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Distribution of marginal effective tax rate in Croatia: do taxes and benefits prevent people from getting employed?. Slavko Bezeredi & Ivica Urban Institute of Public Finance, Zagreb. 2013 EUROMOD research workshop University of Lisbon , October 2013. Goals.
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Distribution of marginal effective tax rate in Croatia: do taxes and benefits prevent people from getting employed? SlavkoBezeredi & IvicaUrban Institute of Public Finance, Zagreb 2013EUROMODresearch workshop UniversityofLisbon, October 2013
Goals • Do taxes and benefits prevent people from getting employedin Croatia? • How high is the marginal effective tax rate (METR) for long-termunemployed and inactive people? • ...speculating (inour model) whether to remain out of work or to get employment • ...peoplefrom a micro-data sample
Problems • (A) Calculate net household income, taxes and benefits, paid/received • miCROmod – microsimulation model • ...uses new 2010 Croatian income survey (harmonised with EU-SILC) • (B) Obtain gross wages for unemployed and inactive, because they are not available in the sample • Wage regression – „selection problem” – tobit II model
Model • A person Q is planning what to do in the next one-year period • ...calculates what would be her household’s income in two different hypothetical states: “0” remains unemployed or inactive “1” gets employed at full-time job M= marginaleffectivetax rate (METR) X,Y, T, B = household’s pre-fiscalincome, post-fiscalincome, taxesandbenefits
Model pre-fiscalincome = Q’s grosswage + + othergrossincomes in Q’s household
Model Notavailableinthedataset... working not-working „selection problem” – becausethe „not-working” are outofsample iworks idoesnot work
Data • EU-SILC Croatia for 2010 • 6,403 householdswith 16,948 members • investigated: long-termunemployedandinactivepeopleaged 16to 65 • pensioners, students and unable to work are excluded from the analysis
Data • Workers: 4.460 persons who worked more than 1000 hours during the year and reported a positive gross wage • Unemployed: 1.616 persons who declared themselves as unemployed during the whole year(0working hours) • Inactive: 684 persons who declared themselves as “housewifes” or “other inactive” during the greater part of the year (0 working hours)
Populationstructure 16 to 65 years
Probit regression (marginaleffects) Threemodels: (1) Notworking are unemployedandinactivetogether (2) unemployedonly (3)inactiveonly
METR - results Unemployed Inactive
Conclusion • distribution of METR for long-termunemployed and inactive; for various subgroups • for majority of unemployed and inactive people METR is relatively low, and should not be the factor detrimental to entering employment • 55% ofunemployedand 71% ofinactivehavelow METR (<30%) • veryhigh METR (>70%) for 3.2% • particularlyvunerablepersons: (a) with three and more children, (b) whose spouses are also inactive or unemployed, (c) withprimaryeducation • the results suggest that policies to make work pay should target thesemost vulnerable groups