econ 230b { graduate public economics tax evasion gabriel...
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Roadmap
1. The size of tax evasion
2. Why do people evade?
3. The supply side of evasion services
2
1 The size of tax evasion
Most models of optimal taxation assume away enforcement issues. Inpractice:
• Enforcement is costly for government (administration) and privateagents (compliance)
• Substantial tax evasion, eg in countries with high self-employment,at top of the wealth distribution, and in businesses
• Two widely used surveys: Andreoni, Erard, Feinstein (JEL 1998);Slemrod and Yitzhaki (Handbook of PE, 2002)
3
Measuring tax evasion with randomized audit studies
Widely used source to study tax evasion: statified random audits
• In the US: IRS conducts thorough audits of stratified sample of taxreturns periodically → National Research Program (NRP)
• Other countries have similar programs, e.g., Denmark (Kleven etal., Econometrica 2011)
• Important for policy (optimal audit strategy) & economic statistics(estimates of unreported income used in national accounts)
4
Tax gap in the United States
Results from latest wave of NRP studies for years 2008, 2009, 2010:
• Tax gap (= taxes evaded / taxes owed) around 16% in total
• No clear trend over time
• Tax gap concentrated among income items with no 3rd partyreporting (such as self-employment income)
•Withholding reduces tax gap (liquidity constraint → sometaxpayers can never pay taxes owed unless withheld at source)
5
Tax Gap Estimates for Tax Years 2008–2010: Attachment 1
Internal Revenue Service | April 2016 3
Tax Gap MapTax Year 2008-2010 Annual Average ($ Billions)
Internal Revenue Service, April 2016
Categories of Estimates
#
Actual Amounts Updated EstimatesNo Estimates Available
IndividualIncome Tax
$26
Individual Income Tax $264Non-Business
Income$64
Business Income$125
Credits$40
Filin
g St
atus
$5
IndividualIncome Tax
$29
IndividualIncome Tax
$319
IndividualIncome Tax
$28
IndividualIncome Tax
$291+ + = =̵
CorporationIncome Tax
#+
Corporation Income Tax $41Small
Corporations$13
LargeCorporations
$28
CorporationIncome Tax
$3
CorporationIncome Tax
$44
CorporationIncome Tax
$9
CorporationIncome Tax
$35+ = =̵
Self-Employment
Tax$4
+Employment Tax $81
FICA Withholding
$15Self-Employment Tax
$65 Une
mpl
oy-
men
t
$1
EmploymentTax$6
EmploymentTax$91
EmploymentTax$12
EmploymentTax$79
+ = =̵
EstateTax$2
Estate Tax
$1+
EstateTax$1
EstateTax$4
EstateTax$3
EstateTax$1
+ = =̵Excise
Tax#
+Excise
Tax
#
ExciseTax$0.4
ExciseTax0.4
ExciseTax$0.2
ExciseTax$0.2
+ = ̵ =
+ = =̵+Nonfiling
Tax Gap$32
Under-payment Tax Gap
$39
Underreporting Tax Gap$387
Net Tax Gap(Tax Not
Collected)
$406
Gross Tax Gap
$458
Enforced & Other
Late Payments
$52
Una
lloca
ted
Mar
gina
l E
ffect
s
Oth
er
Taxe
s
$1
IncomeOffsets
$19 $12
Detail may not add to total due to rounding . Not to scale.
True Tax Liability $2,496
By Type of Tax
Tax Eventually Collected $2,090Net Tax Gap $406
Tax Paid Voluntarily and Timely $2,038Gross Tax Gap $458 Voluntary Compliance Rate= 81.7% of tax liability( )
( )Net Compliance Rate= 83.7% of tax liability
6
Tax Gap Estimates for Tax Years 2008–2010: Attachment 3
Internal Revenue Service | April 2016 5
Figure 1. Effect of Information Reporting on Individual Income Tax Reporting Compliance, Tax Years 2008–2010
7
Detection controlled estimation (DCE)
How is the gap tax estimated?
• If all evasion is detected in random audits, then income unreportedY1i could be studied using following Tobit model:
Y1i =
{Y ∗1i if Y ∗1i > 0
0 if Y ∗1i 6 0
•Where Y ∗1i = X1iβ1 + ε1i latent var measuring propensity to evade
• Problem: only fraction of evasion is detected (auditors miss some)
8
To estimate undetected evasion, IRS uses DCE model (Feinstein ’91)
• Consider Y2i the extent of detection on return i (cond. onY1i > 0)
Y2i =
1 if Y ∗2i > 1 (complete detection)
0 if Y ∗2i 6 0 (no detection)
Y ∗2i if 0 < Y ∗2i < 1 (detection of fraction Y ∗2i of evasion)
•Where Y ∗2i = X2iβ2 + ε2i is latent variable measuring fraction ofevasion detected (cond. on evasion happening)
•X2i: examiner’s experience, complexity of the return, etc.9
Feinstein (1991) estimates this model using ML and finds a lot ofevasion goes undetected in IRS random audit studies:
• Intuition: some examiners find more evasion → if all examinerswere like them, total evasion would be 3 × detected evasion
• But results very sensitive to parametric assumptions (correlationbetween ε1i and ε2i) [examiners not randomly assigned]
• Absolute detection rates are not identified (can’t know whetherthe best examiner captures 100% or less than evasion)
Based on DCE, IRS × detected evasion by 3. Uncertain.
10
2 Why do people evade taxes?
Seminal model: Allingham and Sandmo (JpubE 1972)
• Individual taxpayer problem:
maxw̄
(1− p) · u(w − τ · w̄) + p · u(w − τ · w̄ − τ (w − w̄)(1 + θ))
• where w is true income, w̄ reported income, τ tax rate, pprobability to be caught evading, θ fine factor, u(.) concave
• Let cuncaught = w − τ · w̄
• ccaught = w − τ · w̄ − τ (w − w̄)(1 + θ)11
• FOC in w̄: −τ (1− p)u′(cuncaught) + pθτu′(ccaught) = 0
u′(ccaught)
u′(cuncaught)=
1− ppθ
• Key result: evasion w − w̄ ↓ with p and θ (Yitzhaki, 1987)
• Proof: differentiate FOC with respect to p, θ and w̄
• No effect of marginal tax rate on evasion if linear penalty, lineartaxation & risk-neutrality
• In more general model, substitution effect of the marginal tax rateon evasion is theoretically ambiguous
12
Why is tax evasion so low in OECD countries?
Puzzle: US has low audit rates (p = .01) and fines (θ ' .2). Withreasonable risk aversion (say CRRA γ = 1), tax evasion should bemuch higher than observed.
Two types of explanations:
• Unwilling to cheat: Social norms and morality [people dislike beingdishonest] (Luttmer and Singhal, 2014)
• Unable to cheat: Probability of being caught is much higher thanobserved audit rate because of 3rd party reporting
13
Determinants of tax evasion
Large literature studies tax evasion levels and effect of tax rates,penalties, audit proba, prior audit experiences, socio-economic charac.
Early literature relies on observational [non-experimental] data whichcreates serious identification and measurement issues:
• Evasion is difficult to measure
•Most independent variables [audits, penalties, etc.] are endogenousresponses to evasion and also difficult to measure
→ Recent literature uses random audits and/or field experiments
14
Kleven et al. (Ecometrica 2011)
• Large stratified random sample (40,000 taxpayers audited)
• Very low rates of detected evasion: macro tax gap about 2.5%
• But evasion rate for self-reported items is almost 40%, evasionrate for third party reported items is only 0.3%
• Tot evasion very low because 95% of income is 3rd-party-reported
• Information trumps social & economic factors:Evadei = α+βSelf ReportedIncomei+γSocialFactorsi+εi
15
Determinants of the Probability of Audit Adjustment:Social, Economic, and Information Factors
Social factors Socio-
economic factors
Information factors All factors
Constant 14.42 (0.64) 11.92 (0.66) 1.44 (0.25) 3.98 (0.62)Female -5.76 (0.43) -4.45 (0.45) -2.05 (0.41)Married 1.55 (0.46) -0.36 (0.48) -1.64 (0.44)M b f h h 1 98 (0 59) 2 67 (0 58) 1 19 (0 54)Member of church -1.98 (0.59) -2.67 (0.58) -1.19 (0.54)Copenhagen -0.29 (0.67) 1.20 (0.67) 1.00 (0.62)Age above 45 -0.37 (0.45) -0.35 (0.45) 0.10 (0.42)Home owner 5.96 (0.48) -0.35 (0.46)Home owner 5.96 (0.48) 0.35 (0.46)Firm size below 10 4.43 (0.82) 2.97 (0.76)Informal sector 3.25 (0.86) -0.99 (0.79)Self-Reported Income 9.47 (0.53) 9.72 (0.54)Self-Reported Income > 20K 17.46 (0.91) 17.08 (0.92)Self-Reported < -10K 14.63 (0.72) 14.53 (0.72)Audit Flag 15.48 (0.59) 15.32 (0.60)
R-square 1.1% 2.1% 17.1% 17.4%Adjusted R-square 1.0% 2.1% 17.1% 17.4%
Source: Kleven et al. (2010)
16
02
46
Den
sity
0 .5 1 1.5Ratio Evaded Income / Self-Reported Income
A. Histogram Evaded Income/Self-Reported Income
0.2
.4.6
.81
Eva
sion
rate
0 .2 .4 .6 .8 1Fraction of income self-reported
45 degree lineFraction evadingFraction evaded (evaders)Third-party evasion rate
B. Evasion by Fraction Income Self-Reported
Figure 3. Anatomy of Tax Evasion Panel A displays the density of the ratio of evaded income to self-reported income (after audit adjustment) among those with a positive tax evasion, using the 100% audit group and population weights. Income is defined as the sum of all positive items (so that self-reported income is always positive). Panel A shows that, among evaders, the most common is to evade all self-reported income. About 70% of taxpayers with positive self-reported income do not have any adjustment and are not represented on panel A. Panel B displays the fraction evading and the fraction evaded (conditional on evading) by deciles of fraction of income self-reported (after audit adjustment and adding as one category those with no self-reported income). Panel B also displays the fraction of third-party income evaded (unconditional). Income is defined as positive income. In both panels, the sample is limited to those with positive income above 38,500 kroner, the tax liability threshold (see Table 1).
17
0%
5%
10%
15%
20%
25%
30%
Nor
way
Ic
elan
d S
wed
en
Japa
n Lu
xem
bour
g D
enm
ark
Finl
and
Fran
ce
Irela
nd
Lith
uani
a B
elgi
um
Est
onia
U
nite
d K
ingd
om
Aus
tria
Net
herla
nds
Ger
man
y S
pain
H
unga
ry
Uni
ted
Sta
tes
Slo
veni
a C
zech
Rep
ublic
S
witz
erla
nd
Latv
ia
Por
tuga
l Ita
ly
Slo
vak
Rep
ublic
Tu
rkey
P
olan
d G
reec
e
The share of self-employment income in GDP in OECD countries (Gross mixed income as a % of factor-cost GDP)
18
The effect of marginal tax rates on evasion
• Kleven et al. (2011) also provide quasi-experimental causal effectsof marginal tax rates on evasion
• Use bunching evidence before and after audit
• Find most bunching not due to evasion but avoidance → effect ofMTR on evasion is modest
• Information reporting is much more important than low marginaltax rates to achieve enforcement
19
Bunching at the Top Kink in the Income Tax
400
A. Self-Employed
300
yers
200
ber o
f tax
pay
100Num
b0
200000 300000 400000 500000Taxable Income
Before Audit After Audit
Source: Kleven et al. (2010) 20
Bunching at the Kink in the Stock Income Tax
200
B. Stock-Income
150
yers
100
ber o
f tax
pay
50Num
b0
50000 100000 150000Stock Income
Before Audit After Audit
Source: Kleven et al. (2010) 21
3 The supply of evasion services
Tax evasion at the top
Hard to study with random audits:
• Small number of rich individuals sampled
• Hard to detect complex evasion involving intermediaries
→ Random audits need to be supplemented with other sources tocapture evasion by the wealthy
22
Data to capture evasion by the wealthy
•Macro statistics on wealth held in tax havens (Zucman QJE 2013)
• Tax amnesties (eg, offshore voluntary disclosure program in theUS: Johannesen et al. 2018)
• Leaks from providers of tax evasion services: Panama Papers,Swiss leaks, offshore leaks, etc. (Alstadsæter et al. AER 2019)
23
Alstadsæter et al. (AER 2019)
HSBC Switzerland leak (2007):
• Large bank (≈ 5% of Swiss offshore wealth)
• Representative
• Recorded identity of beneficial owners
• Clear-cut way to identify evasion by linking to tax returns of clients→ linking done in Scandinavia
24
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
P90-P95 [0.6 – 0.9]
P95-P99 [0.9 – 2.0]
P99-P99.5 [2.0 – 3.0]
P99.5-P99.9 [3.0 – 9.1]
P99.9-P99.95 [9.1 – 14.6]
P99.95-P99.99 [14.6 – 44.5]
Top 0.01% [> 44.5]
Net wealth group [millions of US$]
Probability to own an unreported HSBC account, by wealth group (HSBC leak)
Source: Alstadsæter (2019)
25
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
P90-P95 [0.6 – 0.8]
P95-P99 [0.8 – 1.8]
P99-P99.5 [1.8 – 2.7]
P99.5-P99.9 [2.7 – 8.1]
P99.9-P99.95 [8.1 – 13.3]
P99.95-P99.99 [13.3 – 41.4]
Top 0.01% [> 41.4]
Net wealth group [millions of US$]
Probability to appear in the "Panama Papers", by wealth group (Shareholders of shell companies created by Mossack Fonseca)
Source: Alstadsæter (2019)
26
0%
2%
4%
6%
8%
10%
12%
14%
P90-P95 [0.6 – 0.8]
P95-P99 [0.8 – 1.8]
P99-P99.5 [1.8 – 2.7]
P99.5-P99.9 [2.7 – 8.1]
P99.9-P99.95 [8.1 – 13.3]
P99.95-P99.99 [13.3 – 41.4]
Top 0.01% [> 41.4]
Net wealth group [millions of US$]
Probability to voluntarily disclose hidden wealth, by wealth group (Swedish and Norwegian tax amnesties)
Source: Alstadsæter (2019)
27
0%
10%
20%
30%
40%
50%
60%
P0-50 P50-P90 P90-P99 P99-P99.9 P99.9-99.99 P.99.99-P100
% o
f tot
al re
cord
ed o
r hid
den
wea
lth
Position in the wealth distribution
Distribution of wealth: recorded vs. hidden
Hidden wealth disclosed in amnesty
Hidden wealth held at HSBC
All recorded wealth
Source: Alstadsæter (2019)
28
0%
5%
10%
15%
20%
25%
30%
P0-
10
P10
-20
P20
-30
P30
-40
P40
-50
P50
-60
P60
-70
P70
-80
P80
-90
P90
-95
P95
-99
P99
-99.
5
P99
.5-9
9.9
P99
.9-P
99.9
5
P99
.95-
P99
.99
P99
.99-
P10
0
% o
f tax
es o
wed
that
are
not
pai
d
Position in the wealth distribution
Taxes evaded, % of taxes owed
Offshore evasion (leaks)
Tax evasion other than offshore (random audits)
Source: Alstadsæter (2019)
29
Alstadsæter et al. (2019): model
Why high evasion rates at the top? Impossible to understand in ASmodel (= demand side). Need to study the supply
• Population of mass one with wealth density f (y)
•Monopolistic bank sells tax evasion services (historically, Swissbanks have operated as a cartel), charges θ per $ of wealth hidden
• Infinitely elastic demand at price θ: bank optimizes on # of clients
•Manages k(s) in wealth when serves s = 1− F (y) and earnsθk(s) in revenue
30
Bank has probability λs to be caught → fine φk(s)
Risk-neutral bank maximizes profits
π(s) = θk(s)− λsφk(s)
At interior optimum:
θ =
(1
εk(s)+ 1
)φλs
•Where εk(s) = sk′(s)/k(s) is elasticity of the amount of hiddenwealth managed with respect to s
31
If wealth Pareto-distributed, supply of evasion services is:
s =θ
(1 + b)λφ
• b is the inverted Pareto-Lorenz coefficient (high b → highinequality)
Higher λ or higher φ → fewer & richer clients
If high inequality, bank will serve tiny fraction of the pop.
32
Policies to curb tax evasion
• Increase detection probability λ: third-party reporting (but can bedifficult to enforce internationally: need to learn from Fatca)
• High fines for suppliers (φ): shrinks the supply of evasion services
•More practical than high fines for evaders, but “too big to indict”problem
• Tax evasion: increasingly a financial regulation problem?
33
0%
10%
20%
30%
40%
50%
60%
70%
1982 1986 1990 1994 1998 2002 2006 2010
% o
f Sw
iss
acco
unts
am
ount
s Accounts held through
sham corporations
Accounts directly held by Europeans
EU Saving Tax
Directive
Source: Zucman (2015)
34
References
Allingham, M. and A. Sandmo “Income tax evasion: a theoretical analysis”, Journal of Public
Economics, Vol. 1, 1972, 323-338. (web)
Alstadsæter, Annette, Niels Johannesen and Gabriel Zucman, “Tax Evasion andInequality”, American Economic Review, 2019 (web)
Alstadsæter, Annette, Niels Johannesen and Gabriel Zucman, “Who Owns the Wealth in Tax
Havens? Macro Evidence and Implications for Global Inequality”, Journal of Public Economics, 2018
(web)
Andreoni, J., B. Erard and J. Feinstein “Tax Compliance”, Journal of EconomicLiterature, Vol. 36, 1998, 818-60. (web)
Cowell, F. Cheating the Government: The Economics of Evasion (MIT Press, Cambridge, 1990).
Feinstein, Jonathan S., “And econometric analysis of tax evasion and its detection”, Rand Journal of
Economics, 1991
35
IRS, “Tax Gap Estimates for Tax Years 2008?2010”, 2016 (web)
Johannesen, Niels and Gabriel Zucman “The End of Bank Secrecy? An Evaluation of the G20 Tax
Haven Crackdown,” American Economic Journal: Economic Policy, 6(1), 2014. (web)
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paper, 2018 (web)
Kleven, H., M. Knudsen, C. Kreiner, S. Pedersen, and E. Saez “Unwilling or Unableto Cheat? Evidence from a Randomized Tax Audit Experiment in Denmark”,Econometrica 79(3), 2011, 651-692. (web)
Kleven, H. C. Kreiner, and E. Saez “Why Can Modern Governments Tax So Much? An Agency
Model of Firms as Fiscal Intermediaries”, Economica, 2016. (web)
Luttmer, Erzo F. P. and Monica Singhal (2014) “Tax Morale”, Journal of Economic Perspectives
28(4), 149–168. (web)
Omartian, Jim “Tax Information Exchange and Offshore Entities: Evidence from the Panama
Papers”, working paper 2017
36
Slemrod, Joel. 2007. “The Economics of Tax Evasion,” Journal of Economic Perspectives, 21(1),
25–48.
Slemrod, J. and S. Yitzhaki “Tax Avoidance, Evasion and Administration”, in A. Auerbach and M.
Feldstein (eds.), Handbook of Public Economics, Vol. 3 (Amsterdam: North-Holland, 2002),
1423-1470. (web)
Yitzhaki, “On the Excess Burden of Tax Evasion”, Public Finances Quarterly 1987
Zucman Gabriel, “The Missing Wealth of Nations: Are Europe and the US net Debtors or net
Creditors?”, Quarterly Journal of Economics 2013, (web)
Zucman, Gabriel, “Taxing Across Borders: Tracking Personal Wealth and Corporate Profits”,
Journal of Economic Perspectives, 2014 (web)
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