Attitudes Towards TAXATION - PowerPoint Presentation

Slide1

Attitudes Towards TAXATION

ANANDI MANI, SHARUN MUKAND AND DANIEL SGROISlide2

Today’s Talk

Preview

Motivation I: self-serving bias and theory

Motivation II: luck vs. ability and attitudes towards taxation

Experimental Design (including screen shots)

ResultsSlide3

Preview (the idea in a nutshell)

People bias their recall to bolster their self-image.

They would rather think of themselves as hardworking than lazy: blame “bad luck” when they fail, attribute success to high effort/ability.

People are more/less sympathetic towards those who are like themselves.

To be precise: the “deserving rich” are more likely to want to see lower taxes on effort than the “lucky rich”…

…unless the “lucky rich” can fool themselves into thinking luck was not an issue when they succeeded: essentially attitudes are a function of own-experiences but crucially, also of your perceptions of what happened – and these perceptions can be biased.

We show this is true in a controlled lab environment.

And have field tests to come…Slide4

The theory of self-serving bias (SSB)

Motivation ISlide5

Memory is Malleable…

“I have done this, says my memory. I cannot have done that, says my pride, remaining inexorable. Finally – memory yields.” [Friedrich Nietzsche, Beyond Good and Evil; from B&T QJE2002]

“I

had during many years followed the Golden Rule, namely, that whenever a published fact, a new observation or thought came across me, which was opposed to my general results, to make a memorandum of it without fail and at once; for I had found by experience that such (contrary and thus unwelcome) facts and thoughts were far more apt to escape from memory than

favorable

ones.”

[Charles Darwin in The Life of Charles Darwin, by Francis

Darwin; from B&T QJE2002].Slide6

Bias in Assessing Luck vs. Ability?

"For almost two centuries, Spain has hosted an enormously popular Christmas lottery. Based on payout, it is the biggest lottery in the world and nearly all Spaniards play. In the mid 1970s, a man sought a ticket with the last two digits ending in 48. He found a ticket, bought it, and then won the lottery.” In a subsequent interview, he argued that luck had nothing to do with his choice of lottery …

and he was so intent on finding that particular number, “because” he replied, “I dreamed of the number seven for seven straight nights. And 7 times 7 is 48.”

-- Quoted in Stanley

Reisner

(1977

)

Suggestive

Evidence of a Self-Serving Bias (SSB) in

Beliefs about

reasons for

Own Success

.Slide7

Theory in a Nutshell

Put (very) simply, the idea is that we move from maximising utility by choosing actions or gambles to being able to

bias

our recall (or information set) in a way that

boosts our self-image

which forms part of our utility.

E.g. We may have had an argument yesterday (we cannot forget that fact) but we can easily “bias” our memory of whether we won the argument or not to boost our present utility.

This is a “self-serving bias” or

SSB

since the bias in memory is designed to boost our own utility.

We can also consider “

Projection Bias

” wherein you might think of others as “like yourself” – so you project your beliefs about your own situation onto others (“I got rich through hard work, you are poor, so you must have been lazy...”)Slide8

Key Papers

Key papers:

Benabou

&

Tirole

: QJE2002 “Self-confidence and personal motivation”, JPE 2004 “Willpower and personal rules”, QJE2006 “Belief in a just world and redistributive

politics”

Carillo

&

Mariotti

: REStuds2000 “Strategic ignorance as a self-discipline device”Slide9

How beliefs about the importance of luck vs. ability in life can influence attitudes towards

taxation…

Motivation IISlide10

What Shapes Attitudes

HOMO ECONOMICUS EFFECT: An individual’s attitude is a function of effect of redistribution on his net income. (linear redistributive scheme – all individuals with income less than average, will favor a higher tax rate) [Roberts, 1977; Varian, 1979]

EFFECT OF SOCIAL PREFERENCE: Individuals are endowed with a Social Preferences over resource allocations to all individuals in society (Arrow, 1963). So there need not be a direct link between level of individual income and support for redistribution.Slide11

Source of Income may affect Attitudes to Redistribution

Given Social Preferences (Efficiency, Fairness

)…

Decisions

made behind a ‘Veil of Ignorance’ need not favor high taxes (or full equality), if incentives matter for output.

If individuals think that

effort

should be rewarded, they may favor

lower taxes

.

Social Learning environment re: role of Hard work vs. Luck can also affect attitudes towards tax-spend policies –

Piketty

, (QJE 1995

).Slide12

Beliefs about Luck vs. Effort and Attitudes to Redistribution

Attitudes towards redistribution differ both within and across countries….(World Values Survey, 2001)

….

and are correlated with differences in attitudes towards taxation and spending

America

Europe

Poor

people “trapped” in poverty

29%

60%

Poor are lazy

and lack willpower

54%

30%

In the long run, hard work brings better life

59%

34-43%Slide13

Social Expenditure and Beliefs

(

Alesina

and

Glaeser

, 2001)Slide14

Reasons for Heterogeneous Beliefs re: Role of Luck vs. Effort in Life Outcomes

Different

underlying Production Functions:

Some individuals are in occupations where effort is more/less important for outcomes.

Identical

Production Function –

but Learning Bias

Due to Social Learning Environment (

Piketty

)

Due to Self-Serving Bias…

Slide15

Summing Up…

Some ways that SSB and Projection can work:

Beliefs of the Rich:

Effort/ability main driver of life income outcomes, i.e.

He/she got rich (mainly) because of own effort. (

SSB

) Other rich individuals also got rich (mainly) because of own effort. And poor are mostly lazy (

Projection Bias

)

Beliefs of the Poor:

Luck is the main driver of life income outcomes.Slide16

Related Literature

Taxation:

Piketty

and

Saez

(QJE2011), Diamond and

Saez

(JEP2011)

Attitudes towards redistribution:

Alesina

and

Glaeser

, (2001

).

Alesina

and

Angeletos

(AER2005),

Piketty

(QJE1995), Di

Tella

, et al (QJE2006); Giuliano-Spilimbergo(2009)

Psychology. Blind Bias Spot.

Pronin

(2006, 2009)Slide17

Experimental DesignSlide18

Our Questions

BEHAVIOR (Motivation I)

Do individuals have a SSB/Projection

B

ias in how they update and process information (on the role of Luck versus Ability in shaping Life outcomes)?

PUBLIC ECONOMICS (Motivation II)

What are the behavioral underpinnings of Attitudes towards Tax and Redistribution?

Slide19

Three Hypotheses

1: When choosing what tax rate to set, what you are taxing matters (luck or ability/effort).

2: When choosing what tax rate to set, your own life experiences matter (have you been lucky or displayed high ability/effort).

3: People will make use of self-serving biases when they can to bolster their self-perceptions.

Also we examine supplementary issues such as the importance of gender, background, prior political beliefs, etc.Slide20

Why the Lab?

We are hoping to produce a causal link between attitudes and choices

Moreover we are looking at a prior link between experiences/information and attitudes

The former could potentially be done in a field/survey context (albeit with loose incentives)

The later requires more control: only really feasible in a lab where we can endow people with different information and experiences (essentially gift them with luck or not)Slide21

Outline of Key Features

Individuals undertake a task that involves both “effort” and “luck” (a lottery), one of which turns out to matter.

Task completion results in a payout: they become “Rich” or “Poor”. Rich can be of two types: “Deserving” and “Undeserving” (Lucky) Rich. Poor can be of two types: “Lazy” Poor and “Unlucky” Poor.

Subjects choose Tax Rates under Two Information Treatments:

Partial

Information about sources of Own Income (Scope to deceive oneself about role of luck, depending on own outcome).

Full

Information about sources of Own Income (harder to deceive oneself).

Examine Tax rates chosen to test our hypotheses.Slide22

Timeline

Registration and log-in.

Introductory questionnaire (1)

Additions task (2): 5 minutes to add up a series of 5 2-digit numbers) and if they exceed a threshold they are allocated as HIGH effort (equivalently LOW effort).

Random Lottery (3): each subject endowed with HIGH or LOW lottery payouts with 50:50 (known) odds.

Partial or full information on their performance is revealed.

Tax choices (4): 2 screens designed to pick-up how they would tax “luck” and “effort”.

Payment and DebriefingSlide23

Logistical Details

Recruitment and registration fully anonymous.

We need a good number of subjects to cover our hypotheses (we will be comparing across subgroups)

To that end, we obtained 452 subjects in total – that is a large number for a lab experiment.

Fully

computerized on-screen terminals (complete privacy).

Fully incentivized: £5 show-up fee with the potential to win up to £20 for 45 minutes work.Slide24

(1) Questionnaire Content

Initial questions include:

Gender;

Age;

Subject/Maths ability;

“Background” (parents’ occupation, type of school – state or

p

rivate, student loan);

Political views & attitudes to luck and hard

w

ork

Brief probability question.

Slide25
Slide26
Slide27

(2) The Effort Task

Subjects have 5 minutes to undertake some simple additions questions.

Each question consists of Five 2-digit numbers, e.g.

36 + 41 + 84 + 72 + 92 = ?

Typically we saw between 5 and 20 correct additions in the pilot.

We set a threshold of around 15, above which they are categorized (by the software) as HIGH effort, below which LOW effort.Slide28
Slide29

(3) The Wealth Lottery

Subjects face a simple probability (with a prior of 50:50) that they are awarded a LOW lottery win or HIGH lottery win.

They know the density but not necessarily

their own

outcome of the lottery (depends upon their information treatment).Slide30

Rich and Poor

Total earnings follow a simple scheme:

Either the LOTTERY or ADDITIONS task is chosen at random to be the important task.

If the lottery is deemed important then subjects are allocated to be RICH if they scored HIGH in the lottery or POOR if they scored LOW.

If the additions task is deemed important then subjects are allocated to RICH if they scored above the threshold (X) and POOR otherwise.

Common Info (Prior to addition task): Payment Scheme, Distribution of threshold (X),

Expected

Distribution of Rich vs. Poor outcomes .

A sensible choice of X is based on Pilot data (varies around 15). It is not determined for sure to avoid certainty in the minds of the subjects about whether they have made it or not.Slide31

Information Treatments

Roughly half the subjects receive

Full information (FI)

about their performance, the rest

Partial Information (PI)

.

Full information (FI) includes

Wealth Lottery Outcome

Number of correct Additions

Threshold X

Outcome: Rich or Poor (pre-tax)

Partial Information (PI) includes only outcome: Rich or PoorSlide32
Slide33
Slide34

(4) Tax Preferences

All subjects asked to set a tax rate (

for the rich

) on “luck” (income if obtained via the lottery) and a tax rate on “effort” (income if obtained via the additions task).

A key variable we will examine later is the difference between the two tax rates.

One person per session randomly chosen as “tax setter” and his/her tax is used. (Subjects know this).

Two Cases (each applied in half the sessions, known to subjects):

Tax Case 1:

Chosen Tax rate is applied to

all subjects

based on their total (pre-tax) earnings. Tax Revenue is redistributed

equally

among all subjects.

Tax Case 2

: As in (1) above except the “tax-setter” is not subject to taxation or redistribution (they are instead paired with another tax-setter)

.Slide35
Slide36
Slide37

ResultsSlide38

Methodology

We have just finished collecting data so this will be a rough overview…

We will focus on the

tax-setter excluded

results (the tax-setter included are very similar except rates tend to be lower among the rich for obvious (HOMO ECONOMICUS) reasons.

The key variable of interest will be the difference between the tax rate on “luck” (the lottery tax) and on “effort” (the additions tax).

With 452 subjects we can afford to split the sample into rich/poor, or full information/partial information when required.Slide39

Hypothesis 1

Does the source of wealth of the person to be taxed matter?

Here we just need to check if tax rates are chosen to be higher for “luck” than “ability” across all possible subjects – information type does not matter here since they know for sure the source of the person being taxed; so the full sample can be used.

Easily done through eye-balling the raw averages and running t-tests.Slide40

Tax Rates (setter excluded)

Overall

Full Information

Partial Information

No. of

obs.

Addition Tax

Lottery Tax

No. of

obs.

Addition Tax

Lottery Tax

No. of

obs.

Addition Tax

Lottery Tax

Lucky Rich

108

26.3

43.4

39

29.42

40.89

29

24.8

39.8

Deserving Rich

68

19.3

40.3

47

15.28

44.28

61

23.9

42.2

RICH

176

23.6

41.5

86

23.01

42.43

90

22.7

40.5

Unlucky poor

116

43.3

69

65

50.8

72.16

51

44.9

73.9

Low effort poor

160

47.9

72.9

78

42.01

66.23

82

45.2

71.7

POOR

276

46

70.7

143

46.81

68.93

133

45.1

72.5Slide41

Interpretation

Eye-balling makes it clear that hypothesis 1 is right, and in fact the difference between tax rates is very high.

This is supported by a battery of t-tests suggesting with very high confidence that the tax on “luck” is higher than the tax on “effort/ability” across the board.

Note: this also coincides with optimal tax ideas (we should tax something that is not under our control...like “luck”) and not de-incentivize hard work.

However, while of some interest, this is not very surprising – nonetheless without this result hypotheses 2 & 3 would not make sense...Slide42

Hypothesis 2

Does own-source of income matter?

Our underlying hypothesis is that it does – and that those who

know

they got rich through effort will behave differently from those who

know

they got rich through luck.

We need to restrict the sample to those who know their source of income (the full information treatment) – which will reduce the number of observations.

Then we can regress the tax rate on effort and luck on what matters for the tax-setter’s income (luck or effort), together with any controls that seem to matter (from the questionnaire).Slide43

Regression Variables

Effort Income

: the income gained by subjects from effort (a dummy = 1 if they were “high effort” types.

Female

: gender variable (1 = female, 0 = male).

Politics

(political spectrum measure, 1-7: higher indicates more right-wing in the initial questionnaire).

Constant

: a direct measure of the average tax rate, or average difference between rates.

Finally, the number of observations reflects the different subgroups (rich vs. poor, full info only).Slide44

Regressions on The Tax Difference by Source of Income

Regression No

1

2

3

4

5

6

Sample

FI RICH

FI RICH

FI RICH

FI POOR

FI POOR

FI POOR

Effort Tax

Luck Tax

Luck Tax - Effort Tax

Effort Tax

Luck Tax

Luck Tax - Effort Tax

Inc Source is

Effort

-14.143***

3.388

17.000***

8.792

-

5.938

-13.685**

[4.213]

[

6.251

]

[6.043]

[5.436]

[5.044]

[5.664]

Female

-3.972

-14.443**

[5.829]

[5.722]

Politics

0.813

1.687

[3.190]

[2.456]

Constant

29.426***

40.894***

11.008

42.015***

72.169***

31.431***

[3.538]

[4.253]

[11.645]

[3.907]

[3.576]

[11.356]

Observations

86

86

86

143

143

143

R-squared

0.11

0.00

0.11

0.02

0.01

0.1

Robust standard errors in brackets; * sig at 10%; ** sig at 5%; *** sig at 1%Slide45

Interpretation

Powerful support for hypothesis 2 coming from the

rich

:

The rich who got rich through effort are significantly more generous when setting the effort tax – pulling down the rate by over 14%.

The difference (luck – effort) widens for the high effort rich – though the affect is coming through the effort tax rate falling not the luck tax rate rising.

The results from the

poor

are exactly opposite (which again confirms hypothesis 2).

Gender matters

: females seem to care about ex post inequality regardless of income source as compared to males.

Political stance unimportant.Slide46

Hypothesis 3

To what extent to people self-delude when forming their attitudes?

The key here is to compare the partial vs. full information treatments.

Do those who do not know why they were successful behave differently from those who do – and do they do so in a direction that suggests self-serving biases are in place.

We can eyeball the original table to see something interesting is in place and then confirm with some regressions.

The controls from the questionnaire also suggest some interesting gender effects, as well as a role for political leanings and private schooling.Slide47

New Regression Variables

Full Info

: Set equal to 1 if they were in the FI treatment.

Interaction

: Set equal to 1 only if their income source was “effort” (the additions task) and they knew it (FI treatment).Slide48

Regressions on

The Tax Difference by Information

Regression No

7

8

9

10

Sample

FI & PI RICH

FI & PI RICH

FI & PI POOR

FI & PI POOR

Luck Tax - Effort Tax

Luck Tax - Effort Tax

Luck Tax - Effort Tax

Luck Tax - Effort Tax

Inc Source is

Effort

1.51

0.459

-2.595

-1.615

[5.795]

[5.350]

[6.327]

[6.109]

Female

-5.419

-14.042***

[4.031]

[4.233]

Politics

-4.032*

3.236*

[2.103]

[1.840]

Full Information

-4.401

-4.288

1.095

0.154

[5.015]

[5.025]

[6.722]

[6.600]

Interaction

16.021*

17.310**

-12.135

-11.776

[8.201]

[7.998]

[8.544]

[8.318]

Constant

15.869***

34.600***

29.059***

24.883***

[3.432]

[8.790]

[5.009]

[9.012]

Observations

176

176

276

276

R-squared

0.06

0.08

0.03

0.08Slide49

Interpretation

Again,

support for hypothesis 3

(SSBs matter):

A significant interaction term indicates that if I am “deserving” rich and I know it I become more sympathetic towards the rich who obtained their income through effort.

Again, significance falls off on the poor – which makes sense (the taxes are on the rich, not the poor, so “projection” is less relevant here) – but the signs make sense (if I find out I am a low-performing poor then I am not especially sympathetic towards the rich who obtained their income through effort).

Gender

again is important but now so too is

political leaning

: the more right wing (or female) I am the more I want to shrink the gap between tax rates if I am rich. If I am poor this reverses for the right wing, so they become keener on being relatively tough (lenient) on luck (effort).Slide50

ConclusionsSlide51

Results Summary

People tax luck more heavily than effort/ability.

Own source of income matters – the lucky rich are much more lenient towards those others who get rich through luck (remember they are not subject to the tax themselves…), and the high effort rich are much more sympathetic towards those who get rich through effort.

SSB seems very powerful among the rich, with those who know they are lucky much more lenient than those who are not so sure – suggesting self-delusion is in place.Slide52

Interesting Insights

Much of the work is being driven by the rich, but that makes sense (the poor are not being taxed so projection is less of an issue).

While we focus on the difference between luck and effort taxes, much of the movement is in terms of the effort tax.

Gender matters with females having a different notion of fairness (what matters is ex post inequality, less so source of income).Slide53

Next Steps

This matters for so much within Economics including political economy (voting theory), information economics, public economics and of course it changes how we think about the politics of taxation…

But we need to do much more...

More econometrics (so much more to check!), including a more thorough analysis of the questionnaire data (e.g. cultural background).

The next stage in the project will be to take to the field with a survey and look at how real-life shocks affect attitudes: work on this has already begun.Slide54

Many thanks!