Imputed Rent (IR) = Income advantages from owner-occupied, rent-free and reduced-rent housing Baseline Model: Post-Govt.-Income:
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1 Imputed Rent (IR) = Income advantages from owner-occupied, rent-free reduced-rent housing Germany 2002 (SOEP); Denmark, Finl, France 2004 (EU-SILC) Baseline Model: Excluding Imputed Rent. Post-Govt.-Income: Annual income equivalized using the modified OECD-scale; EU-SILC: 1% top bottom trimming. Analysis population: Individuals living in private households with Post-Govt.-Inc.>0 SOEP Implementation of various approaches to measure net IR: (1) Opportunity-cost approach: Regression of gross rent per square meter paid by main tenants in private, non-subsidized housing using heckman-selection. Resulting regression coefficients are applied to otherwise comparable (or tenants in subsidized housing). From the resulting value all relevant costs (mortgage interest, maintenance operating) are deducted. (2) Capital Market approach: The net market-value (market-value minus outsting mortgages) is multiplied with a fix presumed real interest rate of,. From the resulting value owner-specific (maintenance operating) costs are deducted. (3) Self-assessment approach. The original question in the SOEP which is asked from only: "And if you lived in this flat or house as tenant: what do you estimate would be the monthly rent without heating costs? About... Euros." From the resulting value owner-specific (mortgage interest, maintenance operating) costs are deducted. Deduction of owner-specific costs: operating maintenance (1.585 Euro per month per square meter), interest on mortgages Source: SOEP, survey year EU-SILC Implementation of measuring IR; cf: Eurostat (2006): Imputed Rent, 3rd meeting of the EU-SILC task force on methodological issues, 4-5 April 2006, Doc. EU-SILC DOC TFMC-12/06. Denmark "User cost method", i.e. "Capital Market approach", for. Self-assessment approach for tenants. Finl: "Stratification rental equivalence" (Gross Net IR) France: "Regression rental equivalence", i.e. "Opportunity cost approach" Source: EU-SILC, survey year Table 1: Housing tenure Housing tenure (% population living in...) Germany 2002 Denmark 2004 Finl 2004 France 2004 Owner-occupied housing 47,4 67,2 71,4 60,4 Rented accomodation, total 52,6 32,8 28,6 39,6 thereof: # non-subsidized 42,5-11,7 21,1 # rent-free 2,7-0,9 4,0 # reduced rent 7,4-16,0 14,5 Total ,0 100,0 100,0 Source: SOEP 2002, EU-SILC Table 1a: Housing tenure IR Germany (Net IR) Denmark Finl France Finl Owner-occupied housing 74,5 94,6 100,0 97,4 96,1 Rented accomodation, total 19,1 3,8 6,3 36,9 6,3 thereof: # non-subsidized 0,0-0,0 0,0 0,0 # rent-free 100,0-74,2 81,5 74,2 # reduced rent 99,7-7,4 78,2 7,4 Total 45,4 64,8 73,2 73,5 70,5 Source: SOEP 2002, EU-SILC Population with positive IR by housing tenure (%)
2 Table 2: Beneficiaries from IR: Incidence Germany Denmark Finl France Finl Population share of beneficiaries from Imputed Rent (IR) using... Approach Equiv. Post-Gov`t Income Decile User-cost method (owners) / Selfassessment (tenants) Stratification rental equivalence (Opp.cost approach) Regression rental equivalence (Opp.cost approach) Stratification rental equivalence (Opp.cost approach) 1 (bottom) 42,5 20,8 16,2 19,8 20,6 21,1 39,7 52,9 55,5 52,0 2 39,1 25,0 17,5 21,0 22,9 24,2 38,8 57,3 65,0 56,7 3 44,0 31,5 22,8 27,5 32,2 34,2 45,2 61,3 66,2 59,7 4 39,8 29,6 24,6 32,0 34,5 32,6 55,2 70,7 67,3 69,4 5 47,8 35,5 30,0 35,7 38,8 37,5 64,3 72,8 75,7 69,3 6 45,5 38,1 31,4 41,5 44,6 40,3 72,1 78,9 75,8 75,1 7 45,4 39,3 37,8 45,9 49,9 42,4 78,1 80,3 80,8 76,0 8 47,9 40,6 37,7 45,9 48,6 42,8 81,1 82,8 81,7 79,8 9 48,8 44,1 42,7 51,1 55,1 48,4 83,9 86,1 82,7 82,0 10 (top) 52,9 48,8 53,0 59,5 62,5 50,4 89,7 89,1 84,3 84,6 Total 45,4 35,3 31,4 38,0 41,0 37,4 64,8 73,2 73,5 70,5 TOP in % of BOTTOM Table 3: Income Effects by decile: Relevance Germany Denmark Finl France Finl Baseline % Change in Equiv. Post Gov`t Income due to IR by decile using... Approach Equiv. Post-Gov`t Income Decile Euro Euro Euro Euro Euro 1 (bottom) ,6 8,8 2,9 6,3 9,9 11, , , , , ,5 6,0 2,1 4,5 6,9 7, , , , , ,3 5,8 2,3 4,8 7,4 7, , , , , ,2 4,6 1,8 4,0 6,3 6, , , , , ,4 5,8 2,5 5,0 7,7 7, , , , , ,2 5,6 2,3 4,9 7,6 7, , , , , ,5 5,1 2,7 5,3 8,1 6, , , , , ,3 4,9 2,4 4,8 7,3 6, , , , , ,5 4,8 2,2 4,6 7,0 5, , , , ,4 10 (top) ,3 4,6 2,3 4,6 6,8 5, , , , ,2 Total ,1 5,2 2,3 4,8 7,3 6, , , , ,1
3 Table 4: Income Effects by age Age Baseline % Change in Equiv. Post Gov`t Income due to IR by age using... Approach Euro Germany Denmark Finl France Finl Euro Euro Euro Euro Below ,7 3,6 1,4 3,2 5,1 4, , , , , ,0 4,5 2,0 4,0 6,2 5, , , , ,7 Over ,4 10,5 5,2 9,9 14,7 13, , , , ,6 Total ,1 5,2 2,3 4,8 7,3 6, , , , ,1 Table 5: Inequality Poverty effects Inequality / poverty Indicator Germany Denmark Finl France Finl % Change in inequality poverty due to IR using... Approach (using Baseline constant poverty line) Index Index Index Index Index Inequality Gini 0,2949-2,0 0,2 0,5 1,2 2,1 0,4 0,2195 3,9 0,2317-0,6 0,2675-0,1 0,2317-1,2 Atkinson 0.5 0,0762-5,0-0,5 0,6 1,3 2,6-0,5 0,0417 4,5 0,0433-1,5 0,0580-0,8 0,0433-2,5 Atkinson 1.5 0, ,0-3,6-0,2-0,3-0,3-3,3 0,1432-2,7 0,1257-1,3 0,1669-0,5 0,1257-2,7 Mean Log Dev. 0,1594-6,9-1,4 0,3 0,9 2,1-1,2 0,0915 2,1 0,0888-1,4 0,1202-0,6 0,0888-2,7 Half SCV 0,2690-6,3-2,4-0,2-0,7-0,8-3,3 0,0853 6,4 0,0979-2,4 0,1368-2,8 0,0979-2,7 Decile Ratio 90 : 50 1,88-1,8-0,3 0,2 0,5 1,4-0,1 1,57 2,7 1,67-0,9 1,82 0,1 1,67-0,7 90 : 10 3,66-3,4 1,6 0,4 2,3 5,1 2,3 2,68 4,0 2,85 0,7 3,32 1,7 2,85-0,5 50 : 10 1,95-1,5 2,0 0,2 1,8 3,6 2,4 1,71 1,2 1,70 1,6 1,82 1,7 1,70 0,2 Poverty FGT0 15,14-21,2-10,5-4,7-8,0-10,2-12,5 10,95-24,1 10,95-35,2 13,63-34,9 10,95-33,3 FGT1 4,38-24,5-11,3-4,4-8,3-11,6-13,3 2,84-21,1 2,04-37,3 3,14-35,0 2,04-35,4 FGT2 2,08-29,5-14,7-5,6-10,6-14,5-16,4 1,37-25,5 0,68-39,7 1,18-37,3 0,68-37,4 Table 6: Inequality decomposition by age Age Baseline % Change in inequality decomposition (MLD) due to IR by age using... Approach Mean Log Dev. Germany Denmark Finl Mean Log Dev. Mean Log Dev. Mean Log Dev. France Below 25 0,162-6,3 0,0 1,0 1,8 3,0 0,2 0,090 3,6 0,079 6,8 0,106 4,7 0,079 4, ,157-5,4-1,2 0,6 1,1 1,9-1,2 0,087 3,0 0,088-1,0 0,120-1,2 0,088-1,9 Over 64 0,132-10,9-2,4-0,2 1,5 4,9-0,6 0,076 2,3 0,075-8,9 0,131-6,7 0,075-9,2 Total 0,159-6,9-1,4 0,3 0,9 2,1-1,2 0,091 2,1 0,089-1,4 0,120-0,6 0,089-2,7 Within Group Ineq. 0,154-6,5-1,1 0,6 1,3 2,7-0,7 0,086 3,1 0,083 0,0 0,117-0,6 0,083-1,3 Between Group Ineq. 0,005-17,3-11,3-7,2-11,1-13,7-13,4 0,006-13,5 0,006-20,6 0,003 2,2 0,006-23,2 Mean Log Dev. Finl
4 Table 7: Poverty Risk Rate by age Germany Denmark Finl France Finl % Change in Poverty Risk Rate (FGT0) due to IR by age using... Approach (using constant Age Baseline poverty line) FGT 0 FGT 0 FGT 0 FGT 0 FGT 0 Below 25 20,5% -13,0-3,7-1,5-3,2-4,0-4,4 14, -10,7 13,1% -17,2 16,8% -24,2 13,1% -15, ,1% -19,9-8,6-4,1-6,8-8,6-10,1 7,7% -11,3 8, -27,8 11, -31,3 8, -25,3 Over 64 16,8% -39,0-27,6-12,0-19,3-25,2-32,8 16, -66,5 16,0% -73,9 14,9% -64,7 16,0% -73,9 Total 15,1% -21,2-10,6-4,7-8,0-10,2-12,5 11,0% -24,1 11,0% -35,1 13,6% -34,9 11,0% -33,4 Table 8: Poverty Intensity by age Germany Denmark Finl France Finl % Change in Poverty Intensity (FGT2) due to IR by age using... Approach (using Age Baseline constant poverty line) FGT 2 FGT 2 FGT 2 FGT 2 FGT 2 Below 25 3,36-22,3-7,6-2,0-4,7-7,1-8,1 1,95% -19,9 0,96% -23,1 1,59% -28,2 0,96% -20, ,60-28,7-15,5-4,9-9,9-14,0-17,3 1,27% -24,4 0,60% -45,8 1,07% -38,7 0,60% -44,1 Over 64 1,72-53,1-33,1-18,2-30,3-37,8-37,9 0,66% -60,8 0,47% -72,5 0,79% -64,2 0,47% -72,3 Total 2,08-29,5-14,6-5,6-10,6-14,5-16,4 1,37% -25,4 0,68% -39,6 1,18% -37,3 0,68% -37,7 Table 9: Poverty Decomposition (based on FGT2) by age Germany Denmark Finl France Finl % Change in contribution to aggregate poverty (FGT2) due to IR by age using... Approach Age Baseline (using constant poverty line) FGT 2 FGT 2 FGT 2 FGT 2 FGT 2 Below 25 42,6% 10,2 8,3 3,8 6,6 8,7 9,9 40,8% 7,3 40,7% 27,2 40,7% 14,6 40,7% 27, ,9% 1,2-1,0 0,8 0,8 0,5-1,1 51,5% 1,3 48,0% -10,3 47,8% -2,2 48,0% -10,1 Over 64 14,5% -33,5-21,6-13,4-22,0-27,2-25,8 7,7% -47,5 11, -54,4 11, -42,9 11, -55,5 Total 100,0% 100,0% 100,0% 100,0% 100,0%
5 Table 10: Inequality Rankings according to Gini, MLD, Half SCV Gini MLD Half SCV baseline model incl. IR baseline model incl. IR baseline model incl. IR DK FI FR GE * * Opportunity cost approach based on subsidized 1=lowest degree if inequality,..., 8=highest degree of inequality Table 10a: Inequality Rankings (according to MLD) by age Young population (<25) Population aged Elderly population (65 plus) baseline model incl. IR baseline model incl. IR baseline model incl. IR DK FI FR GE * * Opportunity cost approach based on subsidized 1=lowest degree if inequality,..., 8=highest degree of inequality Table 11: Correlation coefficients for different measures of IR in Germany, 2002 Opportunity cost (2 %) (3 %) (4 %) () 0,3823* () 0,4325* 0,9931* () 0,4542* 0,9862* 0,9985* Self-assessment 0,6330* 0,4136* 0,4514* 0,4667* Population:, only *: level of significance <5%. Source: SOEP 2002.
6 Company Cars (CC) = Income advantages from private use of company cars EU-SILC 2004: Belgium (BE), Denmark (DK), Estonia (EE), Finl (FI), Irel (IE), Luxembourg (LU), Norway (NO), Sweden (SE) Baseline Income Measure: Annual cash- near-cash income from employment (gross, employees only); 1% top bottom trimming. (EU-SILC-Variable name PY010G) Income Measure in "Change" Model: Baseline model income PLUS "non-cash components" (in EU-SILC 2004, this encompasses only "private use of company cars"). (EU-SILC-Variable name PY020G) Analysis population: Dependent employed individuals (=<65 years) with positive cash- near cash employee income Source: EU-SILC, survey year Table CC-1: Beneficiaries by cash employee income quintile (% Population receiving CC) [Incidence] Cash Employee Income Quintile BE DK EE FI IE LU NO SE 1 (bottom) 0,6 2,2 1,2 11,3 0,4 0,9 0,2 12,3 2 2,5 2,2 3,5 15,5 0,5 3,1 0,9 16,9 3 5,6 3,2 5,3 16,9 1,8 3,3 1,0 20,6 4 7,0 6,4 7,2 29,1 4,3 3,4 1,4 29,8 5 (top) 22,6 25,9 15,1 52,4 8,5 14,6 6,1 53,1 Total 7,7 8,0 6,5 25,0 3,1 5,0 1,9 26,5 Table CC-2: Income Effects by cash employee income quintile (% Share of income due to CC) [Relevance] Cash Employee Income Quintile BE DK EE FI IE LU NO SE Euro Euro Euro Euro Euro Euro Euro Euro 1 (bottom) , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,54 5 (top) , , , , , , , ,34 Total , , , , , , , ,17 Table CC-3: Inequality effects Inequality indicator BE DK EE FI IE LU NO SE Index Index Index Index Index Index Index Index Inequality Gini 0,297 0,39 0,247 1,29 0,386 1,25 0,272 1,76 0,378 0,45 0,369 0,41 0,320 0,73 0,324 1,31 Atkinson 0.5 0,081 0,65 0,058 2,18 0,123 2,41 0,066 3,15 0,123 0,80 0,113 0,81 0,099 1,10 0,108 1,65 Atkinson 1 0,177 0,52 0,128 1,66 0,242 2,12 0,141 2,44 0,260 0,60 0,231 0,65 0,226 0,77 0,263 0,88 Atkinson 1.5 0,302 0,39 0,221 1,20 0,362 1,80 0,232 1,81 0,413 0,42 0,354 0,52 0,392 0,49 0,501 0,23 Mean Log Dev. 0,195 0,58 0,137 1,79 0,277 2,45 0,153 2,64 0,301 0,70 0,263 0,75 0,256 0,87 0,305 1,03 Half SCV 0,156 1,05 0,107 4,07 0,305 3,42 0,131 5,83 0,253 1,69 0,242 1,58 0,174 2,47 0,179 4,23 Decile Ratio 90 : 50 1,793 0,28 1,618 0,56 2,453-0,69 1,737 1,38 2,259 0,35 2,277 0,31 1,706 0,59 1,726 1,10 90 : 10 4,496 0,40 3,414 0,76 6,077 1,74 3,969 1,71 8,615 0,34 7,044 1,02 7,276 0,69 8,434 1,02 50 : 10 2,506 0,25 2,110 0,21 2,475 2,54 2,283 0,46 3,817 0,00 3,096 0,62 4,274 0,00 4,878 0,00 Table CC-4: Inequality Rankings Gini MLD Half SCV baseline model incl. CC baseline model incl. CC baseline model incl. CC DK FI BE NO SE LU IE EE =lowest degree if inequality,..., 8=highest degree of inequality
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