The crisis and tax evasion in Greece What are the distributional implications? Manos Matsaganis, Chrysa Leventi & Maria Flevotomou 2 nd Microsimulation Research Workshop Bucharest, 11 October 2012

the paper o introduction o methodology and data o results - discussion o conclusion 1 / 22

the paper o introduction o methodology and data o results - discussion o conclusion 2 / 22

introduction o The current Greek crisis and the country’s fiscal consolidation effort have elevated tax evasion to one of the most crucial policy issues of our times o Tax evasion hinders the fiscal efficiency of tax policies most recent estimate of Greece’s informal economy: 24% of GDP (Schneider 2012) o Tax evasion creates horizontal inequality, leads to unfair social outcomes and distorts the intended distributional effect of the tax system 3 / 22

aim of paper to estimate non-compliance patterns of income under- reporting in Greece  by comparing the incomes reported in a large sample of tax returns in 2007 (incomes earned in 2006) with those observed in the EU-SILC survey of that year  redo the exercise for incomes earned in 2010 to estimate the distributional implications of personal income tax evasion in the general population  by using EUROMOD 4 / 22

the paper o introduction o methodology and data o results - discussion o conclusion 5 / 22

empirical research o Two main approaches 1. Macroeconomic approach: use of macroeconomic indicators 2. Microeconomic approach: use of microeconomic data expenditure based method discrepancy method: comparing two alternative and independent measurements of the same variable  comparing income declared to tax authorities to income declared to household income surveys  crucial assumption: individuals reveal their income to survey interviewers more truthfully than they do when filing their tax return 1. 6 / 22

discrepancy method: studies source reference year countrymethod income under- reporting Slemrod & Yitzhaki 1988U.S.A.tax auditing empl: 0.5% self empl: 58.6% Johns & Slemrod 2001U.S.A.tax auditing empl: 1% self empl: 57% Fiorio & D’ Amuri 2000Italy comparison with hh surveys empl: 1.9% self empl: 27.7% Marino & Zizza 2004Italy comparison with hh surveys empl: -1.6% self empl: 56.3% Benedek & Lekles 2005Hungary comparison with hh surveys empl: 4% self empl: 67% Matsaganis & Flevotomou 2004Greece comparison with hh surveys empl: 0.6% self empl: 24.4% 7 / 22

our dataset 1. A large panel data sample of income tax returns filed in (incomes earned in ) 301,577 tax filers in 196,742 tax units (4.3% of tax filers in 2007) 2. EU-SILC 2007 (incomes earned in 2006) 14,759 individuals in 5,643 households  EU-SILC 2011 (2010 incomes) has not yet been released. Solution: uprate EU-SILC 2007 (2006 incomes) to 2010 on the basis of estimates provided by the Bank of Greece, EL.STAT. 8 / 22 improvement \

methodology[1] 1. Create comparable reference populations both datasets were reduced to: a.people reporting annual income from wages/pensions above €6,000 b.people reporting annual farming/self-employment income above €3,000 (i.e. restrictive set of rules for filing a tax return) 2. Create comparable income variables gross incomes minus social insurance contributions 9 / 22

methodology [2] 3. Allocate the reference population into 16 categories defined as combinations of 4 macro-regions and 4 income sources: zFocusing on income sources allows us to account for individuals earning income from multiple sources (‘moonlighting’) macro regions (i)income sources (j) Atticawages and salaries northern Greecepensions central Greeceagricultural income islands other self-employment income (income from commercial business, liberal professions, property) 10 / 22 improvement \

methodology [3] 4. Create adjustment factors: a i,j = Ỹ R i,j / Ỹ T i,j where: Ỹ R i,j = average income from source j by people in region i in tax returns Ỹ T i,j = average income from source j by people in region i in EU-SILC 5. Use these factors for the estimation of a ‘synthetic’ (i.e. adjusted for under-reporting) EU-SILC income distribution  introduction of a zero-mean random term around the estimated rates of income under-reporting by category 6. Use EUROMOD to calculate tax liability and disposable income based on the original and the ‘synthetic’ EU-SILC income distributions 11 / 22 improvement \

the paper o introduction o methodology and data o results - discussion o conclusion 12 / 22

results[1] o Under-reporting by income source and region (%) population share income source wages pensions farming self-employment region northern central Attica islands total / 22

results[2] 14 / 22

results[3] o Income - tax variables (2006) full compliance tax evasion difference (%) mean reported income15,42213, mean tax due4,2613, mean disposable income11,99312, total tax receipts (mill. €)12,1318, Note: mean incomes/taxes are non-equivalised annual personal incomes/taxes in €. They are constructed excluding those earning zero or negative incomes/ paying zero tax. Actual total income tax receipts in 2006 were €8,318 million. The share of positive income earners paying non zero tax is 40.3% under full compliance and 34.4% under tax evasion. 15 / 22

results[4] o Poverty and inequality (2006) full compliancetax evasiondifference poverty line (€ p.a.)6,0416, % poverty rate p.p. Gini % S80/S % coefficient of variation % Note: poverty and inequality indices are computed on the basis of equivalised household disposable income (HDI). The poverty line is set at 60% of median equivalised HDI. 16 / 22

results[5] o Personal income tax progressivity (2006) full compliancetax evasiondifference Kakwani % Reynolds-Smolensky % Note: tax progressivity indices are computed on the basis of equivalised HDI. In the absence of any re-ranking of individuals pre and post-tax, the two indices are proportional. 17 / 22

discussion o Income under-reporting: varies widely by income source and region is biggest at the two ends of the income distribution (U shape)  concentration of pensioners and wage earners in the middle of the distribution reduces personal income tax revenues by 27.8%  14.6% fewer persons paying on average 15.2% less tax o Tax evasion causes a slight increase in relative poverty but a significant increase in income inequality o It severely reduces the progressivity of the tax system 18 / 22

the paper o introduction o methodology and data o results - discussion o conclusion 19 / 22

reasons for caution o measurement & sampling errors o bias from the exclusion of people not filing a tax return o income uprating imperfect o assumption that people reveal their true income in EU-SILC 20 / 22

policy implications o fight against tax evasion both fiscally important and politically crucial o refinement of audit targeting and audit coverage o policy making in the field of taxation should consider tax evasion’s distortionary effects in the intended progressivity of personal income tax 21 / 22

further research o add more dimensions in the construction of adjustment factors o perform sensitivity analysis o re-estimate 2010 under-reporting factors when EU-SILC 2011 becomes available 22 / 22