STATE AGENCY DISCRETION AND IN REGULATED MARKETS: AN ANALYSIS OF A U.S. RENEWABLE ENERGY SECTOR

ABSTRACT

Barriers to entry in regulated markets are frequently conceptualized as static features that must be removed or overcome if new entrants are to successfully enter a market. However, institutions regulating markets often consist of multiple levels existing in tension with one another. We suggest that this tension may render regulatory barriers to entry more malleable, even in the absence of policy changes. To test this proposition, we bring the administrative state center stage and examine how regulatory discretion—the flexibility that officers have to interpret and implement public policies created by elected officials—can influence market entry of new ventures, using data on regulatory approval of hydroelectric facilities in the United States from 1978 to 2014. We find that increased state agency discretion improves outcomes for new entrants by reducing the effectiveness of incumbent firms’ political influence and creating opportunities for entrepreneurs to leverage regulators’ institutional logics. This study has implications for the design of public policies that address growing energy demands while balancing environmental goals and the need to reduce carbon dioxide emissions.

Keywords: institutional theory, entrepreneurship, nonmarket strategy, regulated markets, regulatory discretion, institutional logics

1 INTRODUCTION

The institutional environment can cause entrepreneurial firms to either flourish or fail, by conditioning access to resources (Battilana, Leca, and Boxenbaum, 2009; Tracey, Phillips, and

Jarvis, 2011; Battilana and Lee, 2014), facilitating legitimacy and the support of important stakeholders (King and Soule, 2007; Hiatt, Sine, and Tolbert, 2009), and shaping the nature of competitive interactions (Dobbin and Dowd, 1997; Dowell and David, 2011). The impact of government institutions on de novo entrants is particularly high in regulated markets, such as pharmaceuticals, biotechnology, telecommunications, energy, and finance, where regulatory policies can raise costs and influence entry through product standards and approval, pricing guidelines, and licensing rules (García-Canal and Guillén, 2008; Dowell and Killaly, 2009; Hiatt and Park, 2013). Incumbent firms often create additional challenges for new firms by using their political influence to erect regulatory barriers to entry (Dean, Brown, and Stango, 2000).

Scholarship has generally treated regulatory barriers as relatively static features of the institutional environment that must be removed or overcome if new firms, because of their lack of resources and political connections, are to successfully enter regulated markets (Sine,

Haveman, and Tolbert, 2005). Nevertheless, evidence exists that new entrants enter these markets with significant variation (Sine and Lee, 2009; Gurses and Ozcan, 2015). Little research thus far, however, has theoretically and empirically examined the institutional structures that may allow new entrants to overcome barriers to entry in regulated markets.

This inadequacy may be due in part to the common assumption in the organization theory and strategy literatures that government institutions are monolithic with regard to policy change: elected officials enact or repeal policies that fundamentally shape market features and alter firm behavior (Dobbin and Dowd, 2000). Thus, a large body of literature has explored how firms

2 target elected officials through corporate political activities such as and financial contributions to shape regulatory policies in their favor (Mizruchi, 1989; Walker and Rea, 2014;

McDonnell and Werner, 2016). However, this assumption neglects the role of the state in implementing policy (Baron, Dobbin, and Jennings, 1986; Kalev, Shenhav, and De Vries, 2008).

Government institutions regulating markets often have multiple levels, including elected bodies that create policies and the state agencies that interpret and implement them (Edelman and

Suchman, 1997; Seo and Creed, 2002). Although state agencies are assumed to be constrained by the legislative bodies who monitor them, they can exercise a fair amount of latitude in interpreting and implementing policies (Evans, Rueschemeyer, and Skocpol, 1985; Evans, 1995;

Guillén and Capron, 2016). Consequently, state regulatory agencies may implement policies in ways that differ from the original intent of the elected officials who crafted them. Not only can this foster variation in the regulatory environment, even in the absence of policy changes, but it may also affect the barriers to entry for new firms. We suggest that prior work’s conceptualization of government institutions—as a monolithic entity that enacts or repeals regulatory policy—obscures important political institutional factors that could affect market entry and thereby requires a closer theoretical examination.

We seek to address this limitation by taking a pluralistic view of government institutions and explore how variation in policy implementation by state agencies affects organizations. Our central argument is that regulatory discretion—that is, the formally granted flexibility that regulatory agency officers have to interpret and implement public policies created by elected officials—can foster new entry in regulated markets by reducing the political influence of incumbent firms and providing opportunities for entrepreneurs to use regulators’ institutional logics to their advantage (Almandoz 2012, 2014; Thornton, Ocasio, and Lounsbury, 2012; Cobb,

3 Wry, and Zhao, 2016; Zhao and Wry, 2016). Drawing upon the public administration literature, we propose that regulatory agencies’ decision making is guided by two competing logics that are enacted depending on the degree of discretion regulators have in implementing policy. When state agency officials have greater discretion to implement policy, we suggest, their decisions are guided more by an institutional logic of public service that emphasizes societal welfare, and less by a legalistic logic that emphasizes adherence to policymakers’ intentions. The logic that guides regulator decision making significantly affects regulatory approval of new ventures. By placing the regulatory agency center stage, we show that regulatory-imposed barriers to entry are not always fixed but may vary depending on how firm and institutional factors interact with regulators’ latitude to implement and interpret the law.

Empirically, we examine regulatory approval of new facilities in the U.S. hydroelectric power sector from 1978 to 2014 and consider the impact of institutionalized discretion on state regulatory agency outcomes. This market provides a useful setting to explore the impact of regulatory discretion on new entrants because although the Federal Energy Regulatory

Commission (FERC) ultimately grants all licenses to operate, individual state agencies have the authority to place restrictions on federal regulatory approval, resulting in significant variation across states in how regulatory policy is implemented for new facility licensing.

This paper offers two primary theoretical contributions. First, it contributes to the institutions and entrepreneurship literature (Hiatt, Sine and Tolbert, 2009; Navis and Glynn,

2010) by examining how state agency decision making can substantively shape the barriers to entry for new ventures and incumbent firms. The predominant view in management literature is that incumbent firms use their political influence to erect regulatory barriers that prevent entry.

We seek to uncover the structural aspects of political institutions that can level the playing field

4 for new ventures relative to incumbents in regulated markets even if formal remain static.

Second, the paper contributes to the nonmarket strategy literature (McDonnell and King,

2013; Dorobantu, Kaul, and Zelner, 2017; Dorobantu, Henisz and Nartey, 2017) by exploring how firms affect and are affected by the implementation of public policy by regulatory agencies.

This is an important area of investigation because regulators are often the primary and most frequent point of contact for (Carpenter, 2002), and, unlike elected officials, regulators are less likely to be influenced by the traditional tools of political influence: they are generally not elected, cannot legally receive financial contributions, and often have job protections associated with civil service policies (Skocpol and Finegold, 1982). Yet, research has only begun to explore the possible mechanisms by which firms influence and are influenced by state agencies through policy implementation. The findings of this study enhance our understanding of these mechanisms by illustrating how variation in policy implementation differentially affects new and established firms.

The following section summarizes the literature on entry barriers in regulated markets.

We then place the regulatory agency center stage and describe the origins of regulatory discretion, offer a theoretical framework for how discretion can affect incumbent firms and new entrants, and explore moderating factors of the mechanism. We next describe the empirical context—regulatory approval in the U.S. hydroelectric sector—and use quantitative analysis to test our arguments. Finally, we discuss our results and make suggestions for future research.

5 THEORY AND HYPOTHESES

Regulated Markets and Barriers to Entry

Regulated markets can create substantial obstacles for participating organizations. Compliance with regulations, such as pollution abatement in the chemicals sector (Hoffman, 1999), zoning laws in the urban development market (Pang and Rath, 2007), credit-risks tests in the banking sector (Marquis and Lounsbury, 2007), and consumer health and safety requirements in the pharmaceuticals industry (Maguire and Hardy, 2009), imposes significant financial and organizational costs on regulated firms. Similarly, government may impose costs directly via entry and exit rules, such as those associated with antitrust and permitting or licensing requirements (Dobbin and Dowd, 2000).

However, these costs often disproportionately burden new firms relative to incumbents.

Regulations can increase the required to enter and the complexity of operations, resulting in a significant learning-curve effect (Dean and Brown, 1995). In a longitudinal study of pollution-intensive manufacturing firms, Dean and colleagues (2000) found that environmental regulations deterred entry because of the economies of scale in purchasing pollution-abatement equipment and the administrative costs of understanding complex regulations. Regulations can also disproportionately burden new firms through the permitting process (Biber and Ruhl, 2014). Permits, as pre-conditions for undertaking business activity, are often costlier to new entrants, as incumbent firms are ‘grandfathered in’ to less stringent permitting requirements. Even if permits are equally stringent for entrants and incumbents, permits often involve substantial fixed costs, which are much easier for established firms to bear.

For instance, New York State’s enactment of more stringent environmental permitting regulations resulted in fewer foundings of new manufacturing firms (List, 2003).

6 In contrast to new firms, incumbent firms often have the resources to use the regulatory environment to their benefit, thereby putting potential entrants at a greater disadvantage.

Scholarship suggests that incumbent firms in regulated markets attempt to manage these obstacles by maximizing both their relative and their absolute influence over the institutions that govern them through corporate political activities that include informational, financial, and constituency-building tactics (Mizruchi, 1992; McDonnell, 2016; McDonnell and Werner, 2016).

Given the challenges that new firms face in entering regulated markets, most studies that examine entry into regulated markets tend to focus on policy change. For instance, scholars have showed that policy changes influence how and where firms compete, prompting incumbent firms to adjust their product and market scopes as new firms enter the market (Delmas and Tokat,

2005). , for instance, has been found to affect both the amount of entry and its specific character, such as technological and product differentiation among firms (Russo, 2001;

Delmas, Russo, and Montes-Sancho, 2007).

One reason for the emphasis on policy change is the common assumption in the management literature that government institutions act as a single uniform entity. Once regulatory policies are enacted or repealed by elected officials, the effects are predictable and uniform (Dobbin and Dowd, 1997). However, government institutions consist not only of elected bodies who create policies but also of state agencies that interpret and implement them (Kalev,

Shenhav and De Vries, 2008). In a regulatory context, this suggests that it is possible for policy to be implemented in ways that differ from the original intent of the policymakers. Yet, research to date has not explored the tension that can exist between policymakers and policy implementers and whether this tension can affect barriers to entry into regulated markets. We seek to address this limitation by taking a pluralistic view of regulatory institutions and

7 highlighting the role of state agencies (see Figure A1). Specifically, we explore how regulators’ discretion in interpreting and implementing policies can alter barriers to new venture entry.

Regulatory Discretion and Market Entry of New Ventures

According to the political science literature, the rationale for giving regulatory agencies discretion has several sources. First, elected officials who craft public policy often have less information about the subject matter of their policies than the regulatory agencies charged with implementing them (Huber and Shipan, 2002). Agencies are generally staffed with technical experts possessing more complete information about firms being regulated; therefore, elected officials are more likely to grant greater discretion to more knowledgeable regulators (Skocpol and Finegold, 1982, Skocpol, 1985). Second, because writing detailed public policy takes time and effort, policymakers tend to write policies with vague goals and broad mandates, leaving decisions about implementation to the discretion of regulatory agencies. The degree of discretion granted to agencies varies across states and is conditioned by factors such as historical norms, the professionalism of legislatures, and various state characteristics (Pires, 2011).

Key to understanding how discretion can affect regulatory decision making is the recognition that policymakers and regulators have different incentives. Elected officials are fundamentally motivated by their desire for re-election. As mentioned previously, incumbent firms can leverage elected officials’ incentives for re-election by using corporate political activities—such as financial and informational lobbying—to persuade them to craft policies in their favor. Regulatory agency officials, in contrast, are not elected and often have job protections associated with civil service policies. As such, they are much less likely to be influenced by corporate political activities.

8 Furthermore, according to the public administration literature, regulatory agencies’ decision making is influenced by two competing logics: the public service logic and the legalistic logic. The public service logic emphasizes “the interests of the community” and service to the common good and public interest (Perry and Hondeghem, 2008: 213). Research on epistemic communities—groups of individuals with policy-relevant knowledge, who are guided by common values and beliefs—echoes this perspective and suggests that bureaucratic agencies are chiefly motivated to implement policies in ways that enhance societal welfare (Adler, 1992;

Haas, 2015). Central to this logic is a desire to “balance the scales of justice” in a way that tends to favor the “underdog” (Kay and Jost, 2003; Vandello, Goldschmied, and Michniewicz, 2016).

Research in public administration suggests that this logic often leads regulatory agency officials

“to pursue more equitable outcomes, and to allocate resources where they are most needed”

(Keiser and Soss, 1998: 1134), to distribute benefits to more disadvantaged clients (Keiser,

1999), and to develop relationships with clients that are “personal and emotional, rarely cold and rational” (Maynard-Moody and Musheno, 2000: 334). For example, research conducted at

California’s public school districts showed that when regulatory agency officials had more discretion, their own individual views on fair distribution and social justice had a significant effect on the final implementation of public policy (Kelly, 1994). The management literature also finds that regulatory agency logics support fairness and equitable distribution and that agency officials see themselves as stewards of public funds who are responsible for allocating resources in ways that enhance societal welfare. For instance, Pahnke and colleagues (2015) found that regulatory agency officials distributed funding for new ventures in the surgical device industry across geographically diverse ventures to help ensure that the entire country was represented.

They also showed that officials sought to emphasize egalitarian access to resources. Inasmuch as

9 the public service logic favors clients who are perceived as underdogs, firms from disadvantaged groups such as new ventures may be viewed sympathetically by regulators and receive preferential treatment.

The legalistic logic, on the other hand, emphasizes centralized and united policy implementation with strict accountability to elected officials (Meyer et al., 2014). As a result, policies implemented under this logic are likely to be in harmony with policymakers’ intentions.

To the extent that incumbents successfully influence elected officials’ policy making through corporate political activities, regulatory decisions under a legalistic logic might favor incumbent firms.

Research suggests that when organizations embody multiple logics, sometimes a single logic dominates and overpowers the others, and sometimes different logics simultaneously compete and influence different structures and practices (Thornton Ocasio and Lounsbury, 2012;

Besharov and Smith, 2014; Lee and Lounsbury, 2015; Tracey, 2016; Wry and York, 2017). The dominance of a particular logic is heavily influenced by individual and organizational dependency on key resource providers and therefore may vary over time and across contexts

(Battilana and Dorado, 2010; Jones et al., 2012; Smith and Tracey, 2016). In the context of regulatory agencies, we propose that the dominance of either the public service or legalistic logic in agency decision making depends on the relationship between elected officials and regulatory agencies.

When regulators have little discretion, elected officials can better monitor regulatory decision making and enforce alignment with formal policies, such as by further limiting their autonomy or restricting agency budgets (McCubbins, Noll, and Weingast, 1987). As such, elected officials become very salient resource providers to regulatory agencies. This

10 organizational dependence on elected officials can cause regulatory agencies’ public service logic to become subordinated to a legalistic logic and lead to policy implementation that is consistent with the demands of elected officials and formal policies (Meyer et al., 2014).

Dominance of the legalistic logic in contexts of low discretion may also favor incumbent firms, which can use their corporate political influence at the policymaking level to steer the rules of the game in their favor.

Conversely, when regulators have greater discretion, regulators will be less likely to lose resources if agency decisions are not aligned with lawmakers’ expectations. According to the public administration literature, agency employees—whether due to self-selection or to the work environment—are generally predisposed to be guided by the public service logic (Crewson,

1997). When given discretion, regulators are thus more likely to act in accordance with the public service logic and to implement policies in ways that may differ from the policy objectives of elected officials. At a minimum, discretion can level the playing field for new entrants relative to incumbent firms by reducing the advantages that incumbent firms enjoy. At the extreme, the enactment of the public service logic may favor entrants over incumbents in agency decision making by considering criteria beyond the policy objectives outlined by elected officials when making regulatory decisions (Lipsky, 1980). For instance, relative to other firms seeking regulatory approval, new entrants generally have fewer financial resources and political connections. Therefore, regulators may see them as a disadvantaged group meriting favorable treatment. Furthermore, given that creating equitable outcomes is important to the public service logic, regulators may be more eager to grant regulatory approval to entrepreneurial firms that have not yet established themselves in the market over incumbents who already have significant market share. In sum, we argue that greater discretion will allow enactment of the public service

11 logic in regulatory decision making, thereby reducing the advantages that incumbents might accrue through political activities and increasing new ventures’ favorable outcomes.

Hypothesis 1: The positive effect of corporate political activities on regulatory approval of incumbent firms will decrease as regulatory discretion increases.

Hypothesis 2: Greater regulatory discretion will increase the likelihood of new venture approval.

Moderators of Regulatory Discretion on New Venture Approval

Up to this point, we have argued that greater agency discretion may benefit new venture entry in regulated markets by allowing state agency decision making to be guided more by a public service logic and less by a legalistic logic. To further home in on this mechanism, we consider how two factors related to the political environment—political competitiveness of state legislative elections and alignment of political party control—may interact with discretion to affect the dominance of the competing logics that influence regulatory decision making.

Political competitiveness. One factor that may moderate the effect of discretion on the dominance of the competing logics involved in the regulatory decision-making process is the of local political races (Hiatt and Park, 2013). Studies have showed that political competitiveness causes elected officials to become more receptive to corporate political influence (Lord, 2000; Hillman, Keim, and Schuler, 2004). When an elected official faces tight competition in an upcoming election, his or her incentive is to become more responsive to the needs of organized interests. As lawmakers become more responsive, they can garner greater support from organized interests such as financial contributions, which increases the likelihood of winning the election (Lawton, McGuire, and Rajwani, 2013; McDonnell and Werner, 2016).

For example, during the 2002 midterm elections, the rivalry between electoral candidates in the

U.S. House of Representatives was high in states with steel-related industries. The tight electoral

12 competition significantly increased the bargaining power of U.S. steel producers, who sought increased tariffs on steel imports. Industry lobbyists increased their efforts, and in the months leading to the election, the Bush administration approved the implementation of a 30 percent tariff, solidifying steel industry support for Republican candidates (Bonardi, Holburn, and

Vanden Bergh, 2006).

Increased responsiveness to financial contributions and informational lobbying by incumbent firms may prompt elected officials to examine more closely the decisions made by regulatory agencies, particularly if those decisions favor new entrants. Given that regulatory agencies are primarily concerned with maintaining their departmental budgets and autonomy

(Carpenter, 2002), tight electoral competitions may cause regulators to worry that elected officials will reduce their autonomy or restrict their budgets if they do not act in alignment with elected officials’ policy objectives. The management literature also supports the notion that turbulence in a firm’s external environment—such as uncertainty about an upcoming election— can cause an organization to more closely align itself with the objectives of key resource holders

(Battilana and Dorado, 2010). For example, Almandoz (2012) showed that in turbulent economic conditions, founders with conflicting logics were less likely to succeed; however, espousing an institutional logic consistent with resource holders led to lower cognitive confusion and increased likelihood of successfully founding the venture. Consequently, greater political competitiveness is likely to reduce implementation of policy according to the public service logic and push regulators to implement policy according to a legalistic logic, leading to outcomes closer to policymakers’ desires. Thus, we argue that political competitiveness should reduce the benefit of regulatory discretion on new venture market approval.

Hypothesis 3: Increased competitiveness in the political market will negatively moderate the positive effect of regulatory discretion on new venture approval.

13

Political party control. The alignment of political party control may also moderate the effect of discretion in new firm entry. When a single political party controls both chambers of the state legislature and the executive, the likelihood of successfully passing new legislation increases greatly because policy content is more easily communicated and requires less negotiation (Coleman, 1999). Divided control, on the other hand, greatly reduces the likelihood of passing new legislation because ideological differences create bottlenecks: to pass new legislation, elected officials must bargain across party lines on issues that are often ideologically intractable. Prior research has also found that divided control makes it more difficult for government to pass legislation in a number of areas, including responding to external shocks, reaching budgetary agreements, and raising (Besley and Case, 2003).

In terms of this effect on regulators’ competing institutional logics, political party control can moderate the effect of discretion on which logic dominates the regulatory decision-making process. When party control is aligned, elected officials can more easily enact laws that restrict regulatory agency budgets or legislatively reduce the amount of discretion they enjoy.

Regulatory bureaucrats, who would prefer to avoid this outcome, may be slightly more likely to follow the legalistic logic to signal to elected officials that such actions are unnecessary and that they will adhere to policy makers’ intentions in their regulatory decision making. Divided control, however, reduces the potential threat that elected officials will in the future curtail autonomy and resources. As a result, the public service logic may be even more instantiated in regulatory decision making for agencies endowed with discretion. Thus, we argue that divided political party control should enhance the benefits of discretion on new venture approval:

Hypothesis 4: Divided political party control will positively moderate the positive effect of regulatory discretion on new venture approval.

14 EMPIRICAL CONTEXT

The empirical context of this study is the U.S. hydroelectric power sector during the period

1978–2014. Hydroelectric power is the largest source of renewable electricity in the United

States (USEIA, 2017), spans all 50 states (see Figure A2), and employs over 300,000 people

(NHA, 2017a). The United States is also one of the largest producers of hydroelectric power in the world, after China, Canada, and Brazil (USEIA, 2011). Although hydropower is most frequently associated with very large dams, not all hydropower facilities use dams and not all dams produce electricity: in the United States, only about 3 percent of all dams do so (NHA,

2017b). Other types of hydropower facilities are “diversions” (also known as run-of-river), which channel just a portion of a river’s water through a canal which contains a turbine to generate electricity; “pumped storage,” which uses an upper reservoir to store kinetic energy during non-peak load times; and tidal generators, which use the rising and falling of the ocean tides to drive turbines near the ocean floor. The Department of Energy also classifies hydropower facilities by size (large, small, and micro) based on the amount of electricity they are capable of generating (USDOE, 2017). Most new hydroelectric license applications during the study period were for non-dam facilities in the small or micro categories. The study period begins after the passage of the National Energy Act of 1978 and continues through 2014.1

FERC regulates all hydropower facilities in the United States that are not federally owned or operated. To limit private exploitation of public rivers, FERC grants utilities 30- to 50-year licenses and is mandated to give equal consideration to energy and non-energy interests, such as

1 Prior to the passage of the 1978 Act, independent energy entrepreneurs were not permitted to sell electricity to the grid. Instead, electricity was generated by vertically integrated public and private utility that controlled generation and distribution in specified geographic areas. Under section 210 of the Act, known as the Public Utilities Regulatory Policies Act (PURPA), entrepreneurs were enabled to construct non-utility facilities from which utility companies were required to purchase power at the utilities’ generation cost (USDOE, 2017b). This created a new market for independent power producers and resulted in entrepreneurs entering the electricity sector at varying rates (Sine, Haveman and Tolbert, 2005; Sine and Lee, 2009).

15 recreational opportunities and environmental quality (FERC, 2014). The license application process involves an initial proposal that identifies environmental, historical, or archaeological issues surrounding the proposed project. In consultation with state and federal regulatory agencies, the applicant develops a plan to complete impact studies on these issues (see Figure

A3).

Costs of completing these studies depend largely on the nature of the facility site and can range from $1,000 to $6,000 per study. Completion of impact studies typically takes 1 to 2 years.

Public comments are also solicited at this stage. Once this is complete, a formal license application is submitted including the results of impact studies and detailed descriptions of the facilities, operation, and environmental impact mitigation measures. FERC reviews these documents and again solicits public comment and responses from other regulatory agencies. The applicant must address issues raised during the comment period, which could extend the process several years. A license is not granted until all issues are addressed and the facility is built and inspected. The total capital cost per kilowatt of developing a new hydroelectric facility ranges from $2,200 to $2,700 (USEIA, 2013). Once the facility is established, FERC assesses annual administrative fees that vary by type and size of facility and that total approximately $1 per kilowatt of facility capacity (FERC, 2014). For small-scale hydro facilities, a full return on investment can occur in as little as 5 years (Millman, 2013).

Although all hydroelectric facilities must ultimately be granted a license at the federal level by FERC, individual states have the authority to create their own requirements for licensing and relicensing (FERC, 2014). Under sections 401 and 404 of the Clean Water Act of 1972, states must certify to the federal government that an applicant complies with all state water- quality standards before a license can be granted. This gives states the authority to affect

16 licensing in two ways: they can indirectly deny a license by withholding certification, and they can impose conditions on a federal license by placing additional limitations on certification

(Copeland, 2015). Some states take advantage of this power and create additional restrictions on licensing, while others specifically craft legislation to prevent regulators from creating restrictions greater than applicable federal requirements. This creates significant variation across states in the discretion that regulatory agencies have to interpret and implement licensing legislation.

METHODS

Data

Our data contain all hydroelectric facility license applications and submitting organizations from

1978 through 2014 (see Figure A4). These data were obtained from FERC’s docket library.

During this period, 525 license applications were submitted by 413 potential licensees. Of these,

91 percent were licensed, 5 percent were withdrawn or rejected, and 4 percent were still awaiting approval at the end of the study period.2 The average wait time for a regulatory decision was

1,627 days, and the maximum was 7,494 days. The firms in the data set range from large, publicly traded multinational to very small partnerships and individuals applying for small-scale hydroelectric licenses.3 Information on organization type (public for-, private for-profit, or cooperative), founding dates, and headquarters location was obtained from

2 The data include license application; issue, withdrawal, and rejection dates; operational start-up/shut-down dates; project size (in MWh); facility location; facility type (hydroelectric dam, run-of-the-river, or pumped storage); and waterways used. 3 Although the FERC docket library contains data on license applications by public and for-profit firms, cooperative firms, and municipal and tribal , only publicly traded and private for-profit organizations and electric cooperatives were included in the sample. We excluded government- and tribal-owned facilities because they employ different strategies (e.g., they do not lobby with campaign contributions) and have a level of access to other public agencies that non-government organizations do not.

17 firm websites where possible and supplemented with the OpenCorporates database when firm websites were unavailable.4

We focus on state-level regulatory agencies rather than federal agencies for several reasons. First, state regulatory agencies are a more frequent point of contact than federal agencies for most businesses (Sabatier and Mazmanian, 1980). Second, compliance with state-level regulations is often more onerous than with federal regulations (Ungson, James, and Spicer,

1985) and therefore a more important source of influence over firm activities. Third, state-level agency approval is a prerequisite for obtaining a FERC license in this sector.

Dependent Variable

Regulatory approval. The dependent variable is license approvals of hydroelectric facility projects by new ventures. For this study, we define new ventures as entrants that are less than 7 years old.5 New entrant is coded as a dummy variable—1 for entrants, zero otherwise— and for the analysis is interacted with the predictor variable regulatory discretion.

Predictor Variables

Regulatory discretion. In operationalizing this measure, we borrow a discretion construct from the political science literature. Specifically, we use a weighted index of various private rights acts (PPRAs) that vary by state and year (Hecht, 2004). PPRAs discourage regulations that limit the owner’s use of by attempting to balance the necessity of some legitimate regulation with the possibility of excessive government interference

4 Most of the firms in the sample are not publicly held, and, due to the longitudinal nature of the data, many no longer exist. Therefore, much of the demographic data ordinarily used in this type of analysis (such as profitability) were unavailable for many firms. 5 Results are consistent for entrants between 5 and 10 years of age. There is no universally accepted age limit for defining new ventures; age limits for new ventures in prior research range from between 3 and 7 years old (Tornikoski and Newbert, 2007) to between 6 and 10 years old (Baron, Hannan, and Burton, 2001; Hiatt and Sine, 2014).

18 in an owner’s ability to use their private property.6 Prior research has identified PPRAs as suitable constructs for discretion, which is often difficult to measure directly, because it measures the flexibility that regulatory agencies have in interpreting and implementing public policies (Hecht, 2004; Environmental Law Institute [ELI], 2013). For instance, the law and economics literatures have identified PPRAs as measures that “legislatively preclude [regulators] from taking added actions . . . even if they had the desire to do so” (Wagner, 2005:224) by decreasing regulatory agencies’ scope of regulation and constraining their latitude to implement policies, issue permits, or enforce statutes beyond federal minimum standards (Lingle, 2010;

Brown, 2011; Owen, 2017).

The index we use is from Hecht (2004) and is specific to environmental regulation rather than to statewide agency discretion, thereby serving as an appropriate measure of discretion for our empirical context. For example, the ELI has used this index as a measure of discretion for the approval or denial of permits for facilities that affect state water bodies per the Clean Water Act

(ELI, 2013). The Hecht (2004) index distills 20 different property rights acts, including laws that reduce the threshold for defining a regulatory taking, the degree to which property rights acts affect regulatory agencies and local government decision making, and whether decisions require external review, into a single index that weights rules according to their severity. The scale ranges from 0 to 100; a high score indicates that the state has little discretion in preventing property owners from using their property as they see fit, and a low score indicates great

6 In general, PPRAs require state regulatory agencies to evaluate whether a rule will cause a taking and to implement safeguards to ensure that agency actions do not cause this to occur. A regulatory taking occurs when a regulatory policy deprives the property holder of economically reasonable use of the property. In the context of the hydroelectric sector, regulatory agencies consider the potential upstream or downstream impacts on private property as part of the welfare considerations.

19 flexibility in making regulatory decisions. For purposes of analysis, we reverse-coded this variable.

Financial contributions and lobbying. To examine incumbent firm actions to influence the license process, we use data on financial contributions and informational lobbying from the

National Institute on in State Politics, a non-partisan non-profit organization that collects comprehensive lobbyist and other information from government disclosure agencies. This database provides annual financial contributions to state-level elected officials as well as the number of lobbyists hired per state per year. The data include lobbying and financial contributions from 1990 through 2014.

Political competitiveness. For the lower- and upper-chamber legislative levels we use percentage of seats by which the dominant party holds a majority, and for gubernatorial elections we use the margin of victory. Following prior research, we code the political competitiveness as intense if the margin of victory is less than 5 percent for gubernatorial elections (Bonardi

Holburn and Vanden Bergh, 2006). We extend this logic to legislative seats and code the political competitiveness as intense if the margin by which the dominant party holds a majority is less than 5 percent. These are dummy variables coded as 1 if political competitiveness is high and zero otherwise.

Political party control. For each level of government—the legislative chambers and executive—we code for dominant party control. When the legislative and executive levels of government are controlled by the same political party, political control is united; when they are not controlled by the same party, political control is divided. This is a coded as a dummy variable: 1 if state government has divided control, and zero otherwise.

20 Control Variables

We use a number of control variables in this analysis. At the firm level we control for firm type

(coded as a categorical variable: zero for public for-profit firms, 1 for private for-profit firms, and 2 for cooperatives). As a proxy for firm size, we use the total size of all electric facilities

(measured in MWh). To capture the potential impact of organizational capabilities pertaining to interactions with regulatory agencies, we also control for each firm’s regulatory experience by counting the cumulative number of permits held. These data were obtained from the FERC docket library and from the Energy Information Administration database.

We also control for specific characteristics of the state and the federal regulatory environment. We control for the dominant political party at state-level upper (upper chamber party) and lower chambers (lower chamber party) as well as the governor (governor party). We also control for the political party of the U.S. President in case state regulators choose to resist or oppose federal policy agendas. We also control for pro-environmental sentiment using the

League of Conservation Voters Scorecard (LCV), which scores annually the pro- or anti- environmental sentiment of federal legislators in each state. At the state level, controls for state population and per capita gross state product are also included. Prior research suggests that increasing the number of decision makers and decision points decreases the likelihood of successful policy implementation (Pressman and Wildavsky, 1984). To address this we control for the number of agencies involved in hydropower licensing in each state. The state hydroelectric potential, average commercial energy price, and number of hydroelectric-specific energy incentives for each state are also controlled for to capture potential economic returns to investment in hydropower facilities.

21 We control for formal objections to license applications and lawsuits from facility stakeholders. We obtained formal objections made by incumbents (incumbent objections); by external stakeholders, such as environmental activists (stakeholder objections); and by others

(other objections), including various state and federal regulatory agencies with shared responsibility for waterway protection (e.g., state Fish and Wildlife departments, EPA), from

FERC’s docket library. We also control for the cumulative number of lawsuits in each state surrounding hydroelectric power facilities, as they may be another tactic that incumbent firms or external stakeholders use to affect license approval. Lawsuits data were obtained from the

LexisNexis legal database; we identified 68 lawsuits affecting 102 facilities.

Analysis

For this study, we use event-history analysis because it allows us to take advantage of the richness of the panel data and is the standard technique used in research on similar phenomena surrounding regulatory approvals.7 Specifically, we model project approvals using a Cox proportional hazard model. The hazard rate is defined as

hi(t)= h0(t) exp (β’χ) where h0(t) is the baseline hazard function and β’χ are the covariates and unknown regression parameters. To minimize collinearity on interaction terms between the regulatory discretion variable and predictor dummy variables, we standardized the regulatory discretion variable. We tested for multicollinearity and found that all variance inflation factors in the analysis were less than 5 and that most were near 1, suggesting an acceptable level of multicollinearity.

7 For instance, see Carpenter (2002) and Hiatt and Park (2013) for application of event-history analysis to agency approval of pharmaceuticals and GMOs, respectively.

22 RESULTS

INSERT TABLE 1 ABOUT HERE

Descriptive statistics and bivariate correlations appear in Table 1, and the results of the Cox proportional hazard models appear in Table 2. Model 1 of Table 2 shows the effect of control variables only, and Model 2 adds the effect of regulatory discretion. Model 3 adds political contributions by incumbent firms and the interactions of these variables with regulatory discretion to test Hypothesis 1, and is limited to the years for which political contributions data were available (1990–2014). Model 4 adds entrants, regulatory discretion, and their interaction to test Hypothesis 2. Model 5 adds political competitiveness and its interaction with regulatory discretion and entrants to test Hypothesis 3. Model 6 adds divided political control and its interaction with regulatory discretion and entrants to test Hypothesis 4.

Several control variables had a significant effect on facility licensing. Publicly held corporations were more likely to be granted a license. Formal objections by other regulatory agencies had a negative effect on the likelihood of licensing. Surprisingly, objections by external stakeholders and incumbent firms had no effect on licensing. Per capita gross state product had a negative and significant effect on the probability of licensing. State hydroelectric potential also had a positive and significant effect on the likelihood of licensing. Last, LCV scores had a positive and moderately significant effect on licensing.

INSERT TABLE 2 ABOUT HERE

The results provide support for Hypothesis 1, which predicts that the effectiveness of incumbent firms’ lobbying activities will decrease as discretion increases (see Figure A5). In

Model 3, corporate political contributions improved firm outcomes; however, a one-standard- deviation increase in discretion reduced this effect by 33 percent. The results also provide strong

23 support for Hypothesis 2, which predicts that regulatory discretion will increase the likelihood of new entry. New entrants are 28.4 percent more likely to be licensed for each one-standard- deviation increase in the level of regulatory discretion. Figure A5 illustrates the effect of regulatory discretion on approval times for firms with low and high corporate political contributions. Figure A6 illustrates the effect of regulatory discretion on the approval times for new entrants and incumbent firms.

The results provide support for Hypothesis 3, which predicts that the competitiveness in the political market will negatively moderate the positive influence of discretion on new-entrant licensing. When interacted with entrants and discretion, political competitiveness in the upper and lower chambers of the legislature reduces the likelihood of obtaining a license by 38 and

36.9 percent, respectively. Although the coefficient on executive competitiveness is also negative, it is not statistically significant at the p < 0.05 level. The lack of significance on executive competitiveness may be because the executive branch generally has very little responsibility for overseeing regulatory agencies and therefore electoral competitiveness will be less likely to indirectly affect licensing of new entrants. Figures A7 and A8 illustrate the effect of regulatory discretion and political competitiveness in both the upper and lower legislative chambers on approval time for new entrants.

The results also offer minor support for Hypothesis 4, which predicts that divided political party control will increase the likelihood of licensing new entrants. Although the main effect of divided political party control has no significant effect on licensing, when it is interacted with discretion and entrants, the likelihood of licensing increases by 25.2 percent for every one-standard-deviation increase in regulatory discretion. These effects were significant at p < 0.08, however (see Figure A9).

24 Robustness Checks

We also conducted a number of robustness tests to address alternative models and to offer further evidence for the mechanism of discretion. In addition to Cox proportional hazard models, we ran analyses with parametric survival models with Gompertz, Weibull, and exponential distributions.

The results held across parametric survival models. We also ran piecewise-constant hazard rate models using 4- and 5-year time intervals, and results remained generally consistent with Cox proportional hazard models. We also ran analyses using a pooled cross-sectional logistic regression, as prior research suggests (Fiss and Zajac, 2004). Although results held for hypotheses 2, 3, and 4, the models would not converge to test Hypothesis 1 due to the limited panel size. We also ran the logistic regressions with U.S. state fixed effects. Although the results were still significant, 21 states were eliminated from the analysis because of lack of variation, thereby reducing the effect sizes. As an additional robustness check, we ran poisson and negative binomial models using a count of the days to license approval as a dependent variable. Our results were consistent with the Cox proportional hazard models presented here: financial contributions increased days to approval as discretion increased; for new entrants, days to approval decreased as discretion increased; political competitiveness in both upper and lower chambers increased approval time for new ventures; and divided party control decreased approval time for new ventures as discretion increased.

In addition, whether a regulatory agency wins or loses lawsuits may moderate the proposed link between discretion and the enactment of regulatory logics. To test this, we coded for whether the regulatory agency, the firm, or an external stakeholder won a particular suit. In results not shown here, we found no evidence that a regulatory agency winning or losing a

25 lawsuit had a later effect on the degree to which discretion influences instantiation of the public service or legalistic logic.

To further test the mechanism that regulatory discretion spurs greater use of public service logic in agency decision making, we examined the effect of firm location of operations on regulatory approval. If regulatory discretion does lead to greater instantiation of the public service logic, we would expect firms that are headquartered and operating solely within the jurisdiction of a regulator to benefit. The public service logic values highly the social welfare of local constituents (Maynard-Moody and Musheno, 2000), and empirical evidence in the public administration literature suggests that local governments tend to favor organizations that identify as part of the local community (Bordignon, Colombo, and Galmarini, 2008). If a firm under regulatory review is headquartered and conducts most of its business within a state agency’s geographic jurisdiction, regulators following the public service logic will likely view the venture as integral to the local environment and rate its market entry as a positive metric of local social and economic outcomes (Durose, 2011; Cloutier et al., 2016). We created a dummy variable for firms that operate only in the state of application. Organizations that have past or current licenses or license applications in multiple states are likely to be considered outsiders relative to those firms that were established and operate only in the state of application. When interacted with regulatory discretion, local firms are 30 percent more likely to be licensed than non-local firms.

We believe this provides additional evidence to support the notion that the enactment of the public service logic is enhanced by regulatory discretion.

DISCUSSION

This paper explores an underexamined area of institutions and entrepreneurship research by addressing the question “how can institutional factors enable new (de novo) entrants to overcome

26 barriers to entry in highly regulated markets?” Regulated markets are often characterized by significant regulatory barriers to entry. Although incumbent organizations have the resources to shape policy and navigate such markets (Sine, Haveman and Tolbert, 2005), theory suggests that new ventures often lack these resources. Yet, empirical evidence shows that some new ventures overcome these barriers and enter these markets (Sine and Lee, 2009). Research thus far, however, has neither theoretically nor empirically examined the political institutional factors that may be behind the heterogeneous entry of new ventures into regulated markets. By examining variation in policy implementation by regulatory agencies, we examine the tension that can occur between policymakers and policy implementers and suggest that the barriers to entry in regulated markets may be much more malleable than previously believed and that it can vary in the absence of policy changes.

Our results show how variation in the discretion that state regulatory agencies have in interpreting and implementing policies crafted by elected officials differentially affects both incumbent firms and new entrants. Although incumbent firms seek to maintain barriers to entry through corporate political activities, increased regulatory discretion reduces the effectiveness of these activities and levels the playing field for new entrants relative to incumbent firms. The results also suggest that new entrants benefit from greater discretion because it allows entrepreneurs to leverage state agencies’ institutional logic of public service, leading to greater new venture entry.

When state agencies have little discretion, elected officials can better monitor regulatory decision making, which can subordinate the public service logic to a legalistic logic that is more consistent with legislative objectives. However, when state agencies have greater discretion, the logic of public service can dominate decision making, reducing the advantages for incumbent

27 firms, lowering the barriers to entry erected by regulatory policy, and leading to greater entry by new ventures.

In addition, we find that the effect of discretion on the competing logics that influence regulatory decision making is moderated by political competitiveness and political party control.

Political competitiveness indirectly reduces the effect of regulatory discretion on new venture entry by causing regulators to follow more of a legalistic logic in their decision making, which can favor incumbent firms over new ventures. Facing tight re-election campaigns, elected officials become more receptive to corporate political influence strategies and will thus more closely monitor regulatory agency decisions to ensure alignment with their policy objectives.

Divided political party control, on the other hand, positively moderates the effect of regulatory discretion on competing institutional logics by reducing the ability of elected officials to enact policies that limit agency budgets or autonomy, thereby enhancing the ability of regulatory agencies to enact a logic of public service. In additional analyses, we also find that the effect of discretion is moderated by local concentration of firms’ activities. Because regulatory decisions are influenced by professional logics that prioritize local conditions, firms that are more locally concentrated within state agencies’ jurisdictions are more likely to gain regulatory approval when there is more agency discretion.

This study has two limitations worth noting. First, we were unable to control for size and profitability for all companies in the sample because 38 percent of the firms are privately owned and thus data were not available for those firms. We attempt to control for firm size using the electricity output of all electric facilities owned by each firm. While this figure likely correlates with firm size, it is not a perfect substitute. Second, although we examine what is arguably the most important influence strategy that incumbent firms use—financial contributions—this is just

28 one of many such political influence tactics. Future studies could examine how the influence of other political tactics, such as network ties to regulatory agencies, legislative testimony, or corporate grassroots mobilization (Hiatt, Grandy, and Lee, 2015; Walker and Rea, 2014), are affected by regulatory discretion.

This study makes a number of theoretical contributions. Primarily, it contributes to the institutions and entrepreneurship literature (Tracey Philips and Jarvis, 2011; Navis and Glynn,

2010; Almandoz, 2014; Nelson, 2014; Eesley, 2016; Eesley, Li and Yang, 2016) by exploring how political institutions and regulatory logics can affect new venture entry in regulated markets.

We know relatively little about the institutional factors that can facilitate new venture entry into regulated markets in the absence of policy changes. We address this limitation by highlighting the tension that can exist between lawmakers and regulators and by examining how different regulatory logics influence agency decision making.

The results also contribute to the nonmarket strategy literature by shedding light on the multiple political levels and interests that often exist in tension with one another in government.

Some of this criticism may be due to extant literature treating the state as a single, uniform entity, which potentially neglects important strategic and institutional factors that may be derived from a pluralistic view of the state (Mizruchi, 1989; Hillman and Hitt, 1999; Dorobantu, Kaul, and Zelner, 2017). By moving beyond the view of political influence as a dyadic interaction between suppliers and demanders of public policy and focusing on the implementation of public policy by regulatory agencies, we address scholarly calls to dive deeper into the relationship between regulators and regulated firms. While a large body research has modeled the behavior of firms, legislators, and regulatory agencies as self-interested and atomistic market actors seeking to maximize their personal utility (Holburn and Vanden Bergh, 2008), others have questioned

29 this approach because it ignores the important roles of social influence on regulatory decision making (Hiatt and Park, 2013; King, Felin, and Whetten, 2010). By directly examining not only the discretion of regulatory agency officials but also the professional logics that drive their decision making, this study takes a more nuanced approach to the study of business–government relations.

Additionally, this study enhances our understanding of the effectiveness of firms’ nonmarket activities (Mizruchi 1992; Henisz, Dorobantu, and Nartey, 2014). Recent research has begun to question whether simple measures of number of lobbyists or campaign contributions are sufficient to explain firm outcomes (Hill et al., 2013). For example, despite ample research, findings on the effectiveness of corporate political contributions are conflicting: some studies find a positive relationship (Alexander, Mazza, and Scholz, 2009) while others find a negative

(Hadani and Schuler, 2013) or not statistically significant relationship (Hersch, Netter, and Pope,

2008). The results suggest that future nonmarket strategy studies should account for institutional factors such as the relationship between elected officials who craft policy and the regulatory agencies who implement it. It may be that discrepancies related to the effectiveness of corporate political activity in prior studies is due in part to agency discretion, which, until now, has not been examined.

The findings open several avenues of future research. For example, studies might directly explore the strategies used by new ventures when entering regulated markets in which multiple governmental actors influence entry. Although recent studies have examined the unconventional ways by which entrepreneurs can enter regulated markets (Gurses and Ozcan, 2015), they have yet to theoretically or empirically explore the differences in strategies used by new ventures and incumbent firms to influence their regulatory environment, or their relative effectiveness with the

30 various institutional actors who control entry. For instance, are resource-rich entrants just as effective as incumbent firms at lobbying elected officials and regulatory agencies? Would it be better for entrants to engage regulatory agencies and incumbent firms with framing and collective action strategies simultaneously, or would it be better for them to avoid regulatory approval as long as possible and focus on other market-building activities?

In addition, research might examine the tactics that entrepreneurs seeking regulatory approval can take to leverage the public service logics. For example, in a study on the pay TV market, Gurses and Ozcan (2015) found that entrepreneurs seeking to enter the market framed their ventures’ products and services as improving consumer welfare and enhancing egalitarian distribution. Given that the public service logic places a high on creating distributional justice and fairness, how organizations frame their activities as solutions to these issues could be a fruitful strategy and merits additional research. In a similar vein, what role do endorsements and resources from important stakeholders, such as a local chamber of commerce or social movements (Pacheco, York, and Hargrave, 2014), play in signaling agency officials that their operations can enhance the local public welfare? For instance, the rise of the recycling industry was made possible through the actions of environmental activists who questioned the legitimacy of waste incinerators by highlighting the latter’s contribution to air pollution and promoted the establishment of recycling facilities as a cleaner alternative (Lounsbury, Ventresca, and Hirsch,

2003). Equally, scholars may wish to explore the degree to which entrepreneurs’ affiliation with local institutional actors such as senior figures in the media and prominent governmental figures can affect regulatory outcomes (Hiatt, Carlos, and Sine, 2017).

Another question this study raises is how the attributes of the entrepreneur interact with regulatory agency discretion to facilitate entry. Prior studies showed that entrepreneurs who were

31 formerly employed at firms that use the new venture’s products as inputs have better knowledge and experience in navigating regulatory hurdles and are more likely to recognize opportunities in regulated markets than entrepreneurs lacking such experience (Adams, Fontana, and Malerba,

2016). Other research suggested that an entrepreneur’s ability to recognize and exploit weak regulatory enforcement may lead to more successful entry into a regulated market, particularly when institutional actors lack incentives or expertise to adequately monitor or enforce regulations (Webb et al., 2009). Future research on entrepreneurs’ prior experiences is warranted.

An alternative potential stream is to explore the role of regulatory discretion where public policy is explicitly designed to favor entrants (Armanios et al., 2017; Eberhart, Eesley, and

Eisenhardt, 2017). Although public policies can be designed to lower barriers to entry and provide resources that make entry more viable, empirical studies have found mixed results for such reforms. Some studies showed that lowering entry barriers leads to greater founding, such as when the U.S. government passed laws that allowed the sale of power to the electric grid by independent energy firms (Sine, Haveman and Tolbert, 2005), while others suggested that entry does not significantly increase following regulatory reforms (Klapper and Love, 2010). It is possible that regulatory discretion is an important moderating factor.

How regulatory discretion affects the ability of external stakeholders, such as social movement activists, to support or constrain organizational activities may also be an important area for future research. Although studies have established a link between stakeholder activism and entrepreneurial activity (Hiatt, Sine and Tolbert, 2009; Sine and Lee, 2009; York, Hargrave, and Pacheco, 2016), much of this research takes a relatively static view of political opportunity structures that enable activist influence. Regulatory discretion may allow activists to shape the institutional environment by questioning the legitimacy and reputation of regulatory agencies,

32 making political opportunity structures more dynamic features of the institutional environment

(Carpenter, 2002). Thus, the variation in regulatory discretion across states may both trigger and pattern the ability of external stakeholders to affect organizational outcomes.

The sensitivity of these results under different types of regulatory discretion may also be a fruitful area for future investigation. In the field of environmental policymaking, regulatory discretion is often institutionalized through private property rights and no-more-stringent laws which span multiple regulatory agencies and are not readily changed (Organ, 1995; Hecht,

2004). In other contexts, regulatory discretion is linked more closely to organizational norms

(Kelly, 1994) and may be more easily changed through social or political pressures. How discretion unfolds in the long term, how it is affected by political competitiveness, and how it affects entry may be of interest to future scholars.

Finally, we believe that this study has practical implications for entrepreneurs, managers, and elected officials. First, it informs entrepreneurs about how they might better navigate regulatory-agency interactions and achieve positive outcomes. Entrepreneurial firms often face unique challenges in confronting their regulatory environment due to lack of resources, legitimacy, and political connections that large, established firms often enjoy. Understanding how different characteristics of the regulatory environment help entrepreneurs overcome these limitations is valuable for entrepreneurs seeking to launch new ventures in regulated markets.

New ventures in states with high regulatory discretion received approval decisions about 351 days sooner than average. This is consequential, as it can cost a new hydroelectric power venture up to $7,740 in forgone revenue for each day it awaits license approval.

Second, this paper informs managers of incumbent organizations how best to direct their corporate political activities. The results suggest that, despite ample research demonstrating the

33 effectiveness of lobbying activities and corporate political contributions (Hillman, Keim and

Schuler, 2004; Lawton, MaGuire and Rajwani, 2013), regulatory discretion may undermine their effectiveness. Incumbent organizations, therefore, should dedicate their resources to pursuing other means of corporate political influence that are not weakened by regulatory discretion.

Last, the results of this paper can inform elected officials about how to structure state governance to achieve the desired policy outcomes. Promoting and entrepreneurship has become a key element of many state and federal policy agendas. However, the discretion granted regulators by elected officials may either positively or negatively affect the ability of such policies to achieve their stated goals. This echoes the concerns of policy scholars who have advised that policy creation should not be divorced from policy implementation (Pressman and

Wildavsky, 1984). Therefore, this study suggests that policymakers should consider the institutional design of regulatory agencies and their degree of regulatory discretion over policy implementation when seeking to foster entrepreneurship.

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37 TABLE 1: Descriptive Statistics and Bivariate Correlations Variable Mean S.D. 1 2 3 4 5 6 7 8 9 10 11 1 New Entrant 0.142 0.349 2 Financial Contributions & Lobbying 7640.349 65658.71 -0.047 3 Pol. Comp. (upper) 0.714 0.452 0.052 0.059 4 Pol. Comp. (lower) 0.122 0.328 -0.032 -0.037 -0.296 5 Pol. Comp (exec) 0.264 0.441 0.034 -0.039 0.017 0.042 6 Divided Control 0.469 0.499 -0.054 0.019 0.208 -0.253 0.013 7 Firm Size (MW) 44.761 146.000 -0.097 0.100 0.020 -0.037 0.013 0.079 8 Firm Type 1.065 1.125 0.003 -0.109 -0.072 0.020 -0.008 -0.034 -0.019 9 Firm Age 63.385 44.802 -0.557 0.083 0.001 -0.018 -0.027 0.057 0.090 0.214 10 Regulatory Experience 0.363 0.481 -0.166 0.083 0.048 0.012 0.015 0.047 0.015 -0.422 0.082 11 SMO Objections 0.618 3.191 -0.05 0.151 0.037 -0.019 0.008 0.068 0.061 -0.090 0.062 0.124 12 Incumbent Objections 0.174 0.456 0.005 -0.016 0.015 -0.023 -0.007 -0.079 0.002 -0.055 -0.025 -0.029 -0.025 13 Other Objections 0.597 0.854 -0.067 0.066 -0.042 0.034 -0.01 0.068 0.062 -0.082 0.034 0.139 -0.022 14 Lawsuits 0.197 1.596 -0.021 0.012 -0.004 -0.043 -0.055 -0.011 -0.004 -0.027 0.030 0.028 0.000 15 Gross State Product 0.026 0.012 -0.048 0.125 -0.086 -0.016 0.018 -0.105 0.057 0.004 0.081 -0.004 0.024 16 State Population 15.414 1.205 -0.008 0.061 0.249 -0.086 0.051 0.185 0.118 -0.098 0.067 0.135 0.018 17 Number of Agencies 2.925 2.255 -0.031 0.073 0.178 -0.138 0.057 0.448 0.116 -0.049 0.103 0.168 -0.004 18 Energy Price 6.962 1.300 -0.051 0.14 -0.047 0.052 0.048 -0.098 0.050 -0.004 0.087 0.021 0.068 19 State Hydro Potential 1132.242 1208.55 -0.021 0.057 0.024 -0.080 0.037 0.236 0.147 0.016 0.068 0.087 -0.021 20 Energy Incentives 0.561 1.569 -0.014 0.03 -0.094 0.025 0.003 -0.033 0.049 0.028 0.070 -0.035 0.007 21 U.S. President 0.413 0.492 -0.086 0.018 -0.104 0.134 0.027 -0.137 0.010 -0.071 0.030 0.067 0.008 22 Exec. Party 0.053 0.224 0.064 0.048 -0.021 -0.020 0.012 0.088 0.046 0.063 -0.022 -0.069 -0.008 23 House Party 0.097 0.288 -0.015 -0.05 0.17 -0.122 0.035 0.581 0.081 -0.043 -0.018 0.038 0.063 24 Senate Party 0.064 0.308 -0.033 -0.025 0.129 -0.091 0.001 0.752 0.095 -0.048 -0.002 0.009 0.070 25 LCV Score 58.536 29.118 0.000 -0.039 -0.096 0.130 0.038 0.207 -0.032 -0.043 -0.012 0.099 -0.090

12 13 14 15 16 17 18 19 20 21 22 23 24 13 -0.027 14 0.014 0.010 15 0.102 0.127 0.026 16 0.038 0.126 0.028 0.201 17 -0.031 0.12 0.069 0.061 0.533 18 0.068 0.124 0.029 0.839 0.074 -0.042 19 0.010 0.134 0.090 0.120 0.356 0.816 -0.023 20 0.015 -0.017 0.000 0.453 -0.042 -0.028 0.425 -0.033 21 0.014 0.034 0.052 0.266 0.002 -0.057 0.255 -0.050 -0.031 22 0.004 0.026 -0.021 0.444 0.076 0.041 0.464 0.056 0.265 0.290 23 -0.032 0.076 -0.085 -0.079 0.346 0.161 -0.162 -0.046 -0.064 -0.110 0.064 24 -0.092 0.063 -0.046 -0.154 0.167 0.282 -0.149 0.031 -0.033 -0.116 0.054 0.783 25 -0.037 0.124 0.011 0.114 0.291 0.192 0.081 0.043 0.088 0.020 0.131 0.385 0.294

43 TABLE 2: Cox Event-History Regressions Variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 New entrant 0.039 0.048 0.205 0.105 (0.120) (0.124) (0.214) (0.157) Discretion -0.022 0.019 -0.125 -0.248 -0.111 (0.068) (0.000) (0.089) (0.195) (0.088) Financial contributions & lobbying 0.004** (0.002) Financial contributions & lobbying x -0.001** Discretion (0.001) New entrant x Discretion 0.250* 1.048*** 0.463*** (0.128) (0.326) (0.094) Pol. Comp (upper) 0.367** (0.159) Pol. Comp. (upper) x New entrant -0.333 (0.204) Pol. Comp. (upper) x Discretion 0.149 (0.171) Pol.Comp. (upper) x New entrant x -0.476** Discretion (0.233) Pol. Comp (lower) -0.254 (0.282) Pol. Comp. (lower) x New entrant 0.307 (0.357) Pol. Comp. (lower) x Discretion 0.171 (0.188) Pol. Comp. (lower) x New entrant x -0.460** Discretion (0.195) Pol. Comp. (exec) 0.123 (0.166) Pol. Comp (exec) x New entrant -0.267 (0.200) Pol. Comp (exec) x Discretion 0.001 (0.243) Pol. Comp (exec) x New entrant x -0.117 Discretion (0.174) Divided Party -0.017 (0.179) Divided Party x New entrant -0.228 (0.184) Divided Party x Discretion -0.027 (0.101) Divided Party x New entrant x 0.290* Discretion (0.170) Firm Size 0.000 0.000 0.000 0.000 0.000 0.000 (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) Firm Type 0.275** 0.268** 0.268** 0.244* 0.145 0.092 (0.119) (0.123) (0.124) (0.125) (0.136) (0.138) Firm Age -0.003 -0.002 -0.002 -0.002 -0.003 -0.003 (0.002) (0.002) (0.002) (0.002) (0.002) (0.002)

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Variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Regulatory Experience 0.038 0.033 0.043 0.050 0.010 -0.067 (0.108) (0.110) (0.108) (0.110) (0.119) (0.112) Stakeholder Objection -0.155 -0.158 -0.164 -0.152 -0.098 -0.087 (0.110) (0.113) (0.121) (0.111) (0.113) (0.109) Incumbent Objection -0.039 -0.039 -0.045 -0.047 -0.059 -0.051 (0.071) (0.071) (0.076) (0.072) (0.081) (0.079) Other Objection -0.325*** -0.325*** -0.337*** -0.327*** -0.392*** -0.376*** (0.086) (0.086) (0.089) (0.084) (0.089) (0.081) Lawsuits -0.053 -0.052 -0.052 -0.048 -0.042 -0.04 (0.037) (0.037) (0.038) (0.038) (0.042) (0.050) Gross State Product -34.629*** -33.942*** -34.108*** -35.187*** -48.563*** -46.201*** (11.481) (11.863) (11.929) (12.097) (16.273) (15.616) State Population -0.056 -0.057 -0.063 -0.067 -0.153** -0.123** (0.062) (0.062) (0.063) (0.066) (0.063) (0.057) Number of Agencies -0.067 -0.068 -0.066 -0.068 0.002 0.025 (0.045) (0.045) (0.045) (0.045) (0.052) (0.052) Energy Price -1.99 -1.995 -1.944 -1.829 -0.017 -0.019 (3.703) (3.706) (3.667) (3.534) (0.024) (0.023) State Hydro Potential 0.000** 0.000** 0.000** 0.000** 0.000* 0.000 (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) Energy Incentives 0.063 0.058 0.062 0.063 -0.046 -0.026 (0.051) (0.054) (0.055) (0.058) (0.059) (0.058) U.S. President 0.093 0.098 0.151 0.095 0.27 0.251 (0.623) (0.622) (0.633) (0.643) (0.613) (0.631) Executive Party -0.537 -0.55 -0.556 -0.584 -0.204 -0.263 (0.335) (0.342) (0.340) (0.363) (0.489) (0.476) House Party 0.054 0.05 0.063 0.072 0.874** 0.787** (0.348) (0.348) (0.349) (0.355) (0.344) (0.329) Senate Party -0.002 0.01 -0.005 0.019 -0.713** -0.431 (0.255) (0.257) (0.258) (0.259) (0.295) (0.330) LCV Score 0.003* 0.004* 0.004* 0.004* 0.001 0.001 (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) Wald Chi-squared 74.38*** 74.17*** 84.48*** 85.44*** 116.92*** 109.29*** Observations 1,269 1,269 553 1,269 1,269 1,269 Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

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