november 2015 prof. dr. friedrich schneider, university of linz / austria estimating the size of...

November 2015 Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA

Estimating the Size of the Shadow Economy in the Czech Republic and her Neighboring Countries:

What do we (not) know?

Prof. Dr. DDr.h.c. Friedrich SchneiderDepartment of EconomicsJohannes Kepler University of LinzA-4040 Linz-Auhof

ShadEcEstimation_CzechRep.ppt

E-mail: [email protected]: 0043-732-2468-8210

Fax: 0043-732-2468-8209http://www.econ.jku.at

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All over the world, empirical research about the size

and development of the shadow economy has strongly

increased.

Hence, the goal of this lecture is to present the latest

results of the size and development of the shadow

economies for the Czech Republic and her neighboring

countries.

1. Introduction

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1) Introduction

2) Defining the Shadow Economy

3) Methods to Estimate the Size of the Shadow Economy

4) Results of the Size of the Austrian, Czech, German, Polish and Slovakian Shadow Economies

5) Concluding Remarks

Appendix A1

Content

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2. Defining the Shadow Economy

Type of activity Monetary transactions Non-monetary transactions Illegal Activities

Trade with stolen goods; drug dealing and manufacturing; prostitution; gambling; fraud; etc.

Barter of drugs, stolen goods, smuggling etc. Produce drugs for own use. Theft for own use.

Tax Evasion

Tax Avoidance

Tax Evasion

Tax Avoidance

Legal Activities

Unreported income from self-employment; wages, salaries and assets from unreported work

Employee discounts, fringe benefits

Barter of legal services and goods

All do-it-yourself work; neighbor help; and voluntary work

Table 2.1: A taxonomy of types of underground economic activities

Structure of the table is taken from Lippert and Walker (1997, p. 5) with additional remarks

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The shadow economy includes all market-based legal production of goods and services that are deliberately concealed from public authorities for the following reasons:

(1) to avoid payment of income and/or indirect taxes,

(2) to avoid payment of social security contributions,

(3) to avoid certain legal labor market standards, such as minimum wages, maximum working hours, safety standards, etc., and

(4) to avoid complying with certain administrative procedures.


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Figure 2.1: Legal, shadow, illegal and informal economy and tax evasion

Legal/official economy

Shadow economy

Illegal (criminal) underground activities

Informal household economy;

do-it-yourself activities; voluntary activities

Pure tax evasion


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(1) These are microeconomic approaches that employ

either well designed surveys or samples based on

voluntary replies or tax auditing and other

compliance methods.

(2) Estimates of the shadow economy can also be based

on the discrepancy between income declared for tax

purposes and the actual detected one by audits.

Advantage of (1) and (2): Detailed knowledge about the

shadow economy on an individual basis.

3. Methods to Estimate the Size of the Shadow Economy3.1 Direct Approaches

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These approaches, which are also called “indicator”

approaches, are mostly macroeconomic ones and use various

(mostly economic) indicators that contain information about

the development of the shadow economy (over time).

Five indicator approaches:

3.2.1 The Discrepancy between National Expenditure and Income Statistics;

3.2.2 The Discrepancy between the Official and Actual Labor Force;

3.2.3 The Transactions Approach;3.2.4 The Currency Demand Approach; and3.2.5 The Physical Input (Electricity Consumption) Method.

3. Methods to Estimate the Size of the Shadow Economy3.2 Indirect Approaches

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Figure 3.1: MIMIC estimation procedure

Share of Direct taxation

Burden of state regulation

Employment quota

Change of local currency per capita

Average working time (per week)

Share of Indirect taxation and of social security contribution

Tax morale

Unemployment quota

GDP per capita (in US$)

Shadow

Economy

+

ε1

ε2

ε3

(1) Time Period: various years(2) The currency demand method will be used to transform the ordinal index into cardinal index

of shadow economy.

+

+

+

+

-

-

-

+

3. Methods to Estimate the Size of the Shadow Economy3.3 Multiple Indicators, Multiple Causes (MIMIC) Approach

30,6

28,0

27,7

26,2

25,8

23,6

23,3

23,3

22,4

21,9

20,6

18,2

18,2

17,6

16,2

15,1

14,1

13,2

12,4

12,3

12,2

12,0

11,3

9,4

9,0

8,2

0,0

5,0

10,0

15,0

20,0

25,0

30,0

35,0

Size

of t

he sh

adow

eco

nom

y (in

% o

f GD

P)

Figure 4.1: Size of the shadow economy of 25 European countries in 2015 (in % of official GDP)

4. Results of the Size of the Shadow Economies of 31 European Countries

November 2015 Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA 10 of 18

Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA

Figure 4.2: Size and development of the Czech and Slovakian shadow economies over 2005 to 2015 (in % of off. GDP)

18,5 18,117,0 16,6 16,9 16,7 16,4 16,0 15,5 15,3 15,117,6 17,3 16,8

16,016,8 16,4 16,0 15,5 15,0 14,6 14,1

0,0

2,0

4,0

6,0

8,0

10,0

12,0

14,0

16,0

18,0

20,0

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Size

of t

he S

hado

w E

cono

my i

n %

of G

DP

Czech Republic Slovakia

4. Results of the Size of the Shadow Economies in the Czech Republic and Slovakia

November 2015 11 of 18


Figure 4.3: Percentage change of the Czech and Slovakian shadow economies to the previous year over 2006 to 2015 (in %)

-2,2%

-6,1%

-2,4%

1,8%

-1,2% -1,8% -2,4%-3,1%

-1,3% -1,3%-1,7%-2,9%

-4,8%

5,0%

-2,4% -2,4%-3,1% -3,2% -2,7%

-3,4%

-7,0%

-5,0%

-3,0%

-1,0%

1,0%

3,0%

5,0%

7,0%

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Chan

ge in

the

Shad

ow E

cono

my i

n %

Czech Republic Slovakia

4. Results of the Size of the Shadow Economies in the Czech Republic and Slovakia


Table 4.1: Size and development of the shadow economies of the Czech Republic and her neighboring countries over 2005 to 2015

Countries/Year

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Austria 10.3 9.7 9.4 8.1 8.5 8.2 7.9 7.6 7.5 7.8 8.2

Czech Republic

18.5 18.1 17.0 16.6 16.9 16.7 16.4 16.0 15.5 15.3 15.1

Germany 15.4 15.0 14.7 14.2 14.6 13.9 13.2 12.9 12.4 12.2 12.2

Poland 27.1 26.8 26.0 25.3 25.9 25.4 25.0 24.4 23.8 23.5 23.3

Slovakia 17.6 17.3 16.8 16.0 16.8 16.4 16.0 15.5 15.0 14.6 14.1

Source: Calculation by Friedrich Schneider, University of Linz, Austria, January 2015.


4. Results of the Size of the Austrian, Czech, German, Polish and Slovakian Shadow Economies


Table 4.2: Average relative impact of the causal variables on the shadow economy in the Czech Republic and her neighboring countries (1998:2010) in %

Countries/YearPersonal income

tax

Indirect taxes

Tax morale

Unem-ployment

Self-employ-

ment

GDP-growth

Business Freedom

Austria 15.3 31.4 10.5 11.3 19.5 2.9 9.0

Czech Republic

6.3 34.3 8.2 17.2 21.7 4.1 8.1

Germany 13.8 28.0 7.5 22.9 16.1 2.6 9.1

Poland 4.8 31.9 7.3 23.9 23.6 3.4 5.0

Slovakia 3.4 35.4 4.9 28.5 14.8 6.1 6.9

Source: Schneider und Buehn (2015), p. 29.


4. Results of the Size of the Austrian, Czech, German, Polish and Slovakian Shadow Economies



(1) The size and development of the Czech shadow

economy has been continually decreasing since

2009. In 2015 it has a forecasted value of 15.1% of

official GDP, in the year 2003 it was 19.5%; hence, a

decline of 4.4 percentage points .

5. Concluding Remarks

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(2) Incentive-oriented policy measures could further

reduce the size and development of the Czech

shadow economy:

(2.1) An exemption of the value-added tax on labor-intensive

economic activities, like reconstruction of old houses.

(2.2) A mini-job regulation like in Germany.

(2.3) Labor-intensive services could be tax-deductible per

household up to a certain amount per year.


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(3) Through implementing such incentive-oriented

policy measures, strong incentives would shift

shadow economy activities to the official economy.

In this case all affected people/institutions would

profit, the public authorities with additional tax and

social security contribution revenues and the

“official” economy entrepreneurs with additional

work orders.


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Thank you very much for your attention!

November 2015 Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA 18 of 18


Table A.1: MIMIC model estimations (standardized coefficients) – Part 1

November 2015

Specification 2 3 4CausesPersonal income tax 0.33***

(3.99)0.37***(4.30)

0.40***(4.80)

Payroll taxes -0.11(1.35)

- -

Indirect taxes 0.22***(2.66)

0.31***(3.85)

0.21***(2.67)

Tax morale -0.22***(2.40)

-0.26***(2.84)

-0.22***(2.51)

Unemployment 0.65***(6.30)

0.63***(5.96)

0.55***(5.56)

Business freedom -0.26***(3.11)

-0.29***(3.36)

-0.35***(4.06)

Self-employment 0.30***(2.88)

0.34***(3.17)

0.33***(3.18)

Rule of Law -0.14*(1.83)

-0.10(1.31)

-0.08(1.03)

Appendix A1

Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIANovember 2015

Specification 2 3 4Causes

GDP growth0.30***(3.62)

0.31***(3.70)

0.27***(3.35)

Education - --0.31***

(3.51)Corruption - - -

IndicatorsGDP pc -0.52 -0.48 -0.51

Currency in circulation0.07

(1.07)0.10*(1.75)

0.10*(1.69)

Labour force participation-0.55***

(6.58)-0.52***

(6.36)-0.50***

(6.48)Observations 151 151 151Degrees of Freedom 54 42 52Chi-squared 89.68 24.10 32.51RMSEA 0.06 0.00 0.00

Note: The sample includes 39 OECD countries and the estimation period is 1998 to 2010. Absolute z-statistics are reported in parentheses. * , **, *** indicate significance at the 10%, 5%, and 1% level, respectively.

Appendix A1 (cont.)Table A.1: MIMIC model estimations (standardized coefficients) – Part 2

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