Center for Urban and Regional Studies Technion – Israel Institute of Technology, Haifa, Israel
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Estimating the Added Costs of Conserving Buildings with Cultural Heritage Value Dr. Eyal Salinger and Prof. Daniel Shefer Center for Urban and Regional Studies Technion – Israel Institute of Technology, Haifa, Israel February 2012 This research was financed by the Israel Science Foundation
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Estimating the Added Costs of Conserving Buildings with Cultural Heritage Value Dr. Eyal Salinger and Prof. Daniel Shefer. Center for Urban and Regional Studies Technion – Israel Institute of Technology, Haifa, Israel February 2012. This research was financed by the Israel Science Foundation. - PowerPoint PPT Presentation
Transcript of Center for Urban and Regional Studies Technion – Israel Institute of Technology, Haifa, Israel
Estimating the Added Costs of Conserving Buildings
with Cultural Heritage Value
Dr. Eyal Salinger and Prof. Daniel Shefer
Center for Urban and Regional StudiesTechnion – Israel Institute of Technology, Haifa, Israel
February 2012
This research was financed by the Israel Science Foundation
The added costs of conserving buildings
- The restrictions and requirements of conservation impose extra costs on building owners.
- Demolition of buildings designated for conservation is forbidden.
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The objective of the paper
1. To estimate the probability of conserving a building designated for conservation, using the binary choice model (Logit model).
2. To investigate whether the lack of “the option to rebuild” a building designated for conservation theoretically decreases its value, using the Hedonic Price model.
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Literature review1. The decision to conserve
Rational behavior maximizing profits
Davis A.O., Whinston B.A. (1961) "Economic Problems in Urban Renewal"
Law and Contemporary Problems Vol. 26, No. 1.
Pavlov A., Blazenko G. W. (2005) “The Neighborhood Effect of Real Estate
Maintenance” The Journal of Real Estate Finance and Economics Vol 30(4)
2. The high cost of conservation
Building materials
Construction techniques
Skilled labour
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Literature review (cont.)3. The lack of “the option to rebuild”- The myopia assumption- The perfect foresight assumptionAmin K., Capozza D. R. (1993) “Sequential Development” Journal of Urban Economics,Vol. 32, pp. 142-158.Brueckner J. K. (1981) “A Dynamic Model of Housing Production” Journal of UrbanEconomics, Vol. 10, pp. 1-14.
- The option to rebuild (repeatedly) Williams J. T. (1997) “Redevelopment of Real Assets” Real Estate Economics, Vol 25(3),pp. 387-407.
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Research assumptions1. The probability of conserving a building
designated for conservation is lower than that of renovating a building not designated for conservation.
2. In most cases, the lack of “the option to rebuild” a building designated for conservation theoretically decreases its value.
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The study area: The White City of Tel Aviv
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The study area: The White City of Tel Aviv (cont.)
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Methodology
The Binary Choice Model (Logit Model) Alternative i: to conserve/renovate the buildingAlternative j: not to conserve/renovate the building
Ln Pn(i) = Vin (B, O)
• 1-Pn(i)
Pn(i) - the probability of choosing alternative I
B - vector of building characteristicsO - vector of ownership characteristics
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Methodology (cont.)
The Hedonic Price Model
Phj = Ph(S, R, L, T)
Phj - Price of housing unit jS - vector of structural characteristicsR - vector of planning regulations that apply
to the plotL - vector of location characteristicsT - vector of time
Main data sources
1. Field surveys:Physical survey 4 groups of buildings:
Door to door survey2. Real estate appraiser firm
secondary data sources11
Not conserved/not renovated
Conserved/renovated
Buildings designated for conservation
A C
Buildings not designated for conservation
B D
Results – the probability of conservingLn ( p )= 2.81 + –0.038*YEAR_BUILT + -0.344*INDEX_ALL + -0.248*INDEX_CONSERVATION (1-p)
P – predicted probability of conserving __________________________________________Independent Variables Estimated coefficients (t-value)----------------------------------------------------------------------CONSTANT 2.81
(4.1)*YEAR_BUILT -0.038
(-2.23)**INDEX_ALL -0.344
(-3.95)*INDEX_CONSERVATION -0.248
(-3.59)*
Number of observations: 145Log-likelihood at zero -98.98Log-likelihood at estimates -83.009___________________________________________________________
* Significant at 1% ; ** significant at 5%
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Results – the probability of conserving (cont.)
Index variables
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INDEX_ALL
Variables Weight
ELEVATOR 0.4
OWNERS1 0.6
Total 1
INDEX_CONSERVATION
Variables Weight
OWNERS1 0.35
PROTECTED_TENANTS 0.2
BALCONY 0.15
DEVELOPMENT_RIGHTS 0.3
Total 1
Results – the probability of conserving (cont.)
Probability difference
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The “average building” Probability to conserve/renovate
Building for conservation 22.5%
Building not for conservation 45.5%
Probability difference -23%
Results – the probability of conserving (cont.)
Linear regression results
P = 1.122 + -0.299*ELEVATOR + -0.428*OWNERS1 +
-0.079*BALCONY_CONSERVATION + -0.008*YEAR_BUILT + -0.044*PROTECTED_TENANTS1_CONSERVATION + 0.099*DEVELOPMENT_RIGHTS_CONSERVATION ++ -0.268*CONSERVATION
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Results – the probability of conserving (cont.) Linear regression results
Independent variables Estimated coefficients (t-value)-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
CONSTANT 1.122 (48.04)*ELEVATOR -0.299 (-24.92)*OWNERS1 -0.428 (-18.59)*BALCONY_CONSERVATION -0.079 (-3.42)*YEAR_BUILT -0.008 (-14.23)*PROTECTED_TENANTS1_CONSERVATION -0.044 (-13.17) *DEVELOPMENT_RIGHTS_CONSERVATION 0.099 (4.83)*CONSERVATION -0.268 (-11.19) *
Number of observations 145F= 202.886Adjusted-Rsq 0.908___________________________________________________________
* Significant at 1% ; ** significant at 5%
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Results - the lack of “the option to rebuild”
Separate modelsModel 1 – Buildings designated for conservation
LN(BUILD_PRICE) = 9.19 + 0.79*LN(PARCEL_AREA) + 0.723*LN(BUILDING_%_USED) + -0.237*UNEMPLOYMENT + 0.307*EXTERNALITIES_POS + -0.253*EXTERNALITIES_NEG
Model 2 - Buildings not designated for conservation
LN(BUILD_PRICE) = 9.19 + 0.901*LN(PARCEL_AREA) + -0.152*UNEMPLOYMENT + 0.359*EXTERNALITIES_POS + 0.283*FACADE + 0.566*YEAR_2009
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Results - the lack of “the option to rebuild” (cont.)
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_________________________________________________________________________________________________________________________________________
Model 1 Model 2Buildings For Conservation Not for ConservationIndependent Variables Estimated coefficients Estimated coefficients----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
CONSTANT 9.19 11.366PARCEL_AREA 0.79 * 0.901 *BUILDING _%_USED 0.723 *UNEMPLOYMENT -0.237 * -0.152 *YEAR_2009 0.566 *EXTERNALITIES_NEG -0.253 **EXTERNALITIES_POS 0.307 * 0.359 **FACADE 0.283 *
Number of observations: 35 28F = 31.93 37.7Adjusted R Square. 0.82 0.873_________________________________________________________________________
*significant at 1% ; ** significant at 5%
Results - the lack of “the option to rebuild” (cont.)
Calculation method(using Difference-In-Difference method)
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Nominal price in Ln
(P)
Value with “the option to rebuild” in Ln
(V)
Difference in Ln
( P( – )V)
Differencein%
17.52 17.45 0.07 7%
16.35 16.41 -0.06 -6%
Results - the lack of “the option to rebuild” (cont.)
Average theoretical decrease in value
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The lack of the option to rebuild Number of cases in%
No negative impact 10 30%
Negative impact 25 70%
Average decrease in value 12.5%
Summary and conclusions1. The lack of “the option to rebuild” a building
designated for conservation theoretically decreases its value in 70% of the cases. The average decrease in value is 12.5%.
2. The probability of conserving a building designated for conservation is lower than that of renovating a building not designated for conservation. The extent of which depends on several other attributes of the building, and is on average 25% lower.
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Summary and conclusions (cont.)- Incentives should differentiate based on
building’s characteristics and the complexity involved in conserving the building.
- The predicted probability of conserving, taken from the logit model results, can set as a measure for determining the incentives to be given for each building.
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Results- the lack of “the option to rebuild” (cont.)
Combined model – all buildings
LN(BUILD_PRICE) = 11.366 + 1.014*LN(PARCEL_AREA) + -01967*UNEMPLOYMENT + 0.383*EXTERNALITIES_POS + 0.195*FACADE + 0.524*YEAR_2009 +-0.44*PARCEL_AREA_CONSERVATION + 0.537*BUILDING_%_USED_CONSERVATION
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Results- the lack of “the option to rebuild” (cont.)_______________________________________________________Independent Variables Estimated coefficients (t-value)-------------------------------------------------------------------------------------------CONSTANT 11.023 (20.689)*PARCEL_AREA 1.014 (11.48)*PARCEL_AREA_CONSERVATION -0.44 (-6.34)*BUILDING_%_USED_CONSERVATION 0.537 (5.98)*UNEMPLOYMENT -0.196 (-9.06)*EXTERNALITIES_POS 0.383 (5.35)*FACADE 0.195 (3.24)*YEAR_2009 0.524 (3.72)* Number of observations: 63F = 51.52Adjusted R Square. 0.851____________________________________________________________________________
* Significant at 1% ; ** significant at 5%
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