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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Thank you!

Eyal Salinger

eyalsalinger@yahoo.com

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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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