Abstract
For more than a decade, governments have been incentivizing, and now requiring, private developers to construct energy efficient, sustainable projects. We examine the effectiveness of green single-family construction incentive programs. A cross-sectional comparison of municipalities with and without green private residential incentive programs indicates which government levels of policy issuance and which types of certification programs prove most successful, and when those impacts should be expected. Findings indicate that only municipalities experience success with construction-related policies, which may be tailored to their local market’s construction demands. Business-related policies, however, prove effective at all levels of government implementation, with particular success at the state level. Lastly, event studies and multiyear window data indicates that green incentive policies elicit the greatest change 2 to 3 years after their implementation.
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Notes
World Green Building Council, “The Business Case for Green Building: A Review of the Costs and Benefits for Developers, Investors and Occupants,” 2013.
There are several rating systems in the United States, many created by the state or local governments specifically to address their own needs. We focus on LEED as it is the most commonly used rating tool. 23 of the listed policies allow for other ratings tools to be used as well as LEED.
National Trust for Historic Preservation (2011). The Greenest Building: Quantifying the Environmental Value of Building Reuse, Accessed Jan. 26, 2012 via http://www.preservationnation.org/issues/sustainability/green-lab/usefulfacts-about-greenest-buildings.html
Department of Energy (2011). Buildings Energy Data Book. Buildings Share of Electricity Consumption/Sales. Accessed October 26, 2011 via http://buildingsdatabook.eren.doe.gov/docs/xls_pdf/6.1.1.pdf
Energy Information Administration (2008). Assumptions to the Annual Energy Outlook.
Lenssen and Roodman (1995). Worldwatch Paper 124: A Building Revolution: How Ecology and Health Concerns are Transforming Construction. Worldwatch Institute.
World Green Building Council, “The Business Case for Green Building: A Review of the Costs and Benefits for Developers, Investors and Occupants,” 2013.
Much of the data are taken from each program’s respective website: www.energystar.gov and www.usgbc.org.
Some municipalities had more than one policy enacted.
The balance of impacted municipalities are suppressed from the analysis due to data limitations, the most commonly being insufficient levels of single-family construction (less than five single-family building permits over the 9-year period).
Due to confounding state-level policies in AZ and CO, both those policies and all affected municipalities were dropped from this analysis.
Certification was available prior to that, but was not pursued for single-family market-rate homes until 2006.
Ibid. World Green Building Council, “The Business Case for Green Building: A Review of the Costs and Benefits for Developers, Investors and Occupants.”
Additionally, controlling for hybrid and electric car sales seems poor because the location of a car’s sale has more to do with the supply of this car type than the demand. Someone that lives in rural ND would need to drive to a more cosmopolitan area to purchase a hybrid or electric car, invalidating that measure.
This is evidenced through the control variable’s consistently significant results in both this research and in Bond and Devine (2015).
Following the Diamond and Sekhon (2005) method, Iacus et al. (2012) completes 5,000 Monte Carlo replications. CEM, propensity score matching, nearest neighbor Mahalanobis matching, and genetic matching results are compared in terms of bias, standard deviation, and root mean square error. CEM dominates all three evaluation categories.
All of the following analysis was tested using different structural breaks in the certification levels, but the results were not different from those utilizing all certification levels and are therefore suppressed. Similarly, LEED single family construction began to ramp-up in 2008. However, subsample analysis of this later time period also did not alter the results.
The addition of CEM weights results in only a small decrease in sample size and a strengthening of the model when compared to unweighted estimations of the same models.
In addition to the analysis reported, an Endogenous Participation Endogenous Treatment (EPET) model is used to test for sample selection bias. The root of this bias lies in the relationship between answering the two questions posed (Does an incentive policy encourage any LEED construction? How much green construction does an incentive policy encourage?). The EPET model (Bratti and Miranda 2011) allows for simultaneous testing of both those questions. The multiple equation modeling results indicate that there is a correlation between incentive policies and green construction, with correlations being strongest for municipal-level policies, followed closely by state-level policies. Results are available upon request.
Event studies were conducted for each government level of policy implementation as well, and the results supported the full sample findings.
Unweighted models were also tested and offered similar results.
A fourth lagged year was also tested, and proved uninformative. This may be due to the limited number of policies which have been in place for at least 5 years.
Most county-specific results are suppressed given their poor performance and to save space, but are available upon request.
These results, including county-level results, were suppressed to conserve space and are available upon request.
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The authors would like to thank Andrea Chegut, Lynn Fisher, Piet Eichholtz, Nils Kok, Robert Jalali, the participants at the 2014 Maastricht-NUS-MIT Real Estate Finance and Investment Symposium, and the subsequent blind reviewers for helpful comments.
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Bond, S.A., Devine, A. Incentivizing Green Single-Family Construction: Identifying Effective Government Policies and Their Features. J Real Estate Finan Econ 52, 383–407 (2016). https://doi.org/10.1007/s11146-015-9525-0
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DOI: https://doi.org/10.1007/s11146-015-9525-0