Academic journal article The Journal of Real Estate Research

Opting for a Green Certificate: The Impact of Local Attitudes and Economic Conditions

Academic journal article The Journal of Real Estate Research

Opting for a Green Certificate: The Impact of Local Attitudes and Economic Conditions

Article excerpt

The property sector is important in the current efforts to reduce greenhouse gas emissions. Being responsible for approximately 40% of U.S. energy consumption and approximately 40% of U.S. carbon emissions, this sector offers significant potential to enhance energy efficiency and reduce emission levels (EPA, 2009). However, the adoption of certified green space varies considerably from location to location (Kok, McGraw, and Quigley, 2011). Obtaining a better understanding of what is responsible for the variation in the adoption of green space across different locations appears to be essential if one is interested in promoting the diffusion of energy-efficient buildings.

The literature focuses on the effect of green building practices and certificates on real estate prices or returns of residential and commercial properties (Eichholtz, Kok, and Quigley, 2010a; Pivo and Fisher, 2010; Aroul and Hansz, 2012; Reichardt, Fuerst, Rottke, and Zietz, 2012). By contrast, we analyze which observable locational characteristics induce owners to certify buildings. The analysis is conducted at the level of the individual building and over time. In particular, the study is based on a panel data set of 10,624 Class A buildings for the years 2001 to 2010. The fixed-effects estimator controls for year- and property-specific influences and thereby accounts for time-invariant unobserved heterogeneity. The estimation approach allows us to control for unobserved heterogeneity across buildings that is due to time-invariant building characteristics, such as location. By removing these time-invariant influences, we can focus on variables that may change over time in a locality and, thereby, influence the decision to go green. Among these are such non-economic variables as the political orientation of a location. Local characteristics and market conditions affect real estate prices (Glascock, Jahanian, and Sirmans, 1990; Glascock, Kim, and Sirmans, 1993), construction activity (Born, 1988) or even a property's tenant quality (Archer and Smith, 1992). It is, therefore, expected that time varying characteristics of locations also impact the decision to opt for a green building certifiate.

Some initial work on the local determinants of investing in certified green buildings has been done. For example, Fuerst, Kontokosta, and McAllister (2011) and Kok, McGraw, and Quigley (2011) focus on the diffusion of building space that is certified for energy-efficiency by LEED and ENERGY STAR.1 They analyze the local conditions that are responsible for the geographical clustering of these buildings. Fuerst, Kontokosta and McAllister (2011) investigate the market penetration of certified space and its local determinants in a cross-sectional setting. Kok, McGraw, and Quigley (2011) use a panel data set of 48 MSAs over a period of 15 years. While their empirical setting allows for the analysis of geographical clustering of certified space and of temporal effects, it is aggregate in nature and can, therefore, not capture the decision-making process at the level of the individual building. We focus instead on the decision-making process related to certification at the building level and over time.

In practice, the decision to certify may involve the need to either retrofit the existing building stock to meet the certification standards or to enhance the building plans for new buildings. Either way, additional costs are involved. As a consequence, an increase in the adoption of green building standards has to be based on the expectation that the local conditions allow for either cost savings in operating the buildings or for higher rents that can be charged after a certification. One would presume that savings in operating costs depend inter alia on local weather conditions or energy prices. Similarly, the ability to charge higher rents may be related to the types of companies renting the buildings or the local acceptance of green buildings. The findings by Fuerst, Kontokosta, and McAllister (2011) and Kok, McGraw, and Quigley (2011) largely back up these ideas. …

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