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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 Studies Technion – Israel Institute of Technology, Haifa, Israel February 2012. This research was financed by the Israel Science Foundation.

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Center for Urban and Regional Studies Technion – Israel Institute of Technology, Haifa, Israel

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  1. Estimating the Added Costs of Conserving Buildings with Cultural Heritage ValueDr. 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

  2. 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.

  3. The objective of the paper • To estimate the probability of conserving a building designated for conservation, using the binary choice model (Logit model). • To investigate whether the lack of “the option to rebuild” a building designated for conservation theoretically decreases its value, using the Hedonic Price model.

  4. Literature review 1. 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

  5. Literature review (cont.) 3. The lack of “the option to rebuild” • The myopia assumption • The perfect foresight assumption Amin 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 Urban Economics, 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.

  6. Research assumptions • 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.

  7. The study area: The White City of Tel Aviv

  8. The study area: The White City of Tel Aviv (cont.)

  9. Methodology The Binary Choice Model(Logit Model) Alternative i: to conserve/renovate the building Alternative 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 characteristics O - vector of ownership characteristics

  10. Methodology (cont.) The Hedonic Price Model Phj = Ph(S, R, L, T) Phj - Price of housing unit j S - vector of structural characteristics R - vector of planning regulations that apply to the plot L - vector of location characteristics T - vector of time

  11. Main data sources • Field surveys:Physical survey 4 groups of buildings:Door to door survey • Real estate appraiser firmsecondary data sources

  12. Results – the probability of conserving Ln ( 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: 145 Log-likelihood at zero -98.98 Log-likelihood at estimates -83.009 ___________________________________________________________ * Significant at 1% ; ** significant at 5%

  13. Results – the probability of conserving (cont.) Index variables

  14. Results – the probability of conserving (cont.) Probability difference

  15. 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

  16. 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 145 F= 202.886 Adjusted-Rsq 0.908 ___________________________________________________________ * Significant at 1% ; ** significant at 5%

  17. Results - the lack of “the option to rebuild” Separate models Model 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

  18. Results - the lack of “the option to rebuild” (cont.) _________________________________________________________________________________________________________________________________________ Model1 Model 2 Buildings For Conservation Not for Conservation Independent Variables Estimated coefficients Estimated coefficients ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- CONSTANT 9.19 11.366 PARCEL_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 28 F = 31.93 37.7 Adjusted R Square. 0.82 0.873 _________________________________________________________________________ *significant at 1% ; ** significant at 5%

  19. Results - the lack of “the option to rebuild” (cont.) Calculation method (using Difference-In-Difference method)

  20. Results - the lack of “the option to rebuild” (cont.) Average theoretical decrease in value

  21. Summary and conclusions 1. 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.

  22. 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.

  23. Thank you! Eyal Salinger eyalsalinger@yahoo.com

  24. 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 24

  25. 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: 63 F = 51.52 Adjusted R Square. 0.851 ____________________________________________________________________________ * Significant at 1% ; ** significant at 5% 25

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