antoine bozio master ape and ppd paris { october 2019 · lecture 6: labour income taxation (1)...
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Lecture 6: Labour income taxation (1)
Antoine Bozio
Paris School of Economics (PSE)
Ecole des hautes etudes en sciences sociales (EHESS)
Master APE and PPDParis – October 2019
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Labour income taxation
1 Do tax cut pay for themselves ?• Are we above the Laffer curve ?
2 How much can we tax the rich ?• Do high taxes on top incomes soak the rich or make
everyone worse off ?
3 How to redistribute to the poor ?• Do benefits lead to poverty traps ?• Does workfare works ?
4 Should we introduce basic income/flat tax ?• Is it utopia, nightmare or the future of tax design ?
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Outline of the lecture 6
I. Incidence
1 Theory2 Empirical estimates
II. Labour supply responses
1 Structural labour supply estimates2 Quasi-experimental labour supply estimates3 Macro vs micro estimates
III. Elasticity of taxable income
1 Early studies2 Recent studies
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Outline of the lecture 7
IV. Optimal tax and transfer system
1 Tagging2 Mirrlees model3 Optimal transfer system
V. Policy : Taxing top incomes
1 Measuring top incomes ETI2 International mobility
VI. Policy : Transfer to the poor
1 Traditional welfare2 EITC – bunching3 Take-up of benefits
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History of income taxation• Antiquity/Middle Age
• Labour income is self-employment (or slavery)• Direct taxation is foremost taxation of property• Taxation of commercial/industrial activities
• Collective tax bases• Tax evaluated at local/city level : needs to be paid by
collectivity without individual assessmente.g., taille in France
• “Tax farming” : government sells the right to collect taxesto private collectors
• Head tax, poll tax or capitation• Tax paid by every household irrespective of income• Louis XIV introduced capitation in France in 1685 varying
with social class (Guery, 1986)e.g., 2000 pounds for 1st class, 1 pound for lower class
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History of income taxation
• First attempts at general income taxation (18th c.)• First discussion about measurement of national income• Attempts at general income taxation (Touzery, 1994)
e.g., taille tarifee in France in 1715
• Schedular income tax (19th c.)• Different tax schedule by type of income
e.g., land, farming, trades, pensions, etc.• Income tax, a British invention :
• 1799 income tax by PM William Pitt the Younger• 1803 income tax by PM Henry Addington• 1842 income tax with PM Robert Peel
• France income tax on capital income (impot sur le revenudes valeurs mobilieres) in 1872
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History of income taxation
• First modern income tax• 1891 in Prussia• 1909 in the U.K.• 1913 in the U.S. (Mehrotra, 2013)• 1914 in France (Piketty, 2001 ; Delalande, 2011)
• Comprehensive and progressive• Comprehensive : all income sources taxed in the same tax
schedule• Progressive : only on top incomes• But small : top marginal tax rates at 3%
• Large increases with war efforts• WWI : top rates reached 40% to 70%• WWII : top rates reached 70% to 97%
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Figure 1 – Top marginal tax rates (1900-2013)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Mar
gina
l tax
rat
e ap
plyi
ng to
the
high
est i
ncom
esU.S.
U.K.
Germany
France
Source : Piketty (2013), Fig. 14.1
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Types of labour income taxation
1 Income tax• Taxation of labour and capital income• Progressive tax : increasing average tax rate
2 Social Security contributions (SSCs)• Confer entitlement to receive a future social benefit• Taxation of earnings (not capital income)• Nominally split between employee and employers• Usually capped at threshold
3 Means-tested benefits• Assessed at household level• Child benefits, housing benefits, minimum income, etc.• Analysis similar to labour taxation
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Figure 2 – Income tax as a % of GDP, 1990–2017
0
5
10
15
20
25
30
35
40
1990 1995 2000 2005 2010 2015
Sh
are
of
GD
P (
in p
erc
en
tag
e)
Canada Denmark France Germany Italy
Mexico Sweden U.K. U.S.
Source : OECD.Stat
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Figure 3 – Income tax as a % of GDP, 1990–2017
0,0
1,0
2,0
3,0
4,0
5,0
6,0
7,0
8,0
9,0
10,0
1990 1995 2000 2005 2010 2015
Sh
are
of
GD
P (
in p
erc
en
tag
e)
Argentina Brazil Cameroon Egypt Indonesia
Source : OECD.Stat
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Figure 4 – Income tax as a share of GDP (1914-2014)
0%
2%
4%
6%
8%
10%
12%
14%
16%
1914 1924 1934 1944 1954 1964 1974 1984 1994 2004 2014
Pe
rce
nta
ge
of
GD
PUnited Kingdom
United States
France (IR, CSG and CRDS)
France (IR)
Source : Andre and Guillot, IPP Briefing Note, No. 12, 2014.
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Figure 5 – Share of household paying income tax (France)
0%
10%
20%
30%
40%
50%
60%
70%
1914 1924 1934 1944 1954 1964 1974 1984 1994 2004 2014
En
po
urc
en
tag
e d
u n
om
bre
de
fo
ye
rs
Source : Andre and Guillot, IPP Briefing Note, No. 12, 2014.
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Figure 6 – Social Security Contributions as a % of GDP,1965–2014
0
2
4
6
8
10
12
14
16
18
20
1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
FRANCE
US
UK
OECD
GERMANY
JAPAN
Source : OECD.Stat14 / 131
Figure 7 – Employer SSCs as a % of GDP, 1965–2014
14
12 FRANCE
10
8
6 GERMANY
JAPAN
4
OECDJAPAN
4
US
UK
2
0 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
Source : OECD.Stat
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Mean-tested benefits
• Negative average taxation• Benefits similar to tax credit• Negative tax payment
• Marginal tax rates• Means-testing means that additional euro earned is tax
awaye.g., 100% taper rate = 100% MTR
• Common to find high MTR in benefit design
• Budget constraints• Representation of disponible income by hours worked• Slope is 1-MTR
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Figure 8 – Budget constraint for French single earner (2014)
0
500
1000
1500
2000
2500
0% 50% 100% 150% 200%
Dis
po
sib
le in
com
e (
mo
nth
ly e
uro
s)
Labour income pre tax and benefits (as a fraction minimum wage)
Wage (net of tax)
Income support
Income tax
Working tax credit (PA)
Housing benefits
Disposible income
Source : Ben Jelloul, Bozio, Cottet and Fabre, IPP, April 2017.
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Figure 9 – Benefits for U.S. single earner and two children (2008)
Source : Maag, E., Steuerle, E., Chakravarti, C., and Quakenbush, C. (NTJ, 2012),
Fig. 1.
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I. Incidence
1 Conceptual Framework
2 Empirical evidence for• SSCs• benefits• income tax
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Conceptual Framework
• Standard general equilibrium model of tax incidence withcompetitive markets (Feldstein, 1974)
• Labour demand• Production function F (.) is assumed to be homogeneous of
degree one with two types of workers T and C .• labor cost : zk = wk(1 + τk)
wk : posted wageτk : payroll tax rate on employers
• σ : elasticity of substitution between workers
• Labour supply with tax benefit linkage• wk ≡ wk(1 + qτk) the perceived wage of workers of type k• q : extent to which employees value employer contributions• ηS : elasticity of labor supply
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Pass-Through Formula
• Pass-through ρ of employer SSCs to the wage oftreated workers relative to control workers
ρ =d ln
(wT
wC
)d ln (1 + τT )
≈ −σ + ηS · qσ + ηS
• Three polar cases :
(1) Full linkage (q = 1) ⇒ full shifting to workers (ρ ≈ 1)(2) No linkage (q = 0) and σ � ηS ⇒ full shifting (ρ ≈ 1)
(3) No linkage (q = 0) and ηS � σ ⇒ no shifting (ρ ≈ 0)
Case (2) is the usual assumptions in the laborsupply/elasticity of taxable income literature
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Figure 10 – Incidence with tax-benefit linkage
Wage rate
L0
Supply S(p)
Demand D(p)
wE0
Labour supply
0
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Figure 11 – Incidence with tax-benefit linkage
Wage rate
L0
Supply S(p)
D(p+t)
Demand D(p)
W1
L 1
w
SSCs increase
E0
Labour supply
E1
0
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Figure 12 – Incidence with tax-benefit linkage
Wage rate
L0
W
Supply S(p)
D(p+t)
Demand D(p)
W1
L 1
w
SSCs increase
E0
E2
Labour supply
E1
0
L2
benefit value
2
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Empirical estimates : SSC
• Textbook view• “knowledge of statutory incidence tells us essentially
nothing about who really pays the tax” (Rosen, 2002)• “payroll taxes are borne fully by workers” (Gruber, 2007)
• But relatively little empirical evidence to date
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Empirical estimates : SSC
• Macro evidence• Labour income shares fairly stable• Cross-country studies (Brittain, 1971 ; OECD, 1990 ;
Tyrvainen, 1995 ; Alesina and Perotti, 1997 ; Daveri andTabellini, 2000 ; Nunziata, 2005 ; Ooghe et al, 2003)
• Early micro studies• Hamermesh (1979) ; Neubig (1981) ; Holmlund (1983)
• Quasi-experimental studies• Gruber (1994) : Mandated maternity benefits• Anderson and Meyer (1997, 2000) : US UI• Bennmarker et al. (2009), Korkeamaki (2011) ; Lehmann et
al (2013) : reductions in SSCs
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Empirical estimates : SSC
• Gruber (JOLE, 1997)• Chile privatized its public pension system in 1981• Large cut in SSCs• Expected increase in private pension savings
• Methodology• Time-series and cross-section estimation• Use firm data and firm-level SSC change
• Results• No employment effect and full-shifting of SSCs to wages
(i.e., wage increase of similar magnitude to drop in SSC)
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Gruber (JOLE, 1997)• Difference Specification
∆log(Wijt/Eijt) = a + b1∆tijt + eijt
Table 1 – Coefficient on Contributions/Wages inCross-Sectional Regressions
Pooled Blue-collar White-Collar
Wages Employment Wages Employment Wages Employment
Basic difference -1.120 0.008 -0.899 0.190 -1.350 -0.183(0.099) (0.106) (0.108) (0.130) (0.172) (0.170)
DDD -1.022 -0.113(0.180) (0.165)
N 6,066 6,066 3,298 3,298 2,768 2,768
Source : Gruber (1997), Tab. 3., p. S95.
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Empirical estimates : SSC
• Saez et al. (QJE, 2012)• Greece has high SSC rates (28% employer, 16% employee)• Reform led to different SSC schedule for adjacent cohort• Uncapping of SSC for new entrants in Oct. 1992
• Methodology• RDD approach based on date of entry• Estimate long-run incidence effects• Use administrative data from Greek social insurance
• Results• No labour supply effect (intensive and extensive)• Incidence of SSCs similar to nominal incidence (i.e.,
employer SSCs fall on employers, employee SSCs fall onemployees)
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Saez et al. (2012) – Greece
Figure 13 –
Sources : Saez et al (2012). 30 / 131
Saez et al. (2012) – Greece
Figure 14 –
Sources : Saez et al (2012).
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Saez et al. (2012) – Greece
Figure 15 –
Sources : Saez et al (2012).
32 / 131
Empirical estimates : SSC
• Saez et al. (AER, 2019)• Swedish reform : cut to employer SSCs for workers below
age 25
• Methodology• RDD approach based on age• Estimate long-run incidence effects• Use administrative data from Swedish social insurance
• Results• Large impact on employment• No shifting at individual level to wages (100% pass-through
to firms)• Some evidence of shifting at firm level
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Saez et al. (2019) – Sweden
Figure 16 – Monthly net wage
Sources : Saez et al (2019).34 / 131
Saez et al. (2019) – Sweden
Figure 17 – Monthly labour cost (including employer SSCs)
Sources : Saez et al (2019). 35 / 131
Saez et al. (2019) – Sweden
Figure 18 – Employment impact
Sources : Saez et al (2019).
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Saez et al. (2019) – Sweden
Figure 19 – Net wage on firms with high share of young
Sources : Saez et al (2019).
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Empirical estimates : SSC
• Bozio, Breda and Grenet (2019)• Exploit three uncapping reforms in France• Different tax-benefit linkage
• Methodology• DD approach based on pre-reform earnings w.r.t threshold• Estimate long-run incidence effects• Use administrative data (DADS data)
• Results• Incidence of SSC on employers for reforms with no
tax-benefit linkage• Incidence of SSCs on employees in reform with strong
tax-benefit linkage
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Figure 20 – Marginal Employer SSC Rates, Non-Executives,1976–2010
+9.5 ppts
+8.2 ppts
+7.8 ppts
Reform 3Uncappingof heathSSCs
Reform 2Uncappingof familySSCs
Reform 1Increasein pensionsSSCs
0.0
0.1
0.2
0.3
0.4
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Year
Under SST1 to 3 SST
Sources : IPP Tax and Benefit Tables (April 2016 ; TAXIPP 0.4)
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Figure 21 – Reform 1 : log(z) vs log(w)
-.02
-.01
0.0
1.0
2
-3 -2 -1 0 1 2 3 4 5 6 7 8 9Years since reference year
Hourly labour costGross hourly earnings
Sources : Bozio et al. (2018).
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Figure 22 – Reform 1 : Pass-Through Rate on Workers – w –with trends
-1.0
-0.5
0.0
0.5
1.0
1.5
0 1 2 3 4 5 6 7 8 9Years since reference year
Estimate95% CI
Sources : Bozio et al. (2018).41 / 131
Figure 23 – Reform 2 : log(zh) vs log(wh)
-.02
-.01
0.0
1.0
2
-3 -2 -1 0 1 2 3 4 5 6 7 8 9Years since reference year
Labour costGross earnings
Sources : Bozio et al. (2018).
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Figure 24 – Reform 2 : Pass-Through Rate on Workers– withtrends
-0.5
0.0
0.5
1.0
1.5
2.0
0 1 2 3 4 5 6 7 8 9Years since reference year
Estimate95% CI
Sources : Bozio et al. (2018).43 / 131
Figure 25 – Reform 3 : log(zh) vs log(wh)
-.02
-.01
0.0
1.0
2
-3 -2 -1 0 1 2 3 4 5 6 7 8 9Years since reference year
Labour costGross earnings
Sources : Bozio et al. (2019).
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Figure 26 – Reform 3 : Pass-Through Rate on Workers – withtrends
-0.5
0.0
0.5
1.0
1.5
2.0
0 1 2 3 4 5 6 7 8 9Years since reference year
Estimate95% CI
Sources : Bozio et al. (2018).45 / 131
Bozio et al. (2018) : SummaryTable 2 – Baseline estimates of pass-through rate on workers
Reform : Reform 1 Reform 2 Reform 3
Dep. var. : log(hourly wage) log(earnings) log(earnings) log(earnings)
Panel A. Without controlling for individual-specific trends
t0+8 0.934*** 0.812*** 0.186 0.384**(0.303) (0.293) (0.166) (0.172)
t0+9 0.906*** 0.969*** 0.215 n/a(0.327) (0.324) (0.170) n/a
Panel B. Controlling for individual-specific trends
t0+8 1.077*** 1.112*** 0.100 0.209(0.318) (0.291) (0.224) (0.133)
t0+9 1.064*** 1.157*** 0.061 n/a(0.335) (0.308) (0.229) n/a
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Figure 27 – Meta-Analysis of Payroll Tax Incidence
Gruber & Krueger (1991)
Gruber (1994)
Gruber (1997)
Anderson & Meyer (1997)
Anderson & Meyer (2000)
Komamura & Yamada (2004)
Baicker & Chandra (2006)
Murphy (2007)
Kugler & Kugler (2009)Tax-benefit linkage:
no shifting full shifting
Korkeamäki & Uusitalo (2009)
Bennmarker et al. (2009)
Cruces et al. (2010)
Saez et al. (2012)
Saez et al. (2017)
Bozio et al. (2018)
‐1 ‐0.5 0 0.5 1 1.5 2Estimated pass-through to workers
Tax-benefit linkage:
Strong
Weak
Uncertain
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Empirical estimates : income tax
• Limited evidence• General assumption that income tax falls on individuals• In theory, income tax could be incident on employers
e.g., contract of footballers expressed ‘net of tax’
• Evidence• Kubik (JPubE, 2004) : TRA in the U.S. in 1986, drop in
tax rates lead to lower pre-tax wage• Lehman, Marical and Rioux (JPubE, 2013) : in France
incidence of SSCs reduction vs income tax• Bingley and Lanot (JPubE, 2002) : Denmark, partial
shifting of income tax
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Empirical estimates : benefits
• Limited evidence• General assumption that benefits benefit individuals• In theory, benefits could be incident on employers
e.g., those on benefits could be paid less
• Evidence• Rothstein (AEJ-policy, 2010) : EITC in the U.S.• Fack (2006) : housing benefits in France
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II. Labour supply responses
• Why labour supply matters• If people work less, as response to tax, then limits to
taxation and redistribution• Tax increases will impact the tax base, and raise less
revenues than expected
• Labour supply elasticity• Measures how much labour is reduced when net wage is
reduced
ε =∂logL
∂logw
• Severe challenges to measure ε
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What is labour supply ?
• Time allocation• Endowment of time T• Hours of market work H• Leisure L = T − H
• Leisure is “time not spent in market work”
1 Household production2 Unpaid activities3 Human capital accumulation4 Pure leisure
• Individual trade-offs• Pure leisure vs consumption• Untaxed activities (home production) vs taxed activities
(work and market consumption)
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Figure 28 – Enjoyment of leisure activities in the U.S.
Sources : Ramey and Francis (2009), Tab. 152 / 131
II. Labour supply responses
1 Baseline labour supply model
2 Early empirical studies
3 Randomised controlled trials
4 Quasi-experimental evidence
5 Micro vs macro estimates
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Baseline model
• Key assumptions
(a) Static(b) Pure intensive margin choice(c) No frictions or adjustment costs(d) Linear tax system
• Optimization problem• Trade-off between consumption (c) and leisure (l)• The individual maximizes a utility function u(c , l)• Individuals earns net of tax wage w(1− τ) and has R
non-labour income
maxc,l
u(c , l) subject to c = wl + R
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Baseline model• Uncompensated or Marshallian elasticity of labour
supply• FOC : wuc + ul = 0 defines Marshallian labour supply
function lu(w , l)• Uncompensated elasticity of labour supply : εu
εu =w
l
∂lu
∂w
• % change in hours when net wage increase by 1%
• Income effects• Income effect parameter η
η = w∂l
∂R
• Increase in non-labour income leads to decrease in laboursupply
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Baseline model
• Compensated or Hicksian elasticity of labour supply• Minimization of cost wl − c subject to the constraint of
u(c , l) >= u leads to Hicksian labour supply function• Compensated elasticity of labour supply : εc
εc =w
l
∂lc
∂w
• Deadweightloss depends on εc
• Slutsky equation
∂l
∂w=∂l c
∂w+ l
∂l
∂R
εu = εc + η
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Baseline model
An increase in income tax has three effects :
1 Income effect : lower unearned income⇒ Increases labour supply
2 Income effect : lower after-tax wage⇒ Increases labour supply
3 Substitution effect : lower after-tax wage⇒ Decreases labour supply
⇒ The net effect is theoretically ambiguous ; it is an empiricalquestion.
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Cross-section estimation
• Labour supply estimation• First micro surveys and computers in the 1960s• Data on hours of work, wage rate and non-labour income
• Simple OLS regression
Y = α + εu(1− τ)w + ηR + ζX + ε
• Y a measure of labour supply• (1− τ)w the after-tax wage• R unearned income• X various controls : education, marital status, children• η measures income effects• εu measures uncompensated wage effects
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Estimation issues
1 Unobserved heterogeneity• Identification is based on cross-section variation in w• w likely correlated with taste for work
e.g., hard workers acquire better education and hence havehigher wages
• Omitted variable bias lead to upward biased estimate of ε
2 Non-participation• OLS regression based only on observations participating in
labour force• Wages non-observed for non labour force participants• Bias in OLS estimates : low wage earners must have very
high unobserved propensity to work• Selection correction : heckit, tobit, etc.
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Estimation issues
3 Non-linear budget set• Tax and benefit systems are highly non-linear• Model mis-specification : OLS does not recover structural
parameter ε
(i) Bunching at kinks(ii) Mis-estimate income effects
• Taste for work correlated with tax rate τ• downward bias in estimated ε
4 Dynamics• Temporary/permanent wage/tax change have different
impacts on labour• Intertemporal substitution
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Econometric solutions
• Instrument net wage rate by tax changes• Tax change good instrument for net wage• Convergence of public/labour literature on labour supply
• Public : sufficient statistics approach• Reduced-form : measure impact of taxes without
estimating structural parameters• Sufficient statistics : develop formulas for welfare analysis
that does not depend on structural parameters (Chetty,ARE 2009)
• Labour : structural approach• Non-linear budget constraints estimation (Hausman 1981)• Intertemporal substitution elasticity (Heckman and
MaCurdy, 1980)
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Surveys
• Labour economics literature• Pencavel (1986) HLE, vol. 1• Heckman and Killingsworth (1986) HLE, vol. 1• Blundell and MaCurdy (1999) HLE, vol. 3
• Public economics literature• Hausman (1985) HPE, vol. 1• Moffitt (2003) HPE, vol. 4
• Econometrics literature• Blundell, MaCurdy and Meghir (1985) HPE, vol. 1
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Labour supply elasticities
• Intensive margin• Primary earners (used to be usually men) have low
elasticities (around 0.1).• Secondary earners of the household (typically married
women) have much higher elasticities (between 0.5 and 1).
• Extensive margin• Highly educated men have very low participation elasticities• Low educated men have modest participation elasticities• Married women have much higher elasticities• Lone mothers have very high participation elasticities
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Labour supply elasticities
• Blau and Kahn (JOLE, 2007)• Use grouping instrument on data from 1980-2000• Define cells (year/age/education)• Identification from group-level variations
• Results• Married female labour supply elasticity has been falling
sharply• total hours elasticity : 0.4 in 1980 to 0.2 in 2000• effect of husband earnings reduced over time
• The distinction between primary and secondary earnerstends to blur with the increase in female participation
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Estimates from experimental design
1 RCT
2 Lottery
3 Tax reforms
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Randomized controlled trial
• Negative income tax (NIT)• Complex set of cash and in-kind benefits in the U.S. in the
1960s• NIT : guaranteed income payment to all poor households,
gradually reduced with earnings• Fear that NIT will reduce labour supply
• Income Maintenance Experiments• First major social experiments in the U.S.• Four large randomized controlled trials (RCT) :
1) New Jersey and Pennsylvania (1968-1972)2) Iowa and North Carolina (1969-1973)3) Gary, Indiana (1971-1974)4) Denver and Seattle (1971-1982)
• Large cost of the experiment (1 billion USD)
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Randomized controlled trial• NIT experimented
• Benefit B defined as a function of lump-sum grant G withphaseout rate τ for households with income Y :B = G − τY if Y < G
τ
B = 0 if Y > Gτ
• Gτ is the break-even point
• τ is the marginal tax rate
• Experimental design• Several groups with randomization within each• Around 75 households per group
• Analysis• Rees (JHR 1974)• Munnell (1986) : conference volume on NIT experiments• Ashenfelter and Plant (JOLE, 1990)
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Randomized controlled trial
Figure 29 – Parameters of the 11 NIT experiments
Sources : Ashenfelter and Plant (1990), Tab. 1.
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Randomized controlled trial
• Ashenfelter and Plant (JOLE, 1990)• Analysis of the Denver and Seattle NIT• Present non-parametrics evidence of labour supply effects• Compare actual benefits payments to treated households to
counterfactual benefit payments to control households• Difference in benefits reflects aggregate hours response
• Results• Significant labour supply response but small• Implied earnings elasticities :
• male : 0.1• female : 0.5
• Response of women concentrated along the extensivemargin
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Figure 30 – Payments treated vs control
Note : Standard errors are in brackets ; ∗ denotes mean is more than twice its standard error.Sources : Ashenfelter and Plant (1990), Tab. 3. 70 / 131
Randomized controlled trial
• Shortcomings of the NIT experiments• Self-reported earnings (with incentives to under-report
earnings)• Selective attrition (no incentives to report when above
breakeven point)• GE effects
• Shortcomings of the analysis• No distinction between extensive/intensive margin• No separate estimation of income effects vs substitution
effects• Hard to identify the key elasticity relevant for policy
purposes
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Lottery and income effects
• Cesarini, Lindqvist, Notowidigdo and Ostling (AER,2017)• Universe of Swedish lottery winners and non-winners
matched with administrative data on earnings• Lottery is pretty close to RCT design
• Key results
(i) Effects on both extensive and intensive labor supplymargin, persistent over time
(ii) Significant but small income effects : η ≈ −0.10(iii) Effects on spouse but not as large as on winner
⇒ Rejects the unitary model of household labor supply
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Figure 31 – Effect of Wealth on Individual Gross Labor Earnings
Sources : Cesarini et al. (2017), Fig. 1, p. 3926.
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Lottery and income effects
Figure 32 – Margins of Adjustments
Sources : Cesarini et al. (2017), Tab. 4, p. 3929.
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Figure 33 – Effect of Wealth on Earnings of Married Winners andSpouses
Sources : Cesarini et al. (2017), Fig. 5, p. 3942.
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Experience of tax holiday
• Tax holiday in Iceland• In 1986, Iceland announced major reform to income tax
1 Move to tax withholding in 1988 (pay-as-you-earn)2 Change of tax schedule with lower marg. tax rate and
higher tax-free allowance
• To avoid double taxation during transition, no tax chargedover 1987 incomes
• Bianchi et al. (AER, 2001)• Exploit the 1987 no tax experiment : large and salient tax
variation (4(1−MTR) ' 49%• Data : individual tax returns matched with data on weeks
worked from insurance database• Estimate intertemporal substitution elasticity (work hard in
1987, relax after)
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Figure 34 – Employment rate in Iceland (1960-1996)
Sources : Bianchi, Gudmundsson and Zoega (2001), Fig. 1.77 / 131
Macro estimates
• Macroeconomic approach• Macroeconomists exploit long-term trends or cross-country
comparisons• Use aggregate data on hours/tax
• Identification• Calibration technique : find elasticity that best fits the
data/model• Identification is problematic• Similar to regression without controls• But perhaps more relevant to long-run policy questions of
interest
78 / 131
Macro estimates
• Long-run estimates• Ramey and Francis (AEJ-Macro, 2009)• U.S. real wage from 1900 to today : + 820%• U.S. hours worked reduced (25-54) : -25%• U.S. hours worked reduced (14+) : -16%• Implied labour supply elasticity very small : 0.02-0.03
• Possible explanations• Impact of taxes on labour supply if large compensated
elasticity and large income effects• Or utility depends on relative consumption and these
long-run estimates are misleading
79 / 131
Macro estimates
Figure 35 – Average hours worked per person in the U.S.
0
5
10
15
20
25
30
35
40
45
50
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Males
All
Female
Notes : Population of individuals aged 14 and above.Sources : Ramey and Francis (2009), graph from online dataset. 80 / 131
Macro estimates
• Edward Prescott• Edward Prescott, American macroeconomist, Nobel prize
2004• “virtually all of the large differences between U.S. labor
supply and those of Germany and France are due todifferences in tax systems”
• Prescott (2004)• Data on hours worked and tax rates for 7 OECD countries• Calibration of GE model
u(c , l) = c − l1+ 1ε
1 + 1ε
• Find that labour supply elasticity ε = 0.7 best matchestimes series
81 / 131
Macro estimates
Table 3 – Actual and predicted labour supply (Prescott2004)
Hours worked Prediction factorsPeriod Country Actual Predicted Tax rate C/Y
1993-96 Germany 19.3 19.5 0.59 0.74France 17.5 19.5 0.59 0.74Italy 16.5 18.8 0.64 0.69Canada 22.9 21.3 0.52 0.77U.K. 22.8 22.8 0.44 0.83Japan 27.0 29.0 0.37 0.68U.S. 25.9 24.6 0.40 0.81
1970-74Germany 24.6 24.6 0.52 0.66France 24.4 25.4 0.49 0.66Italy 19.2 28.3 0.41 0.66Canada 22.2 25.6 0.44 0.72U.K. 25.9 24.0 0.45 0.77Japan 29.8 35.8 0.25 0.60U.S. 23.5 26.4 0.40 0.74
Sources : Prescott (2004), Tab. 2.82 / 131
Macro estimates
Figure 36 – Hours and taxes according to Prescott (2004)
Germany 1970-74France, 1970-74
Italy, 1970-73
Canada, 1970-74
US 1970-74
Japan, 1970-74
UK 1970-74
Germany, 1993-96
France, 1993-96
Italy 1993-96
Canada, 1993-96 US 1993-96
Japan, 1993-96
UK, 1993-96
Linear fit: log(h) = 0.7log(1-t) + 7.5
Implied elasticity = 0.7
6,7
6,8
6,9
7,0
7,1
7,2
7,3
7,4
-1,1 -1,0 -0,9 -0,8 -0,7 -0,6 -0,5 -0,4 -0,3 -0,2
log
(ho
urs
)
log(1-tax rate)
Sources : Data from Prescott (2004), Tab. 2.83 / 131
Macro estimates
• Macro vs micro estimates• Macro calibrated models need high labour supply
elasticities• Cross-country evidence suggests high correlation between
hours worked and taxes• Micro (within country) evidence suggests small elasticities
• Debate within economists• “Prescott’s provocative paper” (Alesina, Glaeser and
Sacerdote, 2005)• Results confirmed with other calibrations and more data
(Ohanian, Raffo and Rogerson, JME, 2008)• Prescott Nobel Lecture (JPE, 2006)
84 / 131
Macro vs micro : explanations1 Omitted variable
• Labour market regulations (Alesina, Glaeser and Sacerdote,2005)
• Cultural differences between high tax/low tax countries(Blanchard, 2004 ; Steinhauer, 2013)
2 Extensive vs intensive margin• “Indivisible labour” (Rogerson, JME 1988 ; Rogerson and
Wallenius, JET 2008)
3 Frictions• Macro-elasticity captures long-term responses which could
be larger due to frictions (Chetty, ECA 2012)
4 Other programmes• Pension systems, education, child care, all affect labour
supply at different point in time and for different groups(Blundell, Bozio and Laroque, AER 2011) 85 / 131
Macro vs micro : omitted variables
• Alesina, Glaeser and Sacerdote (2005)• Critical of Prescott (2004)• Use aggregate OECD data confirming the negative
correlation between hours work and tax rates• Correlation of high tax level with low inequality, high
influence of unions, preferences for holidays
• Worksharing policies• Unions have bargained for lower hours with the aim of
“worksharing”e.g., Early retirement policies, 35 hours week, etc.
• Little impact of taxation on unions’ motivation
86 / 131
Macro estimates
Figure 37 – Hours worked per person and marginal tax rate
Sources : Alesina et al. (2005), Fig. 1.5 87 / 131
Macro estimates
Figure 38 – Hours worked vs collective bargaining agreement
Sources : Alesina et al. (2005), Fig. 1.7 88 / 131
Macro estimates
Figure 39 – Days of vacation in the U.S. vs unionization
Sources : Alesina et al. (2005), Fig. 1.9 89 / 131
Macro estimates
Figure 40 – Weekly hours per person versus gini
Sources : Alesina et al. (2005), Fig. 1.10 90 / 131
Cultural differences in labour supply
• Steinhauer (2013)• Cultural differences could explain different labour supply
behaviour• Exploit the language difference with Switzerland between
German/French speakers• RDD along Rostigraben (i.e., rosti ditch or in French
barriere du rosti)
• Results• Little institutional difference• Working mothers more prevalent on the French-speaking
side of the language border• Share of childlessness more prevalent on the
German-speaking side
91 / 131
Cultural differences
Figure 41 – Map of Switzerland by language
Sources : Marco Zanoli ; Swiss Federal Statistical Office ; census of 2000
92 / 131
Cultural differences
Figure 42 – Day-care supply
Note : Swiss French speakers on the left, Swiss German speakers on the rightSources : Steinhauer (2013) 93 / 131
Cultural differences
Figure 43 – LFP of mothers of young children
Note : Swiss French speakers on the left, Swiss German speakers on the rightSources : Steinhauer (2013)
94 / 131
Cultural differences
Figure 44 – Share of childlessness
Note : Swiss French speakers on the left, Swiss German speakers on the rightSources : Steinhauer (2013) 95 / 131
Macro vs micro : frictions• Do frictions attenuate micro elasticities ?
• Idea : frictions prevent workers to optimize fully, henceshort-term responses are lower than structural (orlong-term) responses
• Observed elasticity ε confounds structural elasticity ε withadjustment cost distribution
ε ≤ ε
• Could help reconcile micro with macro elasticities ?
• Chetty (ECA, 2012)• Develop bounds approach to labour supply elasticities• Restrict size of frictions by requiring that utility loss is less
than exogenous threshold δ• Partial identification with choice set• With large price shocks (or large tax change), bounds
shrink96 / 131
Figure 45 – Bounds on Intensive Margin Hicksian Elasticities
Sources : Chetty (2012), Fig. 7.
97 / 131
Figure 46 – Bounds on Intensive Margin Hicksian Elasticities
Sources : Chetty (2012), Fig. 7.
98 / 131
Macro vs micro : frictions
• Chetty, Guren, Manoli and Weber (AER, 2011)• Can frictions reconcile micro with macro elasticities ?• Meta-analysis of micro/macro labour elasticity studies
Figure 47 – Micro vs macro labour supply elasticities
Sources : Chetty et al. (2011), Tab. 1.
99 / 131
Cross-country studies
• Blundell, Bozio and Laroque (AER, 2011 ; FS 2013)• Use micro data from LFS data on three countries since
1960s• Document cross-country variations in hours worked along
many margins• schooling-work margin• women with children• early retirement
• Variations for prime-age workers 30-54 years mostly onhours worked (holidays, hours per week regulations)
• Micro-based cross-country analysis• Lack of this kind of analysis (very big work !)• Done successfully for retirement (series of books by Gruber
and Wise, 1999, 2004, 2007, 2011)
100 / 131
III. Elasticity of taxable income
1 Conceptual framework
2 Early studies
3 Recent studies
101 / 131
Elasticity of taxable income
• Limits of traditional labour supply• Quantitative measures of labour supply (hours and
employment) are not the only behavioural responses totaxation
• Deadweight loss of taxation should depend on allbehavioural responses
• Other behavioural margins
1) Effort on the job2) Career choice3) Form and timing of compensation4) Tax avoidance (legal shifting of income)5) Tax evasion (illegal under-reporting of income)
102 / 131
Elasticity of taxable income
• Elasticity of taxable income (ETI)• Reported income z captures potentially all margins of
behavioural responses to marginal tax rate τ
e =1− τz
∂z
∂(1− τ)
• ETI, e, is the % change in reported income when thenet-of-tax rate increases by 1%
103 / 131
Elasticity of taxable income• ETI as sufficient statistics (Feldstein, RESTAT 1999)
• Deadweight loss is the difference between utility loss fromtaxation W and the revenue from taxation R
• Marginal deadweight loss dDWL
dDWL = dW − dR
• Taxation leads to mechanical effects dM and behaviouralrevenue effects dB
dR = dM + DB
• We have dW = dM (envelope theorem)
dDWL = dM − (dM + dB) = −dB
• dB depends directly from ETI104 / 131
Elasticity of taxable income• ETI not as sufficient statistics (Saez, Slemrod and
Giertz JEL 2012)• Assumption in the basic ETI framework :
(i) reduced z has no other effect on tax revenue• Reasonable assumption for real responses
e.g., labour supply responses
• Problem if reduced z comes from tax shifting or leads tofiscal externalities
• Fiscal externalities• Shifting between personal/corporate income• Shifting over time of income• Externalities (e.g., charitable giving)
• Other parameters neededi) Distinction between real responses vs. shiftingii) How much is shifted income taxed ?
105 / 131
Elasticity of taxable income
• Early studies : high ETI• Lindsey (JPubE, 1987) : Reagan, 1981 tax cuts• Feldstein (JPE, 1995) : Reagan, 1986 tax cuts• Very high estimates of ETI
• More recent studies : smaller ETI• More reforms in the U.S. (Goolsbee, 1999)• More countries (U.K., Denmark, etc.)• Smaller estimates but larger than traditional labour supply
estimates
• Surveys on ETI• Saez, Slemrod and Giertz (JEL 2012)• Slemrod (NTJ, 1998)
106 / 131
Feldstein (JPE, 1995)• Tax reform act (TRA) in 1986
• Biggest tax reform in the U.S. since WWII• Top MTR down from 50% to 28%• Substantial base-broadening : exemptions and preferential
tax treatment repealed
• DiD approach• Use panel of tax return data between 1985 and 1988• Construct three income groups
1 Treatment : highest income, with τ1985 = 49− 50%2 Control 1 : high income, with τ1985 = 42− 45%3 Control 2 : high income, with τ1985 = 22− 38%
• DiD approach : exploit differences in MTR
eDiD =4log(zT )−4log(zC )
4log(1− τT )−4log(1− τC )
107 / 131
Table 4 – Response of taxable income to changes in MTR
1985 data ∆ between 1985 and 1988
MTR Income (K$) 1− τ Adjusted taxable income Nb obs.
22 30.7 9.0 13.6 80025 36.1 13.3 3.5 90928 42.7 16.3 6.0 71333 51.5 8.7 2.5 77138 67.5 16.1 9.6 34542 94.3 24.1 22.0 15245 126.9 30.9 18.5 4549 177.7 41.2 42.7 3550 479.0 44.0 92.4 22
22-38 12.2 6.2 3,53842-45 25.6 21.0 19749-50 42.2 71.6 57
Source : Feldstein (1995), Tab. 1, p. 561.
108 / 131
Table 5 – Response of taxable income to changes in MTR
Taxpayer Groups 1− τ Adj. Taxable Ad. Taxableby 1985 MTR Income Income + Loss
Percentage Changes, 1985–88
Medium (22-38) 12.2 6.2 6.4High (42-45) 25.6 21.0 20.3Highest (49-50) 42.2 71.6 44.8
Differences of Differences
High vs Med. 13.4 14.8 13.9Highest vs High 16.6 50.6 24.5Highest vs Med. 30.0 65.4 38.4
Implied Elasticity Estimates
High vs Med. 1.10 1.04Highest vs High 3.05 1.48Highest vs Med. 2.14 1.25
Source : Feldstein (1995), Tab. 2.Note : the last column add to taxable income the gross partner-ship losses.
109 / 131
Feldstein (JPE, 1995) : results
• Very high ETI estimated• Estimates between 1.04 and 3.05• Much larger than the usual labour supply elasticities
(0.2-0.5)
• Policy implications• The U.S. was on the wrong side of the Laffer curve• Tax cuts with TRA 86 led to no revenu losses• Clinton’s 1993 tax increases should lead to no tax revenues• The top marginal tax rate should not be much higher than
30%
110 / 131
Feldstein (JPE, 1995) : issues1) Mean reversion
• After a negative (positive) income shock, income increases(decreases)⇒ underestimation of ETI
2) Non-tax related changes in inequality• control and treatment groups come from different part of
the income distribution• with increasing inequality, the richer will grow richer than
the rich or middle income group⇒ overestimation of ETI
3) Very small sample : 57 tax filers in the treated group• Auten and Carroll (RESTAT, 1999) : with larger admin
data, they find e=1.10 (compared to Feldstein’s 3.05)• With additional controls, their preferred estimation is
e=0.57111 / 131
Feldstein (JPE, 1995) : issues
4) Heterogenous elasticity• DiD requires homogeneous elasticity• If elasticities are increasing in income⇒ ETI biased upward
Example : suppose eT = e and eC = 0and 4log(1− τC ) = 0.54log(1− τT )Then : 4log(zT )−4log(zC ) = e4log(1− τT )We obtain : eDiD = 2e
5) TRA86 changed the tax rate and tax base• Behavioural effect confounded with definitional effects
6) Short-term vs long-term• Some responses could be short term shifting effects
112 / 131
Gruber and Saez (JPubE, 2002)
• Data• Panel data from 1979-1990• Exploit all tax changes rather single reform
• Methodology• IV regression analysis
4ln(zit) = e4ln(1− τit) + Xit + νit
• Endogeneity issue : τit linked to zit• Use predicted change in 4ln(1− τit) assuming income
stays constant• Isolate changes in tax law as the only source of variation
113 / 131
Gruber and Saez (JPubE, 2002)
Table 6 – Basic elasticity results
Income controls None Log income Log income 10-piece spline
Broad Taxable Broad Taxable Broad Taxableincome income income income income income
Elasticity -0.300 -0.462 0.170 0.611 0.120 0.400(0.120) (0.194) (0.106) (0.144) (0.106) (0.144)
Source : Gruber and Saez (2002), Tab. 4, p. 16.
114 / 131
Gruber and Saez (JPubE, 2002)
Table 7 – Elasticity results by income groups
Income range Broad Taxableincome income
$10K to $50K -0.044 0.180(0.085) (0.164)
N. Obs. 49 364 39 902
$50K to $100K -0.065 0.106(0.154) (0.219)
N. Obs. 16 688 16 293
$100K and above 0.171 0.567(0.240) (0.298)
N. Obs. 3076 3004
Source : Gruber and Saez (2002), Tab. 9, p. 24.
115 / 131
Gruber and Saez (JPubE, 2002)
Table 8 – Elasticity results by itemizing status
Itemizing status Broad Taxableincome income
Itemizers 0.266 0.647(0.068) (0.099)
N. Obs. 28 117 25 746
Non-Itemizers -0.210 -0.179(0.079) (0.122)
N. Obs. 41 012 33 569
Source : Gruber and Saez (2002), Tab. 9, p. 24.
116 / 131
Gruber and Saez (JPubE, 2002)
• Results• ETI estimates of 0.4, and elasticity of broad income of 0.12• Higher ETI for top incomes (0.5-0.6)• Smaller ETI for non-top incomes (0.1-0.2)• Higher ETI comes from itemizers
• Issues : results are fragile
1) Imprecision of the estimates2) Sensitive to exclusion of low income3) Sensitive to controls for mean reversion (Kopczuk, 2005)4) Bundles together small tax change and big tax changes
117 / 131
Kleven and Schultz (AEJ-EP, 2014)
• Danish data• Full-population admin data over 25 years• Sample is 37 million obs.
• Danish tax reforms• Stable income distribution throughout the period• Clear and large tax variations• Separate variations for labour and capital income
• Method• Compelling graphical DiD evidence• Define treatment/control pre-reform and follow the same
group before and after the reforms
118 / 131
Kleven and Schultz (AEJ-EP, 2014)
Figure 48 – Top income shares in Denmark
Source : Kleven and Schultz (AEJ-EP 2014), Fig. 1, p. 273.
119 / 131
Figure 49 – Two Decades of Danish tax reforms
Source : Kleven and Schultz (AEJ-EP 2014), Fig. 2, p. 278.
120 / 131
Kleven and Schultz (AEJ-EP, 2014)
Figure 50 – Danish 1987 reform : labour income
Source : Kleven and Schultz (AEJ-EP 2014), Fig. 4.A
121 / 131
Kleven and Schultz (AEJ-EP, 2014)
Figure 51 – Danish 1987 reform : labour income, large vs smallcuts
Source : Kleven and Schultz (AEJ-EP 2014), Fig. 4.B.
122 / 131
Kleven and Schultz (AEJ-EP, 2014)
Figure 52 – Danish 1987 reform : positive capital income
Source : Kleven and Schultz (AEJ-EP 2014), Fig. 4.C.
123 / 131
Kleven and Schultz (AEJ-EP, 2014)
Table 9 – Elasticity of labour income : heterogeneity
Full Top Top College Women With kidssample 20% 10% or more below age 6
A. All workersElasticity 0.049 0.076 0.085 0.062 0.054 0.083
(0.002) (0.008) (0.012) (0.009) (0.005) (0.010)Obs. (in million) 31.2 6.2 3.1 5.1 15.3 4.7
B. Wage earnersElasticity 0.046 0.073 0.081 0.061 0.052 0.080
(0.002) (0.009) (0.012) (0.010) (0.005) (0.010)Obs. (in million) 25.6 5.9 2.9 4.8 14.8 4.6
C. Self-employedElasticity 0.090 0.135 0.147 0.113 0.116 0.171
(0.014) (0.037) (0.044) (0.039) (0.026) (0.046)Obs. (in million) 1.6 0.3 0.2 0.2 0.5 0.2
Source : Kleven and Schultz (AEJ-EP 2014), Tab. 4, p. 290.
124 / 131
Kleven and Schultz (AEJ-EP, 2014)
• Results• Small labour income elasticities (0.05-0.2)• Larger capital income elasticities (0.1-0.3)• Larger elasticities when estimated from larger reforms
(frictions, cf. Chetty 2012)• Larger labour income elasticities for self-employed, women
with kids• Limited income shifting between labour and capital income
• Implications• Broad base and strong enforcement leads to modest
behavioural responses even under high marginal tax rates
125 / 131
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Definitions
Average tax rate τ is the proportion of income R leading totax T
τ =T
R
Marginal tax rate µ is the share of tax on additional unit ofincome
µ =∂T
∂R
Progressivity A tax schedule is said progressive if the averagetax rate is increasing with income
Regressivity A tax schedule is said progressive if the averagetax rate is increasing with income
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