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Segmenting the Construction Industry: A Quantitative Study of Business Interest Groups in a Low Salience Policy Setting

Segmenting the Construction Industry: A Quantitative Study of Business Interest Groups in a Low... JOURNAL OF SUSTAINABLE REAL ESTATE 2021, VOL. 13, NO. 1, 30–47 ARES https://doi.org/10.1080/19498276.2021.2002504 American Real Estate Society Segmenting the Construction Industry: A Quantitative Study of Business Interest Groups in a Low Salience Policy Setting J. C. Martel School of Public Affairs and Administration, University of Kansas, Lawrence, KS, USA KEYWORDS ABSTRACT Building codes; business The intent of this research is to detect if business interest group involvement in urban sus- influence; microeconomics; tainability policymaking increases or decreases the likelihood of policy adoption. Extant sustainability; urban policy research reports both positive and negative effects with varying magnitude. This study seg- ments the construction industry into distinctive categories to explain conditions under which types of business interest groups support or oppose building regulations drawing from competing theoretical angles—private and public interest group theory. It analyzes the effects of two groups—traditional construction and green building association members— on the adoption of building energy codes, a low salience policy issue that attracts technical experts more so than citizen groups. After applying web scraping algorithms, logistic regres- sion explains the probability of code stringency given differences in the presence of trade association members in cities while controlling for demographic, social, and political factors. Findings suggest that this approach to operationalizing interest groups has merit. Despite being from the same industrial category, the segmented business interest groups have divergent effects on the local building policies with traditional construction interest groups having a greater negative effect on the odds of a city’s energy code adoption compared to the green builder interest group. Introduction interest groups but tend to engage a narrowly focused group of technical professionals, such as Commercial and residential buildings are respon- industry associations (Jones & Baumgartner, 2005; sible for approximately 12% of the U.S. greenhouse Koski, 2010, p. 96). An issue often becomes low sali- emissions portfolio (U.S. Environmental Protection Agency, 2017). While the environmental impact of ence when the public does not directly experience buildings is a central concern for urban sustainabil- the issue (Lachapelle et al., 2012; Leiserowitz, 2007; ity (Garren & Brinkmann, 2018; Krause & Martel, Lowry & Joslyn, 2014, p. 156). Patterns of power, 2018), the buildings policy domain is rarely studied influence, and collusion of business interest groups in political science and policy studies as it is often in low salience urban policy settings are distinct considered low salience and researchers tend to from other issue arenas that attract widespread focus on higher salience situations (Go, 2016; Koski, attention appealing to personal beliefs, such as 2010; Lowry & Joslyn, 2014, p. 158). Low salience immigration or gay rights. It is unknown how policy issues are generally characterized by low lev- insights from the body of interest group scholarship, els of political participation, public attention, and focused mostly on national-level high salience meaningful public opinion, empirically observed as issues, translate to low salience policy arenas at the low levels of media attention or low rankings on local level. The extent to which firms assemble into national polls (Cobb & Elder, 1972; Downs, 1972; groups to pursue profit maximization or assemble Gallup, 2021; Koski, 2010; Lowry & Joslyn, 2014; Wlezien, 2005). These issue arenas can attract to promote public interest—an interplay of classical CONTACT J. C. Martel Jmartel701@hotmail.com School of Public Affairs and Administration, University of Kansas, 5737 Longleaf Drive, Lawrence, KS 66049, USA. 2022 The Author(s). Published with license by Taylor & Francis Group, LLC This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. JOURNAL OF SUSTAINABLE REAL ESTATE 31 economic theory and neocorporatism—may depend economic opportunities; ethical concerns; and regu- on issue salience. latory compliance (Bansal & Roth, 2000; Devine, This research explores this interplay by analyzing 2017). These firms often “float” the burden of added the effects of two types of organized interest costs to construct buildings according to stringent groups—traditional construction industry represen- environmental standards, meaning that the green tatives and “green” business professionals—on construction firm absorbs the incremental cost dur- building energy code adoptions at the local level. It ing the construction process and the extent to asks, what are the effects of traditional and “green” which the consumer will absorb the cost is seem- industry member associations on building energy code ingly uncertain (Ciochetti & McGowan, 2010; Dixon policy adoption? It has been acknowledged that et al., 2014). homebuilders are not a homogeneous group (Berry Segmenting actors within an industrial group— & Portney, 2013; Somerville, 1999), yet how we the- such as traditional and “green” construction industry oretically and empirically segment homebuilders actors—is intended to deepen the understanding of into logical categories in order to understand their diverse business interest groups effects on urban differences and effects of those differences on vari- sustainability policy adoption, an endeavor that has ous phenomena is yet to be fully understood. In been requested in past research (e.g., Portney, 2009; this research, a framework for segmentation is pro- Sharp et al., 2011, p. 438). Extant literature has rec- vided, grounded in classical economic theories and ognized that business interest groups are not newer theories of neocorporatism and corporate homogenous, including homebuilders (Somerville, responsibility, as well as a way to empirically test 1999), and diversity of business interest groups has the homebuilder segments. As Harrison (2017) been largely explored through surveys (e.g., Berry & noted, “The notion that political ideology may Portney, 2013), yet business interest group diversity materially influence real estate market outcomes is has not been tested much in a quantitative way. not new” (p. 89). For the purposes of this study, the Many scholars tend to consider business interests traditional developer community is associated with with respect to the environmental policy as always a pro-development ideology justifying urban growth pursuing deregulation (e.g., Kamieniecki, 2006, for personal gain (Logan & Molotch, 1988; p. 53), yet some industry professional groups might Mohamed, 2006; Molotch, 1976), in line with the support regulations that are in the public interest, classical economic viewpoint of the firm as a profit or in favor of their own market differentiation and maximizer (Coase, 1937) and political-economic the- growth. Bringing more clarity and precision to ory of how firms form political coalitions towards understanding this empowered group of stakehold- the goal of resolving political conflicts (March, ers is important, accomplished by bridging micro- 1962). Interest group pluralism and behavioral eco- economic theories of firms, interest groups nomics suggests that firms will compete with similar scholarship, and urban policy research. Analyzing established groups within the same industry, such business groups in a single category, as typically as green construction interest groups, and ultim- done in urban policy research, fails to discern the ately oppose environmental regulation that imposes motivational spectrum that exists within and across cost burdens, diffuse benefits, or economic uncer- interest groups. There is more complexity in interest tainty to the firm (Mohamed, 2006; Scruggs, 2003). group composition than commonly realized, and it Indeed, May and Koski (2007) found that “the stron- is important to understand how these diverse inter- gest opposition to stronger [building energy] codes ests, albeit within the same economic or industrial comes from the state homebuilder organizations” category, operate in an important policy area. (p. 57). Contrastingly, green developers are associ- This study proceeds as follows. The theory section ated with the neocorporatist theory that some firms explores conditions under which business interest act in the public interest on behalf of the govern- groups are expected to support or oppose environ- ment (Kraft & Kamieniecki, 2007; Scruggs, 2003) and mental regulations and review empirical findings from the corporate environmental responsibility theory relevant extant research leading to three testable that firms act in the public interest as a response to hypotheses. Next, background information on build- stakeholder pressures and corporate image benefits; ing energy codes is provided to orient the reader to 32 J. C. MARTEL the case selection. The research design section pro- the viewpoint for support of environmental regula- vides descriptions of the variables and expectations tion in the interest of common welfare. on how the variables relate to policy adoption, mostly drawing from urban sustainability research. It also Private Interest Group Theory notes technology used to carry out the research, With interest groups conceptualized as “any set of including Python packages, CenPy, Google,and individuals with similar beliefs, identifications, or Beautiful Soup for API integration and algorithmic data interests” (Baumgartner & Leech, 1998, p. 29), the collection; SQLite for data storage and querying; and R traditional economic perspective proposes that eco- for statistical computing. Next, results from logistic nomically rational individuals seek to maximize their regression modeling and exponentiation of the coeffi- positions in society (Berry & Wilcox, 2009,p.64). cients into odds ratios are provided for easier inter- Some individuals join interest groups as leverage to pretation of the model. The study concludes with a improve their position. Economically rational and pol- discussion of the modeling results as it relates to itically strategic individuals will work to advance pol- broader explanations of interest group activity and cit- icy alternatives where their benefits are concentrated ies’ actions on policy adoption, ending with the for self-interest and costs are diffused to other mem- article’s contribution to urban sustainability literature. bers of society (Olson, 1965). Along this line of rea- soning, energy-efficient building mandates are Literature Review expected to foster opposition from the construction Multiple theories generate expectations of how industry as the incremental construction costs are business interest groups will act in policy adoption incurred by the construction professional (Deslatte & settings. These theories commonly address the moti- Swann, 2016, p. 584; Wilms, 1982, p. 555). In the vations of business interest groups and predict “split incentive” case when the builder incurs the costs but others receive the benefits, the benefits of divergent outcomes in support or opposition of energy codes are granted to the buildings’ buyers in environmental policy depending on the group’s terms of lower building operating costs, tenants who motivations (Table 1). The classical economic per- enjoy increased building occupant comfort, and soci- spective that businesses are comprised of executives ety at large who benefits from lesser environmental who are rational profit-maximizers underlies the impacts (Sun et al., 2016, p. 3). Construction profes- idea that private firms will oppose environmental sionals are not expected to support such scenarios as regulation because regulation is perceived to limit it would be financially disadvantageous to the profits from industrial development (Ball, 2003; builder. Generally, construction professionals are Kamieniecki, 2006; March, 1962; May, 2005). expected to collude within an interest group towards However, recent discussions have posed that many the common goal of supporting policies that favor private sector actors are irrational in an economic growth and development and minimize financial sense guided by the desire of individuals and losses to the business (Feiock et al., 2008;Gauthrie & groups to act for the common good (e.g., May, Wooldridge, 2012; Logan & Molotch, 1988;March, 2005; Portney, 2013; Portney & Berry, 2016). These 1962; Molotch, 1976, p. 311; Mulligan et al., 2014). divergent perspectives have been broadly labeled In a survey of building professionals, Mulligan as private and public interest group theories (see et al. (2014) found that increased costs were the Jenner et al., 2012). Private interest group theory most important barrier to the firm deciding to build expects that industry-oriented interest groups will green, followed by client resistance. Gauthrie and oppose environmental regulation in the interest of Wooldridge (2012) also found no empirical evidence personal gain while the public perspective offers that green building incentive programs had influ- Table 1. Expected direction of coefficients in the energy code enced firms to voluntarily utilize green building adoption model. practices, supporting the classical economic per- Theory Policy position Direction of coefficient spective that firms avoid economic uncertainty, Private interest Oppositional Negative increased costs, and diffused benefits. Devine (2017) Public interest Supportive Positive Counterbalanced Negotiated No effect/null hypothesis expects that developers will be slow to adopt green JOURNAL OF SUSTAINABLE REAL ESTATE 33 building technologies due to the economics and construction professionals might support new build- financial viability of passing incremental costs to the ing codes to better provision public goods for their consumer. Further, Harrison (2017) found that green clients and society in terms of cleaner air resulting lease rate premiums vary systematically by political from energy use reduction in buildings and selec- ideology in cities, indicating that there may be tion of cleaner fuel sources for buildings, aligned some rationale for uncertainty in a homebuilder’s with environmental sustainability ideals (May & ability to gain a premium for building to environ- Koski, 2007). While their motivations may partially mentally sustainable standards. be self-interested in an attempt to secure business May and Koski (2007) surveyed state homebuilder from clients who demand cleaner buildings, green associations, national building code organizations, building construction professionals and their associ- professional architect organizations, and other ated interest groups are still supporting codes that, groups involved in building energy advocacy about in effect, protect common pool resources. their influence, measured by asking whether they In the area of corporate environmental responsi- supported, opposed, or were not involved in the bility asking why some firms embrace environmen- policy adoption process for energy-efficient man- tal initiatives while others do not in, Bansal and dates (May & Koski, 2007, p. 57). In the study, May Roth (2000) identify regulatory compliance, eco- and Koski (2007) found that interest groups oppos- nomic opportunities, stakeholder pressures, and eth- ing energy-efficient mandates—the homebuilder’s ical concerns as key motivations. Multiple studies associations—had three times stronger influence find that stakeholder pressures are the most import- than the environmental interest groups supporting ant determinant, as clients and investors call for the mandates (p. 59). environmental protection (e.g., Darnall et al., 2009; H1 (Oppositional): Higher numbers of traditional Gonzalez-Benito & Gonzalez-Benito, 2006). Firms can construction industry interest group members per garner a positive reputation through their support capita are likely to limit the probability of the of environmental initiatives, creating a competitive adoption of energy efficient mandates that apply to edge for the company (Bansal & Roth, 2000, p. 724). privately-owned buildings and development projects. Mulligan et al. (2014) also found that company vision/values were the most important motivation Public Interest Group Theory for a firm’s decision to build green (39% of respond- As economic rationality failed to explain cooper- ents), while 0% were motivated by competition with ation among actors in otherwise competitive envi- other developers (p. 193). This line of reasoning sup- ronments, behavioral theories of rational choice ports that green building firms have a distinctive emerged to argue that individuals within groups are value set as a homebuilder segment. Determining less economically rational than Olson (1965) and which motivational factor is most prevalent in the other interest group analysts had assumed (Berry green construction industry is beyond the scope of et al., 2006; Ostrom, 1990, 1998; Schattschneider, this study, but we can assume that an interaction of 1975). Berry et al. (2006) express, the aforementioned motivations, including market … the initial theory, popularized by Mancur Olson, badly differentiation, stakeholder responsiveness, and eth- underestimated the propensity of individuals to be, in ical motivations, inspires construction firms to oper- economists’ jargon, “irrational.” That is, Americans have ate in the green building market. proven that they are all too willing to join organizations that command tangible costs, such as volunteer time or H2 (Supportive): Higher numbers of green construction financial contributions, but offer ideological rather than industry interest group members per capita are likely material rewards … their work tended to be more to increase the probability of the adoption of energy ideological than self-interested (p. 11) efficient mandates that apply to privately-owned buildings and development projects. Along these lines, Ostrom (1990) had found that in some situations, people naturally organize to Counterbalanced Opposition and Support manage common-pool resources in support of local public goods. The extent to which this line of rea- Orthodox pluralism conceptualized urban policy- soning applies to firms is unknown. Some making as engagement among diverse ethnic, racial, 34 J. C. MARTEL cultural, and social groups. More recent neoplural- significant in selecting a bundle of energy policy ism, as well as neocorporatism, has emphasized tools but many groups were not statistically signifi- cooperation rather than conflict among diverse cant, such as chambers, the general public, environ- groups (Berry, 2010; May & Koski, 2007; Scruggs, mental groups, developers or HOAs. Effects seem to also depend on the type of pol- 2003), as well as less participation of groups in pol- icy, which is the dependent variable in the statistical icymaking than previously considered (Schumaker, models in the reviewed literature. For example, 2013). The idea is that pluralist institutions are open when modeling green construction policies, land- to such a wide diversity of groups, the institution is use decisions, and energy information separately, less likely to be dominated by a single group Deslatte and Swann (2016) found that environmental (Scruggs, 2003). Some policy domains appear to be groups were significant while developers were not. “groupless” (Peterson, 1981, p. 116), meaning that Regarding the strength of influence, May and Koski organized groups are expected to influence policy- (2007) found that homebuilder’s associations had making less than other factors such as economic the strongest opposition to building codes, with conditions or values held by politicians (Schumaker, three times greater influence than advocacy groups 2013, p. 263). Grouplessness may be a misinterpret- including energy code associations and conservation ation of the group consensus-building process that groups (p. 57). Looking across extant research stud- occurs prior to proposing a policy recommendation ies, the significance of various types of interest to elected officials, described as “board room” polit- groups in environmental and sustainability policy ics (Gormley, 1986). This phenomenon has been adoptions has been inconclusive. tested on green building mandates (May & Koski, In a study not in urban policy literature but 2007) and bipartisan agenda-setting for renewable rather in energy policy studies, Jenner et al. (2012) energy policy (Brown & Hess, 2016). These studies examined interest group influence on renewable suggest that what is actually occurring is counterbal- energy policy adoption. The interest groups were ancing, a close relative to grouplessness, that occurs operationalized by years of existence of state chap- when oppositional interest groups reach consensus ters of the International Solar Energy Association or their policy position is otherwise negotiated and (ISEA) and National Nuclear Association (NNA). The shifted towards the middle. For example, Lubell et al. effect sizes for the solar chapters range from 1.33 to (2009) test the theory that “interest groups with pro- 3.77 in relative odds of policy adoption and nuclear environmental attitudes will counterbalance develop- chapters range from 0.24 to 0.67. Overall, the ment interests.” Along this line of reasoning, the effects of interest groups on urban policy adoption counterbalanced hypothesis is proposed: are varied across studies, from having no effect to H3 (Counterbalanced): There is no difference in the having a strong effect. The type of sustainability likelihood to adopt energy efficient building mandates policy and type of interest group seems to matter based on the interaction of traditional and green to the assessment of interest group effects on policy construction interest group members per capita. adoption. Extant research reports mixed findings regarding the effects of interest groups on environmental and Background on Building Energy Codes sustainability policy adoption. Research findings seem to depend on the nature of the interest Building codes are an interactive set of technical groups and the type of policies being studied. In policy statements that govern all aspects of build- some studies, the inclusion of business groups in ings, including structural engineering, fire and life policy deliberations had no statistically significant safety, electrical, mechanical, and fenestration. The effect on sustainability policy adoption but environ- codes include thousands of individual policy state- mental group involvement did have an effect (Berry ments that correspond with or are conditional on & Portney, 2013; Portney & Berry, 2016). Deslatte other statements within the set of codes. Building and Swann (2016) found a different breakdown of energy codes are the policies that govern the interest group effects, discovering that neighbor- energy efficiency component of buildings (e.g., hood associations and corporations were statistically International Code Council, 2012). Building codes JOURNAL OF SUSTAINABLE REAL ESTATE 35 are continually developed by a nonprofit, the adopted only two energy code versions over those International Code Council (ICC) over the course of 30 years (Nelson, 2012, p. 186). More recently, there 3 years, and elected officials at every level of gov- has been a notable increase in governments’ adop- ernment have the option to adopt the revised tion of energy codes. Many governments have building codes in staggered 3 or 6 year cycles. adopted two or three new codes over the last dec- The policies are administered by code officials ade. The American Recovery and Reinvestment Act who are government staff or contractors and imple- of 2009 signed into law by President Obama required mented by construction industry professionals during states to receive stimulus funding to meet or exceed the building design and construction process. Across the 2009 International Energy Conservation Code or the United States, the process of building is regu- its equivalent, ASHRAE Standard 90.1-2007 (U.S. lated at the state and local levels, aside from federal Department of Energy, 2017). Thus, the 2009 energy buildings which are regulated at the federal level. code version is considered the contemporary status Plans for new construction must go through a state quo and previously dated codes are obsolete. Some or local government permit process before building states accepted stimulus funding but refused to begins and this process ensures that builders meet adopt the 2009 energy codes, arguing that the state local codes. Throughout these steps, particularly dur- did not have authority over codes. ing the code development and adoption processes, a Building energy codes are particularly interesting network of construction industry professionals, envir- to study because energy codes represent a clear onmental advocacy groups, code officials, and divergence between the traditional building codes elected officials share information, develop policy that regulate structures, fire and life safety, and the proposals, and compete for policy change (Building expanded scope of codes that also regulate energy Codes Assistance Project, 2017). efficiency, causing a point of contention among The expanded scope of codes to include energy industry professionals who fear that code advance- efficiency was initiated as a result of the 1992 ment will cut into profits and create hardship for Energy Policy and Conservation Act (EPCA) when their companies. A 2016 blog excerpt from the commercial energy code adoption (but not enforce- environmental nonprofit advocacy group, National ment) became mandated for states (Lee & Yik, 2004, Resources Defense Council (NRDC) on the 2018 p. 482; Nelson, 2012, p. 183). However, mainly due code development hearings captures typical contro- to limited federal authority in mandating subna- versies around energy codes: tional codes due to the federalist structure in the Given how critical strong building energy codes are in United States that grants power to the states, 15 the fight against the dangers of climate change, years later only 70% of states had some sort of recent events in the residential energy code energy code—mostly for commercial buildings and development process are very troubling. Code officials, not residential buildings—and the codes have been builders, energy efficiency advocates, and others met poorly enforced (Nelson, 2012, p. 183). State statu- last month in Louisville, KY for Technical Advisory Committee hearings for the development of the 2018 tory structures largely determine code adoption at International Energy Conservation Code. Unfortunately the local level. Some states require the local jurisdic- for those of us who recognize energy efficiency as an tions to meet or exceed the state code (e.g., unequivocal win for both homeowners and the California) while other states require local jurisdic- environment, the advisory committee was beholden to tions to not exceed state law (e.g., Utah). Some the desires of the building industry to stick with the states have a home rule structure where local gov- status quo—or worse. Advisory committee members ernments have the authority to adopt codes inde- not only rejected just about every proposal that would increase the energy efficiency—and therefore, the pendent of the state code (e.g., Colorado, Arizona) important climate benefits—of the energy code, they (International Code Council, 2017). Building energy also took steps to roll back its efficiency. (Natural conservation codes are a key pillar when ranking Resources Defense Council and Lauren Urbanek, 2016) cities and states on energy efficiency and sustain- ability (e.g., ACEEE, 2021). Indeed, adding energy to the model codes has Nelson (2012) built a dataset of state-level code continuously caused backlash from the traditional adoption from 1977 to 2006. On average, states had construction industry, including many builders and 36 J. C. MARTEL code officials alike, who reject that mandatory build- Kansas, Missouri, North Dakota, South Dakota, ing codes should be expanded from their central Wyoming) to understand cities’ actions when focus on structural stability, fire, and life safety to granted autonomy by their state legislatures. The sample size is limited to cities whose energy code also regulate environmental issues (Eisenberg & Yost, adoptions are tracked by national, state, or local 2004). However, energy codes are arguably the most organizations, including data collected from the effective way to reduce energy consumption and International Code Council (ICC) and Building Codes greenhouse gas emissions from the buildings sector Assistance Project (BCAP) as well as information from because this mandatory policy tool applies to all new city ordinances and webpages that is easily access- construction and major renovation of existing build- ible using modern data collection tools, as explained ings, prompting environmental advocates to oppose below. The ICC randomly collects code adoption conservation industry professionals and code officials information by allowing jurisdictions to self-report (Lee & Yik, 2004, p. 479). The 2012 energy code ver- adopted codes on the ICC website and by leveraging sion was determined to achieve 30% more energy- local relationships to stay up-to-date on code efficient than buildings constructed to the 2006 changes (International Code Council, 2017). BCAP, a energy code version (U.S. Department of Energy, program within the Alliance to Save Energy, has a 2014). Given the 50% growth rate in U.S. buildings similar process for code tracking (Building Codes since 1980 and expected exponential growth over Assistance Project, 2018). In an attempt to collect the next few decades (U.S. Energy Information additional data beyond what is available from ICC Administration, 2017), regulating new building con- and BCAP, the Python package, Google was used to struction is imperative to reaching governments’ cli- programmatically return a list of URLs from the mate, energy, and sustainability goals (Nelson, 2012). Google search string, “city of” [state name] adopts international energy conservation code (Vilas, 2018). Data Most web links pointed to a city’s building code or a city’s web page that lists the currently adopted build- Case Selection and Dependent Variable ing codes. Two of the weblinks pointed to databases Historical code adoption data is not readily available of local code adoptions maintained by the States of at the local level. Rather, only current code statuses Colorado and Kansas. Very few local code websites are available for municipalities. The interest of this were found in North Dakota, South Dakota, and study is to examine the contemporary energy code Wyoming. Each landing page was reviewed to add policy arena rather than the historical trends when to the data set of the adopted code version and the codes were updated far less frequently. Thus, the year of the last code update. most recently adopted version of the energy code is The dependent variable contains two ordered used to construct the dependent variable. categories: the base level represents municipalities In-home rule states, energy code adoptions are with outdated energy codes, ranging from no typically tracked at the city levels whereas in non- energy codes to the 2009 International Energy home rule states codes are typically tracked at the Conservation Code (IECC) version. The second cat- state levels due to resource constraints of energy egory represents the most up-to-date energy codes, code advocacy groups and government agencies including cities that have adopted the 2012 or 2015 that perform code tracking. Further, more variation IECC versions. Table 2 shows the fairly balanced dis- of energy code versions exists across cities in home tribution of local policy adoptions in cities within rule states compared to non-home rule states (Cort home rules states. & Butner, 2012), providing optimal case selection. It is unknown the extent to which the results are gen- Focal Independent Variables eralizable to the other 44 states, as the state-level activity may attract different types of policy actors In this study, the interest group variable is con- and interest groups. structed using counts of traditional construction The study involves statistical modeling 221 cities industry association members and green building within seven home rule states (Arizona, Colorado, association members normalized by population, JOURNAL OF SUSTAINABLE REAL ESTATE 37 Table 2. Most recently adopted energy code in cities within the influences of interest groups compared to coun- home rule states. cil-manager governments (Bae & Feiock, 2013; State No Codes 2009 IECC 2012 IECC 2015 IECC Hawkins et al., 2016; Sharp et al., 2011). AZ 2 (4%) 16 (35%) 23 (50%) 5 (11%) Theoretically, the council-manager governments CO 0 21 (39%) 10 (19%) 23 (43%) KS 37 (61%) 8 (13%) 14 (23%) 2 (3%) enable sustainability departments to be somewhat MO 22 (5%) 13 (32%) 9 (24%) 14 (37%) insulated from political pressures and better able to ND 0 2 (29%) 0 5 (71%) SD 5 (71%) 1 (14%) 1 (14%) 0 respond to policy issues with a relatively unbiased WY 1 (13%) 0 2 (25%) 5 (63%) Total 47 (21%) 61 (28%) 59 (27%) 54 (24%) long-term, technical approach that emphasizes operational efficiencies compared to government departments within mayoral forms of government similar to the interest group variable construction in (Bae & Feiock, 2013; Daley et al., 2013; Krause & previous studies (e.g., Baumgartner & Leech, 1998; Gilens & Page, 2014; Jenner et al., 2012; May & Koski, Douglas, 2005). Further, in a low salience, technical 2007). I also create an interaction variable to oper- policy arena such as building energy codes, the ationalize the relational effects between traditional to council-manager institutional structure is expected green interest group members per capita in a city. to be more likely to have government staff engage The dues-paying trade association membership with technical experts to craft a building code pol- represents interest group presence in a city. The icy that has better chances of being adopted than a two most prominent trade associations that partici- code policy that does not include technical input pate in local energy code policy processes across from building professionals prior to the policy hear- U.S. cities are the US Green Building Council ing (Brown & Hess, 2016; Gormley, 1986; May & (USGBC) with more than 12,000 members (U.S. Koski, 2007). The political institutions variable is dichotomously coded as a mayor-council form of Green Building Council, 2017) and the National government (1) or other forms of government (0). Association of Homebuilders (NAHB) with more than 140,000 members, one-third of which are builders Climate Commitment and remodelers (National Association of A measure of city support is whether they have Homebuilders, 2017). Both groups have paid staff made a public commitment to climate protection, and local chapters that lobby locally and mobilize as indicated by mayoral signatories to the Climate their members to support their group’s policy goals. Protection Agreement or if the city is a member of While it is not ideal to use member counts because ICLEI Local Governments for Sustainability. The not all members participate in local policy proc- choice to construct this variable by combining data esses, some degree of member inactivity occurs in on mayoral signatories and ICLEI members is both types of trade associations so the effect of intended to capture preferences and constraints by member inactivity is naturally occurring across the different types of local governments. ICLEI member- two types of groups. The USGBC member list is ship costs money and may be out of reach for available as an Excel download in its entirety, some cities (Yi et al., 2017). Additionally, ICLEI mem- whereas the NAHB member list was created by bership supports a technocratic approach to city examining member address locations from member sustainability where technical resources are utilized directories hosted by local associations. The NAHB by the local governments (Krause et al., 2014,p. data was collected using the Python Beautiful Soup 117). The variable construction is intended to cap- program to programmatically read data from associ- ture the variety of approaches that cities take to ation webpages by accessing text associated with sustainability whether the efforts are led by the HTML tags (Richardson, 2019). mayor or city manager as directed by the city coun- cil. It is dichotomously coded for cities that have Political and Community Characteristics made a climate commitment (1) or not (0). (Control Variables) Political Institutions Government and Industry Capacity The conventional view is that mayor-council forms In most cities, the city planning and building of government are expected to be more open to department relies on general revenue and/or 38 J. C. MARTEL development permit fees to fund government staff and building permits to afford new code adoptions to implement buildings policies. In the absence of a and do not want to deter builders from bringing centralized data source for development permit jobs and capital into the community. Thus, code fees, general revenue is used as a measure of gov- stringency can be seen as a privilege afforded by ernment capacity for adopting new building poli- cities with wealthy, educated residents where sus- cies, as cities with greater financial health are more tainability and advanced buildings policies are more likely to adopt sustainability policies (Krause, 2011; likely to be supported (Hawkins et al., 2016; Lee & Lubell et al., 2009; Sharp et al., 2011). General rev- Koski, 2012; Sharp et al., 2011). May and Koski also enue per capita is used as a measure of government found that states with a larger construction sector and industry capacity. were more likely to adopt green building mandates, Secondly, a measure of government and industry insinuating that energy efficiency is more prevalent capacity for advancing building codes is the number in booming construction markets where wealth is of construction industry professionals in the com- more widespread. The percent of the population munity, as this industry is expected to generate over age 25 that holds a Bachelor’s degree or income for the government in terms of tax revenue higher operationalizes education and median house- and building permit fees and the larger construction hold income for each city operationalizes income. industry is more likely to have the technical expert- The city population is included in the models in the ise to contribute to shaping and implementing new logged form. building code policies. The Chief Building Official with input from staff is typically responsible for pre- Problem Severity senting building code proposals to the legislative Cities may be more likely to adopt new building branch. When building and development in a com- codes when building-related problems in their com- munity are low, then the planning/building depart- munities are heightened. Two measures of building- ment has very limited capacity and is less likely to related issues are urbanization pressures from high propose code advancements because code levels of new construction activity and electricity advancements have transaction costs including costs. Cities vary widely in levels of construction training needed for government staff and industry activity. Some cities are mostly built-out with some members (Nelson, 2012). Governments are less likely infill development but little to no land for new sub- to impose added financial burdens on the construc- divisions. Other cities have plentiful opportunities tion industry when construction activity is low. for new construction, either by demolishing existing Further, some cities have vastly different quantities buildings or using vacant land. Cities with high new of construction activity than other cities, so code construction activity have more opportunities to be advancements could be a lower priority in cities impacted by modern codes than cities with less with little to no new construction. Population and activity. The median housing age in the community the number of construction workers in a city are accounts for this variation. correlated variables, so the only population is When energy is costly, communities are more included in the model. likely to seek opportunities for energy savings, such as through energy codes. Cities with higher local City Size and Socioeconomic Conditions: Population, energy costs have more opportunities to gain costs Income, and Education savings from building operations achieved by mod- Cities with large populations are likely to experience ern energy code advancements (Nelson, 2012). urbanization pressures, such as limited land avail- Where energy is costlier, the payback period on ability and high building density, which in turn puts energy efficiency improvements is lesser compared demands on energy and water resources. These to places where energy is cheaper. It is expected pressures are likely to cause governments to adopt that higher energy costs, measured by average elec- more stringent energy codes to control building tricity costs per county, are associated with a higher growth and resource use (Cidell & Cope, 2014; Daley et al., 2013; Kontokosta, 2011; Saha, 2009). likelihood to adopt more stringent energy codes. However, cities also need income from tax revenue Where county data is not available, the average JOURNAL OF SUSTAINABLE REAL ESTATE 39 Table 3. Variables, descriptions, and data sources for energy codes model. Variable Description Dependent variables Policy adoption or non-adoption Adoption of building energy codes by version (Outdated: No codes to 2009 IECC; Modern: 2012–2015 IECC. Source: Databases publically available from ICC, BCAP, DOE; city, state websites Interest groups (focal predictors) Green interest Number of USBGC members in each city normalized per capita (1000). Source: USGBC member list, 2018 Traditional interest Number of BOMA and NAHB members in each city normalized per capita (1000). Source: BOMA & NAHB member directories, 2018 Interest group interaction Interaction term for green and traditional business interest group members Political and community characteristics (control variables) Political institutions and climate commitment Form of government Dichotomous variable for city that has a mayor-council form of government (1) or other form of government (0). Source: ICMA Survey, 2011 Climate commitment Dichotomous variable for city that is a signatory of Climate Protection Agreement or ICLEI member. Source: U.S. Conf. of Mayors, 2018; ICLEI, 2018 Government and industry capacity General revenue Per capita general revenue for each city ($1000 s). Source: Census of Governments, 2012 City characteristics and socioeconomic conditions Population Logged population of each city. Source: 2016 American Community Survey, 5 Year Estimates Income Median household income ($1000 s). Source: 2016 American Community Survey, 5 Year Estimates Education Percent of population over age 25 with Bachelor’s Degree or higher. Source: 2016 American Community Survey, 5 Year Estimates Problem severity Energy cost Average cost of electricity (kWh) in each county. Where county data is not available, average cost in the state. Source: Energy Information Administration, 2017 Median housing age Median age of housing stock in the city. Source: 2016 American Community Survey, 5 Year Estimates electricity cost for the state is used. Table 3 shows members, so we can expect the climate commit- the descriptions and sources for all variables. ment variable to have a positive effect as well. All Census variables are collected using the General revenue, population, household income, Python program, CenPy, which enables the retrieval and education are all higher in cities with modern of Census data tables into Python for data process- codes. The max median age of housing is lower in ing (e.g., formatting, joining tables) using an API cities with modern codes than outdated codes, sug- integration (Wolf, 2018). The Social Explorer Data gesting that higher levels of new construction activ- Dictionary is used to navigate the American ity relative to the total building stock in these cities Community Survey Tables to identify the unique are happening under outdated codes. This could identifiers for the data tables (Social Explorer, 2019). signify the desire of cities to attract construction The data is stored in an SQLite database that is eas- activity as a way to generate revenue and jobs by ily transportable as a .db file into the R program for keeping old building codes that are more flexible statistical computing (Hipp et al., 2015;R and less costly for construction workers to build. Development Core Team, 2019). Surprisingly, the average and maximum unit costs of energy are lower in cities with modern codes. One could have expected the energy costs to be Methodology higher in these cities, and that they would use Exploratory data analysis lends insights into how energy codes as a way to lower energy costs for the data will perform in the regression model. As homeowners and tenants. expected, far more USGBC members are present in cities with modern codes than in cities with out- Model Selection dated codes, anticipating a positive coefficient on the green interest group variable (Table 4). Further, The regression model includes 221 cities: 76 cities far more cities with modern codes have commit- with outdated energy codes and 145 cities with ments from political leadership as signatories of the modern energy codes. The number of observations Mayor’s Climate Protection Agreement or ICLEI is limited to cities where code adoption information 40 J. C. MARTEL Table 4. Descriptive statistics for energy codes model. Outdated codes Modern codes n¼ 108 n¼ 113 Statistic Mean Min. Max. Mean Min. Max. Green interest group 0.13 0 2 0.31 0 3.54 Traditional interest group 0.87 0 13.4 0.73 0 8.92 Form of city government 0.21 0 1 0.23 0 1 Climate commitment 0.09 0 1 0.31 0 1 General revenue 2.38 0.5 109.91 2.99 0.4 136.66 Population 9.45 6.74 13.06 10.28 5.11 14.26 Income 53.65 19.38 119.52 66.58 27.4 246.53 Education 0.18 0.04 0.43 0.24 0.01 0.61 Energy cost 10.55 1.79 14.46 9.83 6.36 13.13 Housing age 1977 1939 2010 1981 1939 2005 is readily available and control variables matched Table 5. Logistic regression results from modeling energy code adoption. on city name and state. The dependent variable has Dependent variable: two categories of building energy codes represent- Energy code outdated (0) ing an increased level of code stringency, from out- or modern (1) Traditional interest group 0.29 (0.14) dated codes to modern codes. For this study, the Green interest group 0.12 (0.58) outdated codes are grouped as the IECC 2009 and Interest group interaction 0.41 (0.37) Form of city government 0.64 (0.41) any code version published before the IECC 2009, Climate commitment 0.77 (0.46) and modern codes are the 2012 and 2015 IECC. As General revenue 0.03 (0.01) Population 0.50 (0.14) stated in the Background section, the 2009 IECC is Income 0.01 (0.01) considered status quo as it was required as a condi- Education 0.04 (0.03) Energy cost 0.21 (0.09) tion for subnational governments receiving stimulus Housing age 0.01 (0.01) funding under the American Recovery and Observations 221 Log Likelihood 122.75 Reinvestment Act of 2009. Given the nature of the Akaike Inf. Crit. 268.14 R 0.20 (McFadden)/ dependent variable, logistic regression is used to 0.33 (Nagelkerke)/0.25 (CoxSnell) estimate the effects of trade association members Note: Standard errors in parentheses. on code stringency in local jurisdictions while con- p< 0.1; p< 0.05; p< 0.01. trolling for social, economic, and political factors. The regression with logit link function estimates the Table 6. Odds ratios for energy code adoption. log-odds that the event occurs. The model esti- Dependent variable: mates the coefficients corresponding to each focal Energy code outdated (0) or modern (1) predictor and control variables. Due to the lack of Traditional interest group 0.75 (0.14) interpretability of log odds, the logit coefficients are Green interest group 0.89 (0.58) Interest group interaction 1.50 (0.37) converted to odds ratios calculating the odds that Form of city government 1.89 (0.41) the city has adopted modern codes given the vector Climate commitment 2.17 (0.46) General revenue 1.03 (0.01) of X values. The exponent of the coefficient is the Population 1.65 (0.14) odds ratio. Income 1.01 (0.01) Education 1.04 (0.03) Energy cost 0.81 (0.09) Housing age 1.01 (0.01) Results and Discussion Observations 221 Log likelihood 122.75 Traditional industry association groups are hypothe- Akaike Inf. Crit. 268.14 Note: Standard errors in parentheses. sized to be less concerned about negative external- p< 0.1; p< 0.05; p< 0.01. ities associated with the environmental impacts from buildings and more concerned with maximizing prof- its, and therefore less likely to internalize incremental their means, a one standard deviation increase in building costs. This theory is supported as traditional traditional members per 1000 people decreases the industry association groups are associated with lower odds of modern energy code adoption by 16%. levels of modern energy code adoption (Tables 5 Green building interests seek to gain profits and 6). Holding all other independent variables at within the construction industry but may be willing JOURNAL OF SUSTAINABLE REAL ESTATE 41 to internalize some of the incremental costs associ- code policy adoption when this scenario occurs. The ated with building green, which is supported if the interaction variable is not showing statistical signifi- green building interest group is associated with cance; thus the third hypothesis is affirmed. Regarding the control variables, the form of gov- higher levels of energy code adoption. This hypoth- esis is not supported by the model as the green ernment does not seem to matter when it comes to modern energy code adoption. Energy codes have interest group variable is not statistically significant. The effect of green interest groups is generally posi- advanced nearly equally in cities with council-man- tive but the standard errors are too large to get a ager governments and mayor-council governments. This is surprising given the technical nature of reliable estimate of the effects. The lack of signifi- cance of the green interest group is explained by building codes and the tendency for governments the lack of green interest group members in some with city managers to be more likely to collaborate with community stakeholders on policy develop- cities with high probabilities of policy adoption (Figure 1). In addition, green interest group mem- ment, presumably finding technical specifications that work for local building practices. It could be bers are less likely to be concerned with the strin- gency of building energy codes as these industry that the mayor-council governments are able to professionals are building to above-code standards push building codes through the policy adoption process with less engagement from the building given their association with the green building pro- gram, Leadership in Energy and Environmental community. While the codes might get through the Design (LEED). Their building expertise is already at adoption process, engagement with the building community in designing the building codes could an advanced level. The interaction between traditional and green make policy implementation more effective. The industry association members attempts to capture adoption of modern building codes does not neces- the stakeholder engagement process that com- sarily guarantee compliance by the industry, which monly occurs within the energy code policy arena is expected to be improved when stakeholders are where interest groups negotiate a code change engaged in the policy design. A commitment by package that works for both sides described by the local executives to climate protection, indicated by “counterbalanced” hypothesis . Statistically speak- signing the Mayor’s Climate Protection Agreement ing, this is the null hypothesis as neither member- or becoming members of ICLEI, increases the odds ship group is expected to have an effect on energy that a city will adopt higher levels of energy codes Figure 1. Marginal effects of interest groups on predicted policy adoption. 42 J. C. MARTEL Figure 2. Odds Ratios for Energy Code Adoption. Note: Point estimate is the odds ratio. Outer confidence interval is 0.90 and inner confidence interval is 0.80. by an average of 2.18, as cities commonly use build- education variables that come from sustainability lit- ing codes as a strategy to meet their local energy erature might not be entirely applicable to the goals (Figure 2). building code policy domain. Cities with greater financial resources are more Regarding problem severity, the cost of electricity likely to advance codes. Code advancements do is expected to be correlated with energy code have transaction costs, such as training programs adoptions as the payback period for energy effi- and new code books for contractors and building ciency improvements is shorter when energy costs department staff, that are commonly absorbed by are higher, making energy efficiency more attractive the city. While city fiscal conditions are correlated as a solution to high energy costs. Another inter- with modern code adoption, household income is pretation is that energy costs would be lower where not. Building energy code advancements have been communities better handle their energy demand framed as a way to protect lower-income house- with energy efficiency programs. In reality, energy holds from rising energy costs. This could explain politics are far more complex than that. For why modern building codes are advanced in com- example, cities in Wyoming have very inexpensive munities with diverse household incomes. The energy with an average cost of only $0.08 per kWh population is very significant to modern energy compared to Kansas where average energy costs code adoption, while education is not. Urban sus- are $0.12 per kWh. The statistical modeling esti- tainability literature commonly finds that higher mates that a one standard deviation increase in income and education levels are correlated with energy costs is correlated with an 18% decrease in more sustainability policy adoption, but building the likelihood to adopt more stringent energy codes are a foundational policy option sometimes codes. This is counterintuitive and is likely picking grouped with sustainability policies but sometimes up effects of energy conditions and energy mixes not. The sustainability departments may be (i.e., a mix of cheap coal compared to natural gas or engaged in building energy code adoptions as it renewables). Additionally, energy costs as a regres- may be one strategy on their broader agenda, but sor in a statistical model explaining building energy the heavy lifting of building energy code adoption code adoptions may suffer from endogeneity. is typically executed by the building and planning Indeed, the adoption of modern energy codes could departments. Thus, expectations for the income and affect energy prices as buildings using less energy JOURNAL OF SUSTAINABLE REAL ESTATE 43 could reduce peak demand, thereby allowing debates in a formal, well-established policy setting. cheaper energy (Kneifel & O’Rear, 2015). Thus, the A methodological limitation to this study is that coefficient on energy costs could be over or under- state-level fixed effects could not be added to the estimated. Finally, the median year of housing age model due to the low number of observations in was expected to capture information about the lev- some states (North Dakota, South Dakota, els of new construction activity in a community but and Wyoming). was not statistically significant. Given that code, adoption is under the jurisdic- Conclusion and Policy Implications tion of the local governments in home rule states, This research adds depth to the collective under- the sample of data collected for this study suggests standing of the types of groups that are participat- that, when given local autonomy, some local gov- ing in urban sustainability policy processes while ernments adopt modern building standards while others do not. Indeed, some communities have no analyzing organized interest groups in a highly energy codes or building codes at all. One might technical sector of urban sustainability: building assume that building must not be occurring in pla- energy use. To date, sustainability research has ces with no or outdated codes. Yet, the Census esti- examined policy activity in an aggregate fashion, mations for construction industry working in places grouping initiatives from multiple sectors together with outdated codes is similar to cities with modern to better understand why some governments pur- codes, suggesting that construction activity is pre- sue sustainability, and others do not. While this pro- sent in these communities. Given that building vides valuable insight, as the field of inquiry grows, energy codes are a critical policy tool for reaching it is important to more deeply explore specific sec- global climate and energy goals, subsequent work tors to better understand decision-making. The could assess strategies for encouraging these com- actor groups that are responsible for many aspects munities to adopt modern building codes. of the policy processes are overlooked because they A limitation to this study is that there is expected are sector-specific (Koski, 2010). This research adds a to be some contamination of USGBC members who building block to sectoral research intended to be are also NAHB members, but the data collection nested within broader sustainability research. methods cannot detect cross-membership between Building codes and green building programs, in par- the two groups. A second limitation of this study is ticular, hold considerable promise for reducing that it does not include all energy code interest greenhouse gas emissions, and yet, the politics and groups due to resource constraints and lack of feasi- interest group mobilization is understudied. bility in collecting counts on each interest group This study examines the power of interest groups involved in energy code policy advocacy. The in shaping the energy efficiency building require- Building Codes Assistance Project has designed an ments that cities adopt as mechanisms to achieve “energy codes universe” that illustrates the multi- their sustainability goals. It examines the effects of tude of interest groups, nonprofits and government traditional and “green” industry member associa- agencies involved in the energy code policy proc- tions on policy adoption for energy-efficient build- esses involving code development, adoption, imple- ings. Private interest group theory anticipates the mentation, and enforcement (Building Codes opposition of environmental regulation from busi- Assistance Project, 2017). While this study examined ness interest groups in the pursuit of profit maxi- a few of the most widely-known groups, subse- mization while public interest group theory predicts quent research could further examine actors in the that business interest groups will support environ- energy code policy arena. An obvious case selection mental regulation motivated by the protection of to study is the code development hearings where common public goods while being reasonably prof- the various stakeholders join to testify their com- itable. I used counts of members to operationalize pany’s stance on code proposals, government mem- these different homebuilder segments. A subse- bers vote on the proposals, and an elected committee mediates. Subsequent research could quent study could administer surveys to home- review testimony to give insights into the code builder segments to operationalize political ideology 44 J. C. MARTEL Berry, J. M. (2010). Urban interest groups. In Maisel, L. S. & rather than interest group presence, building off of Berry, J. M. (Eds.), The oxford handbook of American polit- the theory presented here. ical parties and interest groups (pp. 502–518). Oxford When granted local autonomy by their state University Press. legislatures under a home rule institutional struc- Berry, J. M., & Portney, K. E. (2013). Sustainability and interest ture, some cities pursue energy code stringency group participation in city politics. Sustainability, 5, while others do not. Modeling 221 cities within 2077–2097. https://doi.org/10.3390/su5052077 Berry, J. M., Portney, K. E., Liss, R., Simoncelli, J., & Berger, L. seven home rule states, the presence of traditional (2006). Power and interest groups in city politics. Rappaport building interest group members affiliated with the Institute of Greater Boston. National Association of Homebuilders decreases the Berry, J. M., & Wilcox, C. (2009). Interest group society (5th odds of a cities’ modern energy code adoption by ed.). Pearson Longman. 16%. The presence of “green” interest group mem- Brown, K. P., & Hess, D. J. (2016). Pathways to policy: Partisanship and bipartisanship in renewable energy legis- bers from the U.S. Green Building Council has a lation. Environmental Politics, 25(6), 971–990. https://doi. positive effect on building energy codes, but the org/10.1080/09644016.2016.1203523 standard errors are too large to generate a reliable Building Codes Assistance Project. (2017). Energy codes uni- parameter estimate. This could be explained by the verse. http://bcapcodes.org/getting-started/energy-codes- association members already building to higher universe/ standards and unconcerned with the advancement Building Codes Assistance Project. (2018). Local adoptions by state. http://bcapcodes.org/code-status/ of building energy codes. Having the most effect on Cidell, J., & Cope, M. A. (2014). Factors explaining the adop- energy code adoption, a city’s commitment to cli- tion and impact of LEED-based green building policies at mate protection more than doubles the likelihood the municipal level. Journal of Environmental Planning and of adoption, indicating the strong relationship Management, 57(12), 1763–1781. https://doi.org/10.1080/ between urban sustainability, climate protection 09640568.2013.835714 and building energy codes. Ciochetti, B., & McGowan, M. (2010). Energy efficiency improvements: Do they pay? Journal of Sustainable Real Estate, 2(1), 305–333. https://doi.org/10.1080/10835547. Note 2010.12091807 Coase, R. H. (1937). The nature of the firm. Economica, 4(16), 1. The member proportion variable is generated from two 386–405. other independent variables. Testing for multicollinearity, Cobb, R., & Elder, C. (1972). American politics: The dynamics of the Variance Inflation Factor on the member proportion agenda-building. Allyn and Bacon. variable is 1.76, indicating a very moderate level of Cort, K. A., & Butner, R. S. (2012). An analysis of statewide multicollinearity. Withholding the member proportion adoption rates of building energy code by local jurisdictions variable from the model does not substantially alter the (No. PNNL-21963). Pacific Northwest National Laboratory. coefficients or significance on any other variables. Daley, D. M., Sharp, E. B., & Bae, J. (2013). Understanding city engagement in community-focused sustainability initia- tives. Cityscape, 15(1), 143–161. Darnall, N., Potoski, M., & Prakash, A. (2009). Sponsorship Disclosure Statement matters: Assessing business participation in government- There are no conflicts of interest associated with this research. and industry-sponsored voluntary environmental pro- grams. Journal of Public Administration Research and Theory, 20(2), 283–307. https://doi.org/10.1093/jopart/ References mup014 ACEEE. (2021). The state energy efficiency scorecard. https:// Deslatte, A., & Swann, W. L. (2016). Is the price right? www.aceee.org/state-policy/scorecard. Gauging the marketplace for local sustainable policy tools. Bae, J., & Feiock, R. (2013). Forms of government and climate Journal of Urban Affairs, 38(4), 581–596. https://doi.org/10. change policies in US cities. Urban Studies, 50(4), 776–788. 1111/juaf.12245 https://doi.org/10.1177/0042098012450481 Devine, A. (2017). Why energy-efficient commercial real estate Bansal, P., & Roth, K. (2000). Why companies go green: A matters. In Coulson, N. E., Wang, Y. & Lipscomb, C. A. model of ecological responsiveness. Academy of (Eds.), Energy efficiency and the future of real estate (pp. Management Journal, 43(4), 717–736. 9–36). Palgrave Macmillan. Baumgartner, F. R., & Leech, B. L. (1998). Basic interests: The Dixon, T., Bright, S., Mallaburn, P., Gabe, J., & Rehm, M. importance of groups in politics and in political science. (2014). Do tenants pay energy efficiency rent premiums? Princeton University Press. Journal of Property Investment & Finance, 32(4), 333–351. JOURNAL OF SUSTAINABLE REAL ESTATE 45 Downs, A. (1972). Up and down with ecology—The issue- Kamieniecki, S. (2006). Corporate America and environmental attention cycle. The Public Interest, 28,38–50. policy: How often does business get its way? Stanford Eisenberg, D., & Yost, P. (2004). Sustainability and building University Press. codes. In Wheeler, S. M. & Beatley, T. (Eds.), The sustainable Kneifel, J., & O’Rear, E. (2015). Benefits and costs of energy standard adoption for new residential buildings: National urban development reader (pp. 193–198). Routledge. summary. National Institute of Standards and Technology. Feiock, R. C., Tavares, A., & Lubell, M. (2008). Policy instru- Kontokosta, C. (2011). Greening the regulatory landscape: ment choices for growth management and land use regu- The spatial and temporal diffusion of green building poli- lation. Policy Studies Journal, 36, 461–480. https://doi.org/ cies in US cities. Journal of Sustainable Real Estate, 3(1), 10.1111/j.1541-0072.2008.00277.x 68–90. https://doi.org/10.1080/10835547.2011.12091821 Garren, S. J., & Brinkmann, R. (2018). Sustainability definitions, Koski, C. (2010). Greening America’s skylines: The diffusion of historical context, and frameworks. In Garren, S. J., & low-salience policies. Policy Studies Journal, 38(1), 93–117. Brinkmann, R. (Eds.), The Palgrave handbook of sustainabil- https://doi.org/10.1111/j.1541-0072.2009.00346.x ity (pp. 1–18). Palgrave Macmillan. Kraft, M. E., & Kamieniecki, S. (2007). Analyzing the role of Gauthrie, J., & Wooldridge, B. (2012). Influences on sustain- business in environmental policy. Business and environ- able innovation: Evidence from leadership in energy and mental policy. Corporate Interests in the American Political environmental design. Business Strategy and the System,3–31. Environment, 21,98–110. Krause, G. A., & Douglas, J. W. (2005). Institutional design ver- https://doi.org/10.1002/bse.716 sus reputational effects on bureaucratic performance: Gilens, M., & Page, B. I. (2014). Testing theories of American Evidence from U.S. government macroeconomic and fiscal politics: Elites, interest groups, and average citizens. projections. Journal of Policy Administration and Research, Perspectives on Politics, 12(3), 564–581. https://doi.org/10. 15, 281–306. 1017/S1537592714001595 Krause, R. M. (2011). Policy innovation, intergovernmental Go, M. H. (2016). Building a safe state: Hybrid diffusion of relations, and the adoption of climate protection initiatives building code adoption in American states. The American by US cities. Journal of Urban Affairs, 33(1), 45–60. https:// Review of Public Administration, 46(6), 713–733. https://doi. doi.org/10.1111/j.1467-9906.2010.00510.x org/10.1177/0275074014563827 Krause, R. M., Feiock, R. C., & Hawkins, C. V. (2014). The Gonzalez-Benito, J., & Gonzalez-Benito, O. (2006). A review of administrative organization of sustainability within local determinant factors of environmental proactivity. Business government. Journal of Public Administration Research and Strategy and the Environment, 15(2), 87–102. Theory, 26(1), 113–127. https://doi.org/10.1093/jopart/ Gormley, W. T. Jr.(1986). Regulatory issue networks in a fed- muu032 eral system. Polity, 18, 595–620. https://doi.org/10.2307/ Krause, R. M., & Martel, J. C. (2018). Greenhouse gas manage- ment: A case study of a typical American city. In Garren, Harrison, D. (2017). The political economy of energy effi- S. J., & Brinkmann, R. (Eds.), The Palgrave handbook of sus- ciency. In Coulson, N. E., Wang, Y., & Lipscomb, C. A. (Eds.), tainability (pp. 119–138). Palgrave Macmillan. Energy efficiency and the future of real estate (pp. 81–98). Lachapelle, E., Borick, C. P., & Rabe, B. (2012). Public attitudes Palgrave Macmillan. toward climate science and climate policy in federal sys- Hawkins, C. V., Krause, R. M., Feiock, R. C., & Curley, C. (2016). tems. Review of Policy Research, 29(3), 334–357. https://doi. Making meaningful commitments: Accounting for vari- org/10.1111/j.1541-1338.2012.00563.x ation in cities’ investments of staff and fiscal resources to Lee, W. L., & Yik, F. W. H. (2004). Regulatory and voluntary sustainability. Urban Studies, 53(9), 1902–1924. https://doi. approaches for enhancing building energy efficiency. org/10.1177/0042098015580898 Progress in Energy and Combustion Science, 30(5), 477–499. Hipp, D. R., Kennedy, D., Mistachkin, J. (2015). SQLite https://doi.org/10.1016/j.pecs.2004.03.002 [Computer software]. SQLite Development Team. Lee, T., & Koski, C. (2015). Multilevel governance and urban International Code Council. (2012). 2012 International energy climate change mitigation. Environment and Planning C: conservation code. https://codes.iccsafe.org/content/ Government and Policy, 33(6), 1501–1517. IECC2012/toc. Leiserowitz, A. (2007). Climate change risk perception and International Code Council. (2017). Code adoption process by policy preferences: The role of affect, imagery, and values. state. https://www.iccsafe.org/gr/Documents/ Climatic Change, 77,45–72. https://doi.org/10.1007/s10584- AdoptionToolkit/HowStatesAdopt_I-Codes.pdf 006-9059-9 Jenner, S., Chan, G., Frankenberger, R., & Gabel, M. (2012). Logan, J. R., & Molotch, H. L. (1988). Urban fortunes: The polit- What drives states to support renewable energy? The ical economy of place. University of California Press. Energy Journal, 33(2), 1–12. https://doi.org/10.5547/ Lowry, W. R., & Joslyn, M. (2014). The determinants of sali- 01956574.33.2.1 ence of energy issues. Review of Policy Research, 31(3), Jones, B. D., & Baumgartner, F. R. (2005). The politics of atten- 153–172. https://doi.org/10.1111/ropr.12069 tion: How government prioritizes problems. University of Lubell, M., Feiock, R. C., La Cruz, D., & Ramirez, E. E. (2009). Chicago Press. Local institutions and the politics of urban growth. 46 J. C. MARTEL American Journal of Political Science, 53(3), 649–665. development sustainable development? Cityscape, 15(1), https://doi.org/10.1111/j.1540-5907.2009.00392.x 45–62. March, J. G. (1962). The business firm as a political coalition. Portney, K. E., & Berry, J. M. (2016). The impact of local envir- The Journal of Politics, 24(4), 662–678. https://doi.org/10. onmental advocacy groups on city sustainability policies and programs. Policy Studies Journal, 44(2), 196–214. 1017/S0022381600016169 https://doi.org/10.1111/psj.12131 May, P. J. (2005). Compliance motivations: Perspectives of farm- R Development Core Team. (2019). R: A language and envir- ers, homebuilders, and marine facilities. Law Policy, 27(2), onment for statistical computing. R Foundation for 317–347. https://doi.org/10.1111/j.1467-9930.2005.00202.x Statistical Computing. May, P. J., & Koski, C. (2007). State environmental policies: Richardson, L. (2019). Beautiful Soup documentation. Crummy. Analyzing green building mandates. Review of Policy https://www.crummy.com/software/BeautifulSoup/bs4/doc/ Research, 24(1), 49–65. https://doi.org/10.1111/j.1541-1338. Saha, D. (2009). Factors influencing local government sustain- 2007.00267.x ability efforts. State and Local Government Review, 41(1), Ball, M. (2003). Markets and the structure of the housebuild- 39–48. https://doi.org/10.1177/0160323X0904100105 ing industry: An international perspective. Urban Studies, Schattschneider, E. E. (1975). The semi-sovereign people: A 40(5–6), 897–916. https://doi.org/10.1080/00420980320000 realist’s view of democracy in America. Harcourt Brace Jovanovich College Publishers. Mohamed, R. (2006). The psychology of residential develop- Scruggs, L. (2003). Sustaining abundance: Environmental perform- ers: Lessons from behavioral economics and additional ance in industrial democracies. Cambridge University Press. explanations for satisficing. Journal of Planning Education Schumaker, P. (2013). Group involvements in city politics and and Research, 26(1), 28–37. https://doi.org/10.1177/ pluralist theory. Urban Affairs Review, 49, 254–281. https:// 0739456X05282352 doi.org/10.1177/1078087412473068 Molotch, H. (1976). The city as a growth machine: Toward a Sharp, E. B., Daley, D. M., & Lynch, M. S. (2011). political economy of place. American Journal of Sociology, Understanding local adoption and implementation of cli- 82, 309–332. https://doi.org/10.1086/226311 mate change mitigation policy. Urban Affairs Review, 47(3), Mulligan, T. D., Mollaoglu-Korkmaz, S., Cotner, R., & 433–457. https://doi.org/10.1177/1078087410392348 Goldsberry, A. D. (2014). Public policy and impacts on Social Explorer. (2019). Data dictionary: American community adoption of sustainable built environments: Learning from survey 2016 (5-year estimates). https://www.socialexplorer. the construction industry playmakers. Journal of Green com/data/ACS2016_5yr/metadata/?ds=ACS16_5yr Building, 9(2), 182–202. https://doi.org/10.3992/1943-4618- Somerville, C. T. (1999). The industrial organization of hous- 9.2.182 ing supply: Market activity, land supply and the size of National Association of Homebuilders. (2017). About NAHB. homebuilder firms. Real Estate Economics, 27(4), 669–694. https://www.nahb.org/en/about-nahb.aspx https://doi.org/10.1111/1540-6229.00788 Natural Resources Defense Council and Lauren Urbanek. Sun, X., Brown, M. A., Cox, M., & Jackson, R. (2016). (2016). Building energy codes: A (slightly wonky) way to con- Mandating better buildings: A global review of building struct a cleaner, safer world. https://www.nrdc.org/experts/ codes and prospects for improvement in the United lauren-urbanek/building-energy-codes-slightly-wonky-way- States. Wires Energy and Environment, 5(2), 188–215. construct-cleaner-safer-world. https://doi.org/10.1002/wene.168 Nelson, H. T. (2012). Lost opportunities: Modeling commercial U.S. Department of Energy. (2014). Saving energy and money building energy code adoption in the United States. with building energy codes in the United States. https:// Energy Policy, 49, 182–191. https://doi.org/10.1016/j.enpol. www.energy.gov/sites/prod/files/2014/05/f15/saving_with_ 2012.05.033 building_energy_codes.pdf Olson, M. (1965). The logic of collective action: Public goods U.S. Department of Energy. (2017). State code adoption track- and the theory of groups. Harvard University Press. ing analysis. https://www.energycodes.gov/adoption/state- Ostrom, E. (1990). Governing the commons: The evolution of code-adoption-tracking-analysis institutions for collective action. Cambridge University Press. U.S. Energy Information Administration. (2017). Frequently Ostrom, E. (1998). A behavioral approach to the rational asked questions: How much energy is consumed in residen- choice theory of collective action: Presidential address, tial and commercial buildings in the United States? https:// American Political Science Association, 1997. American www.eia.gov/tools/faqs/faq.php?id=86&t=1 Political Science Review, 92(1), 1–22. https://doi.org/10. U.S. Environmental Protection Agency. (2017). Inventory of 2307/2585925 U.S. greenhouse gas emissions and sinks: 1990-2015. https:// Peterson, P. (1981). City limits. University of Chicago Press. www.epa.gov/ghgemissions/inventory-us-greenhouse-gas- Portney, K. E. (2009). Sustainability in American cities: A com- emissions-and-sinks-1990-2015 prehensive look at what cities are doing and why. MIT U.S. Green Building Council. (2017). Profile. http://www.usgbc. Press. org/profile Portney, K. E. (2013). Local sustainability policies and pro- Vilas, M. (2018). Project description. Google. https://pypi.org/ grams as economic development: Is the new economic project/google JOURNAL OF SUSTAINABLE REAL ESTATE 47 Wilms, W. W. (1982). Soft policies for hard problems: Wolf, L. J. (2018). CenPy. GitHub. https://github.com/ljwolf/ Implementing energy conserving building regulations in cenpy. California. Public Administration Review, 12(6), 553–561. Yi, H., Krause, R. M., & Feiock, R. C. (2017). Back-pedaling or https://doi.org/10.2307/976125 continuing quietly? Assessing the impact of ICLEI member- Wlezien, C. (2005). On the salience of political issues: The prob- ship termination on cities’ sustainability actions. lem with ‘most important problem’. Electoral Studies, 24(4), Environmental Politics, 26(1), 138–160. https://doi.org/10. 555–579. https://doi.org/10.1016/j.electstud.2005.01.009 1080/09644016.2016.1244968 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Sustainable Real Estate Taylor & Francis

Segmenting the Construction Industry: A Quantitative Study of Business Interest Groups in a Low Salience Policy Setting

Martel, J. C.
Journal of Sustainable Real Estate , Volume 13 (1): 18 – Jan 1, 2021
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JOURNAL OF SUSTAINABLE REAL ESTATE 2021, VOL. 13, NO. 1, 30–47 ARES https://doi.org/10.1080/19498276.2021.2002504 American Real Estate Society Segmenting the Construction Industry: A Quantitative Study of Business Interest Groups in a Low Salience Policy Setting J. C. Martel School of Public Affairs and Administration, University of Kansas, Lawrence, KS, USA KEYWORDS ABSTRACT Building codes; business The intent of this research is to detect if business interest group involvement in urban sus- influence; microeconomics; tainability policymaking increases or decreases the likelihood of policy adoption. Extant sustainability; urban policy research reports both positive and negative effects with varying magnitude. This study seg- ments the construction industry into distinctive categories to explain conditions under which types of business interest groups support or oppose building regulations drawing from competing theoretical angles—private and public interest group theory. It analyzes the effects of two groups—traditional construction and green building association members— on the adoption of building energy codes, a low salience policy issue that attracts technical experts more so than citizen groups. After applying web scraping algorithms, logistic regres- sion explains the probability of code stringency given differences in the presence of trade association members in cities while controlling for demographic, social, and political factors. Findings suggest that this approach to operationalizing interest groups has merit. Despite being from the same industrial category, the segmented business interest groups have divergent effects on the local building policies with traditional construction interest groups having a greater negative effect on the odds of a city’s energy code adoption compared to the green builder interest group. Introduction interest groups but tend to engage a narrowly focused group of technical professionals, such as Commercial and residential buildings are respon- industry associations (Jones & Baumgartner, 2005; sible for approximately 12% of the U.S. greenhouse Koski, 2010, p. 96). An issue often becomes low sali- emissions portfolio (U.S. Environmental Protection Agency, 2017). While the environmental impact of ence when the public does not directly experience buildings is a central concern for urban sustainabil- the issue (Lachapelle et al., 2012; Leiserowitz, 2007; ity (Garren & Brinkmann, 2018; Krause & Martel, Lowry & Joslyn, 2014, p. 156). Patterns of power, 2018), the buildings policy domain is rarely studied influence, and collusion of business interest groups in political science and policy studies as it is often in low salience urban policy settings are distinct considered low salience and researchers tend to from other issue arenas that attract widespread focus on higher salience situations (Go, 2016; Koski, attention appealing to personal beliefs, such as 2010; Lowry & Joslyn, 2014, p. 158). Low salience immigration or gay rights. It is unknown how policy issues are generally characterized by low lev- insights from the body of interest group scholarship, els of political participation, public attention, and focused mostly on national-level high salience meaningful public opinion, empirically observed as issues, translate to low salience policy arenas at the low levels of media attention or low rankings on local level. The extent to which firms assemble into national polls (Cobb & Elder, 1972; Downs, 1972; groups to pursue profit maximization or assemble Gallup, 2021; Koski, 2010; Lowry & Joslyn, 2014; Wlezien, 2005). These issue arenas can attract to promote public interest—an interplay of classical CONTACT J. C. Martel Jmartel701@hotmail.com School of Public Affairs and Administration, University of Kansas, 5737 Longleaf Drive, Lawrence, KS 66049, USA. 2022 The Author(s). Published with license by Taylor & Francis Group, LLC This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. JOURNAL OF SUSTAINABLE REAL ESTATE 31 economic theory and neocorporatism—may depend economic opportunities; ethical concerns; and regu- on issue salience. latory compliance (Bansal & Roth, 2000; Devine, This research explores this interplay by analyzing 2017). These firms often “float” the burden of added the effects of two types of organized interest costs to construct buildings according to stringent groups—traditional construction industry represen- environmental standards, meaning that the green tatives and “green” business professionals—on construction firm absorbs the incremental cost dur- building energy code adoptions at the local level. It ing the construction process and the extent to asks, what are the effects of traditional and “green” which the consumer will absorb the cost is seem- industry member associations on building energy code ingly uncertain (Ciochetti & McGowan, 2010; Dixon policy adoption? It has been acknowledged that et al., 2014). homebuilders are not a homogeneous group (Berry Segmenting actors within an industrial group— & Portney, 2013; Somerville, 1999), yet how we the- such as traditional and “green” construction industry oretically and empirically segment homebuilders actors—is intended to deepen the understanding of into logical categories in order to understand their diverse business interest groups effects on urban differences and effects of those differences on vari- sustainability policy adoption, an endeavor that has ous phenomena is yet to be fully understood. In been requested in past research (e.g., Portney, 2009; this research, a framework for segmentation is pro- Sharp et al., 2011, p. 438). Extant literature has rec- vided, grounded in classical economic theories and ognized that business interest groups are not newer theories of neocorporatism and corporate homogenous, including homebuilders (Somerville, responsibility, as well as a way to empirically test 1999), and diversity of business interest groups has the homebuilder segments. As Harrison (2017) been largely explored through surveys (e.g., Berry & noted, “The notion that political ideology may Portney, 2013), yet business interest group diversity materially influence real estate market outcomes is has not been tested much in a quantitative way. not new” (p. 89). For the purposes of this study, the Many scholars tend to consider business interests traditional developer community is associated with with respect to the environmental policy as always a pro-development ideology justifying urban growth pursuing deregulation (e.g., Kamieniecki, 2006, for personal gain (Logan & Molotch, 1988; p. 53), yet some industry professional groups might Mohamed, 2006; Molotch, 1976), in line with the support regulations that are in the public interest, classical economic viewpoint of the firm as a profit or in favor of their own market differentiation and maximizer (Coase, 1937) and political-economic the- growth. Bringing more clarity and precision to ory of how firms form political coalitions towards understanding this empowered group of stakehold- the goal of resolving political conflicts (March, ers is important, accomplished by bridging micro- 1962). Interest group pluralism and behavioral eco- economic theories of firms, interest groups nomics suggests that firms will compete with similar scholarship, and urban policy research. Analyzing established groups within the same industry, such business groups in a single category, as typically as green construction interest groups, and ultim- done in urban policy research, fails to discern the ately oppose environmental regulation that imposes motivational spectrum that exists within and across cost burdens, diffuse benefits, or economic uncer- interest groups. There is more complexity in interest tainty to the firm (Mohamed, 2006; Scruggs, 2003). group composition than commonly realized, and it Indeed, May and Koski (2007) found that “the stron- is important to understand how these diverse inter- gest opposition to stronger [building energy] codes ests, albeit within the same economic or industrial comes from the state homebuilder organizations” category, operate in an important policy area. (p. 57). Contrastingly, green developers are associ- This study proceeds as follows. The theory section ated with the neocorporatist theory that some firms explores conditions under which business interest act in the public interest on behalf of the govern- groups are expected to support or oppose environ- ment (Kraft & Kamieniecki, 2007; Scruggs, 2003) and mental regulations and review empirical findings from the corporate environmental responsibility theory relevant extant research leading to three testable that firms act in the public interest as a response to hypotheses. Next, background information on build- stakeholder pressures and corporate image benefits; ing energy codes is provided to orient the reader to 32 J. C. MARTEL the case selection. The research design section pro- the viewpoint for support of environmental regula- vides descriptions of the variables and expectations tion in the interest of common welfare. on how the variables relate to policy adoption, mostly drawing from urban sustainability research. It also Private Interest Group Theory notes technology used to carry out the research, With interest groups conceptualized as “any set of including Python packages, CenPy, Google,and individuals with similar beliefs, identifications, or Beautiful Soup for API integration and algorithmic data interests” (Baumgartner & Leech, 1998, p. 29), the collection; SQLite for data storage and querying; and R traditional economic perspective proposes that eco- for statistical computing. Next, results from logistic nomically rational individuals seek to maximize their regression modeling and exponentiation of the coeffi- positions in society (Berry & Wilcox, 2009,p.64). cients into odds ratios are provided for easier inter- Some individuals join interest groups as leverage to pretation of the model. The study concludes with a improve their position. Economically rational and pol- discussion of the modeling results as it relates to itically strategic individuals will work to advance pol- broader explanations of interest group activity and cit- icy alternatives where their benefits are concentrated ies’ actions on policy adoption, ending with the for self-interest and costs are diffused to other mem- article’s contribution to urban sustainability literature. bers of society (Olson, 1965). Along this line of rea- soning, energy-efficient building mandates are Literature Review expected to foster opposition from the construction Multiple theories generate expectations of how industry as the incremental construction costs are business interest groups will act in policy adoption incurred by the construction professional (Deslatte & settings. These theories commonly address the moti- Swann, 2016, p. 584; Wilms, 1982, p. 555). In the vations of business interest groups and predict “split incentive” case when the builder incurs the costs but others receive the benefits, the benefits of divergent outcomes in support or opposition of energy codes are granted to the buildings’ buyers in environmental policy depending on the group’s terms of lower building operating costs, tenants who motivations (Table 1). The classical economic per- enjoy increased building occupant comfort, and soci- spective that businesses are comprised of executives ety at large who benefits from lesser environmental who are rational profit-maximizers underlies the impacts (Sun et al., 2016, p. 3). Construction profes- idea that private firms will oppose environmental sionals are not expected to support such scenarios as regulation because regulation is perceived to limit it would be financially disadvantageous to the profits from industrial development (Ball, 2003; builder. Generally, construction professionals are Kamieniecki, 2006; March, 1962; May, 2005). expected to collude within an interest group towards However, recent discussions have posed that many the common goal of supporting policies that favor private sector actors are irrational in an economic growth and development and minimize financial sense guided by the desire of individuals and losses to the business (Feiock et al., 2008;Gauthrie & groups to act for the common good (e.g., May, Wooldridge, 2012; Logan & Molotch, 1988;March, 2005; Portney, 2013; Portney & Berry, 2016). These 1962; Molotch, 1976, p. 311; Mulligan et al., 2014). divergent perspectives have been broadly labeled In a survey of building professionals, Mulligan as private and public interest group theories (see et al. (2014) found that increased costs were the Jenner et al., 2012). Private interest group theory most important barrier to the firm deciding to build expects that industry-oriented interest groups will green, followed by client resistance. Gauthrie and oppose environmental regulation in the interest of Wooldridge (2012) also found no empirical evidence personal gain while the public perspective offers that green building incentive programs had influ- Table 1. Expected direction of coefficients in the energy code enced firms to voluntarily utilize green building adoption model. practices, supporting the classical economic per- Theory Policy position Direction of coefficient spective that firms avoid economic uncertainty, Private interest Oppositional Negative increased costs, and diffused benefits. Devine (2017) Public interest Supportive Positive Counterbalanced Negotiated No effect/null hypothesis expects that developers will be slow to adopt green JOURNAL OF SUSTAINABLE REAL ESTATE 33 building technologies due to the economics and construction professionals might support new build- financial viability of passing incremental costs to the ing codes to better provision public goods for their consumer. Further, Harrison (2017) found that green clients and society in terms of cleaner air resulting lease rate premiums vary systematically by political from energy use reduction in buildings and selec- ideology in cities, indicating that there may be tion of cleaner fuel sources for buildings, aligned some rationale for uncertainty in a homebuilder’s with environmental sustainability ideals (May & ability to gain a premium for building to environ- Koski, 2007). While their motivations may partially mentally sustainable standards. be self-interested in an attempt to secure business May and Koski (2007) surveyed state homebuilder from clients who demand cleaner buildings, green associations, national building code organizations, building construction professionals and their associ- professional architect organizations, and other ated interest groups are still supporting codes that, groups involved in building energy advocacy about in effect, protect common pool resources. their influence, measured by asking whether they In the area of corporate environmental responsi- supported, opposed, or were not involved in the bility asking why some firms embrace environmen- policy adoption process for energy-efficient man- tal initiatives while others do not in, Bansal and dates (May & Koski, 2007, p. 57). In the study, May Roth (2000) identify regulatory compliance, eco- and Koski (2007) found that interest groups oppos- nomic opportunities, stakeholder pressures, and eth- ing energy-efficient mandates—the homebuilder’s ical concerns as key motivations. Multiple studies associations—had three times stronger influence find that stakeholder pressures are the most import- than the environmental interest groups supporting ant determinant, as clients and investors call for the mandates (p. 59). environmental protection (e.g., Darnall et al., 2009; H1 (Oppositional): Higher numbers of traditional Gonzalez-Benito & Gonzalez-Benito, 2006). Firms can construction industry interest group members per garner a positive reputation through their support capita are likely to limit the probability of the of environmental initiatives, creating a competitive adoption of energy efficient mandates that apply to edge for the company (Bansal & Roth, 2000, p. 724). privately-owned buildings and development projects. Mulligan et al. (2014) also found that company vision/values were the most important motivation Public Interest Group Theory for a firm’s decision to build green (39% of respond- As economic rationality failed to explain cooper- ents), while 0% were motivated by competition with ation among actors in otherwise competitive envi- other developers (p. 193). This line of reasoning sup- ronments, behavioral theories of rational choice ports that green building firms have a distinctive emerged to argue that individuals within groups are value set as a homebuilder segment. Determining less economically rational than Olson (1965) and which motivational factor is most prevalent in the other interest group analysts had assumed (Berry green construction industry is beyond the scope of et al., 2006; Ostrom, 1990, 1998; Schattschneider, this study, but we can assume that an interaction of 1975). Berry et al. (2006) express, the aforementioned motivations, including market … the initial theory, popularized by Mancur Olson, badly differentiation, stakeholder responsiveness, and eth- underestimated the propensity of individuals to be, in ical motivations, inspires construction firms to oper- economists’ jargon, “irrational.” That is, Americans have ate in the green building market. proven that they are all too willing to join organizations that command tangible costs, such as volunteer time or H2 (Supportive): Higher numbers of green construction financial contributions, but offer ideological rather than industry interest group members per capita are likely material rewards … their work tended to be more to increase the probability of the adoption of energy ideological than self-interested (p. 11) efficient mandates that apply to privately-owned buildings and development projects. Along these lines, Ostrom (1990) had found that in some situations, people naturally organize to Counterbalanced Opposition and Support manage common-pool resources in support of local public goods. The extent to which this line of rea- Orthodox pluralism conceptualized urban policy- soning applies to firms is unknown. Some making as engagement among diverse ethnic, racial, 34 J. C. MARTEL cultural, and social groups. More recent neoplural- significant in selecting a bundle of energy policy ism, as well as neocorporatism, has emphasized tools but many groups were not statistically signifi- cooperation rather than conflict among diverse cant, such as chambers, the general public, environ- groups (Berry, 2010; May & Koski, 2007; Scruggs, mental groups, developers or HOAs. Effects seem to also depend on the type of pol- 2003), as well as less participation of groups in pol- icy, which is the dependent variable in the statistical icymaking than previously considered (Schumaker, models in the reviewed literature. For example, 2013). The idea is that pluralist institutions are open when modeling green construction policies, land- to such a wide diversity of groups, the institution is use decisions, and energy information separately, less likely to be dominated by a single group Deslatte and Swann (2016) found that environmental (Scruggs, 2003). Some policy domains appear to be groups were significant while developers were not. “groupless” (Peterson, 1981, p. 116), meaning that Regarding the strength of influence, May and Koski organized groups are expected to influence policy- (2007) found that homebuilder’s associations had making less than other factors such as economic the strongest opposition to building codes, with conditions or values held by politicians (Schumaker, three times greater influence than advocacy groups 2013, p. 263). Grouplessness may be a misinterpret- including energy code associations and conservation ation of the group consensus-building process that groups (p. 57). Looking across extant research stud- occurs prior to proposing a policy recommendation ies, the significance of various types of interest to elected officials, described as “board room” polit- groups in environmental and sustainability policy ics (Gormley, 1986). This phenomenon has been adoptions has been inconclusive. tested on green building mandates (May & Koski, In a study not in urban policy literature but 2007) and bipartisan agenda-setting for renewable rather in energy policy studies, Jenner et al. (2012) energy policy (Brown & Hess, 2016). These studies examined interest group influence on renewable suggest that what is actually occurring is counterbal- energy policy adoption. The interest groups were ancing, a close relative to grouplessness, that occurs operationalized by years of existence of state chap- when oppositional interest groups reach consensus ters of the International Solar Energy Association or their policy position is otherwise negotiated and (ISEA) and National Nuclear Association (NNA). The shifted towards the middle. For example, Lubell et al. effect sizes for the solar chapters range from 1.33 to (2009) test the theory that “interest groups with pro- 3.77 in relative odds of policy adoption and nuclear environmental attitudes will counterbalance develop- chapters range from 0.24 to 0.67. Overall, the ment interests.” Along this line of reasoning, the effects of interest groups on urban policy adoption counterbalanced hypothesis is proposed: are varied across studies, from having no effect to H3 (Counterbalanced): There is no difference in the having a strong effect. The type of sustainability likelihood to adopt energy efficient building mandates policy and type of interest group seems to matter based on the interaction of traditional and green to the assessment of interest group effects on policy construction interest group members per capita. adoption. Extant research reports mixed findings regarding the effects of interest groups on environmental and Background on Building Energy Codes sustainability policy adoption. Research findings seem to depend on the nature of the interest Building codes are an interactive set of technical groups and the type of policies being studied. In policy statements that govern all aspects of build- some studies, the inclusion of business groups in ings, including structural engineering, fire and life policy deliberations had no statistically significant safety, electrical, mechanical, and fenestration. The effect on sustainability policy adoption but environ- codes include thousands of individual policy state- mental group involvement did have an effect (Berry ments that correspond with or are conditional on & Portney, 2013; Portney & Berry, 2016). Deslatte other statements within the set of codes. Building and Swann (2016) found a different breakdown of energy codes are the policies that govern the interest group effects, discovering that neighbor- energy efficiency component of buildings (e.g., hood associations and corporations were statistically International Code Council, 2012). Building codes JOURNAL OF SUSTAINABLE REAL ESTATE 35 are continually developed by a nonprofit, the adopted only two energy code versions over those International Code Council (ICC) over the course of 30 years (Nelson, 2012, p. 186). More recently, there 3 years, and elected officials at every level of gov- has been a notable increase in governments’ adop- ernment have the option to adopt the revised tion of energy codes. Many governments have building codes in staggered 3 or 6 year cycles. adopted two or three new codes over the last dec- The policies are administered by code officials ade. The American Recovery and Reinvestment Act who are government staff or contractors and imple- of 2009 signed into law by President Obama required mented by construction industry professionals during states to receive stimulus funding to meet or exceed the building design and construction process. Across the 2009 International Energy Conservation Code or the United States, the process of building is regu- its equivalent, ASHRAE Standard 90.1-2007 (U.S. lated at the state and local levels, aside from federal Department of Energy, 2017). Thus, the 2009 energy buildings which are regulated at the federal level. code version is considered the contemporary status Plans for new construction must go through a state quo and previously dated codes are obsolete. Some or local government permit process before building states accepted stimulus funding but refused to begins and this process ensures that builders meet adopt the 2009 energy codes, arguing that the state local codes. Throughout these steps, particularly dur- did not have authority over codes. ing the code development and adoption processes, a Building energy codes are particularly interesting network of construction industry professionals, envir- to study because energy codes represent a clear onmental advocacy groups, code officials, and divergence between the traditional building codes elected officials share information, develop policy that regulate structures, fire and life safety, and the proposals, and compete for policy change (Building expanded scope of codes that also regulate energy Codes Assistance Project, 2017). efficiency, causing a point of contention among The expanded scope of codes to include energy industry professionals who fear that code advance- efficiency was initiated as a result of the 1992 ment will cut into profits and create hardship for Energy Policy and Conservation Act (EPCA) when their companies. A 2016 blog excerpt from the commercial energy code adoption (but not enforce- environmental nonprofit advocacy group, National ment) became mandated for states (Lee & Yik, 2004, Resources Defense Council (NRDC) on the 2018 p. 482; Nelson, 2012, p. 183). However, mainly due code development hearings captures typical contro- to limited federal authority in mandating subna- versies around energy codes: tional codes due to the federalist structure in the Given how critical strong building energy codes are in United States that grants power to the states, 15 the fight against the dangers of climate change, years later only 70% of states had some sort of recent events in the residential energy code energy code—mostly for commercial buildings and development process are very troubling. Code officials, not residential buildings—and the codes have been builders, energy efficiency advocates, and others met poorly enforced (Nelson, 2012, p. 183). State statu- last month in Louisville, KY for Technical Advisory Committee hearings for the development of the 2018 tory structures largely determine code adoption at International Energy Conservation Code. Unfortunately the local level. Some states require the local jurisdic- for those of us who recognize energy efficiency as an tions to meet or exceed the state code (e.g., unequivocal win for both homeowners and the California) while other states require local jurisdic- environment, the advisory committee was beholden to tions to not exceed state law (e.g., Utah). Some the desires of the building industry to stick with the states have a home rule structure where local gov- status quo—or worse. Advisory committee members ernments have the authority to adopt codes inde- not only rejected just about every proposal that would increase the energy efficiency—and therefore, the pendent of the state code (e.g., Colorado, Arizona) important climate benefits—of the energy code, they (International Code Council, 2017). Building energy also took steps to roll back its efficiency. (Natural conservation codes are a key pillar when ranking Resources Defense Council and Lauren Urbanek, 2016) cities and states on energy efficiency and sustain- ability (e.g., ACEEE, 2021). Indeed, adding energy to the model codes has Nelson (2012) built a dataset of state-level code continuously caused backlash from the traditional adoption from 1977 to 2006. On average, states had construction industry, including many builders and 36 J. C. MARTEL code officials alike, who reject that mandatory build- Kansas, Missouri, North Dakota, South Dakota, ing codes should be expanded from their central Wyoming) to understand cities’ actions when focus on structural stability, fire, and life safety to granted autonomy by their state legislatures. The sample size is limited to cities whose energy code also regulate environmental issues (Eisenberg & Yost, adoptions are tracked by national, state, or local 2004). However, energy codes are arguably the most organizations, including data collected from the effective way to reduce energy consumption and International Code Council (ICC) and Building Codes greenhouse gas emissions from the buildings sector Assistance Project (BCAP) as well as information from because this mandatory policy tool applies to all new city ordinances and webpages that is easily access- construction and major renovation of existing build- ible using modern data collection tools, as explained ings, prompting environmental advocates to oppose below. The ICC randomly collects code adoption conservation industry professionals and code officials information by allowing jurisdictions to self-report (Lee & Yik, 2004, p. 479). The 2012 energy code ver- adopted codes on the ICC website and by leveraging sion was determined to achieve 30% more energy- local relationships to stay up-to-date on code efficient than buildings constructed to the 2006 changes (International Code Council, 2017). BCAP, a energy code version (U.S. Department of Energy, program within the Alliance to Save Energy, has a 2014). Given the 50% growth rate in U.S. buildings similar process for code tracking (Building Codes since 1980 and expected exponential growth over Assistance Project, 2018). In an attempt to collect the next few decades (U.S. Energy Information additional data beyond what is available from ICC Administration, 2017), regulating new building con- and BCAP, the Python package, Google was used to struction is imperative to reaching governments’ cli- programmatically return a list of URLs from the mate, energy, and sustainability goals (Nelson, 2012). Google search string, “city of” [state name] adopts international energy conservation code (Vilas, 2018). Data Most web links pointed to a city’s building code or a city’s web page that lists the currently adopted build- Case Selection and Dependent Variable ing codes. Two of the weblinks pointed to databases Historical code adoption data is not readily available of local code adoptions maintained by the States of at the local level. Rather, only current code statuses Colorado and Kansas. Very few local code websites are available for municipalities. The interest of this were found in North Dakota, South Dakota, and study is to examine the contemporary energy code Wyoming. Each landing page was reviewed to add policy arena rather than the historical trends when to the data set of the adopted code version and the codes were updated far less frequently. Thus, the year of the last code update. most recently adopted version of the energy code is The dependent variable contains two ordered used to construct the dependent variable. categories: the base level represents municipalities In-home rule states, energy code adoptions are with outdated energy codes, ranging from no typically tracked at the city levels whereas in non- energy codes to the 2009 International Energy home rule states codes are typically tracked at the Conservation Code (IECC) version. The second cat- state levels due to resource constraints of energy egory represents the most up-to-date energy codes, code advocacy groups and government agencies including cities that have adopted the 2012 or 2015 that perform code tracking. Further, more variation IECC versions. Table 2 shows the fairly balanced dis- of energy code versions exists across cities in home tribution of local policy adoptions in cities within rule states compared to non-home rule states (Cort home rules states. & Butner, 2012), providing optimal case selection. It is unknown the extent to which the results are gen- Focal Independent Variables eralizable to the other 44 states, as the state-level activity may attract different types of policy actors In this study, the interest group variable is con- and interest groups. structed using counts of traditional construction The study involves statistical modeling 221 cities industry association members and green building within seven home rule states (Arizona, Colorado, association members normalized by population, JOURNAL OF SUSTAINABLE REAL ESTATE 37 Table 2. Most recently adopted energy code in cities within the influences of interest groups compared to coun- home rule states. cil-manager governments (Bae & Feiock, 2013; State No Codes 2009 IECC 2012 IECC 2015 IECC Hawkins et al., 2016; Sharp et al., 2011). AZ 2 (4%) 16 (35%) 23 (50%) 5 (11%) Theoretically, the council-manager governments CO 0 21 (39%) 10 (19%) 23 (43%) KS 37 (61%) 8 (13%) 14 (23%) 2 (3%) enable sustainability departments to be somewhat MO 22 (5%) 13 (32%) 9 (24%) 14 (37%) insulated from political pressures and better able to ND 0 2 (29%) 0 5 (71%) SD 5 (71%) 1 (14%) 1 (14%) 0 respond to policy issues with a relatively unbiased WY 1 (13%) 0 2 (25%) 5 (63%) Total 47 (21%) 61 (28%) 59 (27%) 54 (24%) long-term, technical approach that emphasizes operational efficiencies compared to government departments within mayoral forms of government similar to the interest group variable construction in (Bae & Feiock, 2013; Daley et al., 2013; Krause & previous studies (e.g., Baumgartner & Leech, 1998; Gilens & Page, 2014; Jenner et al., 2012; May & Koski, Douglas, 2005). Further, in a low salience, technical 2007). I also create an interaction variable to oper- policy arena such as building energy codes, the ationalize the relational effects between traditional to council-manager institutional structure is expected green interest group members per capita in a city. to be more likely to have government staff engage The dues-paying trade association membership with technical experts to craft a building code pol- represents interest group presence in a city. The icy that has better chances of being adopted than a two most prominent trade associations that partici- code policy that does not include technical input pate in local energy code policy processes across from building professionals prior to the policy hear- U.S. cities are the US Green Building Council ing (Brown & Hess, 2016; Gormley, 1986; May & (USGBC) with more than 12,000 members (U.S. Koski, 2007). The political institutions variable is dichotomously coded as a mayor-council form of Green Building Council, 2017) and the National government (1) or other forms of government (0). Association of Homebuilders (NAHB) with more than 140,000 members, one-third of which are builders Climate Commitment and remodelers (National Association of A measure of city support is whether they have Homebuilders, 2017). Both groups have paid staff made a public commitment to climate protection, and local chapters that lobby locally and mobilize as indicated by mayoral signatories to the Climate their members to support their group’s policy goals. Protection Agreement or if the city is a member of While it is not ideal to use member counts because ICLEI Local Governments for Sustainability. The not all members participate in local policy proc- choice to construct this variable by combining data esses, some degree of member inactivity occurs in on mayoral signatories and ICLEI members is both types of trade associations so the effect of intended to capture preferences and constraints by member inactivity is naturally occurring across the different types of local governments. ICLEI member- two types of groups. The USGBC member list is ship costs money and may be out of reach for available as an Excel download in its entirety, some cities (Yi et al., 2017). Additionally, ICLEI mem- whereas the NAHB member list was created by bership supports a technocratic approach to city examining member address locations from member sustainability where technical resources are utilized directories hosted by local associations. The NAHB by the local governments (Krause et al., 2014,p. data was collected using the Python Beautiful Soup 117). The variable construction is intended to cap- program to programmatically read data from associ- ture the variety of approaches that cities take to ation webpages by accessing text associated with sustainability whether the efforts are led by the HTML tags (Richardson, 2019). mayor or city manager as directed by the city coun- cil. It is dichotomously coded for cities that have Political and Community Characteristics made a climate commitment (1) or not (0). (Control Variables) Political Institutions Government and Industry Capacity The conventional view is that mayor-council forms In most cities, the city planning and building of government are expected to be more open to department relies on general revenue and/or 38 J. C. MARTEL development permit fees to fund government staff and building permits to afford new code adoptions to implement buildings policies. In the absence of a and do not want to deter builders from bringing centralized data source for development permit jobs and capital into the community. Thus, code fees, general revenue is used as a measure of gov- stringency can be seen as a privilege afforded by ernment capacity for adopting new building poli- cities with wealthy, educated residents where sus- cies, as cities with greater financial health are more tainability and advanced buildings policies are more likely to adopt sustainability policies (Krause, 2011; likely to be supported (Hawkins et al., 2016; Lee & Lubell et al., 2009; Sharp et al., 2011). General rev- Koski, 2012; Sharp et al., 2011). May and Koski also enue per capita is used as a measure of government found that states with a larger construction sector and industry capacity. were more likely to adopt green building mandates, Secondly, a measure of government and industry insinuating that energy efficiency is more prevalent capacity for advancing building codes is the number in booming construction markets where wealth is of construction industry professionals in the com- more widespread. The percent of the population munity, as this industry is expected to generate over age 25 that holds a Bachelor’s degree or income for the government in terms of tax revenue higher operationalizes education and median house- and building permit fees and the larger construction hold income for each city operationalizes income. industry is more likely to have the technical expert- The city population is included in the models in the ise to contribute to shaping and implementing new logged form. building code policies. The Chief Building Official with input from staff is typically responsible for pre- Problem Severity senting building code proposals to the legislative Cities may be more likely to adopt new building branch. When building and development in a com- codes when building-related problems in their com- munity are low, then the planning/building depart- munities are heightened. Two measures of building- ment has very limited capacity and is less likely to related issues are urbanization pressures from high propose code advancements because code levels of new construction activity and electricity advancements have transaction costs including costs. Cities vary widely in levels of construction training needed for government staff and industry activity. Some cities are mostly built-out with some members (Nelson, 2012). Governments are less likely infill development but little to no land for new sub- to impose added financial burdens on the construc- divisions. Other cities have plentiful opportunities tion industry when construction activity is low. for new construction, either by demolishing existing Further, some cities have vastly different quantities buildings or using vacant land. Cities with high new of construction activity than other cities, so code construction activity have more opportunities to be advancements could be a lower priority in cities impacted by modern codes than cities with less with little to no new construction. Population and activity. The median housing age in the community the number of construction workers in a city are accounts for this variation. correlated variables, so the only population is When energy is costly, communities are more included in the model. likely to seek opportunities for energy savings, such as through energy codes. Cities with higher local City Size and Socioeconomic Conditions: Population, energy costs have more opportunities to gain costs Income, and Education savings from building operations achieved by mod- Cities with large populations are likely to experience ern energy code advancements (Nelson, 2012). urbanization pressures, such as limited land avail- Where energy is costlier, the payback period on ability and high building density, which in turn puts energy efficiency improvements is lesser compared demands on energy and water resources. These to places where energy is cheaper. It is expected pressures are likely to cause governments to adopt that higher energy costs, measured by average elec- more stringent energy codes to control building tricity costs per county, are associated with a higher growth and resource use (Cidell & Cope, 2014; Daley et al., 2013; Kontokosta, 2011; Saha, 2009). likelihood to adopt more stringent energy codes. However, cities also need income from tax revenue Where county data is not available, the average JOURNAL OF SUSTAINABLE REAL ESTATE 39 Table 3. Variables, descriptions, and data sources for energy codes model. Variable Description Dependent variables Policy adoption or non-adoption Adoption of building energy codes by version (Outdated: No codes to 2009 IECC; Modern: 2012–2015 IECC. Source: Databases publically available from ICC, BCAP, DOE; city, state websites Interest groups (focal predictors) Green interest Number of USBGC members in each city normalized per capita (1000). Source: USGBC member list, 2018 Traditional interest Number of BOMA and NAHB members in each city normalized per capita (1000). Source: BOMA & NAHB member directories, 2018 Interest group interaction Interaction term for green and traditional business interest group members Political and community characteristics (control variables) Political institutions and climate commitment Form of government Dichotomous variable for city that has a mayor-council form of government (1) or other form of government (0). Source: ICMA Survey, 2011 Climate commitment Dichotomous variable for city that is a signatory of Climate Protection Agreement or ICLEI member. Source: U.S. Conf. of Mayors, 2018; ICLEI, 2018 Government and industry capacity General revenue Per capita general revenue for each city ($1000 s). Source: Census of Governments, 2012 City characteristics and socioeconomic conditions Population Logged population of each city. Source: 2016 American Community Survey, 5 Year Estimates Income Median household income ($1000 s). Source: 2016 American Community Survey, 5 Year Estimates Education Percent of population over age 25 with Bachelor’s Degree or higher. Source: 2016 American Community Survey, 5 Year Estimates Problem severity Energy cost Average cost of electricity (kWh) in each county. Where county data is not available, average cost in the state. Source: Energy Information Administration, 2017 Median housing age Median age of housing stock in the city. Source: 2016 American Community Survey, 5 Year Estimates electricity cost for the state is used. Table 3 shows members, so we can expect the climate commit- the descriptions and sources for all variables. ment variable to have a positive effect as well. All Census variables are collected using the General revenue, population, household income, Python program, CenPy, which enables the retrieval and education are all higher in cities with modern of Census data tables into Python for data process- codes. The max median age of housing is lower in ing (e.g., formatting, joining tables) using an API cities with modern codes than outdated codes, sug- integration (Wolf, 2018). The Social Explorer Data gesting that higher levels of new construction activ- Dictionary is used to navigate the American ity relative to the total building stock in these cities Community Survey Tables to identify the unique are happening under outdated codes. This could identifiers for the data tables (Social Explorer, 2019). signify the desire of cities to attract construction The data is stored in an SQLite database that is eas- activity as a way to generate revenue and jobs by ily transportable as a .db file into the R program for keeping old building codes that are more flexible statistical computing (Hipp et al., 2015;R and less costly for construction workers to build. Development Core Team, 2019). Surprisingly, the average and maximum unit costs of energy are lower in cities with modern codes. One could have expected the energy costs to be Methodology higher in these cities, and that they would use Exploratory data analysis lends insights into how energy codes as a way to lower energy costs for the data will perform in the regression model. As homeowners and tenants. expected, far more USGBC members are present in cities with modern codes than in cities with out- Model Selection dated codes, anticipating a positive coefficient on the green interest group variable (Table 4). Further, The regression model includes 221 cities: 76 cities far more cities with modern codes have commit- with outdated energy codes and 145 cities with ments from political leadership as signatories of the modern energy codes. The number of observations Mayor’s Climate Protection Agreement or ICLEI is limited to cities where code adoption information 40 J. C. MARTEL Table 4. Descriptive statistics for energy codes model. Outdated codes Modern codes n¼ 108 n¼ 113 Statistic Mean Min. Max. Mean Min. Max. Green interest group 0.13 0 2 0.31 0 3.54 Traditional interest group 0.87 0 13.4 0.73 0 8.92 Form of city government 0.21 0 1 0.23 0 1 Climate commitment 0.09 0 1 0.31 0 1 General revenue 2.38 0.5 109.91 2.99 0.4 136.66 Population 9.45 6.74 13.06 10.28 5.11 14.26 Income 53.65 19.38 119.52 66.58 27.4 246.53 Education 0.18 0.04 0.43 0.24 0.01 0.61 Energy cost 10.55 1.79 14.46 9.83 6.36 13.13 Housing age 1977 1939 2010 1981 1939 2005 is readily available and control variables matched Table 5. Logistic regression results from modeling energy code adoption. on city name and state. The dependent variable has Dependent variable: two categories of building energy codes represent- Energy code outdated (0) ing an increased level of code stringency, from out- or modern (1) Traditional interest group 0.29 (0.14) dated codes to modern codes. For this study, the Green interest group 0.12 (0.58) outdated codes are grouped as the IECC 2009 and Interest group interaction 0.41 (0.37) Form of city government 0.64 (0.41) any code version published before the IECC 2009, Climate commitment 0.77 (0.46) and modern codes are the 2012 and 2015 IECC. As General revenue 0.03 (0.01) Population 0.50 (0.14) stated in the Background section, the 2009 IECC is Income 0.01 (0.01) considered status quo as it was required as a condi- Education 0.04 (0.03) Energy cost 0.21 (0.09) tion for subnational governments receiving stimulus Housing age 0.01 (0.01) funding under the American Recovery and Observations 221 Log Likelihood 122.75 Reinvestment Act of 2009. Given the nature of the Akaike Inf. Crit. 268.14 R 0.20 (McFadden)/ dependent variable, logistic regression is used to 0.33 (Nagelkerke)/0.25 (CoxSnell) estimate the effects of trade association members Note: Standard errors in parentheses. on code stringency in local jurisdictions while con- p< 0.1; p< 0.05; p< 0.01. trolling for social, economic, and political factors. The regression with logit link function estimates the Table 6. Odds ratios for energy code adoption. log-odds that the event occurs. The model esti- Dependent variable: mates the coefficients corresponding to each focal Energy code outdated (0) or modern (1) predictor and control variables. Due to the lack of Traditional interest group 0.75 (0.14) interpretability of log odds, the logit coefficients are Green interest group 0.89 (0.58) Interest group interaction 1.50 (0.37) converted to odds ratios calculating the odds that Form of city government 1.89 (0.41) the city has adopted modern codes given the vector Climate commitment 2.17 (0.46) General revenue 1.03 (0.01) of X values. The exponent of the coefficient is the Population 1.65 (0.14) odds ratio. Income 1.01 (0.01) Education 1.04 (0.03) Energy cost 0.81 (0.09) Housing age 1.01 (0.01) Results and Discussion Observations 221 Log likelihood 122.75 Traditional industry association groups are hypothe- Akaike Inf. Crit. 268.14 Note: Standard errors in parentheses. sized to be less concerned about negative external- p< 0.1; p< 0.05; p< 0.01. ities associated with the environmental impacts from buildings and more concerned with maximizing prof- its, and therefore less likely to internalize incremental their means, a one standard deviation increase in building costs. This theory is supported as traditional traditional members per 1000 people decreases the industry association groups are associated with lower odds of modern energy code adoption by 16%. levels of modern energy code adoption (Tables 5 Green building interests seek to gain profits and 6). Holding all other independent variables at within the construction industry but may be willing JOURNAL OF SUSTAINABLE REAL ESTATE 41 to internalize some of the incremental costs associ- code policy adoption when this scenario occurs. The ated with building green, which is supported if the interaction variable is not showing statistical signifi- green building interest group is associated with cance; thus the third hypothesis is affirmed. Regarding the control variables, the form of gov- higher levels of energy code adoption. This hypoth- esis is not supported by the model as the green ernment does not seem to matter when it comes to modern energy code adoption. Energy codes have interest group variable is not statistically significant. The effect of green interest groups is generally posi- advanced nearly equally in cities with council-man- tive but the standard errors are too large to get a ager governments and mayor-council governments. This is surprising given the technical nature of reliable estimate of the effects. The lack of signifi- cance of the green interest group is explained by building codes and the tendency for governments the lack of green interest group members in some with city managers to be more likely to collaborate with community stakeholders on policy develop- cities with high probabilities of policy adoption (Figure 1). In addition, green interest group mem- ment, presumably finding technical specifications that work for local building practices. It could be bers are less likely to be concerned with the strin- gency of building energy codes as these industry that the mayor-council governments are able to professionals are building to above-code standards push building codes through the policy adoption process with less engagement from the building given their association with the green building pro- gram, Leadership in Energy and Environmental community. While the codes might get through the Design (LEED). Their building expertise is already at adoption process, engagement with the building community in designing the building codes could an advanced level. The interaction between traditional and green make policy implementation more effective. The industry association members attempts to capture adoption of modern building codes does not neces- the stakeholder engagement process that com- sarily guarantee compliance by the industry, which monly occurs within the energy code policy arena is expected to be improved when stakeholders are where interest groups negotiate a code change engaged in the policy design. A commitment by package that works for both sides described by the local executives to climate protection, indicated by “counterbalanced” hypothesis . Statistically speak- signing the Mayor’s Climate Protection Agreement ing, this is the null hypothesis as neither member- or becoming members of ICLEI, increases the odds ship group is expected to have an effect on energy that a city will adopt higher levels of energy codes Figure 1. Marginal effects of interest groups on predicted policy adoption. 42 J. C. MARTEL Figure 2. Odds Ratios for Energy Code Adoption. Note: Point estimate is the odds ratio. Outer confidence interval is 0.90 and inner confidence interval is 0.80. by an average of 2.18, as cities commonly use build- education variables that come from sustainability lit- ing codes as a strategy to meet their local energy erature might not be entirely applicable to the goals (Figure 2). building code policy domain. Cities with greater financial resources are more Regarding problem severity, the cost of electricity likely to advance codes. Code advancements do is expected to be correlated with energy code have transaction costs, such as training programs adoptions as the payback period for energy effi- and new code books for contractors and building ciency improvements is shorter when energy costs department staff, that are commonly absorbed by are higher, making energy efficiency more attractive the city. While city fiscal conditions are correlated as a solution to high energy costs. Another inter- with modern code adoption, household income is pretation is that energy costs would be lower where not. Building energy code advancements have been communities better handle their energy demand framed as a way to protect lower-income house- with energy efficiency programs. In reality, energy holds from rising energy costs. This could explain politics are far more complex than that. For why modern building codes are advanced in com- example, cities in Wyoming have very inexpensive munities with diverse household incomes. The energy with an average cost of only $0.08 per kWh population is very significant to modern energy compared to Kansas where average energy costs code adoption, while education is not. Urban sus- are $0.12 per kWh. The statistical modeling esti- tainability literature commonly finds that higher mates that a one standard deviation increase in income and education levels are correlated with energy costs is correlated with an 18% decrease in more sustainability policy adoption, but building the likelihood to adopt more stringent energy codes are a foundational policy option sometimes codes. This is counterintuitive and is likely picking grouped with sustainability policies but sometimes up effects of energy conditions and energy mixes not. The sustainability departments may be (i.e., a mix of cheap coal compared to natural gas or engaged in building energy code adoptions as it renewables). Additionally, energy costs as a regres- may be one strategy on their broader agenda, but sor in a statistical model explaining building energy the heavy lifting of building energy code adoption code adoptions may suffer from endogeneity. is typically executed by the building and planning Indeed, the adoption of modern energy codes could departments. Thus, expectations for the income and affect energy prices as buildings using less energy JOURNAL OF SUSTAINABLE REAL ESTATE 43 could reduce peak demand, thereby allowing debates in a formal, well-established policy setting. cheaper energy (Kneifel & O’Rear, 2015). Thus, the A methodological limitation to this study is that coefficient on energy costs could be over or under- state-level fixed effects could not be added to the estimated. Finally, the median year of housing age model due to the low number of observations in was expected to capture information about the lev- some states (North Dakota, South Dakota, els of new construction activity in a community but and Wyoming). was not statistically significant. Given that code, adoption is under the jurisdic- Conclusion and Policy Implications tion of the local governments in home rule states, This research adds depth to the collective under- the sample of data collected for this study suggests standing of the types of groups that are participat- that, when given local autonomy, some local gov- ing in urban sustainability policy processes while ernments adopt modern building standards while others do not. Indeed, some communities have no analyzing organized interest groups in a highly energy codes or building codes at all. One might technical sector of urban sustainability: building assume that building must not be occurring in pla- energy use. To date, sustainability research has ces with no or outdated codes. Yet, the Census esti- examined policy activity in an aggregate fashion, mations for construction industry working in places grouping initiatives from multiple sectors together with outdated codes is similar to cities with modern to better understand why some governments pur- codes, suggesting that construction activity is pre- sue sustainability, and others do not. While this pro- sent in these communities. Given that building vides valuable insight, as the field of inquiry grows, energy codes are a critical policy tool for reaching it is important to more deeply explore specific sec- global climate and energy goals, subsequent work tors to better understand decision-making. The could assess strategies for encouraging these com- actor groups that are responsible for many aspects munities to adopt modern building codes. of the policy processes are overlooked because they A limitation to this study is that there is expected are sector-specific (Koski, 2010). This research adds a to be some contamination of USGBC members who building block to sectoral research intended to be are also NAHB members, but the data collection nested within broader sustainability research. methods cannot detect cross-membership between Building codes and green building programs, in par- the two groups. A second limitation of this study is ticular, hold considerable promise for reducing that it does not include all energy code interest greenhouse gas emissions, and yet, the politics and groups due to resource constraints and lack of feasi- interest group mobilization is understudied. bility in collecting counts on each interest group This study examines the power of interest groups involved in energy code policy advocacy. The in shaping the energy efficiency building require- Building Codes Assistance Project has designed an ments that cities adopt as mechanisms to achieve “energy codes universe” that illustrates the multi- their sustainability goals. It examines the effects of tude of interest groups, nonprofits and government traditional and “green” industry member associa- agencies involved in the energy code policy proc- tions on policy adoption for energy-efficient build- esses involving code development, adoption, imple- ings. Private interest group theory anticipates the mentation, and enforcement (Building Codes opposition of environmental regulation from busi- Assistance Project, 2017). While this study examined ness interest groups in the pursuit of profit maxi- a few of the most widely-known groups, subse- mization while public interest group theory predicts quent research could further examine actors in the that business interest groups will support environ- energy code policy arena. An obvious case selection mental regulation motivated by the protection of to study is the code development hearings where common public goods while being reasonably prof- the various stakeholders join to testify their com- itable. I used counts of members to operationalize pany’s stance on code proposals, government mem- these different homebuilder segments. A subse- bers vote on the proposals, and an elected committee mediates. Subsequent research could quent study could administer surveys to home- review testimony to give insights into the code builder segments to operationalize political ideology 44 J. C. MARTEL Berry, J. M. (2010). Urban interest groups. In Maisel, L. S. & rather than interest group presence, building off of Berry, J. M. (Eds.), The oxford handbook of American polit- the theory presented here. ical parties and interest groups (pp. 502–518). Oxford When granted local autonomy by their state University Press. legislatures under a home rule institutional struc- Berry, J. M., & Portney, K. E. (2013). Sustainability and interest ture, some cities pursue energy code stringency group participation in city politics. Sustainability, 5, while others do not. Modeling 221 cities within 2077–2097. https://doi.org/10.3390/su5052077 Berry, J. M., Portney, K. E., Liss, R., Simoncelli, J., & Berger, L. seven home rule states, the presence of traditional (2006). Power and interest groups in city politics. Rappaport building interest group members affiliated with the Institute of Greater Boston. National Association of Homebuilders decreases the Berry, J. M., & Wilcox, C. (2009). Interest group society (5th odds of a cities’ modern energy code adoption by ed.). Pearson Longman. 16%. The presence of “green” interest group mem- Brown, K. P., & Hess, D. J. (2016). Pathways to policy: Partisanship and bipartisanship in renewable energy legis- bers from the U.S. Green Building Council has a lation. Environmental Politics, 25(6), 971–990. https://doi. positive effect on building energy codes, but the org/10.1080/09644016.2016.1203523 standard errors are too large to generate a reliable Building Codes Assistance Project. (2017). Energy codes uni- parameter estimate. This could be explained by the verse. http://bcapcodes.org/getting-started/energy-codes- association members already building to higher universe/ standards and unconcerned with the advancement Building Codes Assistance Project. (2018). Local adoptions by state. http://bcapcodes.org/code-status/ of building energy codes. Having the most effect on Cidell, J., & Cope, M. A. (2014). Factors explaining the adop- energy code adoption, a city’s commitment to cli- tion and impact of LEED-based green building policies at mate protection more than doubles the likelihood the municipal level. Journal of Environmental Planning and of adoption, indicating the strong relationship Management, 57(12), 1763–1781. https://doi.org/10.1080/ between urban sustainability, climate protection 09640568.2013.835714 and building energy codes. Ciochetti, B., & McGowan, M. (2010). Energy efficiency improvements: Do they pay? Journal of Sustainable Real Estate, 2(1), 305–333. https://doi.org/10.1080/10835547. Note 2010.12091807 Coase, R. H. (1937). The nature of the firm. Economica, 4(16), 1. The member proportion variable is generated from two 386–405. other independent variables. Testing for multicollinearity, Cobb, R., & Elder, C. (1972). American politics: The dynamics of the Variance Inflation Factor on the member proportion agenda-building. Allyn and Bacon. variable is 1.76, indicating a very moderate level of Cort, K. A., & Butner, R. S. (2012). An analysis of statewide multicollinearity. Withholding the member proportion adoption rates of building energy code by local jurisdictions variable from the model does not substantially alter the (No. PNNL-21963). Pacific Northwest National Laboratory. coefficients or significance on any other variables. Daley, D. M., Sharp, E. B., & Bae, J. (2013). Understanding city engagement in community-focused sustainability initia- tives. Cityscape, 15(1), 143–161. Darnall, N., Potoski, M., & Prakash, A. (2009). Sponsorship Disclosure Statement matters: Assessing business participation in government- There are no conflicts of interest associated with this research. and industry-sponsored voluntary environmental pro- grams. Journal of Public Administration Research and Theory, 20(2), 283–307. https://doi.org/10.1093/jopart/ References mup014 ACEEE. (2021). The state energy efficiency scorecard. https:// Deslatte, A., & Swann, W. L. (2016). Is the price right? www.aceee.org/state-policy/scorecard. Gauging the marketplace for local sustainable policy tools. Bae, J., & Feiock, R. (2013). Forms of government and climate Journal of Urban Affairs, 38(4), 581–596. https://doi.org/10. change policies in US cities. Urban Studies, 50(4), 776–788. 1111/juaf.12245 https://doi.org/10.1177/0042098012450481 Devine, A. (2017). Why energy-efficient commercial real estate Bansal, P., & Roth, K. (2000). Why companies go green: A matters. In Coulson, N. E., Wang, Y. & Lipscomb, C. A. model of ecological responsiveness. Academy of (Eds.), Energy efficiency and the future of real estate (pp. Management Journal, 43(4), 717–736. 9–36). Palgrave Macmillan. Baumgartner, F. R., & Leech, B. L. (1998). Basic interests: The Dixon, T., Bright, S., Mallaburn, P., Gabe, J., & Rehm, M. importance of groups in politics and in political science. (2014). Do tenants pay energy efficiency rent premiums? Princeton University Press. Journal of Property Investment & Finance, 32(4), 333–351. JOURNAL OF SUSTAINABLE REAL ESTATE 45 Downs, A. (1972). Up and down with ecology—The issue- Kamieniecki, S. (2006). Corporate America and environmental attention cycle. The Public Interest, 28,38–50. policy: How often does business get its way? Stanford Eisenberg, D., & Yost, P. (2004). Sustainability and building University Press. codes. In Wheeler, S. M. & Beatley, T. (Eds.), The sustainable Kneifel, J., & O’Rear, E. (2015). Benefits and costs of energy standard adoption for new residential buildings: National urban development reader (pp. 193–198). Routledge. summary. National Institute of Standards and Technology. Feiock, R. C., Tavares, A., & Lubell, M. (2008). Policy instru- Kontokosta, C. (2011). Greening the regulatory landscape: ment choices for growth management and land use regu- The spatial and temporal diffusion of green building poli- lation. Policy Studies Journal, 36, 461–480. https://doi.org/ cies in US cities. Journal of Sustainable Real Estate, 3(1), 10.1111/j.1541-0072.2008.00277.x 68–90. https://doi.org/10.1080/10835547.2011.12091821 Garren, S. J., & Brinkmann, R. (2018). Sustainability definitions, Koski, C. (2010). Greening America’s skylines: The diffusion of historical context, and frameworks. In Garren, S. J., & low-salience policies. Policy Studies Journal, 38(1), 93–117. Brinkmann, R. (Eds.), The Palgrave handbook of sustainabil- https://doi.org/10.1111/j.1541-0072.2009.00346.x ity (pp. 1–18). Palgrave Macmillan. Kraft, M. E., & Kamieniecki, S. (2007). Analyzing the role of Gauthrie, J., & Wooldridge, B. (2012). Influences on sustain- business in environmental policy. Business and environ- able innovation: Evidence from leadership in energy and mental policy. Corporate Interests in the American Political environmental design. Business Strategy and the System,3–31. Environment, 21,98–110. Krause, G. A., & Douglas, J. W. (2005). Institutional design ver- https://doi.org/10.1002/bse.716 sus reputational effects on bureaucratic performance: Gilens, M., & Page, B. I. (2014). Testing theories of American Evidence from U.S. government macroeconomic and fiscal politics: Elites, interest groups, and average citizens. projections. Journal of Policy Administration and Research, Perspectives on Politics, 12(3), 564–581. https://doi.org/10. 15, 281–306. 1017/S1537592714001595 Krause, R. M. (2011). Policy innovation, intergovernmental Go, M. H. (2016). Building a safe state: Hybrid diffusion of relations, and the adoption of climate protection initiatives building code adoption in American states. The American by US cities. Journal of Urban Affairs, 33(1), 45–60. https:// Review of Public Administration, 46(6), 713–733. https://doi. doi.org/10.1111/j.1467-9906.2010.00510.x org/10.1177/0275074014563827 Krause, R. M., Feiock, R. C., & Hawkins, C. V. (2014). The Gonzalez-Benito, J., & Gonzalez-Benito, O. (2006). A review of administrative organization of sustainability within local determinant factors of environmental proactivity. Business government. Journal of Public Administration Research and Strategy and the Environment, 15(2), 87–102. Theory, 26(1), 113–127. https://doi.org/10.1093/jopart/ Gormley, W. T. Jr.(1986). Regulatory issue networks in a fed- muu032 eral system. Polity, 18, 595–620. https://doi.org/10.2307/ Krause, R. M., & Martel, J. C. (2018). Greenhouse gas manage- ment: A case study of a typical American city. In Garren, Harrison, D. (2017). The political economy of energy effi- S. J., & Brinkmann, R. (Eds.), The Palgrave handbook of sus- ciency. In Coulson, N. E., Wang, Y., & Lipscomb, C. A. (Eds.), tainability (pp. 119–138). Palgrave Macmillan. Energy efficiency and the future of real estate (pp. 81–98). Lachapelle, E., Borick, C. P., & Rabe, B. (2012). Public attitudes Palgrave Macmillan. toward climate science and climate policy in federal sys- Hawkins, C. V., Krause, R. M., Feiock, R. C., & Curley, C. (2016). tems. Review of Policy Research, 29(3), 334–357. https://doi. Making meaningful commitments: Accounting for vari- org/10.1111/j.1541-1338.2012.00563.x ation in cities’ investments of staff and fiscal resources to Lee, W. L., & Yik, F. W. H. (2004). Regulatory and voluntary sustainability. Urban Studies, 53(9), 1902–1924. https://doi. approaches for enhancing building energy efficiency. org/10.1177/0042098015580898 Progress in Energy and Combustion Science, 30(5), 477–499. Hipp, D. R., Kennedy, D., Mistachkin, J. (2015). SQLite https://doi.org/10.1016/j.pecs.2004.03.002 [Computer software]. SQLite Development Team. Lee, T., & Koski, C. (2015). Multilevel governance and urban International Code Council. (2012). 2012 International energy climate change mitigation. Environment and Planning C: conservation code. https://codes.iccsafe.org/content/ Government and Policy, 33(6), 1501–1517. IECC2012/toc. Leiserowitz, A. (2007). Climate change risk perception and International Code Council. (2017). Code adoption process by policy preferences: The role of affect, imagery, and values. state. https://www.iccsafe.org/gr/Documents/ Climatic Change, 77,45–72. https://doi.org/10.1007/s10584- AdoptionToolkit/HowStatesAdopt_I-Codes.pdf 006-9059-9 Jenner, S., Chan, G., Frankenberger, R., & Gabel, M. (2012). Logan, J. R., & Molotch, H. L. (1988). Urban fortunes: The polit- What drives states to support renewable energy? The ical economy of place. University of California Press. Energy Journal, 33(2), 1–12. https://doi.org/10.5547/ Lowry, W. R., & Joslyn, M. (2014). The determinants of sali- 01956574.33.2.1 ence of energy issues. Review of Policy Research, 31(3), Jones, B. D., & Baumgartner, F. R. (2005). The politics of atten- 153–172. https://doi.org/10.1111/ropr.12069 tion: How government prioritizes problems. University of Lubell, M., Feiock, R. C., La Cruz, D., & Ramirez, E. E. (2009). Chicago Press. Local institutions and the politics of urban growth. 46 J. C. MARTEL American Journal of Political Science, 53(3), 649–665. development sustainable development? Cityscape, 15(1), https://doi.org/10.1111/j.1540-5907.2009.00392.x 45–62. March, J. G. (1962). The business firm as a political coalition. Portney, K. E., & Berry, J. M. (2016). The impact of local envir- The Journal of Politics, 24(4), 662–678. https://doi.org/10. onmental advocacy groups on city sustainability policies and programs. Policy Studies Journal, 44(2), 196–214. 1017/S0022381600016169 https://doi.org/10.1111/psj.12131 May, P. J. (2005). Compliance motivations: Perspectives of farm- R Development Core Team. (2019). R: A language and envir- ers, homebuilders, and marine facilities. Law Policy, 27(2), onment for statistical computing. R Foundation for 317–347. https://doi.org/10.1111/j.1467-9930.2005.00202.x Statistical Computing. May, P. J., & Koski, C. (2007). State environmental policies: Richardson, L. (2019). Beautiful Soup documentation. Crummy. Analyzing green building mandates. Review of Policy https://www.crummy.com/software/BeautifulSoup/bs4/doc/ Research, 24(1), 49–65. https://doi.org/10.1111/j.1541-1338. Saha, D. (2009). Factors influencing local government sustain- 2007.00267.x ability efforts. State and Local Government Review, 41(1), Ball, M. (2003). Markets and the structure of the housebuild- 39–48. https://doi.org/10.1177/0160323X0904100105 ing industry: An international perspective. Urban Studies, Schattschneider, E. E. (1975). The semi-sovereign people: A 40(5–6), 897–916. https://doi.org/10.1080/00420980320000 realist’s view of democracy in America. Harcourt Brace Jovanovich College Publishers. Mohamed, R. (2006). The psychology of residential develop- Scruggs, L. (2003). Sustaining abundance: Environmental perform- ers: Lessons from behavioral economics and additional ance in industrial democracies. Cambridge University Press. explanations for satisficing. Journal of Planning Education Schumaker, P. (2013). Group involvements in city politics and and Research, 26(1), 28–37. https://doi.org/10.1177/ pluralist theory. Urban Affairs Review, 49, 254–281. https:// 0739456X05282352 doi.org/10.1177/1078087412473068 Molotch, H. (1976). The city as a growth machine: Toward a Sharp, E. B., Daley, D. M., & Lynch, M. S. (2011). political economy of place. American Journal of Sociology, Understanding local adoption and implementation of cli- 82, 309–332. https://doi.org/10.1086/226311 mate change mitigation policy. Urban Affairs Review, 47(3), Mulligan, T. D., Mollaoglu-Korkmaz, S., Cotner, R., & 433–457. https://doi.org/10.1177/1078087410392348 Goldsberry, A. D. (2014). Public policy and impacts on Social Explorer. (2019). Data dictionary: American community adoption of sustainable built environments: Learning from survey 2016 (5-year estimates). https://www.socialexplorer. the construction industry playmakers. Journal of Green com/data/ACS2016_5yr/metadata/?ds=ACS16_5yr Building, 9(2), 182–202. https://doi.org/10.3992/1943-4618- Somerville, C. T. (1999). The industrial organization of hous- 9.2.182 ing supply: Market activity, land supply and the size of National Association of Homebuilders. (2017). About NAHB. homebuilder firms. Real Estate Economics, 27(4), 669–694. https://www.nahb.org/en/about-nahb.aspx https://doi.org/10.1111/1540-6229.00788 Natural Resources Defense Council and Lauren Urbanek. Sun, X., Brown, M. A., Cox, M., & Jackson, R. (2016). (2016). Building energy codes: A (slightly wonky) way to con- Mandating better buildings: A global review of building struct a cleaner, safer world. https://www.nrdc.org/experts/ codes and prospects for improvement in the United lauren-urbanek/building-energy-codes-slightly-wonky-way- States. Wires Energy and Environment, 5(2), 188–215. construct-cleaner-safer-world. https://doi.org/10.1002/wene.168 Nelson, H. T. (2012). Lost opportunities: Modeling commercial U.S. Department of Energy. (2014). Saving energy and money building energy code adoption in the United States. with building energy codes in the United States. https:// Energy Policy, 49, 182–191. https://doi.org/10.1016/j.enpol. www.energy.gov/sites/prod/files/2014/05/f15/saving_with_ 2012.05.033 building_energy_codes.pdf Olson, M. (1965). The logic of collective action: Public goods U.S. Department of Energy. (2017). State code adoption track- and the theory of groups. Harvard University Press. ing analysis. https://www.energycodes.gov/adoption/state- Ostrom, E. (1990). Governing the commons: The evolution of code-adoption-tracking-analysis institutions for collective action. Cambridge University Press. U.S. Energy Information Administration. (2017). Frequently Ostrom, E. (1998). A behavioral approach to the rational asked questions: How much energy is consumed in residen- choice theory of collective action: Presidential address, tial and commercial buildings in the United States? https:// American Political Science Association, 1997. American www.eia.gov/tools/faqs/faq.php?id=86&t=1 Political Science Review, 92(1), 1–22. https://doi.org/10. U.S. Environmental Protection Agency. (2017). Inventory of 2307/2585925 U.S. greenhouse gas emissions and sinks: 1990-2015. https:// Peterson, P. (1981). City limits. University of Chicago Press. www.epa.gov/ghgemissions/inventory-us-greenhouse-gas- Portney, K. E. (2009). Sustainability in American cities: A com- emissions-and-sinks-1990-2015 prehensive look at what cities are doing and why. MIT U.S. Green Building Council. (2017). Profile. http://www.usgbc. Press. org/profile Portney, K. E. (2013). Local sustainability policies and pro- Vilas, M. (2018). Project description. Google. https://pypi.org/ grams as economic development: Is the new economic project/google JOURNAL OF SUSTAINABLE REAL ESTATE 47 Wilms, W. W. (1982). Soft policies for hard problems: Wolf, L. J. (2018). CenPy. GitHub. https://github.com/ljwolf/ Implementing energy conserving building regulations in cenpy. California. Public Administration Review, 12(6), 553–561. Yi, H., Krause, R. M., & Feiock, R. C. (2017). Back-pedaling or https://doi.org/10.2307/976125 continuing quietly? Assessing the impact of ICLEI member- Wlezien, C. (2005). On the salience of political issues: The prob- ship termination on cities’ sustainability actions. lem with ‘most important problem’. Electoral Studies, 24(4), Environmental Politics, 26(1), 138–160. https://doi.org/10. 555–579. https://doi.org/10.1016/j.electstud.2005.01.009 1080/09644016.2016.1244968

Journal

Journal of Sustainable Real Estate – Taylor & Francis

Published: Jan 1, 2021

Keywords: Building codes; business influence; microeconomics; sustainability; urban policy

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