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Nonmarket allocation and the willingness to pay in regulated housing markets. Jos N van Ommeren and Arno J van der Vlist Department of Economics Department of Economic Geography VU University University of Groningen [email protected] [email protected]. ERES – July 4, 2013. - PowerPoint PPT Presentation
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Nonmarket allocation and the willingness to pay in regulated housing markets
Jos N van Ommeren and Arno J van der Vlist
Department of Economics Department of Economic Geography VU University University of [email protected] [email protected]
ERES – July 4, 2013
Regulated housing in Global cities
Households cannot reveal
their true willingness to pay
Literature on regulated housing markets
› Random housing allocation -> misallocation (Glaeser and Luttmer, 2003)
› Rent control in private regulated housing -> limited housing supply (Olsen and Barton, 1983; Gyourko and Linneman, 1989)
This paper
› Methodology that exploit the queueing time to estimate the households’ marginal willingness to pay (MWP)
› Present and compare results for households’ MWP for regulated housing vis-a-vis private housing in Amsterdam Metropolitan Housing Market
21/04/23 | 4
Model outline
Housing market
•Number of households N0
•Private market vs. regulated market
•Regulated housing is preferred over private
•Households in queue stay in private market
•v= v (X,r) with market value X and rent r
•
•Number of regulated housing N1 < N0
v > v0
v
vdvNN1
Model - households
T
tt dtevevV
)(0
0
Households’ lifetime utility V
Private market Regulated market
Model – households’ optimal queueing time
T
tt dtevevV
)(0
0
Maximizing lifetime utility V with respect to queueing time
Maxτ(v)gives
0])([
1/
0
e
ee
vvv
T
τ(v)
Model – housing market
Steady state Housing market
• nv/τ(v) households receive a house offer
• Nv/[T-τ(v)] households leave the housing market
• Excess demand equals queue:
• In steady state: nv/τ(v) = Nv/[T-τ(v)]
•
∂nv/∂v = ∂nv/∂τ(v) * ∂τ(v)/ ∂v > 0
( )
( )v
v
N vn
T v
v
v NNn 10
21/04/23 | 9
0])([
1/
0
e
ee
vvv
T
∂nv/∂v = ∂nv/∂τ(v) * ∂τ(v)/ ∂v > 0
Model –towards an empirical model
/ log /.
/ log /
v X X
v r r
From households’ maximization we have
From the steady state housing market condition we have
It follows that
Empirical model
rX logloglog
log / log.
log / logx
X rMWP
r X
τ(v) Queuing time
X property tax appraisal value
r regulated rent
-+
Data
Data
Estimation results
Robustness analysis
› Eligible vs noneligible households (low- high income)
› Tobit analysis for Censoring duration
Estimation results
Conclusion
› Queueing time can be exploited to estimate the MWP for housing in regulated markets
› Queuing time varies with market value + and rent –
› MWP for regulated housing is close to the annual capitalization rate for private housing [4.7-6.2]
› Households pay about (2/3) of MWP so that inefficient housing consumption is most likely