1. Are Housing Benefits an Efficient Way to Redistribute Income ? Evidence From a Natural experiment in France ? By Grabrielle Fack (2004) Working paper presentation

2. Introduction In France, cost of housing subsidies = 12.8 billion euros in 2002 (0,8% of GDP) But any study can evaluate precisely the effect of this help Goal of the paper : evaluate the effect of the housing benefits on the rents

3. 1. Theoretical model hypothesis of segmented housing markets :  the first segment is for households of income y1  the second for those of income y2, with y1 ≤ y2 Equilibrium without subsidy (period 1) : max U(ci1; si1) sous la contrainte de budget : ci1 + si1.ri1 < yi => equilibrium rent : ri1*

4. 1. Theoterical model Equilibrium with subsidy (period 2) : housing subsidy reform is passed : low income household y1 can receive a12 > 0 Housing is a normal good => SD1 (r12 - a12) > SD1 (r11) increase of rents is a function of the elasticity of housing supply : ∆r1 = θ.∆a1 with θ = ed / (es + ed) the lower the housing supply elasticity compared to housing demand elasticity, the higher θ.

5. 2. Empirical Specification  Model : r it = α + Σ β k.. quartile ik + δ  t + Σ γ j.. X ij + θ.a i + ε i  Problem : sources of biases with OLS correlation between ε i and a i => a i not exogenous => utilisation of differences in differences methods

6. 2. Empirical Specification Differences in differences method : consist in comparing the rents before and after the reform for a group affected by the change (the treatment group T) to a group not affected by the policy reform (the control group C) Group T = 1 st quartile of revenue, group C = 2 nd quartile of revenue, reform = reform of 91-93 Estismation is unbiaised if, absent the reform, the evolution of the rents would have been the same for the two groups

7. 2. Empirical Specification Methods in two stages : 1) regress the housing benefit per square meter on the instruments : ait = α' + β'.quartile 1 + γ'. post + Σ δ' j.X ij + ε'. quartile 1.post + µ' it 2) regress the rent per square meter on the predicted housing benefit (and the controls) : r it = α + β. quartile 1 + γ. post + + Σ δ j.X ij + θ.Pa i t + µ it

8. 3. Data and Results Estimate must take into account the structural socio- demographic existing between the first and the second quartile => add dummies for type and size of the household, for geographical location... Utilisation of the French Housing Survey,called “Enquête et Logement" from 1988 to 2002 Result : θ = 0,78 significant at 5% level

9. 4.Refinement of the study the reform has had an unpredicted impact on students decision to become independent => straight effect on the students' rents, side effect on other households' rents => parting the sample in two zones :  Zone 1 has a stong proportion of students  Zone 2 has a weak proportion of students Θ is higher in the zone 1 than in the zone 2 => students had played a role in the increase in rents of low income households by contributing to the rent increase in the areas where they have moved in

10. Conclusion : for 1 euro of housing benefits, 78 cents are absorbed by landlords in rent increases and only 22 cents are left to low income households Because :  housing supply is inelastic in the short and middle term  Increase in demand provoked by the new benefits (students) If the aim of the public policy was to increase housing consumption, it would be better to work directly on housing supply. Otherwise, cash transfers, by giving more choice to households,would certainly minimise these price effects and generate higher welfare gains for poor households.