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 Schneider Department of Economics Johannes Kepler University of Linz A-4040 Linz-Auhof ShadEcEstimation_CzechRep.ppt Phone: Fax: of 18

November 2015  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA 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 2 of 18

November 2015  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA 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 3 of 18

November 2015  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA 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 4 of 18

November 2015  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA 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. 2. Defining the Shadow Economy 5 of 18

November 2015  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA 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 2. Defining the Shadow Economy 6 of 18

November 2015  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA (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 Economy 3.1 Direct Approaches 7 of 18

November 2015  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA 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: 3.2.1The Discrepancy between National Expenditure and Income Statistics; The Discrepancy between the Official and Actual Labor Force; The Transactions Approach; The Currency Demand Approach; and The Physical Input (Electricity Consumption) Method. 3. Methods to Estimate the Size of the Shadow Economy 3.2 Indirect Approaches 8 of 18

November 2015  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA 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 + ε1ε1 ε2ε2 ε3ε3 (1)Time Period: various years (2)The currency demand method will be used to transform the ordinal index into cardinal index of shadow economy Methods to Estimate the Size of the Shadow Economy 3.3 Multiple Indicators, Multiple Causes (MIMIC) Approach

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) 4. Results of the Size of the Shadow Economies in the Czech Republic and Slovakia November of 18

 Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA Figure 4.3: Percentage change of the Czech and Slovakian shadow economies to the previous year over 2006 to 2015 (in %) 4. Results of the Size of the Shadow Economies in the Czech Republic and Slovakia November of 18

Table 4.1: Size and development of the shadow economies of the Czech Republic and her neighboring countries over 2005 to 2015 Countries/ Year Austria Czech Republic Germany Poland Slovakia Source: Calculation by Friedrich Schneider, University of Linz, Austria, January  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA 4. Results of the Size of the Austrian, Czech, German, Polish and Slovakian Shadow Economies November of 18

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/Year Personal income tax Indirect taxes Tax morale Unem- ployment Self- employ- ment GDP- growth Business Freedom Austria Czech Republic Germany Poland Slovakia Source: Schneider und Buehn (2015), p. 29.  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA 4. Results of the Size of the Austrian, Czech, German, Polish and Slovakian Shadow Economies November of 18

November 2015  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA (1)The size and development of the Czech shadow economy has been continually decreasing since 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 15 of 18

November 2015  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA (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. 5. Concluding Remarks 16 of 18

November 2015  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA (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. 5. Concluding Remarks 17 of 18

Thank you very much for your attention! November 2015  Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA 18 of 18

 Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA Table A.1: MIMIC model estimations (standardized coefficients) – Part 1 November 2015 Specification234 Causes Personal income tax 0.33*** (3.99) 0.37*** (4.30) 0.40*** (4.80) Payroll taxes (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) (1.31) (1.03) Appendix A1

 Prof. Dr. Friedrich Schneider, University of Linz / AUSTRIA November 2015 Specification234 Causes GDP growth 0.30*** (3.62) 0.31*** (3.70) 0.27*** (3.35) Education *** (3.51) Corruption--- Indicators GDP pc Currency in circulation 0.07 (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) Observations151 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. Appendix A1 (cont.) Table A.1: MIMIC model estimations (standardized coefficients) – Part 2