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Behavioral Public Finance Sendhil Mullainathan Harvard University (joint projects with William Congdon, Alex Gelber, Jeff Kling and others…)

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Presentation on theme: "Behavioral Public Finance Sendhil Mullainathan Harvard University (joint projects with William Congdon, Alex Gelber, Jeff Kling and others…)"— Presentation transcript:

1 Behavioral Public Finance Sendhil Mullainathan Harvard University (joint projects with William Congdon, Alex Gelber, Jeff Kling and others…)

2 Promise of Behavioral Policy Psychology provides novel insights How to integrate these with policy?

3 Promise of Behavioral Policy Madrian and Shea (2001) Choi, Laibson, Madrian, Metrick (2004)

4 Promise of Behavioral Policy Implemented in law – Pension Protection Act 2006 – Gives incentives for companies to provide automatic enrollment Provides safe harbors – Delineates rates and funds Important observation: governments often set the welfare function – Analogy to externalities

5 Outline of Lecture The Welfare Challenge Integration within Public Finance Framework Broader Lessons

6 Outline of Lecture The Welfare Challenge Integration within Public Finance Framework Broader Lessons

7 Setup Want to set up a trivial framework – Abstracts from richness of psychology – Illustrates broad contours of the policy problem Individuals choose to do an action x or not. – Eat potato chips (e.g. O’Donoghue-Rabin) Their private utility: b-c if they do. 0 otherwise – b represents their type and is distributed f(b). High b love potato chips, low b do not

8 Rationality and Government Intervention Suppose people are rational – Eat potato chips if b > c No rationale for intervention Libertarian solution: – free to choose…potato chips!

9 Behavioral Assumption Fraction q of the population is behavioral – Behavioral individuals choose as if their benefit were β(b) So they buy if β (b) > c. Example from present bias models: – Temptation: overvalue potato chips β(b) >b – Healthy goods: undervalue potato chips β(b)

10 Behavioral Policy Now the government can possibly intervene Price levers: Subsidies, taxes – Hedonic utility of individual can be b+t > c – Behavioral types choose according to β(b)+τ(t)>c – Incorrect response to the price lever: The horizon of the tax for the hyperbolic (ex: Bernheim- Rangel) Tax salience (Ex: Chetty)

11 Behavioral Policy Non-price levers (nudges) – Behavioral types choose to β(b,n) >c – Non-behavioral types b > c – Definition of a nudge captures idea that rational type is largely unaffected by them Many nudges are “near” nudges b(n)≈b Examples – Label the potato chips – Opt-out taxes

12 Automatic Enrollment Revisited Default is a nudge Issues: – How do we know what the right savings rate is? – What savings rate do we choose?

13 Central feature of Challenge Inferring hedonic utility – How are we to infer b when people choose according to β(b)? – If under different nudges we see different revealed preference β(b,n) what is the true b? Related problem: welfare functions that account for these changing preferences – Can we use some sort of Pareto criteria across “selves”?

14 Key challenge How to do welfare economics in the presence of behavioral agents? What is true hedonic welfare? Lack of revealed preference dilutes issues Other examples: – Energy paradox. What should weight be? – Job search and procrastination – Program to increase high school graduation rate

15 Some Approaches Sin Taxes (Odonoghue and Rabin) – Observe that for reasonable welfare functions taxes will always be reasonable Small tax has second order losses to rational self – They are optimizing wrt hedonic utility Small tax has first order gains to behavioral self – They are not optimizing wrt hedonic utility – Richer frameworks needed on how to combine nudges and prices Berneheim-Rangel: Lay out desirable criteria of a welfare function – Bottom line: not much specific possible – Some “intuitive” criteria fail obvious desirable axioms (e.g. in hyperbolic discounting)

16 Some Approaches Libertarian paternalism: use only nudges – Sunstein-Thaler and Camerer et. al. – Implicitly assume lexicographic social welfare function First ensure rationals get at least utility they get in equilibrium. Then weight behaviorals – Other rationales: Uncertainty/disagreement about existence of behavioral types Take welfare function as given (Congdon et. al.) – We take inter-personal weights as given, we do not derive them. – Why not take intra-personal weights as given. – Interesting economics follows: If nudges so important in 401(k), why not lower subsidy as well?

17 Outline of Lecture The Welfare Challenge Integration within Public Finance Framework Broader Lessons

18 Different Class of Problems Logic so far: – Issue with no traditional role for government – Behavioral insights generate role for government Different class of problems – Issues with pre-existing roles for government – How do behavioral insights affect these designs? Examples: – Redistribution

19 Redistribution Government would like to transfer resources to all types to ensure utility of u – All types b>u+c achieve this utilty on their own – Ideal transfer: Types in [u+c,c] given u-[b-c] and choose action Types b

20 Key Feature Problems Behavioral type imposes an “externality” Suppose some high types fail to work, e.g. procrastination in job search. Makes the transfer problem as a whole more difficult Allows a smaller transfer to genuine hardships Government has incentive to fix the procrastination problem for its own reasons in addition to helping the individual

21 Welfare Function Two components to welfare function now – Traditional component Preferences for redistribution – Weight on behavioral type All the problems identified earlier Will abstract from the latter. – Simplifying assumption – Reasonable abstraction in many practical cases Because primary goal not to fix the behavioral problem Allows us to put a sign on behavior – Induce job search

22 Key Insights Interaction between underlying economic problem and behavioral insight essential Suggests very different kind of data needed Analogy to case of retirement savings automatic enrollment often misleading in these cases

23 Method of Analysis Assume policy makers presume full rationality – Set policies as if all were rational – Only thing behavioral types can affect is the estimated elasticity Two questions: – What mistakes does this produce? – How would the realization of a behavioral type alter the design?

24 Redistribution Wrong model – Misinterpreting price responses – Mis-tagging – False fear of moral hazard Opportunities – Behavioral tagging Nudges – Locally good nudges can be globally bad – Using nudges -> change in price lever as well – Libertarian paternalism would not be optimal even if we only cared about rational type

25 Transfer Policy Portfolio of policies with broadly similar challenges at a structural level Including: – Cash: TANF, etc. – Non-cash: Education: Head Start, job training, etc. Health: Medicaid, CHIP, etc.

26 Transfer policy: Challenges Delivery – Getting benefits to targeted groups, individuals – Take-up rates are imperfect Design – Structuring benefits to aid recipients – Benefits ≠ outcomes Disincentives – Providing benefits without distorting incentives – Incentives to work

27 Transfer policy: Behavioral lens Delivery – How do individuals engage participation decisions? – E.g., defaults and 401(k)s Design – What problems do benefits leave in hands of recipients? – E.g., food stamps and planning problem Disincentives – How do individuals respond to program incentives? – E.g., TANF time limits and commitment

28 Trasfer Policy: Delivery Incomplete take-up on some programs – 73% enrollment in Medicaid – SCHIP: 8 to 14% in 2002 (more now) – SSI: low 60% Near complete on others – EITC – Increasingly Medicaid – Noteworthy that “nudges” played a role in the lattr

29 Transfer policy: take-up Hard to understand in standard model (Moffitt 1983) – Tansactions costs, stigma Behavioral augmentation of this model (Bertrand, Mullainathan, Shafir 2006) – Limited attention, channel factors, etc. Design consequences – Simplification: Savers’ credit, student aid – Role of third parties: Tax preparers, hospitals

30 Channel & Hassle Factors (Lewin) Bank rep. on site increases take up of bank accounts Giving college students map to health center increased number who get inoculation Long forms, lines, feeling that you don ’ t belong

31 The Traditional View of Redistribution Social programs and tagging – Find a way to transfer t such that high b (value work) types do not find useful Classic example: queuing. Useful solution to moral hazard problem because high b types will find transfer less valuable.

32 Interpreting Low Take-Up Rational model: Efficient tagging – Administrative hassles, bad information flows, stigma all serve to screen the most needy Behavioral model – Misresponse to tag τ(t) ≠ t – Procrastination and response to hassle costs – Complexity and who can see through the veil – Consequences of mistagging Most of the non-taker uppers could be behavioral Many of the takers could be high b type Particularly bad targetign

33 Evidence Revisited Section 8 voucher takeup – Takeup lowest amongst the poorest – Currie: Reeder (1985) examines the percentage of households in each income and family size class who participated in any HUD program in The highest participation rate in any of the 77 classes was less than 25 percent. For unknown reasons, the poorest households of each size have very low participation rates. Disability insurance (Benitez-Silva, Buchinsky, and Rust 2003) …28% of the SSI/DI applicants who are ultimately awarded benefits are not disabled (by their own reports to HRS), while 61% of the applicants whose applications are denied are disabled. Both errors are biggest amongst the neediest

34 Transfer policy: Screening Rational model: Efficient tagging – Costs of take-up including administrative hassles, bad information flows, stigma, etc. all serve to screen for the most needy – Classic example: queuing. Behavioral model: Inefficient tagging – No longer true that such costs deter the right group Procrastination and response to hassle costs Complexity and who can see through the veil – Consequences of inefficient tagging Most of non-taker uppers could be behavioral Many of the takers could be high type

35 Transfer Policy: Evidence Revisited Barriers might sometimes deter the neediest: Section 8 voucher – Currie: Reeder (1985) examines the percentage of households in each income and family size class who participated in any HUD program in The highest participation rate in any of the 77 classes was less than 25 percent. For unknown reasons, the poorest households of each size have very low participation rates. Disability insurance – … 28% of the SSI/DI applicants who are ultimately awarded benefits are not disabled (by their own reports to HRS), while 61% of the applicants whose applications are denied are disabled. Both errors are biggest amongst the neediest (Benitez-Silva, Buchinsky, and Rust 2003) But an empirical question: – SNAP appears to be taken up by neediest

36 Transfer Policy: Data Needed Takeaways: (1) Which model? (2) Nudging to what? Efficient screening or inefficient screening? Simple application of nudges begs some questions: – automatic enrollment in social programs: good or bad? – Depends: efficient screening or inefficient screening? – 401(k) example makes things seem simple – But we don ’ t want everyone taking up TANF Potential for breakthroughs is tangible but need more research, evidence, data Can use this data to create experimental tests of: – Efficient nudges to increase take-up of right groups.

37 Transfer policy: Design Benefits need to take a form that is useful to individuals Rational model: – Cash is best, people can smooth benefits over time, etc. – PDV of benefit really all that matters Behavioral model: – Complexity and planning – Smoothing and self-control

38 Transfer policy: Meeting Needs Food stamp example (Shapiro 2005) – Want benefits to translate to improved nutrition – Big to small problem, limits to self-control – Declining nutrition over month “Give it to us in two installments. At the end of the month I'm dying [for money]. If you got it on the 1st and 15th, or whatever, it would be so much better. Checks or coupons, it doesn't matter, either way, but it does not last a month. The second part of the month is always a struggle.”

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40 An example: meeting preferences Timing of EITC Lump sum vs. advanced Want income to translate to consumption Commitment device?

41 Disincentives Provide benefits without distorting incentives (or even while reinforcing desirable incentives) – Work incentives a particular concern Rational model: – Programs like TANF create a moral hazard – Government interests, recipient interests at odds – Create restrictions, e.g., time limits Behavioral model: – Program incentives mediated by psychology – Incentives interact with, e.g., self-control – Recipients act on incentives as construed

42 False Fear of Moral Hazard Fear of moral hazard inhibits redistribution Suppose however that b < c for most b but β(b) < c for behavioral types – Driving without a helmet – Teen pregancy Those who engage in behavior are behavioral – Transfer of min(b)-c would induce no moral hazard Note: existence of those doing it leads to misestimation of f(b) type distribution under assumption of rationality

43 Construal of Incentives Eissa and Hoynes (2004): “ A consistent and somewhat puzzling finding in the empirical literature on the EITC and labor supply is the large response of the participation decision and the lack of any response by the reported hours worked by taxpayers in the labor force. ” Some evidence that people do not understand marginal incentives: information “ induce[s] treated clients to increase their EITC refunds by choosing an earnings level closer to the peak of the EITC schedule. Clients treated by complying tax professionals are 10% less likely to have very low incomes than control group clients. ” Chetty and Saez (2009) Interesting possibility: – Assume can still work and get benefits, but do not understand marginal and therefore hours substitution – Behavioral tagging: can transfer to these types without affecting (hours) incentives

44 Behavioral Tagging Direct implication of above – Ironically bad behaviors present redistribution opportunities with little cost Must still worry about elasticity of behavioral type Note: problem is simpler if behavioral type were known to be correlated with b Then these behaviors themselves are a poverty tag – Note contrast between arbitrage for welfare benefits vs. schooling AFDC

45 Behavioral Tagging UI: – Transfers to deal with loss aversion in job search – Threat of Re-employment services Black et. al. estimate that the program reduces mean weeks of UI benefit receipt by about 2.2 weeks, reduces mean UI benefits received by about $143, and increases subsequent earnings by over $1,050. Most of the effect results from asharp increase in early UI exits in the treatment group relative to the control group. – More fine-grain incentives for inputs (resumes sent) rather than outputs Key insight: incentives can match the behavioral type

46 Benefit of Behavioral Tagging In some cases: – Transfer without fear of moral hazard – Low types are behavioral In other cases: – Undo what appears to be “moral hazard” without giving up insurance – High types are behavioral

47 Incentives and Self-Control TANF time limits – Serve as a commitment device (Fang and Silverman 2004) – Interests of policymakers and recipients align Moral hazard confounded with behavioral tendencies – Moral hazard is not the only mechanism for disincentives – Benefits can induce, indulge procrastination – Some behaviors are more likely to be evidence of behavioral tendencies than moral hazard (e.g., teen pregnancy)

48 Transfer policy: Design Need more research on demonstration projects and evidence on – Cash transfers or structured transfers? – Moral hazard or procrastination? Understanding could lead to transfer programs with much less moral hazard. – Potential for more efficient transfers. Need more research, evidence, data

49 Outline of Lecture The Welfare Challenge Integration within Public Finance Framework Broader Lessons

50 General Lessons Principles – Price mechanisms do not effectively sort – Behavioral types affect the information extraction problem government performs in sorting and incentive problems – Social return of nudges depend on the marginal type – Incentives should match the behavioral type if they are marginal Integrate behavioral insights more broadly could.. – Transform both our intuitions (about nudges) and intuitions about traditional levers Empirical Work – In these contexts, much more interesting measurement needed


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