Jung and Mellers (2016) Look at US Attitudes Towards Nudges
Janice Y. Jung and Barbara A. Mellers, “American Attitudes toward
Nudges.” Judgment and Decision Making 11(1): 62-74, January 2016.
• System 1 nudges are those that take advantage of our relatively automatic, unthinking mechanism for making decisions – canny default settings are an example of a System 1 nudge.
• System 2 nudges enhance our cognitive abilities, perhaps by providing more information – calorie counts on food items are an example of a System 2 nudge.
• Study 1 conducted by Jung and Mellers looks at nine System 1 nudges and four System 2 nudges, in an internet-based survey (n=250). Subjects are asked if they are for or against nudges, and then rate the intensity of their feelings on the subject. (If you are unsure, you will be asked to explain why!) Subjects also rate nudges on various scales, such as whether they are a threat to autonomy.
• Jung and Meller's Study 2 manipulates the “framing” of the nudges, sometimes emphasizing individual effects, sometimes social effects; sometimes highlighting the benefits, sometimes highlighting the avoidance of costs. Attitudes also are collected about companies that institute nudges.
• System 2 nudges receive more support than System 1 nudges – but one System 2 nudge, where government provides a website that tracks people’s expenditures on food, energy, and so on, is disliked in a System 1-like manner.
• Also disliked are opt-out organ donation lists, those misleading white lines on Lake Shore Drive, one-click charitable donation opportunities at store check-outs, and credit card online payment mechanisms that default to fully paying off the debt.
• Empathic folks tend to support System 1 and System 2 nudges; conservatives and individualists tend to oppose both types of nudges. (“Reactant” people oppose System 1 nudges.) System 2 nudges are viewed as more effective, though evidence generally supports the superior effectiveness of System 1 nudges.
• Framing doesn’t matter much on average, but does matter with some sub-groups; for instance, “reactant” people oppose nudges more strongly when the frame points out the individual costs of not going along. Feelings about companies that nudge basically track the feelings about the nudges the companies implement.
• System 1 nudges are those that take advantage of our relatively automatic, unthinking mechanism for making decisions – canny default settings are an example of a System 1 nudge.
• System 2 nudges enhance our cognitive abilities, perhaps by providing more information – calorie counts on food items are an example of a System 2 nudge.
• Study 1 conducted by Jung and Mellers looks at nine System 1 nudges and four System 2 nudges, in an internet-based survey (n=250). Subjects are asked if they are for or against nudges, and then rate the intensity of their feelings on the subject. (If you are unsure, you will be asked to explain why!) Subjects also rate nudges on various scales, such as whether they are a threat to autonomy.
• Jung and Meller's Study 2 manipulates the “framing” of the nudges, sometimes emphasizing individual effects, sometimes social effects; sometimes highlighting the benefits, sometimes highlighting the avoidance of costs. Attitudes also are collected about companies that institute nudges.
• System 2 nudges receive more support than System 1 nudges – but one System 2 nudge, where government provides a website that tracks people’s expenditures on food, energy, and so on, is disliked in a System 1-like manner.
• Also disliked are opt-out organ donation lists, those misleading white lines on Lake Shore Drive, one-click charitable donation opportunities at store check-outs, and credit card online payment mechanisms that default to fully paying off the debt.
• Empathic folks tend to support System 1 and System 2 nudges; conservatives and individualists tend to oppose both types of nudges. (“Reactant” people oppose System 1 nudges.) System 2 nudges are viewed as more effective, though evidence generally supports the superior effectiveness of System 1 nudges.
• Framing doesn’t matter much on average, but does matter with some sub-groups; for instance, “reactant” people oppose nudges more strongly when the frame points out the individual costs of not going along. Feelings about companies that nudge basically track the feelings about the nudges the companies implement.
Thursday, March 8, 2018
Schulz, Thiemann, and Thöni (2016) on Nudging Generosity
Jonathan F. Schulz, Petra Thiemann, and Christian Thöni, “Nudging Generosity: Choice Architecture and Cognitive Factors in Charitable Giving,” USC-INET Research Paper No. 16-26, September 13, 2016.
• The subjects (n=869) are students at a Swiss university, who are asked at the end of a pen-and-paper study if they would like to donate to charity some of any winnings they make from the experiment.
• In one treatment, the students who indicate that they want to donate to charity must write in a charity name in a blank space. In the alternative treatment, the students are given a list of five well-known charities which they can choose among, along with a blank space in case they want to indicate another charity.
• The one-line summary of the results is that providing a short list of recommended charities, along with a “choose your own” option, doubles the number of donors relative to just having the “choose your own” option.
• The average donation per donor is unchanged, so the “list” treatment also doubles total contributions. Most donations in the "list" treatment go to listed charities; other charities are "crowded out" by not being listed.
• Females donate significantly more than males.
• The subjects (n=869) are students at a Swiss university, who are asked at the end of a pen-and-paper study if they would like to donate to charity some of any winnings they make from the experiment.
• In one treatment, the students who indicate that they want to donate to charity must write in a charity name in a blank space. In the alternative treatment, the students are given a list of five well-known charities which they can choose among, along with a blank space in case they want to indicate another charity.
• The one-line summary of the results is that providing a short list of recommended charities, along with a “choose your own” option, doubles the number of donors relative to just having the “choose your own” option.
• The average donation per donor is unchanged, so the “list” treatment also doubles total contributions. Most donations in the "list" treatment go to listed charities; other charities are "crowded out" by not being listed.
• Females donate significantly more than males.
Shakespeare on the Benefits of Information Avoidance
What sense had I of her stol'n hours of lust?
I saw't not, thought it not, it harm'd not me:
I slept the next night well, was free and merry;
I found not Cassio's kisses on her lips:
He that is robb'd, not wanting what is stol'n,
Let him not know't, and he's not robb'd at all.
(Othello, Act 3, Scene 3, Lines 2015-2020; this passage appears as the epigraph to Russell Golman, David Hagmann, and George Loewenstein, “Information Avoidance,” Journal of Economic Literature 55(1): 96-135, March 2017.)
********************************************
I had been happy, if the general camp,
Pioners and all, had tasted her sweet body,
So I had nothing known. O, now, for ever
Farewell the tranquil mind! farewell content!
(Othello, Act 3, Scene 3, Lines 2022-2025)
********************************************
How blest am I
In my just censure, in my true opinion!
Alack, for lesser knowledge! how accursed
In being so blest! There may be in the cup
A spider steep'd, and one may drink, depart,
And yet partake no venom, for his knowledge
Is not infected: but if one present
The abhorr'd ingredient to his eye, make known
How he hath drunk, he cracks his gorge, his sides,
With violent hefts. I have drunk,
and seen the spider.
(The Winter's Tale, Act 2, Scene 1, Lines 645-655)
I saw't not, thought it not, it harm'd not me:
I slept the next night well, was free and merry;
I found not Cassio's kisses on her lips:
He that is robb'd, not wanting what is stol'n,
Let him not know't, and he's not robb'd at all.
(Othello, Act 3, Scene 3, Lines 2015-2020; this passage appears as the epigraph to Russell Golman, David Hagmann, and George Loewenstein, “Information Avoidance,” Journal of Economic Literature 55(1): 96-135, March 2017.)
********************************************
I had been happy, if the general camp,
Pioners and all, had tasted her sweet body,
So I had nothing known. O, now, for ever
Farewell the tranquil mind! farewell content!
(Othello, Act 3, Scene 3, Lines 2022-2025)
********************************************
How blest am I
In my just censure, in my true opinion!
Alack, for lesser knowledge! how accursed
In being so blest! There may be in the cup
A spider steep'd, and one may drink, depart,
And yet partake no venom, for his knowledge
Is not infected: but if one present
The abhorr'd ingredient to his eye, make known
How he hath drunk, he cracks his gorge, his sides,
With violent hefts. I have drunk,
and seen the spider.
(The Winter's Tale, Act 2, Scene 1, Lines 645-655)
Friday, February 23, 2018
Zarghamee et al. (2017) on Nudging Charitable Giving
Homa S. Zarghamee, Kent D. Messer, Jacob R. Fooks, William D. Schulze, Shang Wu, and Jubo Yan, “Nudging Charitable Giving: Three Field Experiments.” Journal of Behavioral and Experimental Economics 66: 137-
149, February 2017 [abstract here].
• Study 1: Students had earned money over the duration of the semester by taking part in experiments; this study asked them if they wanted to donate some or all of their earnings to charity.
• Envelopes were provided such that students could either donate some of their earnings (opting in to charity, n=69), or, request a refund from the contribution of their money (opting out of charity, n=118).
• The opt-out version increases contributions by some 25%.
• Study 2 (n at most 59) looks at whether some cheap talk and a vote prior to deciding to contribute to charity – and potentially to keep donating for 10 months – can induce more giving than without the chitchat and vote. The cheap talk does the (cheap) trick, inducing higher donations by some 47%.
• Study 3 (n=70) involves one treatment where the charity mentions HIV, whereas the other treatment does not. The treatment makes no difference to donations, but changes to positive and negative affect during the experiment do influence giving. A lower positive affect decreases giving, but an increase in negative affect increases giving.
• Study 1: Students had earned money over the duration of the semester by taking part in experiments; this study asked them if they wanted to donate some or all of their earnings to charity.
• Envelopes were provided such that students could either donate some of their earnings (opting in to charity, n=69), or, request a refund from the contribution of their money (opting out of charity, n=118).
• The opt-out version increases contributions by some 25%.
• Study 2 (n at most 59) looks at whether some cheap talk and a vote prior to deciding to contribute to charity – and potentially to keep donating for 10 months – can induce more giving than without the chitchat and vote. The cheap talk does the (cheap) trick, inducing higher donations by some 47%.
• Study 3 (n=70) involves one treatment where the charity mentions HIV, whereas the other treatment does not. The treatment makes no difference to donations, but changes to positive and negative affect during the experiment do influence giving. A lower positive affect decreases giving, but an increase in negative affect increases giving.
Bosman, Hennig‐Schmidt, and van Winden (2016) on Power-to-Take Games
Ronald Bosman, Heike Hennig‐Schmidt, and Frans van Winden, “Emotion at Stake: The Role of Stake Size and Emotions in a Power-To-Take Game Experiment in China with a Comparison to Europe.” CESifo Working Paper Series No. 5858, April 19, 2016.
• In the two-player power-to-take game, Player A indicates what percentage of Player B’s monetary endowment Player A will claim.
• Player B learns of A’s claim, and then can choose to destroy some or all of her own endowment. Whatever is left after the destruction, Player A receives the chosen percentage of it, while Player B retains the remainder.
• Power-to-take is sort of a generalized version of the ultimatum game, and in particular, it allows Player B to have intermediate responses, in between accepting Player A’s suggestion or destroying the entire “endowment.”
• Three conditions: China Low (stakes), n=36; China High, n=36; and, EU, n=40. The results for the two China treatments are similar.
• Take rates in China average more than 50%; while most people do not destroy any of their endowment, the average amount of destruction is considerable, more than 20%. Higher take rates lead to more destruction.
• Higher take rates strengthen negative emotions in Players B, and it is possibly worse with higher stakes.
• Destruction decisions seem to be mostly driven by emotions.
• The results, including emotional responses, seem to be similar in China and Europe.
• In the two-player power-to-take game, Player A indicates what percentage of Player B’s monetary endowment Player A will claim.
• Player B learns of A’s claim, and then can choose to destroy some or all of her own endowment. Whatever is left after the destruction, Player A receives the chosen percentage of it, while Player B retains the remainder.
• Power-to-take is sort of a generalized version of the ultimatum game, and in particular, it allows Player B to have intermediate responses, in between accepting Player A’s suggestion or destroying the entire “endowment.”
• Three conditions: China Low (stakes), n=36; China High, n=36; and, EU, n=40. The results for the two China treatments are similar.
• Take rates in China average more than 50%; while most people do not destroy any of their endowment, the average amount of destruction is considerable, more than 20%. Higher take rates lead to more destruction.
• Higher take rates strengthen negative emotions in Players B, and it is possibly worse with higher stakes.
• Destruction decisions seem to be mostly driven by emotions.
• The results, including emotional responses, seem to be similar in China and Europe.
Sunday, January 28, 2018
Koessler, Torgler, Feld, and Frey (2016) on Promising to Pay Your Taxes
Ann-Kathrin Koessler, Benno Torgler, Lars P. Feld, and Bruno S. Frey,
“Commitment to Pay Taxes: A Field Experiment on the Importance of
Promise.” Tax and Transfer Policy Institute, Australian National University,
Working Paper 10/2016, November 29, 2016 [pdf here].
• A natural field experiment (n≈2000) is conducted in Switzerland (in 2013); the subjects, Swiss taxpayers, do not know that they are taking part in an experiment.
• The experiment concerns whether it is possible to encourage timely tax payments by having taxpayers voluntarily promise to remit their taxes on time. One potentially confounding factor, however, is that a new “dunning” policy for late taxpayers is enacted concurrently with the experiment.
• There are two “promise” treatments. In both cases, subjects are told that if they fill in and return a postcard promising to pay their taxes on time, and then do pay their taxes on time, they will be entered into a lottery. The differences between these two treatments is that in one case the lottery prize is cash – 1000 Swiss francs – and in the other, the prize is a wellness spa trip for two, worth approximately 1000 Swiss francs.
• Both promise treatments have parallel treatments that provide the same lottery to punctual payers, but that do not require or provide the option for the non-binding promise. A control treatment with no lottery or promise completes the collection.
• Almost one-third of the subjects who are given an opportunity to promise to pay on time make the promise. The willingness to promise is a pretty strong signal both of whether you have paid on time in the past, and of whether you will pay on time this year.
• Those who were in the spa lottery and who made the promise saw a significant jump in their compliance rates. But the lotteries with promise opportunities do not seem to do any better overall than the lotteries without the promise opportunities.
• My takeaway, perhaps not as optimistic as that of the authors, is that the “promise” intervention is pretty weak tea.
• A natural field experiment (n≈2000) is conducted in Switzerland (in 2013); the subjects, Swiss taxpayers, do not know that they are taking part in an experiment.
• The experiment concerns whether it is possible to encourage timely tax payments by having taxpayers voluntarily promise to remit their taxes on time. One potentially confounding factor, however, is that a new “dunning” policy for late taxpayers is enacted concurrently with the experiment.
• There are two “promise” treatments. In both cases, subjects are told that if they fill in and return a postcard promising to pay their taxes on time, and then do pay their taxes on time, they will be entered into a lottery. The differences between these two treatments is that in one case the lottery prize is cash – 1000 Swiss francs – and in the other, the prize is a wellness spa trip for two, worth approximately 1000 Swiss francs.
• Both promise treatments have parallel treatments that provide the same lottery to punctual payers, but that do not require or provide the option for the non-binding promise. A control treatment with no lottery or promise completes the collection.
• Almost one-third of the subjects who are given an opportunity to promise to pay on time make the promise. The willingness to promise is a pretty strong signal both of whether you have paid on time in the past, and of whether you will pay on time this year.
• Those who were in the spa lottery and who made the promise saw a significant jump in their compliance rates. But the lotteries with promise opportunities do not seem to do any better overall than the lotteries without the promise opportunities.
• My takeaway, perhaps not as optimistic as that of the authors, is that the “promise” intervention is pretty weak tea.
Friday, January 5, 2018
Horton and Zeckhauser (2016) on Peer Effects in Production
John J. Horton and Richard J. Zeckhauser, “The Causes of Peer Effects in Production: Evidence from a Series of Field Experiments.” NBER Working Paper No. 22386, July 2016 [ungated pdf version here].
• A worker’s productivity is influenced by the productivity of her co-workers. Why?
• Do low-productivity workers fear punishment, because their slackerdom imposes more work on others, or because others simply view the provision of low effort as unfair? Do workers have a preference to not be unproductive? Does the performance of other employees signal to a worker the employer’s expectations?
• The field experiments involve hiring workers online (MTurk) to label images; the workers do not know that they are taking part in an experiment.
• Among the findings are that peers will punish slackers even when the slackers do not impose any harm on the other workers; and, that equity concerns motivate such punishment, through a suspicion of low effort from slackers. Workers therefore want either to avoid being slackers, or, perhaps, to avoid being perceived as slackers.
• Workers (the subjects in the experiments) label images and evaluate the labelling performance of other workers. Evaluations involve a recommendation as to whether the peer worker should be paid, and also, a suggestion of how a 9-cent bonus should be split between the evaluator and the evaluated. The recommended bonus splits are implemented. A recommendation that a worker not be paid, though not implemented, is taken to be a type of punishment of that worker.
• All of the subjects also evaluate the work of either a (specific) high effort or a low effort worker, based on work from a previous experiment. A description of the four treatments in the field experiment follows:
Baseline: Workers are shown either a very good labelling job, or a minimal effort version. They then choose to take the task (if indeed they want to), and start labelling.
Punish: After seeing a sample of excellent work, this treatment proceeds like Baseline, except that then some good or bad work requires peer evaluation.
Peers: After evaluation, subjects then are given a second labelling task. Will evaluating a good or a bad job (done by someone else) alter the worker’s second-round performance?
Explicit: This is like Peers, except that workers are told to produce only two labels per image. But when they evaluate others, some of the subjects see an image with the requisite two labels, while the others see an image with 11 labels (produced by some Stakhanovite). Note that this excessive production explicitly contravenes the injunction to provide only two labels.
• And the results...
Baseline: If you are shown a high-quality sample, you are less likely to take the job, but if you take it, you increase your effort.
Punish: Peer evaluation leads to lessened punishment for good as opposed to bad work; workers who themselves produce good work punish more.
Peers: If you evaluate a strong worker, your subsequent work is stronger, and the effect is more pronounced if you yourself are a high productivity worker.
Explicit: Workers shown against-the-rules overproduction do not punish it, and many workers themselves switch to excessive output.
• A worker’s productivity is influenced by the productivity of her co-workers. Why?
• Do low-productivity workers fear punishment, because their slackerdom imposes more work on others, or because others simply view the provision of low effort as unfair? Do workers have a preference to not be unproductive? Does the performance of other employees signal to a worker the employer’s expectations?
• The field experiments involve hiring workers online (MTurk) to label images; the workers do not know that they are taking part in an experiment.
• Among the findings are that peers will punish slackers even when the slackers do not impose any harm on the other workers; and, that equity concerns motivate such punishment, through a suspicion of low effort from slackers. Workers therefore want either to avoid being slackers, or, perhaps, to avoid being perceived as slackers.
• Workers (the subjects in the experiments) label images and evaluate the labelling performance of other workers. Evaluations involve a recommendation as to whether the peer worker should be paid, and also, a suggestion of how a 9-cent bonus should be split between the evaluator and the evaluated. The recommended bonus splits are implemented. A recommendation that a worker not be paid, though not implemented, is taken to be a type of punishment of that worker.
• All of the subjects also evaluate the work of either a (specific) high effort or a low effort worker, based on work from a previous experiment. A description of the four treatments in the field experiment follows:
Baseline: Workers are shown either a very good labelling job, or a minimal effort version. They then choose to take the task (if indeed they want to), and start labelling.
Punish: After seeing a sample of excellent work, this treatment proceeds like Baseline, except that then some good or bad work requires peer evaluation.
Peers: After evaluation, subjects then are given a second labelling task. Will evaluating a good or a bad job (done by someone else) alter the worker’s second-round performance?
Explicit: This is like Peers, except that workers are told to produce only two labels per image. But when they evaluate others, some of the subjects see an image with the requisite two labels, while the others see an image with 11 labels (produced by some Stakhanovite). Note that this excessive production explicitly contravenes the injunction to provide only two labels.
• And the results...
Baseline: If you are shown a high-quality sample, you are less likely to take the job, but if you take it, you increase your effort.
Punish: Peer evaluation leads to lessened punishment for good as opposed to bad work; workers who themselves produce good work punish more.
Peers: If you evaluate a strong worker, your subsequent work is stronger, and the effect is more pronounced if you yourself are a high productivity worker.
Explicit: Workers shown against-the-rules overproduction do not punish it, and many workers themselves switch to excessive output.
Tuesday, January 2, 2018
Hermann and Musshoff (2016) on Measuring Time Preferences
Daniel Hermann and Oliver Musshoff, “Measuring Time Preferences:
Comparing Methods and Evaluating the Magnitude Effect.” Journal of
Behavioral and Experimental Economics 65: 16-26, December 2016.
• Two different approaches to measuring discount rates in the past have revealed similar rates for US students – but what about for entrepreneurs, and for German students?
• This article consist of a web-based experiment with German farmers (n=111) and students (n=178); farmers are standing in for entrepreneurs, as farmers must make significant investment decisions that only yield results in the long-term.
• The experiments are conducted with both 100 and 300 euro benchmark amounts; the idea is to test for the “magnitude effect,” in which revealed discount rates fall as monetary amounts rise.
• Further, some previous estimates of discount rates might be skewed by the assumption of risk neutrality.
• The Coller and Williams (CW) task: You can receive €100 in three weeks. Or, you can receive more than €100 in twelve weeks. How much more than €100 do you need before you are willing to wait the extra nine weeks? This experiment is repeated for amounts 3 times as high.
• The Holt and Laury (HL) task: Lottery A offers prizes of either €180 or €144, while lottery B offers the outcomes €346.50 or €9. The higher prize has the same probability of occurring in both lotteries. How high does the probability of the higher prize have to be to get you to choose Lottery B?
• The p task, from Laury et al. (2012): Lottery A pays out zero half the time and €100 half the time, with the prize collected in three weeks. Lottery B pays out zero or €100 too, but doesn’t pay out until 12 weeks from now. How much greater than .5 does the probability of winning €100 have to be to get you to choose Lottery B, and thus wait the additional nine weeks? As with CW, this experiment is replicated with payouts three times as high.
• For farmers, the estimated average discount rate from CW is 12.9% for €100 tests, and 8.8% for €300 tests. For the p task, rates are significantly higher, at 30.6% for the €100 test, and 28.6% for the €300 test.
• In the joint estimation, student discount rates are similar to the farmers’. For the p-test on students, while this method still led to higher discount rates (significantly so for the €300 version) compared to the joint estimation, the increase was not nearly as a great as it was for farmers.
• For both students and farmers, raising the stakes to €300 lowers discount rates significantly in the joint estimation – the decline is greater for students. In the p-test approach, the fall in discount rates associated with higher stakes is not significant. This non-result suggests that for risky alternatives, the magnitude effect might not exist.
• Two different approaches to measuring discount rates in the past have revealed similar rates for US students – but what about for entrepreneurs, and for German students?
• This article consist of a web-based experiment with German farmers (n=111) and students (n=178); farmers are standing in for entrepreneurs, as farmers must make significant investment decisions that only yield results in the long-term.
• The experiments are conducted with both 100 and 300 euro benchmark amounts; the idea is to test for the “magnitude effect,” in which revealed discount rates fall as monetary amounts rise.
• Further, some previous estimates of discount rates might be skewed by the assumption of risk neutrality.
• The Coller and Williams (CW) task: You can receive €100 in three weeks. Or, you can receive more than €100 in twelve weeks. How much more than €100 do you need before you are willing to wait the extra nine weeks? This experiment is repeated for amounts 3 times as high.
• The Holt and Laury (HL) task: Lottery A offers prizes of either €180 or €144, while lottery B offers the outcomes €346.50 or €9. The higher prize has the same probability of occurring in both lotteries. How high does the probability of the higher prize have to be to get you to choose Lottery B?
• The p task, from Laury et al. (2012): Lottery A pays out zero half the time and €100 half the time, with the prize collected in three weeks. Lottery B pays out zero or €100 too, but doesn’t pay out until 12 weeks from now. How much greater than .5 does the probability of winning €100 have to be to get you to choose Lottery B, and thus wait the additional nine weeks? As with CW, this experiment is replicated with payouts three times as high.
• For farmers, the estimated average discount rate from CW is 12.9% for €100 tests, and 8.8% for €300 tests. For the p task, rates are significantly higher, at 30.6% for the €100 test, and 28.6% for the €300 test.
• In the joint estimation, student discount rates are similar to the farmers’. For the p-test on students, while this method still led to higher discount rates (significantly so for the €300 version) compared to the joint estimation, the increase was not nearly as a great as it was for farmers.
• For both students and farmers, raising the stakes to €300 lowers discount rates significantly in the joint estimation – the decline is greater for students. In the p-test approach, the fall in discount rates associated with higher stakes is not significant. This non-result suggests that for risky alternatives, the magnitude effect might not exist.
Monday, January 1, 2018
Wang, Rieger, and Hens (2017) on Culture and Loss Aversion
Mei Wang, Marc Oliver Rieger, and Thorsten Hens, “The Impact of Culture
on Loss Aversion.” Journal of Behavioral Decision Making 30: 270-281, 2017.
• Wang, Rieger, and Hens look at loss aversion in 53 countries. The underlying notion is that emotions are implicated in loss aversion, but the display and regulation of emotions is culturally influenced.
• In their data, higher (nationwide) levels of loss aversion are connected to: individualism; “power distance” (which means strength of social hierarchy, according to Wikipedia); and masculinity. A fourth factor, uncertainty avoidance, is less meaningful. These factors are drawn from a 2001 book on the consequences of culture by Geert Hofstede. [But it seems the subsequently expanded Hofstede criteria might be even more connected to loss aversion. Again, from Wikipedia: “Independent research in Hong Kong led Hofstede to add a fifth dimension, long-term orientation, to cover aspects of values not discussed in the original paradigm. In 2010, Hofstede added a sixth dimension, indulgence versus self-restraint.”]
• Loss aversion is measured by the answers to two questions. If you have a 50% chance of losing $25, and a 50% chance of winning x, how high does x have to be for you to agree to take this bet? The second question replaces $25 with $100. The loss aversion parameter is determined by dividing the answer by the stakes (25 or 100), and the overall measure averages the two stake-differentiated results.
• The survey is given to college students and the stakes are expressed in ways that, for students, are comparable across countries. Georgians have (easily) the highest loss aversion, at 7.5, with a few countries (Luxembourg, Bosnia, Tanzania) around 1 (no loss aversion). The mean across countries is 2.0. Eastern Europeans have the highest loss aversion, and Africans have the lowest.
• Women tend to be more loss averse, even though an increase in “masculinity” brings higher loss aversion. A greater percentage of Orthodox Christians leads to more loss aversion in a nation.
• Economic factors don’t seem to matter: it is culture, not the economy, that drives international differences in loss aversion.
• Wang, Rieger, and Hens look at loss aversion in 53 countries. The underlying notion is that emotions are implicated in loss aversion, but the display and regulation of emotions is culturally influenced.
• In their data, higher (nationwide) levels of loss aversion are connected to: individualism; “power distance” (which means strength of social hierarchy, according to Wikipedia); and masculinity. A fourth factor, uncertainty avoidance, is less meaningful. These factors are drawn from a 2001 book on the consequences of culture by Geert Hofstede. [But it seems the subsequently expanded Hofstede criteria might be even more connected to loss aversion. Again, from Wikipedia: “Independent research in Hong Kong led Hofstede to add a fifth dimension, long-term orientation, to cover aspects of values not discussed in the original paradigm. In 2010, Hofstede added a sixth dimension, indulgence versus self-restraint.”]
• Loss aversion is measured by the answers to two questions. If you have a 50% chance of losing $25, and a 50% chance of winning x, how high does x have to be for you to agree to take this bet? The second question replaces $25 with $100. The loss aversion parameter is determined by dividing the answer by the stakes (25 or 100), and the overall measure averages the two stake-differentiated results.
• The survey is given to college students and the stakes are expressed in ways that, for students, are comparable across countries. Georgians have (easily) the highest loss aversion, at 7.5, with a few countries (Luxembourg, Bosnia, Tanzania) around 1 (no loss aversion). The mean across countries is 2.0. Eastern Europeans have the highest loss aversion, and Africans have the lowest.
• Women tend to be more loss averse, even though an increase in “masculinity” brings higher loss aversion. A greater percentage of Orthodox Christians leads to more loss aversion in a nation.
• Economic factors don’t seem to matter: it is culture, not the economy, that drives international differences in loss aversion.
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