SHADOW ECONOMIES IN 7 EASTERN EUROPEAN COUNTRIES: LATEST RESULTS AND WHAT ARE THE DRIVING FORCES?

Transcription

1 ShadEc_EasternEurope2015_DrivingForces_short.ppt SHADOW ECONOMIES IN 7 EASTERN EUROPEAN COUNTRIES: LATEST RESULTS AND WHAT ARE THE DRIVING FORCES? November 17, 2015 Prof. Dr. Friedrich Schneider friedrich.schneider@jku.at Phone:

2 OUTLINE 1. Introduction 2. Some Theoretical Considerations 3. The Size of the Shadow Economies 4. Summary and Policy Measures Against the Shadow Economy November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 2 of 28

3 1. INTRODUCTION (1) Size and development of the shadow economies are hot scientific and political topics around the world. (2) Numerous political statements, that the shadow economy causes severe damages on the official economy. (3) Unfair (ruinous) competition between the entrepreneurs working in the shadow economy and the ones working in the official economy! (4) Mostly only one common policy measure: increase effective punishment to get rid of the shadow economy. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 3 of 28

4 1. INTRODUCTION Aim of this lecture: (i) (ii) (iii) Empirical results about the size of the shadow economies of seven Eastern European countries. Analysing the most influential factors on (driving forces of) the shadow economies in these countries. Some incentive oriented policy measures against the shadow economy. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 4 of 28

5 2. SOME THEORETICAL CONSIDERATIONS 2.1 DEFINITIONS (i) The shadow economy includes all legal production and provision of goods and services, that are deliberately concealed from public authorities for the following four reasons: (1) To avoid income, value added or other taxes, (2) to avoid social security contributions, (3) to avoid having to meet certain legal standards such as minimum wages, safety standards, etc., and (4) to avoid complying with certain administrative procedures. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 5 of 28

6 2. SOME THEORETICAL CONSIDERATIONS 2.1 DEFINITIONS (ii) (iii) (iv) Underground (classical crime) activities are all illegal actions that fit the characteristics of classical crime activities like burglary, robbery, drug dealing, etc. Informal household economy consists of household activities (e.g. do-it-yourself ) that are not registered officially under various specific forms of national legislation. These two activities are not included in the shadow economy activities. However, there are overlapping areas; e.g. for (ii) prostitution and for (iii) do-it-yourself activities. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 6 of 28

7 2.1 DEFINITIONS Figure 2.1: Legal, shadow, illegal and informal economy Illegal (criminal) underground economy Informal household economy (e.g. do-ityourself activities) Shadow economy Tax evasion from shadow economy activities Legal/official economy November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 7 of 28

8 2. SOME THEORETICAL CONSIDERATIONS 2.2 MEASURING THE SHADOW ECONOMY Three procedures: (1) Direct procedures using the micro level and aiming at determining the size of the shadow economy. An example of this method are surveys. (2) Indirect procedures that make use of macroeconomic indicators proxying the development of the shadow economy over time; e.g. the currency demand approach. (3) Statistical models that use statistical tools to estimate the shadow economy as an unobserved or latent variable; e.g. the MIMIC (Multiple Indicator, Multiple Causes) Method. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 8 of 28

9 2.3 ESTIMATION OF THE SIZE OF THE SHADOW ECONOMY Figure 2.2 MIMIC Estimation Procedure 1) Causes: Share of Direct taxation Share of Indirect taxation and of social security contribution Burden of state regulation Tax morale Unemployment quota GDP per capita (in US$) Shadow Economy Indicators: Employment quota Average working time (per week) Change of local currency per capita ε 1 ε 2 ε 3 1) The estimations of the currency demand method for single countries will be used to transform the ordinal shadow economy indices to cardinal values of shadow economy. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 9 of 28

10 2. SOME THEORETICAL CONSIDERATIONS 2.3 ESTIMATION OF THE SIZE OF THE SHADOW ECONOMY Calculation of the size of the shadow economy: (1) The estimation of the size of the shadow economy is a combination of the MIMIC procedure and the currency demand method. (2) The first assumes that the shadow economy is an unobserved phenomenon which is estimated using causes, e.g. tax burden, regulation intensity, and indicators, e.g. currency demand and official work time. A disadvantage of the MIMIC procedure is that it produces only relative estimates of the size of the shadow economy. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 10 of 28

11 2. SOME THEORETICAL CONSIDERATIONS 2.3 ESTIMATION OF THE SIZE OF THE SHADOW ECONOMY Calculation of the size of the shadow economy: (3) The currency demand method is used to calibrate the relative estimates from the MIMIC method into absolute ones by using two or three the absolute values of the absolute size of the shadow economy. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 11 of 28

12 2. SOME THEORETICAL CONSIDERATIONS 2.4 MAIN CAUSES DETERMINING THE SHADOW ECONOMY i. Tax and Social Security Contribution Burdens Increase Increase in shadow economy, ceteris paribus. ii. Intensity of Regulations Increase Increase in shadow economy, ceteris paribus. iii. Public Sector Services Decrease Increase in shadow economy, ceteris paribus. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 12 of 28

13 2. SOME THEORETICAL CONSIDERATIONS 2.4 MAIN CAUSES DETERMINING THE SHADOW ECONOMY iv. Quality of Public Institutions In particular, corruption is associated with larger unofficial (shadow) activities, while a good rule of law by securing property rights and contract enforceability, increases the benefits of being legal, ceteris paribus. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 13 of 28

14 2. SOME THEORETICAL CONSIDERATIONS 2.4 MAIN CAUSES DETERMINING THE SHADOW ECONOMY v. The lower the tax morale, the higher the incentive to work in the shadow economy, ceteris paribus. vi. vii. The higher the unemployment, the more people engage in shadow economy activities, ceteris paribus. The lower the GDP per capita in a country, the higher is the incentive to work in the shadow economy, ceteris paribus. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 14 of 28

15 3. THE SIZE OF THE SHADOW ECONOMIES Table 3.1: MIMIC-estimation of 39 OECD countries; estimation period: 1998/ Specification / Causes Personal income tax Indirect taxes Tax morale Unemployment rate Business freedom Self-employment rate Rule of Law GDP growth *** (4.30) 0.31*** (3.85) -0.26*** (2.84) 0.63*** (5.96) -0.29*** (3.36) 0.34*** (3.17) (1.31) 0.31*** (3.70) Education *** (4.80) 0.21*** (2.67) -0.22*** (2.51) 0.55*** (5.56) -0.35*** (4.06) 0.33*** (3.18) (1.03) 0.27*** (3.35) -0.31*** (3.51) Corruption *** (4.74) 0.24*** (2.97) -0.21*** (2.38) 0.53*** (5.47) -0.35*** (4.20) 0.27*** (2.57) *** (3.52) -0.26*** (2.83) 0.14 (1.56) November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 15 of 28

16 3. THE SIZE OF THE SHADOW ECONOMIES Table 3.1: MIMIC-estimation of 39 OECD countries; estimation period: 1998/ (cont.) Indicators GDP pc Currency in circulation per capita 0.10* (1.75) 0.10* (1.69) 0.08 (1.26) Labour force participation rate -0.52*** (6.36) -0.50*** (6.48) -0.51*** (6.46) Observations Degrees of Freedom Chi-squared RMSEA Note: The sample includes 39 OECD countries and the estimation period is 1998 to Absolute z-statistics are reported in parentheses. *, **, *** indicate significance at the 10%, 5%, and 1% level, respectively. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 16 of 28

17 3. THE SIZE OF THE SHADOW ECONOMIES Bulgaria Romania Turkey Croatia Estonia Lithuania South-Cyprus Malta Latvia Poland Slovenia Greece Hungary Italy Spain Average Portugal Belgium Czech Republic Slovakia Sweden Norway Finland France Germany Denmark Ireland United Kingdom Netherlands Luxembourg Austria Switzerland Figure 3.1: Size of the shadow economies of 31 European countries in 2015 (in % of off. GDP) Source: own calculations, January November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 17 of 28

18 3. THE SIZE OF THE SHADOW ECONOMIES Table 3.2: Size and Development of the Shadow Economies of 7 Eastern European Countries (Bulgaria, Estonia, Hungary, Latvia, Lithuania, Poland, Romania) 2003 to 2015 in % of GDP Country/ Year Average over Bulgaria Estonia Hungary Latvia Lithuania Poland Romania Source: Calculation by Friedrich Schneider. University of Linz, Austria, January November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 18 of 28

19 3. THE SIZE OF THE SHADOW ECONOMIES Table 3.3: Size of the shadow economies of the Baltic countries in % of GDP (95% confidence intervals in parentheses) Country / Year Estimation Method Estonia 1) Estonia 2) Latvia 1) Latvia 2) Lithuania 1) Lithuania 2) 20.2% (18.7, 21.7) 29.6% (28.0, 31.2) 36.6% (34.3, 38.9) 27.1% (24.7, 29.5) 17.7% (15.8, 19.7) 29.6% (27.7, 31.5) 19.4% (18.0, 20.8) 29.3% (27.7, 30.9) 38.1% (35.9, 40.3) 27.3% (24.9, 29.7) 18.8% (16.9, 20.6) 29.7% ( ) 1) Source: Putnins and Sauka (2015), Table 1, p.13 2) Source: Schneider (2015) 18.9% (16.8, 20.9) 28.6% (27.0, 30.2) 30.2% (27.6, 32.7) 26.5% (24.1, 28.9) 17.1% (15.2, 19.0) 29.0% (27.1, 30.9) 19.2% (16.6, 21.9) 28.2% (26.6, 29.8) 21.1% (18.5, 23.6) 26.1% (23.7, 28.5) 18.2% (16.4, 20.1) 28.5% (26.6, 30.4) 15.7% (13.5, 17.9) 27.6% (26.0, 29.2) 23.8% (20.7, 26.9) 25.5% (23.1, 27.9) 15.3% (13.6, 17.1) 28.0% (26.1, 29.9) 13.2% Index (11.3, 15.1) Approach 27.1% (26.3, 29.9) MIMIC 23.5% Index (20.5, 26.6) Approach 24.7% ( ) MIMIC 12.5% Index (11.0, 13.9) Approach 27.1% ( ) MIMIC November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 19 of 28

20 3. THE SIZE OF THE SHADOW ECONOMIES Size of the shadow economy in % of GDP Figure 3.2: Size of the shadow economies of the Baltic countries in % of GDP 40 Putnins and Sauka Schneider Estonia Latvia Lithuania 1) Source: Putnins and Sauka (2015), Table 1, p. 13 2) Source: Schneider (2015) November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 20 of 28

21 3. THE SIZE OF THE SHADOW ECONOMIES Table 3.4: Average relative impact (in %) of the shadow economy determinants in 7 Eastern European countries (1999 to 2010) Average impact in % Country Personal income tax Indirect taxes Tax morale Unemploy -ment Selfemployment GDP growth Business freedom Bulgaria 3.7% 43.0% 4.6% 20.9% 15.7% 6.0% 6.0% Estonia 7.8% 39.2% 9.6% 18.8% 9.3% 7.4% 7.8% Hungary 9.8% 38.9% 5.5% 16.8% 16.9% 4.3% 7.7% Latvia 6.5% 35.3% 12.0% 19.3% 12.4% 8.2% 6.3% Lithuania 7.3% 32.9% 14.6% 16.8% 15.5% 6.6% 6.2% Poland 4.8% 31.9% 7.3% 23.9% 23.6% 3.4% 5.0% Romania 3.3% 27.9% 12.9% 12.0% 33.0% 5.6% 5.4% Source: Schneider and Buehn (2015), Table 10. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 21 of 28

22 3. THE SIZE OF THE SHADOW ECONOMIES Table 3.5: Size and development of pure tax evasion (in % of GDP) in 7 Eastern European countries Country Bulgaria Estonia Hungary Latvia Lithuania Poland Romania Average over 38 countries Source: Buehn and Schneider (2012) Aver -age November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 22 of 28

23 4. SUMMARY AND POLICY MEASURES AGAINST THE SHADOW ECONOMY (1) Is a decreasing size of the shadow economy a blessing or a curse? 60% of all activities in the shadow economy complement those in the official sector, 40% of the shadow economy activities substitute the official sector and could be shifted to the official one. A decline of the shadow economy will increase total welfare only if almost all of it is transferred into the official one. Only such policy measures should be implemented that increase the incentive to move the production from the unofficial into the official economy. Only then the decline of the shadow economy will be a blessing for the entire economy. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 23 of 28

24 4. SUMMARY AND POLICY MEASURES AGAINST THE SHADOW ECONOMY (2) Cash is still used in many shadow economy activities because it does not leave traces. A reduction of cash can reduce shadow economy activities as transaction costs rise, but as the profits of shadow economy activities are still very high, the reduction will be modest (10-20% at most!). (3) Besides the indirect tax and personal income tax burden, which the government can directly influence by policy actions, self-employment and unemployment are very important. (4) Unemployment may be controllable by the government through economic policy in a traditional Keynesian sense. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 24 of 28

25 4. SUMMARY AND POLICY MEASURES AGAINST THE SHADOW ECONOMY (5) The impact of self-employment on the shadow economy is only partly controllable and may be ambiguous from a welfare perspective. (6) Government can deregulate the economy or incentivize to be your own entrepreneur, which would make selfemployment easier. (7) Such actions however need to be accompanied with a strengthening of institutions and tax morale to reduce the probability that self-employed shift reasonable proportions of their economic activities into the shadow economy. (8) My paper clearly shows that a reduction of the shadow economy can be achieved using various channels the government can influence. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 25 of 28

26 4. SUMMARY AND POLICY MEASURES AGAINST THE SHADOW ECONOMY Outlook: Concept of a digital shadow economy (1) Digital shadow economy is a part of shadow economy, when illegal profit-driven online trade or service provision is performed. (2) Digital shadow economy refers to global networks emerging in closed internet forums and promoting chains of e-crimes, including bank attacks, payment card crimes, identity steals and other internet intrusions. (3) (Un-)interrupted, financial gain driven provision of particular commodities or services in the remote space, performed without activity registration. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 26 of 28

27 4. SUMMARY AND POLICY MEASURES AGAINST THE SHADOW ECONOMY Outlook: Concept of a digital shadow economy (4) Digital shadow economy is an illegal operation in the internet space, which generates illegal money flows for commodity/service providers or purchasers, and deprives legal traders/service providers from the revenue that could be officially accounted, calculated and declared. November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 27 of 28

28 THANK YOU VERY MUCH FOR YOUR ATTENTION November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 28 of 28

29 Appendix: THE SIZE OF THE SHADOW ECONOMIES in % of official GDP Figure A.1: Size of the shadow economies of the Baltic countries Estionia, Latvia and Lithuania from 2005 to 2015 (in % of off. GDP) Estonia Latvia Lithuania Source: own calculations, January November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 29

30 Appendix: THE SIZE OF THE SHADOW ECONOMIES in % of official GDP Figure A.2: Size and development of the Bulgarian, Hungarian, Polish and Romanian shadow economies over 2005 to 2015 (in % of off. GDP) Bulgaria Hungary Poland Romania Source: own calculations, January November 2015 Prof. Dr. Friedrich Schneider, University of Linz, Austria 30