Analyzing the Perceived Benefits of LEED-Certified and Energy Star–Certified Buildings in the Realm of Local Economic Development

Abstract

Data collected from a national survey of economic development professionals are used in this study to examine the perceived role of Leadership in Energy and Environmental Design–certified and Energy Star–certified buildings in the business recruitment process. A series of ordinal logistic regression models are estimated to examine economic developers’ attitudes toward these buildings after controlling for their personal characteristics and the characteristics of the communities where they work. The results suggest less favorable perceptions about this form of sustainable real estate development in smaller communities and those with weaker economic fundamentals. Furthermore, women employed in economic development are found to have more favorable attitudes toward these buildings than their male counterparts. Increasing support for sustainable real estate development among economic developers working in local government may therefore require a combination of thoughtful policy making, executive education, and greater gender diversity in the profession.

Keywords

real estate development environmental sustainability LEED certification Energy Star economic development

Environmentally sustainable real estate development projects have the potential to confer a number of economic benefits to local governments. They can help attract residents to a community by improving the quality of life (Schindler, 2010); they can encourage the formation of innovative new businesses by increasing the demand for “green” building materials (Allen & Potiowsky, 2008; Fitzgerald, 2010); and they can play a role in the recruitment of firms interested in occupying environmentally friendly space (Eichholtz, Kok, & Quigley, 2009). All these factors would appear to provide economic developers with an incentive to support this type of development throughout their jurisdictions. However, it remains unclear whether this is the case. Several studies have shown that economic developers have mixed feelings toward policies intended to simultaneously advance economic and environmental goals (Grodach, 2011; Jepson, 2003; Zeemering, 2009).¹ Perspectives such as these are important because they may influence the extent to which practitioners support these policies when exercising professional discretion.

The empirical analysis presented in this research contributes to the study of economic developers’ attitudes toward sustainable real estate development by focusing on two programs designed to encourage resource conservation in the building industry. Survey data collected from more than 500 members of the International Economic Development Council (IEDC) are used to determine whether Leadership in Energy and Environmental Design (LEED)–certified and Energy Star–-certified buildings are viewed as a tool that can be leveraged in the business recruitment process. Perceived obstacles to sustainable real estate development are also considered, along with attitudes about the appropriate role of government in this policy area. Survey responses are used to estimate a series of ordinal logistic regression models exploring these attitudes after controlling for respondents’ personal characteristics and the characteristics of the communities they serve. This approach allows for an examination of one “sustainable economic development” strategy aligning economic and environmental objectives (Blakely & Leigh, 2010; Colgan, 1997; Opp & Saunders, 2013; Roberts & Cohen, 2002).²

Studying economic developers’ attitudes is valuable because these professionals garner influence over policy decisions in their jurisdictions by synthesizing information, mobilizing stakeholders, and building consensus among individuals with opposing points of view (McGuire, 2000). They often leverage a professional network of nongovernmental entities, such as business owners and trade organizations, to apply political pressure when it is deemed necessary to create jobs or expand the local tax base (Grodach, 2011). Their willingness to engage in such activities can affect the success or failure of various policy initiatives, including those intended to encourage sustainable building practices. Examining the perceptions of economic developers can therefore offer insight into both information asymmetries and legitimate economic concerns capable of eroding support for sustainable real estate development policies at the local level.

The aforementioned issues are considered in this study as follows. First, to provide context for the analysis, we discuss building certification systems used in the United States to promote resource conservation. We then present hypothesized linkages between sustainable building practices and economic growth to demonstrate the relevance of the study to the field of economic development. We outline the data and methodology used to evaluate attitudes about LEED- and Energy Star–certified buildings, and then provide a summary of the empirical results. The findings indicate that economic developers’ attitudes toward sustainable real estate development are more favorable in populous areas and in those with stronger economies. There is also evidence that women in economic development perceive LEED- and Energy Star–certified buildings as more useful recruiting tools than their male counterparts. Both findings are consistent with theoretical expectations and contribute to the economic development literature.

Building Certification Systems and the Economics of Sustainable Real Estate Development

A number of different certification systems exist throughout the world to identify buildings with environmentally sustainable design features. The two most common in the United States are LEED and Energy Star (Oberle & Sloboda, 2010). The LEED certification is administered by the U.S. Green Building Council, a nonprofit organization formed in 1993 to promote sustainable development practices. Building owners voluntarily pursue certification by receiving points in six areas: (1) energy efficiency, (2) water conservation, (3) site design, (4) waste reduction, (5) environmentally conscious use of materials, and (6) indoor environment quality. Depending on the number of points accumulated, a building may receive the base certification or an advanced certification level of silver, gold, or platinum. The Energy Star system, jointly administered by the U.S. Environmental Protection Agency and the Department of Energy since 1992, focuses exclusively on energy efficiency. Building owners pursuing the certification receive it if their project is determined to be in the top 25% of buildings in the United States in terms of energy efficiency. Several thousand buildings have received both of these certifications. Office developers have led the way, but certified buildings can now be found in the industrial, residential, retail, and hospitality sectors of the real estate market as well (Allen & Potiowsky, 2008; McGraw-Hill Construction, 2008).

During the past decade, a wave of empirical research has been conducted to quantify the costs and benefits of LEED- and Energy Star–certified buildings to the private sector. Several of these studies have found that certified buildings cost slightly more to build than conventional structures, with the magnitude of the cost premium increasing as developers pursue advanced certification levels (Kats, 2003; Miller, Pogue, Gough, & Davis, 2009). Despite the construction cost premium, many of these investments have proved to be financially attractive because they outperformed their competitors by achieving higher rental rates, occupancy levels, and sale prices on completion (Dermisi, 2009; Eichholtz, Kok, & Quigley, 2010; Fuerst & McAllister, 2009; Wiley, Benefield, & Johnson, 2010). These outcomes are presumably the product of strong tenant demand for certified space in select cities and intense capital market competition for real estate assets that are somewhat insulated from functional obsolescence (Dorsey & Read, 2012).

Although the existing research offers promising results regarding the financial viability of LEED- and Energy Star–certified buildings, it does not suggest that these projects have a high probability of economic success in all locations. Several recently conducted geographic diffusion studies conclude that these projects are more likely to be developed in populous areas with high levels of income, education, and service-sector employment, as well as in areas with liberal political orientations (Choi & Miller, 2011; Cidell, 2009; Cidell & Beata, 2009; Kok, McGraw, & Quigley, 2012; Kontokosta, 2011; Ola, 2011). LEED- and Energy Star–certified buildings may therefore be more financially successful in certain types of geographic areas than others. This may be because of differences in tenant demand across geographies and differences in local real estate developers’ ability to supply these buildings to the market efficiently.

Differences in tenant demand across markets can be better understood by considering the underlying benefits firms seek to obtain by occupying certified space. These benefits may include reduced real estate occupancy costs, increased employee productivity, satisfaction of corporate social responsibility commitments, or the projection of an environmentally conscious image (Eichholtz et al., 2009; Miller et al., 2009). Some of these benefits can be amplified in certain types of markets. For example, large firms with well-publicized corporate social responsibility initiatives and highly skilled workforces often choose to headquarter in large metropolitan areas to access consumers, vendors, and prospective employees. This may translate into heightened demand for LEED- and Energy Star–certified buildings in these locations. Furthermore, projecting an environmentally conscious image and focusing on resource conservation may be more valuable in areas where natural resources are scarce and political views are left-leaning. These factors help explain the high concentration of LEED- and Energy Star–certified buildings in select markets from a demand perspective.

Supply-side variables can also influence the location of sustainable real estate development projects. Populous areas with strong economic fundamentals tend to have high concentrations of real estate practitioners qualified to execute LEED- and Energy Star–certified projects (Cidell, 2009). Human capital availability encourages the construction of assets with sustainable design features in these markets (Kok et al., 2012). Over time, the trend is perpetuated by knowledge spillovers and agglomeration economies that reduce the cost of building in this manner (Kaza, Lester, & Rodriguez, 2013). The end result is a sustainable real estate development industry that gradually builds on itself. Communities lacking real estate practitioners with these skills can find themselves at a disadvantage as demand for LEED- and Energy Star–certified buildings emerges.

Leveraging LEED- and Energy Star–Certified Buildings for Economic Development

The availability of LEED- and Energy Star–certified space is not the only factor companies consider when evaluating alternative locations. However, the existing research indicates that it can serve as an “arrow in the quiver” of economic development professionals throughout the business recruitment process. This appears to be particularly true in communities with defined characteristics. Certified buildings can be very attractive to firms evaluating larger metropolitan areas with highly skilled workforces, strong economies, and progressive political landscapes. This should translate into favorable attitudes about sustainable real estate development, especially if local real estate developers working in these areas have the skills necessary to deliver these assets to the market in an efficient manner.

Community characteristics should also influence economic developers’ beliefs about the factors motivating companies to seek out certified buildings and the role government should play in encouraging this type of development. LEED and Energy Star mandates might be favored in markets where companies are anticipated to value sustainable buildings as a means of reducing occupancy costs or attracting skilled workers, but disfavored in markets where such benefits are perceived as speculative. None of these propositions have been empirically tested, to the authors’ knowledge, and warrant further exploration to assess the level of support likely to exist for sustainable real estate development policies in different markets. The issue is salient because many communities have considered incorporating LEED and Energy Star certification systems into their local land use regulations (Retzlaff, 2009; Simons, Choi, & Simons, 2009).

At this point, it is important to note that information asymmetries may exacerbate attitudinal differences about sustainable real estate development that exist across communities. This could be the case if economic developers representing more populous areas or those with stronger economies have greater exposure to sustainable development projects or better access to executive education programs focusing on the topic. The same could be true for practitioners working in areas with scarce natural resources or liberal political orientations where environmental conservation is highly valued. A better understanding of LEED and Energy Star certification systems in these communities could result in more favorable attitudes about the economic benefits derived from these projects. On the other hand, economic developers working in markets offering little exposure to sustainable real estate development may have less favorable attitudes toward certified buildings. Empirically testing these hypotheses can shed light on the acceptance of sustainable building practices in diverse communities.

Controlling for Economic Developers’ Personal Characteristics

To isolate the relationship between community characteristics and attitudes toward sustainable real estate development, personal characteristics of economic developers must be taken into account. This is necessary because there are theoretical reasons to believe personal characteristics will influence perceptions about LEED- and Energy Star–certified buildings. Hoffman and Henn’s (2008) exploration of social barriers to “green” building identifies gender, age, education, and political affiliation as important considerations. Greater environmental awareness among women, young people, the well educated, and liberals will likely translate into heightened appreciation for sustainable real estate development among individuals with these characteristics. These presumptions are consistent with the findings of other studies examining environmental concerns across demographic groups (Hawkins & Wang, 2012; Konisky, Milyo, & Richardson, 2008; Mohai, 1992; Portney & Berry, 2010; Scott & Willits, 1994; Tindall, Davies, & Mauboules, 2003; Xiao & McCright, 2012).

Another demographic variable of interest is race. Mohai and Bryant (1998) concisely summarize three theoretical explanations for differing levels of environmental concern among people of color when compared to Caucasians. The “hierarchy of needs” explanation focuses on income inequalities that have historically existed along racial lines in the United States, which may force racial minorities to devote their attention to higher-order needs as opposed to environmental preservation. This is hypothesized to result in lower levels of environmental concern among racial minorities because a clean environment is perceived as a luxury good. The second explanation focuses on “cultural differences.” Caucasians are anticipated to express higher levels of environmental concern because they have been conditioned to view nature and the outdoors as places of refuge, whereas people of color have not been conditioned in the same manner because of racial discrimination and exclusion from environmental amenities. Finally, the “environmental deprivation” explanation posits that people of color should actually express higher levels of concern about the environment. This outcome is expected because racial minorities are disproportionately burdened by environmental pollution as a result of the types of places where they live and work. These competing hypotheses offer a compelling theoretical reason to empirically examine the relationship between race and attitudes toward LEED- and Energy Star–certified buildings.

Any observed linkages between demographic variables and economic developers’ attitudes toward sustainable real estate development are noteworthy in light of the research that has been done in the field of representative bureaucracy. Advocates of this theoretical paradigm call for greater diversity among those working in government to ensure demographic profiles of bureaucratic organizations match those of the constituencies they serve (Bradbury & Kellough, 2008; Meier, 1975). This is deemed important because individuals of the same age, gender, and race are anticipated to experience common socializations processes that result in similar values and beliefs (Pitts, 2005; Read & Leland, 2013). Demographically representative bureaucracies are therefore expected to be better positioned to advocate on behalf of a community’s collective interests, as opposed to those only benefiting elites or other influential groups. The study of representative bureaucracy can be extended to sustainable real estate development by examining economic developers’ attitudes toward LEED- and Energy Star–certified buildings. To the extent that attitudinal differences exist across demographic groups, greater diversity in the economic development profession may serve to promote more inclusive policy decisions.

Data and Methodology

The data used to complete this study were collected through a self-administered Internet survey distributed to members of the IEDC in 2012.³ Through collaboration with the organization’s research department, an electronic link to the survey was sent to all of the organization’s 4,500+ domestic members with a valid email address on record. The survey instrument covered a variety of topics, including questions evaluating economic developers’ attitudes toward LEED- and Energy Star–certified buildings. Prizes were offered throughout the data collection phase to encourage participation and more than 500 responses were obtained.⁴ Responses received from economic developers working in local government were used to estimate the models presented in this study.

General perceptions about certified buildings were evaluated using a 4-point Likert-type scale measuring the extent to which an economic developer strongly disagreed, disagreed, agreed, or strongly agreed with the following five statements: (1) the availability of certified buildings is important to companies considering my region, (2) some form of environmental certification should be required for new real estate development, (3) economic development incentives should be offered to encourage the development of certified buildings, (4) companies considering my region distinguish between different levels of certification (i.e., LEED silver, gold), and (5) developers in my region are knowledgeable about the construction of certified buildings.⁵ The first question was used to determine if certified buildings are perceived to be useful in business recruitment, whereas the second and third questions were used to assess whether economic developers believe sustainable development should be encouraged or required by local government. Statements 4 and 5 were used to explore perceived barriers to sustainable development associated with incomplete information held by tenants and real estate practitioners.

To explore economic developers’ attitudes further, five additional questions were asked to examine “motivating factors” encouraging firms to seek out certified buildings. These included (1) conformance with employee values, (2) increasing employee workplace satisfaction, (3) enhancing employee recruitment, (4) obtaining capital cost savings, and (5) capturing government incentives. A 4-point Likert-type scale was once again used to measure the extent of agreement with each of these statements. The responses offer insight regarding the value proposition of LEED- and Energy Star–certified buildings from the perspective of economic developers working in local government.

Responses to each of the aforementioned attitudinal questions were regressed on a series of explanatory variables to estimate 10 ordinal logistic regression models.⁶ Ordinal logistic regression was selected as opposed to ordinary least squares because the dependent variables were derived from scores on a 4-point Likert-type scale, which cannot be interpreted in the same manner as interval data.⁷ Numeric values assigned to attitudes via a scale are considered somewhat arbitrary because the distance between adjacent categories is unknown. Thus, these scores should not be placed on an equally spaced continuum for the purpose of statistical analysis (Long, 1997). Ordinal logistic regression offers a means of overcoming this problem and is more appropriate than ordinary least squares regression when analyzing these types of data.

The explanatory variables included in the models were constructed using data collected from the survey instrument. Each of these questions was designed to control for the mitigating effects of personal characteristics and community characteristics on respondents’ attitudes. The size of the population served by an economic developer was measured using an ordinal variable with values ranging from 1 to 9 to represent areas with less than 10,000 residents to those with two million residents or more.⁸ Another ordinal variable with values ranging from 1 to 6 was created to account for communities with unemployment rates less than 5% to those with unemployment rates of 13% or more. These variables were used as an alternative to U.S. census data when controlling for population and economic conditions because self-reported region of employment was the only reliable geographic identifier available for all respondents. Zip codes were not provided by a number of survey participants, which prevented more robust spatial analysis.⁹ Ranges were used in the survey to take into account the fact that economic developers may not know the exact population or unemployment rate within their jurisdiction.

An economic developer’s region of employment was identified by asking survey respondents to select the Midwest, Northeast, South, or West as defined by the U.S. Census Bureau.¹⁰ Binary variables for each of these regions were created and initially included in the ordinal logistic regression models, with the West region excluded as the comparative category to account for natural resource constraints in this part of the country anticipated to make LEED- and Energy Star–certified buildings attractive. None of these variables were statistically significant. An alternative model specification, including a single dichotomous variable designed to compare attitudes in the West region to those in the rest of the country, also proved to be insignificant. In fact, geographic variables only yielded significant coefficients in a specification including a single binary variable representing the South region. The results presented in this study reflect this model specification. Once again, the absence of a reliable geographic identifier other than self-reported region of employment made it impossible to conduct more robust spatial analysis. Control variables derived from the survey for population and economic conditions in the area served by a respondent did, however, offer a limited means of addressing intraregional factors.

Personal characteristics of economic developers were controlled for as follows. Two binary variables were created to represent an economic developer’s gender and race with 1 representing men and Caucasians and 0 representing women and minorities. Another three binary variables were created to account for self-identified political ideologies of conservative, liberal, and moderate. An ordinal variable with values ranging from 1 to 4 was created to measure four levels of educational attainment from high school graduation to postgraduate education, and a similar variable was created for age with values ranging from 1 to 6 to denote those younger than 25, 25 to 34, 35 to 44, 45 to 54, 55 to 64, and 65 and older.

Variance inflation factors were examined for all of the variables included in the models and none of the variables were found to be highly correlated.¹¹ This was necessary to make sure women and minority economic developers were not concentrated in certain regions of the country or in larger cities with stronger economies. Similarly, steps needed to be taken to ensure women and minority economic developers were not younger or better educated than their peers as a result of historic inequalities in hiring practices within local governments. All these scenarios could result in the misattribution of attitudinal differences to gender, age, or race, which might be better explained by differences in support structures or organizational values across communities with different characteristics. The reduced functional form of the models presented in this study can therefore be expressed as follows:

Economic Developer ’ s Attitude H_{1 - 10} = f (G, A, R, I, E, P, U, L, ε)

H_1-10 = Extent to which an economic developer agrees/disagrees with 10 different statements

G = Gender

A = Age

R = Race

I = Political ideology

E = Educational attainment

P = Population of the city or region an economic developer serves

U = Unemployment rate in the city or region an economic developer serves

L = Region of the country an economic developer serves

ε = Error term

The models are suitable to test several hypotheses emerging from the sustainable real estate development literature. LEED- and Energy Star–certified buildings are anticipated to have the greatest perceived value to economic developers representing populous areas and those with low unemployment rates. These outcomes are expected as a result of strong tenant demand for sustainable buildings in these markets, as well as greater awareness of building certification systems among real estate developers, tenants, and economic developers working in these areas. Women, younger professionals, the well educated, and those with more liberal political ideologies are also expected to have more favorable attitudes toward LEED- and Energy Star–certified buildings as a result of heightened environmental concern. Racial and regional differences in attitudes toward sustainable buildings are more difficult to predict.

Empirical Results

Table 1 reports descriptive statistics for the variables included in the models. The results suggest a relatively seasoned and well-educated sample of economic development professionals, with unsurprising racial and gender inequalities. More than 91% of the respondents identified themselves as Caucasian, 65% as male, 57% as holding postgraduate degrees, and 90% as 35 or older. Approximately 57% of the respondents identified themselves as moderates, whereas 31% and 12% reported conservative and liberal political ideologies, respectively. Just more than half of the respondents represented communities with more than 100,000 residents, and nearly all worked in jurisdictions with unemployment rates of 10% or less. Respondents were heavily concentrated in the South and Midwest regions, which is consistent with IEDC’s membership. Additional descriptive statistics and a complete articulation of the survey questions can be found in the Measurement Appendix.

Table 1.

Descriptive Statistics.

Variable	n	Minimum	Maximum	Mean	SD
Economic developer attitudes
GP1: Availability	417	1	4	2.43	0.779
GP2: Requirements	416	1	4	2.36	0.899
GP3: Incentives	416	1	4	2.73	0.819
GP4: Levels	414	1	4	2.24	0.798
GP5: Knowledge	417	1	4	2.82	0.779
MF1: Employee values	415	1	4	2.42	0.724
MF2: Workplace satisfaction	415	1	4	2.47	0.704
MF3: Employee recruitment	414	1	4	2.54	0.747
MF4: Capital cost savings	412	1	4	2.50	0.806
MF5: Government incentives	413	1	4	2.91	0.747
Economic developer characteristics
Liberal	404	0	1	0.12	0.329
Moderate	403	0	1	0.57	0.496
Age	409	1	6	3.90	1.071
Caucasian	406	0	1	0.91	0.292
Education	408	1	4	3.50	0.635
Male	408	0	1	0.65	0.476
Community characteristics
Population	420	1	9	4.70	2.011
Unemployment	415	1	6	3.41	1.230
South	373	0	1	0.42	0.494

Because IEDC does not keep comprehensive statistics on the age, education, political ideology, or race of its members, it is impossible to determine if the sample is perfectly representative of the population. However, the survey used in this study achieved a response rate approaching 12%, which is consistent with the response rates achieved in IEDC salary surveys conducted nationally on a biannual basis. A review of the organization’s membership directory also revealed a population composed of 37% women and 43% working in the South region, both of which are very similar to the sample. These comparisons do not completely preclude the possibility of response bias but do dispel significant concerns regarding the generalizability of the results to the population of IEDC members.¹²

Responses to the first attitudinal question (GP1) suggest that economic developers are relatively evenly split as to whether LEED- and Energy Star–certified buildings are important to firms considering their region. A majority of these respondents agreed or strongly agreed with the use of incentives to encourage this type of development (GP2), whereas less favorable attitudes existed toward the use of regulatory mandates (GP3). Tenants operating in these markets appear to have an understanding of building certification systems and were generally perceived to distinguish between certification levels (GP4). Real estate developers, on the other hand, were less frequently perceived to be knowledgeable about the construction of LEED- and Energy Star–certified buildings, with just more than half of the respondents agreeing or strongly agreeing that this is the case in the region they serve (GP5).

Turning next to motivating factors, the survey results demonstrate that economic developers have divergent opinions regarding the reasons why companies seek out certified buildings. Attitudes were relatively evenly split regarding these buildings’ ability to support employee values (MF1), increase workplace satisfaction (MF2), assist in employee recruitment (MF3), or generate cost savings (MF4). A greater number of respondents believed companies seek out certified buildings to take advantage of government incentives (MF5). These attitudes appear to denote concern among economic developers regarding the value proposition of certified buildings in the absence of public sector support.

Results of the ordinal logistic regression models presented in Tables 2 and 3 illustrate the mitigating effects of personal and community characteristics on attitudes toward LEED- and Energy Star–certified buildings.¹³ The most striking pattern emerges in the coefficients measuring the impact of gender on general perceptions. In all five of these models, women were found to have more favorable attitudes toward certified buildings than their male counterparts working in local economic development. Women tended to view the availability of these buildings as being important to companies considering their region and expressed greater levels of support for the use of mandates and incentives to encourage sustainable real estate development. They also perceived incomplete information about building certification programs among companies and real estate developers to be less significant problems than their male counterparts.

The other results reported in Table 2 offer little support for the hypothesized relationships between personal characteristics and perceptions about sustainable real estate development. Younger, well-educated, and liberal economic developers did not consistently express more favorable attitudes toward LEED- and Energy Star–certified buildings than their peers. Economic developers with liberal political ideologies were less supportive of the use of economic incentives to encourage the development of certified buildings, whereas older professionals had stronger preferences for the use of government mandates. Caucasians expressed greater concerns about incomplete information serving as an obstacle to sustainable real estate development. Because the source of these attitudinal differences is not apparent from the theoretical literature, additional research is needed to understand these relationships.

Table 2.

Ordinal Logistic Regression Results: General Perceptions About Certified Buildings.

Variable	GP1: Availability	GP2: Requirements	GP3: Incentives	GP4: Levels	GP5: Knowledge
Economic developer characteristics
Moderate	0.011	0.250	−0.141	0.272	0.055
Liberal	−0.027	0.361	−0.661*	−0.129	−0.531
Caucasian	−0.191	0.351	−0.280	−0.792**	−0.786*
Age	0.078	0.169*	−0.129	−0.036	0.031
Education	0.071	−0.143	−0.064	0.149	−0.075
Male	−0.425**	−0.454**	−0.393*	−0.392**	−0.417**
Community characteristics
Unemployment rate	−0.136*	0.060	−0.045	0.037	−0.043
Population	0.110**	0.213***	0.006	0.041	0.107**
South	0.397**	−0.257	−0.099	0.272	0.471***
Model	0.050**	0.000***	0.050*	0.080*	0.003***
Nagelkerke R²	0.050	0.090	0.042	0.0410	0.070

p < .10. **p < .05. ***p < .001.

For the most part, community characteristics performed as expected in Table 2. Economic developers working in areas with higher unemployment rates perceived certified buildings to be less important to companies considering their region, whereas those working in more populous areas perceived certified buildings to be more important. Those working in regions with larger populations also expressed stronger preferences for government mandates. The results may be attributable to heightened demand for certified buildings, as well as to a greater understanding of the benefits provided by these assets, in larger markets with stronger economies. As expected, economic developers working in more populous regions perceived real estate developers to be more familiar with LEED- and Energy Star–certification programs. This outcome corresponds with higher levels of business sophistication in these markets and greater exposure to sustainable building practices.

Economic developers working in the South region perceived certified buildings to be more important to companies and expressed more confidence that real estate developers were familiar with LEED and Energy Star programs. This outcome is difficult to interpret and may be attributable in part to the manner in which regional variables were specified. U.S. Census Bureau regions cover large portions of the country and offer only a limited means of controlling for geographic differences influencing attitudes toward sustainable real estate development. For example, Washington, D.C. and Birmingham, Alabama are both located in the South region, even though they have very different economic bases, regulatory environments, and demand for natural resources. Controlling for population and economic conditions takes into account some of these intraregional differences, but certainly not all the factors anticipated to influence attitudes. Thus, the observed regional differences in economic developers’ perceptions must be interpreted with caution and in light of data limitations preventing more robust spatial analysis.

The results of the ordinal logistic regression models presented in Table 3 examine the motivating factors anticipated to encourage companies to seek out certified buildings. Several interesting outcomes emerge. Gender differences are not observed for the most part and only in the model examining anticipated capital cost savings do women report more favorable attitudes toward certified buildings than men. These findings, interpreted in conjunction with the results reported in Table 2, suggest that women in economic development are generally more optimistic about building certification programs than their male counterparts, but they do not have significantly different perceptions about the benefits derived by companies occupying these facilities. This may reflect heightened levels of environmental concern among women rather than a unique understanding of the factors driving tenant demand for these buildings.

Table 3.

Ordinal Logistic Regression Results: Motivating Factors.

Variable	MF1: Values	MF2: Satisfaction	MF3: Recruitment	MF4: Savings	MF:5 Incentives
Economic developer characteristics
Moderate	0.280	0.078	0.111	0.470	−0.021
Liberal	−0.100	−0.515*	−0.032	−0.171	0.126
Caucasian	−0.570	−0.577	0.094	−0.199	−0.209
Age	0.032	0.084	0.075	−0.216**	−0.155*
Education	0.084	0.094	−0.138	−0.138	−0.292*
Male	−0.100	0.010	−0.208	−0.813***	−0.262
Community characteristics
Unemployment	−0.164**	−0.142*	−0.207***	−0.052	0.148
Population	0.135***	0.127***	0.143***	0.012	−0.044
South	−0.560***	−0.019	0.131	0.240	0.394**
Model	0.003***	0.050**	0.033**	0.001***	0.023**
Nagelkerke R²	0.070	0.050	0.048	0.076	0.054

p < .10. **p < .05. ***p < .001.

The other relationships between personal characteristics and economic developers’ attitudes presented in Table 3 are more difficult to interpret. However, a much clearer pattern emerges in relation to community characteristics. Those working in communities with higher unemployment rates identified employee values, workplace satisfaction, and employee recruitment as less important factors encouraging companies to seek out certified buildings. This is logical because competition for employees in weak markets is likely to be less robust and fewer efforts may be required to attract human capital. Alternatively, economic developers working in more populous areas expressed stronger support for statements suggesting companies seek out certified buildings to improve the employee work environment and to assist in recruitment initiatives. These perceptions are potentially attributable to concentrations of highly skilled employees in larger metropolitan areas, who have been found to be more productive and more satisfied when working in buildings with sustainable design features. Economic developers working in the South region were found to perceive government incentives as an important factor encouraging companies to occupy certified buildings, whereas employee values were identified as a less important factor. These outcomes are once again difficult to interpret because of the large geographic areas covered by each of the regional dummy variables.

Conclusions

Economic developers working in local government often have the ability to use their professional discretion to support sustainable real estate development policies and projects. Their eagerness to do so is likely to hinge on the anticipated economic benefits derived from such initiatives. The analysis presented in this study indicates that economic developers have divergent views on this issue, which are influenced by their personal characteristics and the characteristics of the communities where they work. Generating support for sustainable building practices among this group may therefore require thoughtful policy making that is considerate of local economic conditions, ongoing executive education to ensure the benefits of LEED- and Energy Star–certified buildings are well understood, and greater efforts to increase gender diversity in the economic development profession.

The observed skepticism about the role certified buildings can play in the business recruitment process among economic developers working in smaller communities and those with weaker economies highlights the importance of tailoring sustainability initiatives to the local market. Because significant rent premiums for environmentally sustainable space may prove difficult to achieve, communities with these characteristics should focus on policies that accentuate operating cost savings and reduce any cost premium associated with “green” construction. This approach is likely to prove more fruitful than imposing broad sustainable development mandates that do not take into account economic realities or tenant demand.

At the same time, economic developers working in challenging markets must be provided with executive education opportunities that focus on the declining cost of constructing LEED- and Energy Star–certified buildings, the operating efficiencies offered by these facilities, and the benefits that can be derived from sustainable building practices across all types of markets. Such an approach is necessary to address information asymmetries capable of impinging on a community’s ability to align economic and environmental policy objectives.

Finally, the models presented in this study support the need for gender diversity in the economic development profession to heighten the level of environmental concern in local government and to increase support for sustainable real estate development initiatives. This is necessary because women participating in the study consistently viewed LEED- and Energy Star–certified buildings to be more important to companies considering their region when compared to their male counterparts. They also expressed greater support for government programs intended to increase the supply of certified buildings and perceived fewer obstacles to sustainable development associated with information asymmetries. Gender equality among economic developers working in local government may therefore help bring sustainable real estate development initiatives to the forefront of the public policy discourse. This assertion is grounded in the principles of representative bureaucracy theory, which espouses the value of bureaucratic organizations with demographic profiles similar to the constituencies they serve.

Before concluding, it is important to note that this study offers only a starting point when examining economic developers’ attitudes toward sustainable real estate development. At least four issues require further analysis. First, research must be conducted to assess whether community characteristics, other than those controlled for in this study, influence perceptions about LEED- and Energy Star–certified buildings. Noteworthy examples include intraregional differences in land use regulations, climate, and population density. Second, efforts must be made to distinguish between legitimate concerns held by economic developers and unsubstantiated biases capable of eroding support for sustainable real estate development. Recognizing the difference between these two sources of opposition may aid in policy formation. Third, steps must be taken to determine if economic developers’ attitudes translate into active advocacy or antagonism toward sustainable real estate development initiatives. This is essential because there are reasons to believe economic developers can influence policy outcomes at the local level by framing issues, synthesizing information, and building stakeholders consensus. And fourth, the attitudes of economic developers working in different professional capacities and those representing trade organizations other than the IEDC must be examined. Both of these factors are important because they are anticipated to influence perceptions about the role economic developers should play in sustainable real estate development policy. These issues are outside of the scope of this research endeavor, but they provide a path forward for future study.

Measurement Appendix

All measures are drawn for the International Economic Development Council Survey conducted in 2012.

Dependent Variables

GP1

An ordinal dependent variable indicating responses to a question asking whether, and how strongly, the respondent agrees with the statement: “The availability of certified buildings is important to companies considering my region.” Potential and observed range 1 to 4, where 4 denotes respondent strongly agrees with the statement. M = 2.43; SD = 0.779; Strongly Disagree (12.44%); Somewhat Disagree (37.32%); Somewhat Agree (44.50%); Strongly Agree (5.74%).

GP2

An ordinal dependent variable indicating responses to a question asking whether, and how strongly, the respondent agrees with the statement “Some form of environmental certification should be required for new real estate development.” Potential and observed range 1 to 4, where 4 means that the respondent strongly agrees with the statement. M = 2.36; SD = 0.899; Strongly Disagree (18.94%); Somewhat Disagree (36.21%); Somewhat Agree (35.01%); Strongly Agree (9.83%).

GP3

An ordinal dependent variable indicating responses to a question asking whether, and how strongly, the respondent agrees with the statement “Economic incentives should be offered to encourage the development of certified buildings.” Potential and observed range 1 to 4, where 4 means that the respondent strongly agrees with the statement. M = 2.73; SD = 0.818; Strongly Disagree (9.11%); Somewhat Disagree (22.78%); Somewhat Agree (53.48%); Strongly Agree (14.63%).

GP4

An ordinal dependent variable indicating responses to a question asking whether, and how strongly, the respondent agrees with the statement “Companies considering my region distinguish between different levels of certification (i.e., LEED silver, gold)” Potential and observed range 1 to 4, where 4 means that the respondent strongly agrees with the statement. M = 2.24; SD = 0.798; Strongly Disagree (19.28%); Somewhat Disagree (41.20%); Somewhat Agree (36.14%); Strongly Agree (3.37%).

GP5

An ordinal dependent variable indicating responses to a question asking whether, and how strongly, the respondent agrees with the statement “Developers in my region are knowledgeable about the construction of certified buildings” Potential and observed range 1 to 4, where 4 means that the respondent strongly agrees with the statement. M = 2.82; SD = 0.779; Strongly Disagree (5.02%); Somewhat Disagree (26.08%); Somewhat Agree (51.20%); Strongly Agree (17.70%).

MF1

An ordinal dependent variable indicating responses to a question asking whether, and how strongly, the respondent agrees with the statement “Employee values are an important reason why companies in my region seek out certified buildings.” Potential and observed range 1 to 4, where 4 means that the respondent strongly agrees with the statement. M = 2.42; SD = 0.724; Strongly Disagree (9.38%); Somewhat Disagree (43.99%); Somewhat Agree (41.83%); Strongly Agree (4.81%).

MF2

An ordinal dependent variable indicating responses to a question asking whether, and how strongly, the respondent agrees with the statement “Workplace satisfaction for employees is an important reason why companies in my region seek out certified buildings.” Potential and observed range 1 to 4, where 4 means that the respondent strongly agrees with the statement. M = 2.82; SD = 0.779; Strongly Disagree (7.45%); Somewhat Disagree (42.55%); Somewhat Agree (44.95%); Strongly Agree (5.05%).

MF3

An ordinal dependent variable indicating responses to a question asking whether, and how strongly, the respondent agrees with the statement “Employee recruitment is an important reason why companies in my region seek out certified buildings.” Potential and observed range 1 to 4, where 4 means that the respondent strongly agrees with the statement. M = 2.54; SD = 0.747; Strongly Disagree (7.23%); Somewhat Disagree (39.28%); Somewhat Agree (45.06%); Strongly Agree (8.43%).

MF4

An ordinal dependent variable indicating responses to a question asking whether, and how strongly, the respondent agrees with the statement: “Capital cost savings are an important reason why companies in my region seek out certified buildings.” Potential and observed range = 1 to 4, where 4 means that the respondent strongly agrees with the statement. M = 2.5; SD = 0.806; Strongly Disagree (8.47%); Somewhat Disagree (43.83%); Somewhat Agree (36.08%); Strongly Agree (11.62%).

MF5

An ordinal dependent variable indicating responses to a question asking whether, and how strongly, the respondent agrees with the statement “Government incentives are an important reason why companies in my region seek out certified buildings” Potential and observed range = 1 to 4, where 4 means that the respondent strongly agrees with the statement. M = 2.91; SD = 0.747; Strongly Disagree (3.86%); Somewhat Disagree (21.01%); Somewhat Agree (55.07%); Strongly Agree (20.05%).

Independent Variables

Male

A dummy variable where 1 indicates male (65%); 0 indicates female (35%). M = 0.65; SD = 0.476.

Age

An ordinal scale with six categories indicating the respondent’s age from youngest to oldest. Observed range = 1 to 6; M = 3.9; SD = 1.071; Under 25 (0.35%); 25 to 34 (9.65%); 35 to 44 (22.81%); 45 to 54 (32.81%); 55 to 64 (28.77%); 65+ (5.61%).

Caucasian

A dummy variable where 1 indicates Caucasian (91%); 0 indicates non-White (9%). M = 0.91; SD = 0.292.

Conservative

A dummy variable where 1 indicates conservative; 0 indicates other such as liberal or moderate. M = 0.12; SD = 0.329; Conservative (31%); Liberals (12%).

Moderate

A dummy variable where 1 indicates moderate; 0 indicates other such as conservative or liberal. M = 0.57; SD = 0.496; Moderates (57%).

Educational Attainment

An ordinal scale with four categories indicating the respondent’s highest level of education. Observed range 1 to 4; M = 3.5; SD = 0.635; High school or less (.53%); Associate’s degree/some college (4.75%); Bachelor’s degree (37.50%); Postgraduate degree (57.22%).

Population

Of the jurisdiction an economic developer serves. An ordinal scale from 1 to 9 indicating population ranges from lowest to highest. M = 4.7; SD = 2.011; Under 10,000 (4.04%); 10,000 to 24,999 (8.31%); 25,000 to 49,999 (15.68%); 50,000 to 99,999 (16.86%); 100,000 to 249,999 (21.85%); 250,000 to 499,999 (12.35%); 500,000 to 999,999 (9.03%); 1m to 1.99m (4.75%); 2m+ (7.13%).

Unemployment Rate

Of the jurisdiction an economic developer serves. An ordinal scale from 1 to 6 indicating unemployment ranges from lowest to highest. M = 3.41; SD = 1.23; Under 5% (4.57%); 5% to 6% (18.99%); 7% to 8% (30.77%); 9% to 10% (29.57%); 11% to 12% (8.89%); 13%+ (7.21%).

South

A dummy variable where 1 indicates the economic developer’s jurisdiction of employment is located in the South region (42%), 0 = All other regions (58%). M = 0.42; SD = 0.494.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author Biographies

Suzanne M. Leland serves as a professor in the Department of Political Science and Public Administration at the University of North Carolina at Charlotte, as well as the director of the MPA program. Her research interests include economic development, local government structure, and transportation governance.

Dustin C. Read serves as an assistant professor in the Department of Apparel, Housing, and Resource Management at Virginia Tech. His research interests include real estate management, development, and land use policy.

Michael Wittry is a PhD student in finance at the University of Washington’s Foster School of Business. His research interests currently include corporate finance, financial institutions, and real estate.

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