minimum wage and tax evasion: theory and evidence mirco tonin university of southampton warsaw, 29...

Minimum Wage and Tax Evasion:

Theory and Evidence

Mirco Tonin

University of Southampton

Warsaw, 29 November 2007

Objective of the paper: study the interaction between minimum wage and underreporting of earnings by employed labour

• build a formal model• test some of the implications

Basic idea: minimum wage is a lower bound for declared earnings in the formal sector

Plan of presentation:

• Some evidence on underreporting

• Review of related literature

• Model

• Empirical evidence

Relevance of underreporting (I)

“Envelope wages" above the officially declared minimum "exists in practically all of the Central and Eastern European countries" (European Commission, 2004.)

In Eastern Europe and the Former Soviet Union “disproportionately high shares of workers cluster on declared wages at or just above the minimum wage, with evidence of additional undeclared incomes above the minimum” (World Bank, 2005.)

OECD (2004) estimates a 30% shortfall in social security contributions due to undeclared incomes in Hungary, Mexico, and South Korea and 20% in Italy, Poland, Spain and Turkey.

Relevance of underreporting (II)

“Did you know that more than half of the people nominally employed at the minimum wage earn more, and the only reason for such a declaration is to evade taxes and social security contributions?”

Related literature

Minimum Wage: impact on employment (Card and Krueger, 1995; Neumark and Wascher, 2006), job composition (Acemoglu, 2001), fringe benefits (Simon and Kaestner, 2004), training (Booth et al., 2004), prices (Lemos, 2006), working hours (Stewart and Swaffield, 2006), profits (Draca et al., 2006);

Tax Evasion / Informal Economy: models with a separate informal sector (Fugazza and Jacques, 2003; Boeri and Garibaldi, 2005), models with partial compliance (Cowell, 1985; Kolm and Nielsen, 2005);

Empirical literature (microdata): surveys (Lemieux et al., 1994), comparison of income and participation data from different sources (Fiorio and D’Amuri, 2005), comparison of income and consumption data (Pissarides and Weber, 1989; Gorodnichenko and Sabirianova, 2006; Feldman and Slemrod, forthcoming);

• Competitive labour market

• Free entry of firms

• Risk neutral firms

• Firms act as withholding agent

• No capital

• Production = labour input

• y : worker’s productivity

• w : worker’s gross wage / labour cost

• t : proportional tax rate (PIT and SSC)

• Objective functions:

Firms:

Workers:

… but there is Tax Evasion!

• x : declared income

• ỹ : detected income

• γ : probability of auditing

• θ : 1 + fine on evaded taxes

Equilibrium with No Tax Evasion

Enforcement of taxation (I)

ỹ ỹ fine base

Enforcement of taxation (II)

f : expected fine in case of auditing

if ỹ distributed uniformly over [0,y]:

Equilibrium without minimum wage (I)

Declared income is chosen to maximize total income net of expected payment to fiscal authorities

Equilibrium without minimum wage (II)

where:

Equilibrium without minimum wage (III)

Free entry Zero profit condition

Equilibrium with a minimum wage

Declared income is given by the solution to

unaffectedout of formal labour market

Example

α =33% Minimum Wage=80

High Productivity Worker: y = 150 => x* = 100

Intermediate Productivity Worker: y = 100 => x* = 66

Low Productivity Worker: y = 30 => x* = 20

Effects on distribution of declared earnings

affected unaffected

Effects on incomes of an increase in MW

• Workers operating already underground

• Workers declaring before the minimum wage increase between the old and new minimum wage

• Workers declaring already more than the new minimum wage

An empirical test: Hungary 2000-2001

2001: MW increased from 25500 HUF (98 EUR) to 40000 HUF (156 EUR)

Wage dynamics in Hungary 1992-2005

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Real MW - CPI - 1992=100 (lhs) Real Average Wage - CPI - 1992=100 (lhs)

Kaitz Index - % (rhs)

Institutional context (I)

Minimum Wage: relates to gross monthly earnings net of overtime pay, shift pay and bonuses; legally binding; covers all employment contracts

1998-2002: set unilaterally by government

Taxation: tax wedge on low wage earners around 46% in 2000-2001, marginal rate around 56%

Institutional context (II)

Informal economy:

• 56% of households are aware of the practice of employers declaring to the tax authority the minimum wage, while paying additional wage unofficially, taking place in their neighbourhood

• Informal Economy around 25% of official GDP in the period 1999-2003 (Schneider, 2005)

• Size of Undeclared work around 18% of GDP in 1998 (Renooy et al. 2005)

Effects on the labour market

“Despite the brutal price shock the immediate effect did not seem dramatic” Kertesi and Köllő (2003)

1.High levels of compliance with minimum wage regulation; minor spillover

2. Jobloss risk of minimum wage workers:

Male, 25 years old, 5 years tenure: QQ outflow to unemployment rates:

• Treatment (90-110% MW 2001) : 0.243%

• Control (110-125% MW 2001) : 0.119%

3. Outflows from unemployment

Job finding probability of low-wage unemployed relative to unskilled as a whole dropped by 7-8% in 2001

y: 250 €

x: 98 €

Net I (reported): 78 €

Net I (true): 250-70 = 180 €

y: 250 €

x: 156 €

Net I (reported): 120 €

Net I (true): 250-107 = 143 €

2000/2001

ΔNet I

-reported = + 42 €

-true = - 37 €

2000 2001

Monthly Minimum Wage 25,500 Ft 40,000 Ft

98 € 156 €Net Take Home Pay 20,273 Ft 30,800 Ft

78 € 120 €Labour Cost 38,580 Ft 58,300 Ft

148 € 227 €Total Fiscal Payments 18,308 Ft 27,500 Ft

70 € 107 €

Tax Wedge on Minimum Wage

Empirical strategy

Minimum wage hike in 2001: shock to “underreporting technology” for affected group

Difference-in-Difference Approach:

Treatment group: households affected by MW hike

Control group: “similar” but unaffected households

where ci,t : food consumption for household i at time t

Estimated equation:

The dataset – the sample

Household Budget Survey:

• 10000 households interviewed every year

• One-third of the sample is rotated every year

• 2Y panel: around 3500 households for 1999-2000 and 2000-2001

Main variables

Food consumption: distinction between food bought in the market and food produced at home

Income: distinction between income including or not home production

Month dummies: month of diary keeping in two consecutive years

Geographical dummies: 20 counties + type of settlement

Employee characteristics: number of HH members employed in:

• Sector (60 branches)

• Hierarchical position (10 categories)

• Type of employer (4 categories)

Definitions of treatment

“Actual Treatment”

• defined on characteristics in 2000 and 2001

• can also account for “intensity of treatment”

“Potential Treatment”

• defined only on the basis of characteristics in 2000

• perform a “placebo test” using 1999-2000 panel

“Actual Treatment” - Treatment at individual level

All employees for the whole 2001

150% (200%) MW 200190% MW 2001

Wage 2000

Wage 2001

Public SectorPrivate Sector

150% (200%) MW 2001

Wage 2000

Wage 2001

90% MW 2000

110% MW 2001

90% MW 2001 110% MW 2001

0 22950 40000 80000 150000Year 2000

Dashed lines indicate 90% of the MW in 2000, 90%, 110%, 150%, 200% of the minimum wage in 2001Only households with constant family structure; HH with positive net income below 200000 in both years.For 2000 earnings bounded at 200000 (3 outliers)

(Red: treated; Black: control)

Earnings from main activity

TREATi: number of HH members treated ( i.e. belonging to T )

Regression run on all households:

• where at least one member belongs to T or C

• with constant family structure

• with positive net income below 200,000 HUF in both years

“Actual Treatment” - Treatment at household level

Descriptive Statistics

T 150 200

Total net income HH EUR 290 € 337 € 345 €Expenditures on food EUR 77 € 85 € 86 €

27% 25% 25%

Total net income HH EUR 363 € 401 € 410 €

Expenditures on food EUR 93 € 106 € 107 €

26% 26% 26%

EUR 68 € 59 € 61 €

(% HUF) 23% 17% 17%

EUR 15 € 19 € 20 €

(% HUF) 20% 22% 23%

Increase in expenditures on food:

Expenditures on food as % of net income:

Increase in HH total net income:

Expenditures on food as % of net income:

0 100000 200000 300000

0 100000 200000

With (lhs) and without (rhs) home production

T - treatment group; C:200 - control group using 200% MW as upper bound; C:150 - control group using 150% MW as upper bound;

Kernel density estimation (epanechnikov); HH with positive net income below 200000 HUF in both years;

Household Total Net Income: Kernel Density Estimation

Results (I)

Dependent variable:

Reference group: MW2000<Wage 2000<2* MW2001 MW2000<Wage 2000<1.5* MW2001

-1385 -1292

(0.034) (0.081)

R-Squared 0.31 0.34

Additional Controls:

-1766 -1794

(0.018) (0.039)

R-Squared 0.39 0.42

Treatment -1595 -1671

(0.040) (0.062)

R-Squared 0.41 0.45

Number of HH 808 571

HH treated 149 149

Food, not own production; monthly

Treatment

Year and Month dummies, Employee characteristics for 2001, Geographical dummies.

Year and Month dummies, Employee characteristics for 2001.

Year and Month dummies.

Treatment

Fixed Effect estimation - Robust p values in brackets

-1500 HUF ≈ -5.8 EUR Reminder: ΔNet I (true)= - 37 €

Results (II)

Dependent variable:

Reference group:-1165 -1471 -1126 -1372(0.078) (0.022) (0.129) (0.061)

- 0.05 - 0.05

(0.009) (0.033)

0.02 0.02

(0.059) (0.129)

R-Squared 0.31 0.32 0.35 0.35

-1579 -1745 -1647 -1761(0.036) (0.019) (0.057) (0.041)

- 0.04 - 0.04

(0.019) (0.083)

0.02 0.02

(0.225) (0.250)

R-Squared 0.39 0.39 0.42 0.43

-1473 -1573 -1578 -1624(0.061) (0.042) (0.079) (0.068)

- 0.05 - 0.05

(0.016) (0.032)

0.01 0.02

(0.384) (0.382)

R-Squared 0.42 0.42 0.45 0.45

Number of HH

HH treated

Tot HH Income - excl. Home Production

Food, not own production; monthlyMW2000<Wage 2000<2* MW2001 MW2000<Wage 2000<1.5* MW2001

Treatment

Tot HH Income - excl. Home Production*(t-1)

Treatment

-Tot HH Income - excl. Home Production*(t-1)

808 571

Tot HH Income - excl. Home Production*(t-1)

149 149

Continuous Treatment - Definition

40,000 HUFWage 2000

: ∑j dij

• Private employees in 2001

• Wage in 2000: [90% MW 2000 – 100% MW 2001]

• Wage in 2001: [90% MW 2001 – 100% MW 2001]

Continuous Treatment – Results (I)

Dependent variable:

Reference group: MW2000<Wage 2000<2* MW2001 MW2000<Wage 2000<1.5* MW2001

-0.09 -0.08(0.154) (0.240)

R-Squared 0.31 0.34

-0.14 -0.15(0.073) (0.069)

R-Squared 0.38 0.42

-0.14 -0.14(0.068) (0.099)

R-Squared 0.41 0.45

Number of HH 808 571

HH treated 153 153

Treatment

Continuous Treatment - Results (II)

Dependent variable:

Reference group:-0.07 -0.11 -0.07 -0.10(0.276) (0.086) (0.339) (0.153)

- 0.05 - 0.05

(0.009) (0.032)

0.02 0.02

(0.049) (0.115)

R-Squared 0.31 0.32 0.34 0.35

-0.12 -0.14 -0.14 -0.16(0.120) (0.059) (0.093) (0.057)

- 0.04 - 0.04

(0.017) (0.074)

0.02 0.02

(0.189) (0.222)

R-Squared 0.39 0.39 0.42 0.43

-0.13 -0.15 -0.14 -0.15(0.098) (0.054) (0.122) (0.081)

- 0.05 - 0.05

(0.014) (0.028)

0.01 0.02

(0.365) (0.366)

R-Squared 0.41 0.42 0.45 0.45

Number of HH

HH treated

Food, not own production; monthlyMW2000<Wage 2000<2* MW2001 MW2000<Wage 2000<1.5* MW2001

Treatment

Tot HH Income - excl. Home Production * t

Treatment

808 571

153 153

Private Sector

Public Sector

MW 2000 MW 2001 150% (200%) MW 2001

Sector 2000

Wage 2000

“Potential Treatment” - Treatment at individual level

All employees for whole period (24M) :

0 25500 80000 150000 200000

Year 2000a

0 25500 80000 150000 200000

Year 2000b

The dash lines indicate MW in 2000, MW in 2001, 150% and 200% of MW in 2001

Only employees employed for whole period (24 months) in HH with constant family structure. HH with positive net income below 200000 in both years.

(Red: treated; Black: control)

Earnings from main activity

“Potential Treatment” - Treatment at household level

TREATi: number of HH members treated ( i.e. belonging to T )

Regression run on all households:

• where at least one member belongs to T or C

• with constant family structure

• with positive net income below 200,000 HUF in both years

0 100000 200000

2000 - 99/000

0 100000 200000

2000 - 99/00

0 100000 200000

2000 - 00/01

0 100000 200000

2000 - 00/01

0 100000 200000

2000 - 99/00

0 100000 200000

2000 - 99/00

0 100000 200000

2000 - 00/01

0 100000 200000

2000 - 00/01

0 100000 200000

With (lhs) and without (rhs) home production

T - treatment group; C:200 - control group using 200% MW as upper bound; C:150 - control group using 150% MW as upper bound;

Kernel density estimation (epanechnikov); HH with positive net income below 200000 HUF in both years;

Household Total Net Income: Kernel Density Estimation

Results (I)

Dependent variable:

99-00 00-01 99-00 00-01

Reference group:-743 -1287 -624 -1029

(0.255) (0.046) (0.373) (0.161)

R-Squared 0.22 0.30 0.21 0.30

212 -1942 554 -1843(0.772) (0.019) (0.500) (0.047)

R-Squared 0.30 0.38 0.30 0.41

156 -1717 602 -1608(0.837) (0.041) (0.491) (0.092)

R-Squared 0.32 0.41 0.34 0.45

Number of HH 848 782 609 564

HH treated 197 195 197 195

MW2000<Wage 2000<2* MW2001 MW2000<Wage 2000<1.5* MW2001

Treatment

Results (II)

Dependent variable:

99-00 00-01 99-00 00-01

Reference group:-510 -1538 -494 -1218

(0.413) (0.019) (0.465) (0.103)

0.08 0.05 0.06 0.04

(0.000) (0.010) (0.005) (0.076)

R-Squared 0.24 0.31 0.23 0.31

529 -2178 747 -1936(0.456) (0.010) (0.352) (0.038)

0.08 0.05 0.06 0.03

(0.000) (0.018) (0.011) (0.208)

R-Squared 0.32 0.39 0.32 0.42

468 -1951 794 -1690(0.521) (0.023) (0.351) (0.079)

0.08 0.05 0.06 0.02

(0.000) (0.026) (0.010) (0.362)

R-Squared 0.35 0.42 0.35 0.45

Number of HH 848 782 609 564

HH treated 197 195 197 195

Treatment

MW2000<Wage 2000<2* MW2001 MW2000<Wage 2000<1.5* MW2001

Treatment

Robustness checks

• Other controls: income change & income level, own production of food

• Other types of consumption

• “Placebo test”: replication assuming that a minimum wage in 2000 equivalent to 50,000 HUF (instead of 25,500), increasing in 2001 to 64,500 HUF (instead of 50,000)

• “Hand-to-mouth” households

Other (theoretical) results

• The interaction of minimum wage and underreporting transforms a nominally neutral tax system into a regressive one

• When underreporting is high fiscal revenues increase with the minimum wage

• Under some conditions, the size of the spike at minimum wage level and the size of the informal economy are positively correlated

Link between informal economy and size of the spike (I)

Kaitz index and minimum wage spike

25 30 35 40 45 50 55

minimum wage/ average wage 2002

Source: Eurostat, except France - Kaitz Index: own calculations

USSK ES

PT SI NL

Link between informal economy and size of the spike (II)

Informal Economy and minimum wage spike

0 5 10 15 20 25 30 35 40 45

Informal economy (% of official GDP) 2001/02

US UK NL IE

Sources: informal economy: Schneider (2005); spike: Eurostat

Link between informal economy and size of the spike (III)

Thank you for your attention!

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