1. Matti Viren Department of Economics and Public Choice Research Centre, University of Turku, and Monetary policy and Research Department, Bank of Finland Housing allowance: subsidy to landlords? Presentation at the RPTU workshop in Bank of Finland, November 26, 2009

2. Research problem Incidence of housing assistance (subsidy), who will finally get the subsidy, who will pay? Next to pensions, biggest income transfer in Finland Literature: Ditch, J. Lewis, A. and Wilcox, S. (2001) Fack (2006) Gibbons, S., Manning, A. (2003) Kangasharju, A. (2003, 2008) Olsen, E. (2001) Poterba, J. (1984) Rosen, H. (1985) Slesnick, D.T. (1996) Susin, S. (2002)

3. Policy problem Allowances (subsidy to housing) create deadweight losses Allowances increase the general rent level; also the rents of those who do not receive allowances will increase Income dependence of allowances creates poverty traps Large fiscal burden; inflationary bias

4. Government Poor households Other households Rents increase House prices increase due to capitalization of subsidies Rent income increases Landlords Tax revenues increase Transfer of income

5. What are the demand and supply elasticities? D S D’ P Q Elasticities are probably not very high; no “corner” solutions

6. Estimating equation ( v/p) it = a 0i + a 1 (MC/p) t + a 2 N t + a 3 Space t + a 4 Year t + a 5 (Y/p) t + a 6 (Max/p) t + a 7 D t + u it, where v denotes the rent level, MC the cost of renting, N the size of household, Year the age of house, Y income, p the price level and Max the maximum amount of subsidy. D is a dummy for not changing the apartment. Alternative: “Event study” framework

7. The data Two set of data are used: (1) Large panel data with 50 000 households for 2000-2008 from the Finnish National Pension Fund which consist of households that have obtained housing allowance in 2008, and (2) Finnish income distribution data that consist of about 26500 households (half of the annual sample is overlapping)

12. % -muutos% -osuus x < - 150.31 -15 ≤ x < -100.14 -10 ≤ x < -50.91 -5 ≤ x < 07.49 x = 026.83 0 < x ≤ 550.52 5 < x ≤ 109.97 10 < x ≤ 152.26 15 < x ≤ 200.77 25 < x ≤ 250.22 25 < x0.58 Annual changes in the rent level, n = 4163

13. Frequencies of annual changes in rents, %, n=152623

14. Change of rent for those who receive allowance

16. Estimation Results in the subsequent tables represents panel data estimates for 2000-2008 with or without fixed effects. Table 3 represents cross-estimates for the 2007 Finnish income distribution data The displayed results are OLS estimates, here the estimator (e.g. using the GMM) does not seem to make much difference.

17. (1) level (2) level (3) Level (4) log (5) Log (6) Level/m 2 Max/P.435 (42.02).429 (26.65).269 (14.67).345 (36.36).204 (20.35).589 (40.17) MC/P.352 (51.00).389 (47.66).342 (43.92).235 (49.78).219 (48.03) 4.800 (31.75) Space.185 (37.06).194 (24.69).226 (23.95).361 (45.58).434 (53.72) -.002 (27.40) N-.185 (9.53) -.310 (8.25) -.006 (1.67) -.022 (4.96).018 (4.02) -.006 (7.62) Y/P3.862 (30.74) 4.219 (8.56).003 (5.42).009 (8.96).005 (5.25).014 (1.43) Age of the house -.013 (15.46) -.020 (8.88) -.027 (12.24) -.527 (6.06) -.008 (9.43).037 (6.77) No change-.057 (16.61) -.045 (14.02) -.020 (16.49) -.017 (14.23) -.008 (10.81) R2R2 0.9350.9520.9560.9520.9560.895 DW1.281.481.491.451.461.47 Fixed ECS CS +localCSCS + local Rent equation estimates

18. (1) level (2) log (3) log (4) log (5) Log Assistance /p.503 (23.53).186 (70.09).215 (84.39).068 (49.69).078 (52.72) Y/P.101 (18.01).139 (48.26).172 (50.75).046 (34.78).057 (36.89) N.008 (61.16).328 (123.7).295 (99.89).088 (56.24).080 (50.52) Rentm 2 /p-4.024 (122.1) -.421 (121.5) -.441 (125.9) -.155 (61.58) -.172 (63.40) No change-.002 (21.57 -.019 (12.73) -.020 (13.62) -.058 (31.04) -.060 (32.47) Space -1.721 (213.4).711 (205.9) PanelNo FE Period FENo FELocal R2R2 0.7040.7160.7230.9050.906 DW0.370.320.331.561.54 Demand equation

19. (1) level (2) level (3) level (4) level (5) level (6) log Dependent variable Rent/m 2 Rentm2m2 m2m2 Log(m 2 ) Assistance.169 (2.51) 1.515 (4.06) 1.776 (4.62) Assistance Dummy.127 (0.84) 28.656 (3.47).088 (6.16) Y (W/Tr).024 (6.07).022 (5.57).025 (6.42.253 (8.57).296 /.542 (9.05/6.01).167 (13.81) N.401 (5.59).444 (6.40) 45.896 (7.91) 10.030 (18.95) 9.270 (15.72).366 (27.09) m2m2 -.079 (15.85) -.079 (15.88) 1.799 (5.65) Rent/m 2 -2.799 (15.74) -2.773 (15.60) -.355 (16.77) R2R2 0.2420.2400.3980.5660.5770.616 SEE2.9142.918155.017.3017.190.273 Results from 2007 cross-section data

20. 123456 constant.054 (1.09/1.59).008 (0.95).018 (1.25/1.42).032 (0.47/0.94).011 (2.06/).016 (1.33(1.52) ∆(Space)-.588 (8.34/14.65) -.451 (5.17/12.32) A2001>0-.033 (0.36/0.97) A2002>0.072 (1.04/2.30) A2005>0.041 (0.74/1.64) S2005>0.069 (0.98/2.53) SEE0.5160.5200.4010.5290.5300.342 MethodOLSLADOLS LADOLS DataA2001>0 all 2001 & 2002 A2005>0 all 2005 &2006 Results from 2001/2002 and 2005/2005 panels

21. Conclusions More than 20 % of housing subsidy goes to rents Subsidy increases housing demand more than other transfers or income in general The rent level (rent/m 2 ) does not seem to depend on the allowance (The law of one price.) Rents are relatively persistent