The Value of a Green Building Certificate for Office Buildings in CEE

Michal Gluszak, Gunther Maier, Sabine Sedlacek, Malgorzata Zieba

Content

Introduction The project team Conceptual background Interviews Survey instrument First results

Introduction

Green Building movement in Central and Eastern Europe Green Building Councils in almost all CEE countries Various strategies, various certification schemes Internationally active developers and consultants got

involved

What is the value of green building certificates in the CEE market? Very few certified buildings Limited information on transactions Need to do a contingent valuation study

The Research Team

Currently Cracow (Poland) and Vienna (Austria) Interested in expansion to other countries

Team Cracow: Michal Gluszak, University of Economics, Cracow Malgorzata Zieba, University of Economics, Cracow

Team Vienna: Gunther Maier, WU Vienna Sabine Sedlacek, Modul University, Vienna

Conceptual Background

Evidence for a positive effect of Green Building certificates on values and rents Eichholtz, Kok & Quigley (2010) (US; LEED and Energy

Star): effective rent premium + 7%, sales price premium +16%; the label by itself has a positive value above the implied energy savings.

Fuerst & McAllister (2011) (US; LEED and Energy Star): rent premium +5% (LEED) and 4% (Energy Star); sales price premium +25% (LEED), +26% (Energy Star)

Wiley, Benefield & Johnson (2010) (US; LEED and Energy Star): rent premium +7% to +17%; higher occupancy by 10% to 18%; selling premium per sqft $30 (Energy Star) to $130 (LEED).

Conceptual Background

Positive image of Green Buildings Addae-Dapaah, Hiang & Shi (2009) (Singapore, survey

of occupants): No effect of awareness and appreciation of green benefits beyond cost savings and higher building values. Benefits are very uncertain.

Hypotheses: Green building certificates have a significant positive

effect on rents and sales prices. In less developed markets (CEE) awareness will be low

Conceptual Background

Method of choice Hedonic price estimation with certificate as explanatory

variable

Problem: Too few green buildings yet in CEE markets; very

limited information on rents and transactions

Solution: Expert interviews Contingent valuation survey

Interviews

Interviews with 16 commercial property professionals

Semi-structured in-depth interviews Main results

Certificate recognition: weak (LEED the most popular), some experts were not familiar with different certification schemes

Green profile: is not a key attribute in a decision process, only one expert spontaneously mentioned it as somewhat important when office space decisions are concerned

Interviews

Main results (cont.) no single expert expected higher rents in certified properties. no single expert expected that company would move to

certified building from not certified premises even if they were provided assistance.

some experts suspected green washing Barriers: supply; current economic conditions Differences by size (bigger companies are more interested in

standard and wellbeing of employees) and nationality (US and UK companies are used to green standards)

Development is driven by international investors (SKANSKA most eminent example)

Interviews

Most important factors in office space choice in Poland:

No Attribute Frequency

1 rent 10

2 location 9

3 structure and size 7

4 maintenance costs 6

5 parking lots 6

6 tenant-mix 4

7 Facilities 3

8 architectural design 1

9 green building certificate 1

Survey instrument

Survey of companies who have moved to new office space within the last 2 years

Goal: identify the WTP (implicit price) for green building certificate

Strategy: contingent valuation Compare current office space with a similar hypothetical

alternative – which one would you have chosen? Analysis by use of a conditional logit model

Survey (start page)

Survey (page 1)

Survey (page 2)

Survey (page 3, repeated 10 times)

Survey

Generating the hypothetical alternatives Criteria are sorted in decreasing expected

attractiveness (new before old, city center before periphery)

For all criteria except price, operating costs and certificate: For the new alternative, we either stay at the criteria value (40%) or go one step up (30%) or down (30%). When out of bounds, it is set to the boundary value.

For certificates: When certificate: 50% same certificate, 50% no certificate; when “no certificate”: 40% no certificate, LEED, BREEAM and DGNB with 20% each

Survey

Generating the hypothetical alternatives Sum of characteristics gives a rough measure of

attractiveness Randomly generated price deviations by 0%, 5%, 10%,

15% or 20% up or down Result centered around zero and shifted by difference in

attractiveness Correction over the experiment:

When only the original option is chosen, the alternative option becomes cheaper

When only the alternative option is chosen, it becomes cheaper

First results

Based on only TWO respondents from Vienna Therefore: no significant coefficients, limited

model qualityIteration 0: log likelihood = -11.46822 Iteration 1: log likelihood = -10.436821 Iteration 2: log likelihood = -10.328076 Iteration 3: log likelihood = -10.327686 Iteration 4: log likelihood = -10.327686

Conditional (fixed-effects) logistic regression Number of obs = 40 LR chi2(3) = 7.07 Prob > chi2 = 0.0697Log likelihood = -10.327686 Pseudo R2 = 0.2550

------------------------------------------------------------------------------ choice | Coef. Std. Err. z P>|z| [95% Conf. Interval]-------------+---------------------------------------------------------------- const | -.9396476 .8159093 -1.15 0.249 -2.5388 .6595052 rent | -.1215278 .0835022 -1.46 0.146 -.2851891 .0421335 cert01 | 1.074909 1.112476 0.97 0.334 -1.105504 3.255322------------------------------------------------------------------------------

First results

Iteration 0: log likelihood = -13.862944 .....Iteration 12: log likelihood = -4.938938

Conditional (fixed-effects) logistic regression Number of obs = 40 LR chi2(8) = 17.85 Prob > chi2 = 0.0224Log likelihood = -4.938938 Pseudo R2 = 0.6437

------------------------------------------------------------------------------ choice | Coef. Std. Err. z P>|z| [95% Conf. Interval]-------------+---------------------------------------------------------------- loc | -.6671478 1.751317 -0.38 0.703 -4.099666 2.765371 transp | 16.89953 3649.109 0.00 0.996 -7135.223 7169.022 age | -2.088071 3.2887 -0.63 0.525 -8.533804 4.357663 type | -1.473766 3.592481 -0.41 0.682 -8.5149 5.567368 qual | -38.38153 7382.253 -0.01 0.996 -14507.33 14430.57 const | -.5146494 2.223854 -0.23 0.817 -4.873324 3.844025 rent | -.296666 .306436 -0.97 0.333 -.8972694 .3039375 cert01 | 18.15025 3649.109 0.00 0.996 -7133.972 7170.272------------------------------------------------------------------------------

Conclusions

Important question Survey instrument is tested and ready Lot of additional work needs to be done Interesting to add additional CEE countries