Corporate Political Strategy in Contested Regulatory Environments
Abstract
We examine how firms strategically manage opposition from organized stakeholders who participate in regulatory agency policy-making processes. As stakeholder opposition in regulatory agency hearings increases, we argue that firms invest more in developing counter-balancing support from elected politicians who oversee regulators, and more so when regulators are less experienced or are closer to reappointment dates. We find robust statistical support for our predictions in a statistical analysis of financial campaign contributions to state politicians by firms in the U.S. electric utility industry during the period 1999–2010. Our findings contribute to nonmarket strategy research by providing evidence that firms respond to contested regulatory environments by cultivating support from elected political institutions, contingent on the degree of regulator sensitivity to political and stakeholder pressures.
Firms in a wide range of industries routinely or occasionally confront opposition to their operations from local activists, nongovernmental organizations (NGOs), or other organized stakeholders who seek to influence government regulation of industry behavior or to disrupt firm-specific customer and supplier relationships. Such “nonmarket” opposition has covered a diverse set of issues in recent years, ranging from global sourcing to environmental pollution to CEO pay, ultimately leading, in some cases, to changes in government regulations or corporate strategy. A growing body of academic research has explored the types of firms that are likely to be targeted by activist organizations (Lenox and Eesley 2009), how firms can strategically preempt or respond to activist campaigns (King 2008, King and Lenox 2000, Maxwell et al. 2000, McDonnell et al. 2015, Short and Toffel 2010), and the impact on firm financial performance of stakeholder opposition in nonmarket arenas (Hadani and Schuler 2012, King and Soule 2007).
In this paper we contribute to nonmarket strategy research by examining how firms strategically manage competition from organized stakeholders who participate in formal government policymaking processes, to mitigate potentially adverse effects on public policy. While existing literature has focused on how firms interact with activist stakeholders in the context of “private politics” strategies (Baron and Diermeier 2007, Delmas and Montes-Sancho 2010, Ingram et al. 2010, Reid and Toffel 2009, Lyon and Maxwell 2011, McDonnell and King 2013)—aiming to avoid costly boycotts or reputational damage—our paper provides the first statistical analysis, as far as we are aware, of how firms respond to direct competition from stakeholders in regulatory processes.
Administrative processes that govern regulatory decision-making afford organized stakeholders the opportunity to shape regulator decisions by providing information and testimony on policy alternatives and consequences, and to propose alternative policy directions, during public hearings. Regulators, while having some discretion in their policymaking, are required to take account of evidence presented during hearings and to rationalize their decisions. By shaping the informational environment underpinning regulatory deliberations, stakeholders that present credible evidence to support their preferred policies thus have an ability to potentially sway regulators’ decisions in their favor.
We predict that in contested regulatory environments where firms face more extensive opposition from stakeholders, firms will invest in developing greater political support—for instance, through election campaign contributions or by lobbying—for their preferred regulatory outcomes.1 Although legislators and executives cannot veto independent agency decisions, they determine regulatory agency appointments, budgets and jurisdictional authority, which can provide political leverage over regulatory decisions. Having implicit or explicit political support enables regulators to enact rules and orders in contentious situations when policies are vigorously opposed during hearings by stakeholders. By contrast, when policy proposals are less contested, firms have less need to shore up political cover and to counteract stakeholder influence on regulators.
We argue further that the incentive for firms to develop political support in response to stakeholder opposition depends in part on characteristics of the regulatory institutions. First, regulators with longer experience in office are likely to develop stronger information processing capabilities, which enable them to better scrutinize stakeholder evidence and claims about policy, and to sort out “fact from fiction.” They are hence less susceptible to being swayed by organized stakeholders opposing the firm, reducing the need for firms to counteract any adverse effects. Second, regulators with longer time horizons before their reappointment are likely to be less sensitive to immediate pressure from elected politicians, lowering the incentive for stakeholders to appeal to political actors as a means of influencing regulator decisions.
We test our predictions in the context of the U.S. electric utility industry, which is regulated by state-level independent regulatory agencies that have responsibility, inter alia, for setting rates, permitting new infrastructure, and approving corporate mergers and acquisitions (Delmas and Tokat 2005, Russo 1992). A unique feature of this setting is that we are able to construct a precise measure of the degree of expected stakeholder opposition specific to each firm, and its variation over an extended time period. Prior studies of stakeholder opposition in regulatory arenas have relied on state-level measures, implicitly assuming that all firms in a state face similar levels of opposition (Bonardi et al. 2006, Fremeth and Holburn 2012, de Figueiredo and Edwards 2016). Our data reveals there is significant firm-level heterogeneity in stakeholder opposition within a jurisdiction and over time, which we are able to leverage in our statistical analysis to identify the impact on firms’ political strategies.
Using panel data and a two-way fixed effects regression model to control for unobserved (time-invariant) firm characteristics and temporal factors, we estimate that firms increased their political campaign contributions by 27% when stakeholder opposition, as operationalized by the count of stakeholders who had contested the firm in prior regulatory hearings, was one standard deviation above the average level. This effect is significantly magnified in environments where regulators are relatively inexperienced and when they are close to reappointment dates. Our findings provide new insights into how firms seek to strategically offset the effect of organized stakeholder competition in regulatory policymaking, and the regulatory conditions under which stakeholder competition motivates firms to forge political relationships.
Corporate Political Strategy in Contested Regulatory Environments
Public policymaking is frequently depicted as a “political market” in which demanders (firms and organized stakeholders) and suppliers (elected politicians, regulatory agencies and courts) transact over public policies (Buchanan and Tullock 1962). In this view, policymakers such as elected politicians exchange their influence over legislation and regulation for valuable resources from stakeholders that improve their electoral prospects; for instance, in the form of financial campaign contributions, information, votes, or public advocacy. Firms that design and implement nonmarket strategies, either individually or in coalition with aligned stakeholders, thus have an opportunity to proactively shape policy outcomes (Bonardi et al. 2005, Macher and Mayo 2015).
Empirical research on nonmarket strategy has substantially focused on how supply-side characteristics of political markets shape firms’ nonmarket actions, with less attention paid to demand-side factors. The degree of electoral competition between rival politicians or parties, for example, has been found to affect the amount of campaign contributions from interest groups (e.g., Ansolabehere et al. 2003). Politicians with institutionally influential positions—committee members or chairs, or those who are pivotal in majoritarian voting processes—are also found to generally accrue more resources from stakeholders (e.g., de Figueiredo and Silverman 2006; Stratmann 1995, 1998). Recent research has identified how firms that establish ties or connections to powerful policymakers, through board memberships and other mechanisms, can benefit financially through improved access to government contracts or subsidies, or from less stringent regulatory oversight (Hillman 2005, Faccio et al. 2006, Claessens et al. 2008).
Perhaps due to the challenge of collecting detailed data on the demand-side of political markets, little research has explored statistically how the stakeholder environment influences nonmarket strategies. Conceptually, Bonardi et al. (2005) argue that as the degree of competition from stakeholders increases, political markets become less attractive from the firm’s perspective since organized stakeholders can affect regulatory and legislative policies in ways that are costly for the firm: NGOs and local activists may contest applications by firms in the energy sector for environmental and other permits from regulatory agencies, leading to delays or denials; public interest groups may seek to block mergers in the telecommunications or media industries due to anti-trust concerns; or consumer advocates may challenge automobile, pharmaceutical or food companies in regulatory hearings on product safety standards. In these and other industry contexts, stakeholders can influence regulatory outcomes by presenting testimony and evidence on the impact of policy proposals, by suggesting alternative policies, and by signaling to politicians where their constituent support lies (McCubbins and Schwartz 1984). Research has found that in jurisdictions with more organized consumer groups, for instance, regulators establish rate policies that constrain utilities’ financial performance (Fremeth et al. 2014). In general, firms that confront more numerous and better-resourced stakeholders in regulatory settings are likely to find it harder to achieve their ideal policy objectives.
One way in which firms can respond to stakeholder opposition is by directly countering stakeholder claims in regulatory processes—producing evidence, arguments and expert testimony that refute or disprove them—with the expectation that regulators will respond accordingly to the firm’s information. An alternative approach involves engaging with aligned stakeholders to build coalitions in support of firm activities (Henisz et al. 2014), although this depends on the presence of supportive, organized, and willing stakeholders in the relevant jurisdiction. Here we propose that another means for firms to mitigate stakeholder opposition is by augmenting support for their positions with elected politicians. While regulatory agencies generally make decisions without obtaining approval from politicians, they still have an incentive to account for political preferences (Shipan 2004, Weingast and Moran 1983). The executive branch of government typically controls the appointments process for heads of regulatory agencies: regulators who stray too far from executive policy ideals in their rulings and orders may thus risk nonreappointment in the future (Snyder and Weingast 2000). In addition, the legislature can sanction wayward agencies by conducting public hearings and committee investigations into agency actions, or by enacting legislation that overturns agency decisions or curtails their jurisdiction (Ferejohn and Shipan 1990). Agency budget approvals and appropriations present another mechanism for elected politicians to influence agency decisions.
Firms that build support among elected politicians for their preferred policy goals can therefore indirectly reduce the impact of stakeholder opposition on regulatory policy. A central way for firms to cultivate politicians is by making financial contributions to their election campaigns, through which corporations may seek to influence legislative and executive behavior and policy preferences (Hillman and Hitt 1999).2 Research suggests that financial resources are an important means for corporations to effect implicit quid pro quo exchange with politicians (Snyder 1990, Stratmann 1998, de Figueiredo and Edwards 2007), or to gain access to pivotal policymakers (Austen-Smith 1995). Financial contributions targeted at legislators thus have the potential to induce pressure on regulators, thereby offsetting the influence of competing stakeholders in regulatory contexts. This leads to our baseline hypothesis.
Firms will make greater financial campaign contributions to elected politicians when they face greater contestation from stakeholders in regulatory agency hearings.
Regulators at both the federal level (McCubbins et al. 1987, 1989) and state level (de Figueiredo and Vanden Bergh 2004) are required to follow administrative procedures that govern policymaking, such as public notification of proposed regulations, and organization of public hearings that enable interested parties to testify and present evidence about the impact of proposed policies.3 An important requirement is that regulators demonstrate a logical relationship between the evidence received and the policy finally chosen: under the Federal Administrative Procedure Act, “The proponent of a rule or order has the burden of proof … a rule or order [may not be] issued except on consideration of the whole record … and supported by and in accordance with reliable, probative, and substantial evidence” (Title 5, Part 1, Chapter 5.II, 556(d)). Judicial precedent has established that an agency must demonstrate it has “examine[d] the relevant data and articulate[d] a satisfactory explanation for its action, including a rational connection between the facts found and the choice made” (State Farm vs. Motor Vehicles Manufacturers’ Association, 463 U.S. 29 (1983)).4
Scholars have argued that legislatures strategically deploy administrative procedure requirements to resolve principal agent problems that arise when they delegate policymaking authority to expert but independent regulatory agencies (McCubbins et al. 1997). The requirement to base decisions on available evidence and testimony helps ensure that regulators respond to the preferences of organized stakeholders who participate during hearings. As the amount of credible information supporting a particular position from stakeholders increases, so too does the cost to the regulator of selecting a policy that substantively differs. Processing information from multiple parties and formulating arguments to justify policies other than those supported by stakeholders takes time and skill. By raising regulators’ decision costs, evidentiary requirements thus enable politicians to “stack the deck” in regulatory arenas in favor of constituent stakeholder groups.
Yet regulators differ in their abilities to manage administrative procedures and to expedite policymaking efficiently (Tiller and Spiller 1999, Fremeth and Holburn 2012, Leaver 2009). Regulators with stronger information processing capabilities can craft more coherent arguments based upon the information presented in regulatory hearings, and are better able to address stakeholder claims in justifying their preferred policies. Regulators with weaker capabilities, on the other hand, find it more challenging to counter stakeholder evidence, and are more likely to accept stakeholder arguments and positions in formulating their policy decisions. One source of heterogeneity in regulators’ information processing capabilities lies in experiential learning that occurs during execution of their responsibilities. Experience in the task of regulation enables regulators to learn about the nuances and full range of implications of policy issues, the validity of arguments advanced by stakeholders, and the idiosyncrasies of elected politicians concerned with their policy decisions. In formulating and justifying regulatory policies, then, experienced regulators are less likely to be influenced by the claims of organized stakeholders. From the firm’s perspective, more experienced regulators mitigate the threat from stakeholders contesting the firm in regulatory hearings, reducing the need to develop counterbalancing political support. This leads to Hypothesis 2.
The relationship between firms’ financial campaign contributions to elected politicians and the degree of stakeholder contestation in regulatory agency hearings is negatively moderated by the extent of regulators’ prior experience in office.
In addition to heterogeneity in regulators’ information processing capabilities, we argue that regulators also vary in their responsiveness to political principals depending on the stage in their appointment cycle. Appointments are one means through which politicians, responding to concerns (“fire alarms”) voiced by industry stakeholders, can create ex post accountability in independent agencies (McCubbins and Schwartz 1984). Agency and commission regulators are generally appointed by the executive branch of government for fixed terms, often for five years, after which they may be reappointed. Models of regulatory decision-making predict that regulators’ policies will tend to reflect the policy preferences of elected politicians with the authority to appoint or confirm, assuming regulatory officials are motivated at least in part by reappointment prospects (Bawn 1995). While it can be challenging for researchers to disentangle empirically the preferences of regulators from those of appointing politicians, a number of studies have found that regulators update policies in response to significant changes in political regimes (Moe 1990), and that regulators that fail to adjust policy face greater risk of sanctions such as not being reappointed (Shipan 2004, Weingast and Moran 1983).
Here we propose that regulators are likely to be more sensitive to the policy ideals of elected political institutions the closer they are to reappointment dates. Hauge et al. (2012) demonstrate how remaining in office is a key motivator for regulators, and that political pressure and possible punishment by the threat of premature removal can discipline regulators. Thus, regulator’s actions and decisions in the period shortly before a reappointment decision will have greater visibility and weight in the appointing politician’s calculus, as compared to those early in a regulator’s tenure which are more easily discounted or forgotten by politicians and stakeholders. There is also less opportunity for regulators to “compensate” for an errant policy on a particular issue by adjusting future policy decisions on other issues the closer to a reappointment date. By contrast, at the beginning of a regulator’s time in office, he or she has greater latitude to forge a more independent policy path knowing that over time he or she can move closer to political ideal points.
For regulated firms, the cost of raising concerns about regulator behavior directly with politicians, and seeking their support, will hence be greater when regulators are in the earlier stages of their tenure. It will be more difficult for politicians to induce changes in regulatory decision making than at later stages in the appointment cycle, reducing the incentives for firms to lobby or to make financial campaign contributions to political actors. Hence:
The relationship between firms’ financial campaign contributions to elected politicians and the degree of stakeholder contestation in regulatory agency hearings is negatively moderated by the length of time until reappointment of the regulator.
Empirical Design
To test our hypotheses we construct a detailed panel data set for all 183 firms in the U.S. electric utility industry, containing information for each firm on the degree of stakeholder opposition during major regulatory hearings and on monthly election campaign contributions to state politicians during the 12-year period from 1999 to 2010.5 Firms in the electricity sector are regulated by state Public Utility Commissions (PUCs), independent regulatory agencies whose primary task is to approve costs and to set rates during periodic rate reviews. Rate reviews are formal administrative processes that permit multiple stakeholders, termed “intervenors,” to present evidence and arguments during public hearings about appropriate allowable costs and rates, which are ultimately voted upon by PUC Commissioners.6 PUCs are generally headed by three to five commissioners who are appointed by the governor, with the approval of the state senate, for staggered terms of five years.7
Our dependent variable, Campaign Contributions, is the monthly sum of political campaign contributions made by a firm’s top management team and political action committee (PAC) (which is normally controlled by senior executives) to state legislators, to the governor, and to candidates for election, in the state in which the utility operates.8 The average value of monthly contributions in our sample is $2,589 or approximately $31,000 annually.9 Campaign contributions are one element of firms’ nonmarket strategies and tend to be positively correlated with lobbying activities (Ansolabehere et al. 2002), so the full extent of firms’ political responses to stakeholder contestation will usually be greater than just through campaign contributions.
To gauge stakeholder contestation during regulatory procedures—our focal independent variable—we measure the number of intervenors that participated in every formal regulatory review of a firm’s regulated rates since 1980.10 State Administrative Procedure Acts permit intervenors to access firm records, provide evidence and expert testimony, and cross-examine firm witnesses during regulatory hearings. The variable Count of Intervenors is the firm-specific count of intervenors that were active in the most recent rate review for a firm. The average value is 7.4 intervenors (with a standard deviation of 6.2) though there is considerable variation among firms: for instance, UNS Electric in Arizona confronted five or fewer intervenors during its rate reviews, but Commonwealth Edison in Illinois faced up to 60 intervenors contesting its rate applications, ranging from public consumer advocates to industrial consumer groups, municipal governments, and environmental NGOs. States such as Colorado, Illinois, Ohio, and Wisconsin had the highest levels of intervenor participation in rate reviews (averaged across all utilities in each state), while Alabama, New Hampshire, North Dakota, Tennessee, and Vermont had the lowest levels.
While the count of intervenors is a simple one-dimensional measure, it acts as a reasonable proxy for the extent of stakeholder opposition that firms experience in regulatory hearings: we randomly sampled 100 rate reviews and found, after analyzing stakeholder testimony and documentation, that a substantial majority of participating stakeholders argued against firm requests for increased rates, with the occasional exceptions being labor unions and shareholder representatives. Empirical research also supports the notion that organized stakeholders are associated with regulatory policies that economically disadvantage utilities: Fremeth et al. (2014) find evidence that regulators in states with public consumer advocates who intervene in rate hearings constrain utilities’ financial returns and revenues, lowering consumer rates. Based on our sample, the most prevalent types of intervenors were industrial consumers (who participated in approximately 75% of rate reviews), public consumer advocates (50%), municipalities (40%), and residential groups (33%).
Two variables capture heterogeneity in regulatory institutions, which we argue in Hypotheses 2 and 3 have implications for firms’ political strategy: The first, Regulator Experience, is the average number of days that the commissioners of the state Public Utility Commission have been in their positions. The mean value is 1,676 days (just over 4.5 years) with a standard deviation of 923 days. PUC commissioners often serve multiple terms, and in one case the PUC’s average commissioner experience was over 22 years (North Dakota in December 2000).11 The second variable, Time to Reappointment, is the average number of days that PUC commissioners have remaining until their reappointment dates. The mean value is 930 days (about 2.5 years) with a standard deviation of 319 days.
We include state-level political and economic variables to control for time-varying state-level factors that could affect the amount of campaign contributions by a firm. Competition between legislators for partisan control of the legislature has been associated with increased campaign contributions (e.g., Ansolabehere et al. 2003): Legislature Rivalry, which is equal to
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Table 1: Descriptive Statistics
| Variable | Mean | Std. dev. | Minimum | Maximum | Units | Source |
|---|---|---|---|---|---|---|
| Campaign Contributions | 2,589 | 12,398 | 0 | 489,200 | U.S. dollars | National Institute on Money in State Politics |
| Count of Intervenors | 7.37 | 6.19 | 1 | 42 | Count | State Public Utility Commission documents |
| Merger | 0.06 | 0.23 | 0 | 1 | Indicator | SNL/State PUC documents |
| Regulator Experience | 1,676 | 923 | 15 | 8,176 | Days | SNL/State PUC documents |
| Time to Reappointment | 930 | 316 | 0 | 2,176 | Days | SNL/State PUC documents |
| Democrat Control | 0.21 | 0.40 | 0 | 1 | Indicator | Book of the States/State gov’t websites |
| Republican Control | 0.27 | 0.45 | 0 | 1 | Indicator | Book of the States/State gov’t websites |
| Population | 7,970 | 7,596 | 491.78 | 37,338 | Thousands | U.S. Census |
| Change in Unemployment | 7.31 | 17.65 | −64.74 | 66.52 | 10 × Percentage points | Bureau of Labor Statistics |
| Change in Gross State Product (GSP) | 12.81 | 27.31 | −108.58 | 119.98 | 10 × Percentage points | Bureau of Economic Analysis |
| Legislature Rivalry | 0.77 | 0.18 | 0.19 | 1 | Score out of 1 | Book of the States/State gov’t websites |
| Election Year | 0.49 | 0.50 | 0 | 1 | Indicator | Book of the States/State gov’t websites |
| Rate Review | 0.24 | 0.43 | 0 | 1 | Indicator | SNL/State PUC documents |
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Table 2: Correlation Matrix
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 Campaign Contributions | ||||||||||||
| 2 Count of Intervenors | 0.137 | |||||||||||
| 3 Merger | −0.003 | 0.054 | ||||||||||
| 4 Regulator Experience | −0.017 | −0.096 | −0.028 | |||||||||
| 5 Time to Reappointment | 0.027 | −0.0496 | −0.034 | −0.132 | ||||||||
| 6 Democrat Control | −0.005 | −0.061 | 0.007 | −0.110 | 0.127 | |||||||
| 7 Republican Control | 0.017 | 0.053 | −0.033 | 0.156 | −0.005 | −0.310 | ||||||
| 8 Population | 0.097 | 0.332 | −0.010 | −0.218 | −0.003 | −0.045 | 0.077 | |||||
| 9 Change in Unemployment | −0.009 | −0.002 | 0.047 | −0.001 | −0.004 | −0.095 | 0.133 | 0.015 | ||||
| 10 Change in GSP | −0.021 | −0.051 | 0.016 | 0.064 | 0.013 | 0.014 | 0.072 | −0.056 | 0.499 | |||
| 11 Legislature Rivalry | 0.044 | 0.209 | 0.021 | −0.067 | 0.032 | −0.106 | −0.082 | 0.245 | −0.031 | −0.096 | ||
| 12 Election Year | 0.045 | 0.009 | −0.028 | 0.001 | −0.144 | −0.029 | 0.010 | 0.015 | 0.086 | 0.158 | 0.018 | |
| 13 Rate Review | 0.019 | 0.015 | −0.006 | −0.020 | 0.023 | 0.029 | −0.026 | −0.033 | −0.077 | −0.084 | 0.003 | 0.026 |
To identify the impact of stakeholder opposition on firms’ political campaign contributions, we exploit the panel structure of our data by using a fixed effects linear regression model with firm and time fixed effects (Angrist and Pischke 2009). Such a model enables us to control for unobserved firm characteristics that are time-invariant and that might be correlated with the level of stakeholder rivalry or characteristics of the regulatory environment, as well as with campaign contributions. By leveraging changes in contributions over time we control for fixed characteristics, such as firm management quality, and for time-varying factors that are common across all firms. The core model is specified as a linear regression with fixed effects:
Results
In Table 3 we present the results of several models that estimate the statistical relationship between stakeholder competition, regulator characteristics, and political campaign contributions. Overall, the models perform relatively well with R-squared values up to 0.29 and with expected coefficient signs on most control variables. The baseline model 1 reveals a strong positive correlation between the extent of stakeholder contestation and firms’ campaign contributions. The coefficient on Count of Intervenors is positive and statistically significant at the 1% confidence level, and it is also economically meaningful: a one standard deviation increase from the mean in the number of intervenors (about six additional intervenors) is associated with a 27% increase in contributions to state politicians by the firm’s PAC and senior executives, equivalent to an additional $8,546 annually. This provides strong support for our first hypothesis, and is consistent with firms strategically seeking greater political support when dealing with higher levels of stakeholder competition in regulatory arenas.
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Table 3: Fixed Effects Regression Models of Political Campaign Contributions
| (1) | (2) | (3) | (4) | (5) | |
|---|---|---|---|---|---|
| Count of Intervenors | 114.875∗∗∗ (34.149) | 199.498∗∗∗ (62.342) | 173.436∗∗ (87.762) | 194.955∗∗∗ (64.536) | 165.528∗ (97.842) |
| Regulator Experience | −0.395∗∗∗ (0.102) | −0.124 (0.142) | −0.394∗∗∗ (0.144) | −0.107 (0.101) | −0.395∗∗∗ (0.102) |
| Time to Reappointment | −0.563∗∗ (0.235) | −0.667∗∗∗ (0.234) | −0.088 (0.236) | −0.656∗∗∗ (0.485) | −0.185 (0.526) |
| Merger | 102.741 (182.221) | 113.437 (181.918) | 99.018 (181.997) | −399.817 (681.233) | −2,314.989∗∗ (960.316) |
| Democrat Control | −366.489∗∗ (177.947) | −376.256∗∗ (186.937) | −381.566∗∗ (193.819) | −373.466∗∗ (187.075) | −382.225∗∗ (190.747) |
| Republican Control | −693.229∗∗∗ (157.603) | −687.977∗∗∗ (158.100) | −684.347∗∗∗ (154.207) | −688.672∗∗∗ (157.229) | −665.778∗∗∗ (152.866) |
| Population | 2.257∗∗∗ (0.386) | 2.288∗∗∗ (0.384) | 2.269∗∗∗ (0.393) | 2.289∗∗∗ (0.383) | 2.272∗∗∗ (0.395) |
| Change in Unemployment | −59.979∗∗∗ (11.894) | −58.997∗∗∗ (11.832) | −59.328∗∗∗ (11.795) | −59.018∗∗∗ (11.833) | −58.808∗∗∗ (11.777) |
| Change in GSP | −3.671 (3.116) | −3.522 (3.120) | −3.603 (3.097) | −3.386 (3.126) | −3.795 (3.117) |
| Legislature Rivalry | 1,232.556∗∗ (601.233) | 1,294.594∗∗ (606.373) | 1,198.769∗ (698.842) | 1,318.575∗∗ (604.675) | 1,203.124∗∗ (599.606) |
| Election Year | 1,811.818∗∗∗ (143.303) | 1,804.904∗∗∗ (143.086) | 1,821.728∗∗∗ (145.683) | 1,813.000∗∗∗ (142.983) | 1,826.121∗∗∗ (144.284) |
| Rate Review | 283.302 (217.721) | 288.748 (218.618) | 283.993 (217.472) | 287.320 (218.680) | 288.628 (217.235) |
| Intervenors × Regulator Experience | −0.053∗∗ (0.021) | −0.056∗ (0.020) | |||
| Intervenors × Time to Reappointment | −0.062∗ (0.033) | −0.063 (0.086) | |||
| Regulator Experience × Merger | −0.261 (0.290) | ||||
| Time to Reappointment × Merger | 1.611∗ (0.878) | ||||
| Intervenors × Merger | 50.955 (101.151) | 78.982 (123.348) | |||
| Intervenors × Regulator Experience × Pre-review | 0.035∗∗ (0.012) | ||||
| Intervenors × Time to Reappointment × Merger | 0.039∗ (0.017) | ||||
| Constant | 4,629.342∗∗ (2,355.940) | 3,735.052 (2,357.227) | 4,190.113 (2,560.431) | 3,724.692 (2,361.811) | 4,322.104∗ (2,591.778) |
| Observations | 25,066 | 25,066 | 25,066 | 25,066 | 25,066 |
| Firms | 183 | 183 | 183 | 183 | 183 |
| R-squared | 0.287 | 0.287 | 0.287 | 0.288 | 0.288 |
Notes. All models include firm and month-year fixed effects. Robust standard errors clustered by firm in parentheses.
∗p < 0.1; ∗∗p < 0.05; ∗∗∗p < 0.01.
Models 2 and 3 in Table 3 include interaction terms for testing the second and third hypotheses. It is not possible to rely on the estimated statistical significance of a single variable coefficient as a guide to overall statistical significance when interaction terms are included in a model, as this depends on the values of the underlying variables (Brambor et al. 2006). We therefore estimate the statistical significance of Count of Intervenors × Regulator Experience and Count of Intervenors × Time to Reappointment at different values of the two regulatory agency variables. To facilitate interpretation of the models with interaction terms, we calculate in Table 4 the estimated marginal effects of an additional intervenor on campaign contributions.
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Table 4: Marginal Impact of Count of Intervenors on Campaign Contributions Conditional on Values of Regulator Experience and Time to Reappointment
| (Model 2, Table 3) | (Model 3, Table 3) | |
|---|---|---|
| Value of interaction variable | Regulator experience | Time to reappointment |
| Min | $198.7∗∗∗ | $173.4∗∗ |
| Mean − 1 std. dev. | 159.8∗∗∗ | 135.2∗∗∗ |
| Mean − 1/2 std. dev. | 135.4∗∗∗ | 125.3∗∗∗ |
| Mean | 111.1∗∗∗ | 115.4∗∗∗ |
| Mean + 1/2 std. dev. | 86.7∗∗ | 105.5∗∗∗ |
| Mean + 1 std. dev. | 62.4∗ | 95.5∗∗∗ |
| Max | −232.0 | 37.6 |
∗p < 0.1; ∗∗p < 0.05; ∗∗∗p < 0.01.
Model 2 of Table 4 presents evidence that firms substantially augment their political campaign contributions in response to stakeholder contestation during regulatory hearings when the regulatory agency is relatively inexperienced. As a benchmark, at the mean level of regulator experience, increasing the count of intervenors by one is associated with an increase of $111 ($1,332 annually) in a firm’s monthly political campaign contributions, all else equal. When regulator experience is instead equal to one standard deviation below the mean value (about two years of experience), the marginal impact on political campaign contributions of increasing the number of intervenors increases to $160 (44% increase). Increasing the number of intervenors by one standard deviation is associated with a $990 per month or $11,880 annual (38%) increase in a firm’s campaign contributions from the baseline average. By contrast, if regulatory experience is one standard deviation above the mean level (about seven years of experience), the corresponding marginal impact falls to $62. This provides strong statistical support for Hypothesis 2.
In Model 3 of Table 4 we assess the interaction between Count of Intervenors and Time to Reappointment and present the marginal effect of an additional intervenor. As expected, the marginal impact of intervenor opposition on campaign contributions increases as regulators approach their reappointment dates. When the Time to Reappointment variable is one standard deviation below the mean value, the marginal effect of Count of Intervenors increases by 17% to $135 (from $115 at the mean). Increasing the number of intervenors by one standard deviation is associated with a $835 per month or $10,020 annual (32%) increase in a firm’s campaign contributions from the baseline average. We thus find strong statistical support for Hypothesis 3: that firms increase their political support activities to offset opposition from stakeholders in regulatory agency hearings when regulators are nearer reappointment decisions, and hence more likely to be attuned to political preferences over regulatory policy.
We turn now to a brief discussion of the control variable results, which are largely consistent with our expectations. Two “supply-side” measures of the political market—legislature rivalry and election year periods—are associated with increased campaign contributions, confirming the findings of other research. In election years, utilities increase their political campaign contributions by approximately $21,700 on average. Larger states and falling unemployment are also associated with greater contributions from PACs and senior executives. Somewhat surprisingly, campaign contributions are lower under unified Democrat Control and Republican Control compared to divided party governments. One potential explanation is that it is costlier to build supportive political coalitions for policy reform under divided government contexts where legislator policy preferences are more heterogeneous.
Robustness
A limitation of our panel structure empirical design is that we abstract away from analyzing stakeholder contestation of specific regulatory policies, so it is possible that omitted factors that vary over time, such as governments’ adoption of new energy policy agendas, may be driving the observed positive correlation between stakeholder contestation and firms’ political campaign contributions, but not in a direct causal manner. To address this possibility, we replicate our analysis but focus the time period around utility merger and acquisition events since 83 (45%) utilities engaged in mergers and acquisitions during our sample period, and they required approval by Public Utility Commissions who have the authority to impose costly conditions (Clougherty 2003, 2005). Utility mergers tend to be publicly visible events, often attracting local media and political scrutiny, and are contested during regulatory hearings by organized stakeholders seeking economic rents through PUC approval conditions.14 For instance, organized groups, such as the American Association for Retired Persons, have advocated in merger proceedings for reductions in residential consumer rates15; local unions for employment guarantees; and environmental NGOs for renewable energy investments. By advocating for their interests in merger hearings, stakeholders may pressure regulators to impose costly conditions on a merger—thereby reducing the anticipated financial gains to shareholders—or even to deny approval altogether. From the regulator’s perspective, mergers and acquisitions are relatively rare and complex events, placing new analytical and political demands on regulatory commissions as they review and assess them, and conduct public hearings, before reaching a public interest determination.
Given the saliency of M&A events for firms, stakeholders, and politicians, we anticipate that firms’ political campaign contributions will be especially responsive to stakeholder opposition, and regulator characteristics, in the time period around regulatory review. Firms that expect greater stakeholder resistance to merger and acquisition proposals will have a stronger incentive to foster political support—as a means of facilitating regulatory approval and to mitigate the extent of costly conditions. As demonstrated by prior empirical research (Holburn and Vanden Bergh 2014), regulated firms are especially likely to curry political support in the period before public announcement of merger proposals, rather than during or after regulatory review; during this preannouncement period, firms have private information about the proposed merger, which protects them from immediate stakeholder opposition.16
To assess firms’ political strategies during merger and acquisition event periods, we interact the Merger indicator variable with Count of Intervenors × Regulator Experience and with Count of Intervenors × Time to Reappointment (see Models 4 and 5 in Table 3). For ease of interpretation of three-way interaction terms, we calculate the marginal effect of an additional intervenor on campaign contributions, inside and outside the merger event window, in Table 5.
|
Table 5: Marginal impact of Count of Intervenors on Campaign Contributions Conditional on Values of Regulator Experience and Time to Reappointment During Merger Periods
| (Model 4, Table 2) | (Model 5, Table 2) | ||
|---|---|---|---|
| Value of interaction variable | Merger window | Regulator experience | Time to reappointment |
| Mean − 1 std. dev. | Outside | $152.7∗∗∗ | $126.7∗∗ |
| Mean | Outside | 100.7∗∗∗ | 106.5∗∗∗ |
| Mean + 1 std. dev. | Outside | 48.8 | 86.4∗∗ |
| Mean − 1 std. dev. | Inside | 230.6∗∗∗ | 229.7∗∗∗ |
| Mean | Inside | 210.6∗∗∗ | 222.1∗∗∗ |
| Mean + 1 std. dev. | Inside | 191.2∗∗∗ | 214.4∗∗∗ |
Note. Differences in marginal effects outside vs. inside are significant at 5% level.
∗∗p < 0.05; ∗∗∗p < 0.01.
By comparing the magnitudes of the coefficients inside and outside the merger event window, we can see that firms’ campaign contributions are much more sensitive, as predicted, to anticipated stakeholder contestation during periods just before merger announcements than during all other time periods. To illustrate, the marginal impact of Count of Intervenors on campaign contributions when Regulator Experience is equal to its mean value is $215 inside the merger event window, but less than half that value ($102) in other periods. Economically significant differences in marginal effects remain at different values of Regulator Experience and Time to Reappointment. For example, when these variables are set at one standard deviation below their mean values, the marginal impact of an additional intervenor is $236 inside the merger event window versus $172 outside (when Regulator Experience = Mean − 1 s.d.), and $229 inside versus $140 outside (when Time to Reappointment = Mean − 1 s.d.). Differences between the estimated marginal effects inside and outside event window are statistically significant at the 5% level. Hence, especially during merger periods, firms ramp up their political contributions to counteract stakeholder competition when regulators are less experienced or are near reappointment.
These results provide further statistical support for our hypotheses, and suggest that our predictions are particularly germane for highly salient regulatory policies such as corporate merger and acquisition approvals.
Discussion and Conclusion
In this study we examine how regulated firms seek to defend economic rents against dissipation by competing organized stakeholders. While most firms in an industry are unlikely to be targeted by activists or NGOs in public media campaigns, many experience less visible but more routine opposition from stakeholders who contest firms in regulatory agency processes, and who aim to influence regulatory policies. Developing strategies and methods for responding to such opposition in regulatory arenas is thus an integral part of firms’ overall nonmarket strategy. We argue that one way for firms to mitigate the regulatory risk that stakeholder opposition creates is by proactively developing political relationships and political support for the firm’s objectives. Political actors can exert implicit or explicit pressure on regulatory agencies, counteracting the effect of stakeholder contestation during regulatory hearings. Our statistical analysis of campaign contributions by firms in the electric utility industry over a 12-year period provides support for our hypotheses: after controlling for observed and unobserved (time-invariant) firm characteristics, we found that firms contributed significantly more to state politicians when stakeholder opposition in prior regulatory rate hearings was greater, and especially when regulators were more likely to be sensitive to stakeholder pressure (less experienced regulators) or to political pressure (closer to reappointment).
Our analysis contributes to nonmarket strategy research by providing new evidence that demand-side characteristics of political markets have a central role in shaping firms’ political strategies. Our firm-level time-varying measure of the extent of stakeholder contestation advances on prior research that typically uses either a binary indicator of whether a firm is targeted by an activist group’s public campaign, or whether specific NGOs or advocacy organizations are present in the same jurisdiction as a firm. While our construct provides a more accurate depiction of the heterogeneity in stakeholder competition that a particular firm confronts, it is nonetheless limited by the implicit assumption that each stakeholder has an equal and linear impact on firm strategy. Yet stakeholder organizations vary in their resources, capabilities, and objectives. Future research could explore differences between types of stakeholder organizations or stakeholder coalitions, and their differential effects on firms’ strategic responses.
We also develop new insights into the integration of firms’ market and nonmarket strategies that aim to jointly create and capture economic value. Our finding that firms invest more in their political strategies when anticipating merger and acquisition benefits is consistent with the expectation of enhanced stakeholder rent-seeking efforts. One implication for managers is that the more successful is a firm at creating value in the market place, the greater is the need to design effective nonmarket strategies that protect economic rents from stakeholder competition in nonmarket institutions. Our analysis further suggests that the timing of nonmarket action is important: when executives have private information about their firm’s future strategy, they are not subject to immediate stakeholder opposition, which lends an advantage in building political relationships prior to public announcement of the firm’s intentions.
A number of unexplored questions emerge from our study. We assume here that intervenors are an economic threat to firms through their influence on regulatory decisions, which prompts firms to invest in campaign contributions and political relationships as a defensive, counterbalancing mechanism. Natural avenues to address in future research are whether, and under what conditions, the degree and type of intervenor rivalry actually affects regulatory policies; and the extent to which firm implementation of appropriately designed nonmarket strategies can offset adverse stakeholder impacts, leading to improved firm performance.
Our study naturally has a variety of limitations. We focus on one dimension of nonmarket strategy, political campaign contributions, yet firms often engage in complementary lobbying and coalition building, so our ability to make specific observational inferences about the impact of campaign contributions alone is limited. Detailed state-level lobbying data is not readily available in this industry context but this could be a fruitful avenue for further research in another sector where both lobbying and campaign contribution data are publicly accessible. Extending our research in this way would also address the question of the generalizability of our findings to other industries and regulatory policy issues.
Another limitation of the empirical model is the implicit assumption that stakeholder participation in regulatory hearings is essentially exogenous, and independent of firms’ political activities. Two aspects of our empirical approach help mitigate this potential concern. First, our measure of stakeholder opposition is lagged since it measures the number of intervenors in the prior rate review. Rate reviews occur on average every four years, so the typical lag in the variable will be two years. Hence, even if there were reverse causality whereby firm campaign contributions stimulated contemporary intervenor participation in regulatory hearings, our measure of intervenor opposition should not be effected since it is backwards looking. Second, our robustness analysis around M&A events, where we find consistent results, should not be affected by endogeneity concerns (as elaborated in Footnote 16).
In conclusion, and despite the limitations noted above as well as others, our analysis herein extends understanding of how firms strategically manage competition from stakeholders that participate in regulatory policymaking processes, a salient issue for firms in many industry sectors.
The authors thank conference and seminar participants for providing helpful comments at George Washington University, Harvard Business School, the Industry Studies Association Annual Conference, Marshall School of Business at University of Southern California, Ross School of Business at University of Michigan, the Society for Institutional and Organizational Economics Annual Meeting, and Tulane University. The authors also thank Jack Bunce, Minku Kang, Emily Ng, and Matthew Kehoe for exceptional research assistance. All authors contributed equally to this paper. The authors gratefully acknowledge the financial support of the Social Sciences and Humanities Research Council of Canada [Grant no. 435-2014-0885].
1 Research related to our analysis includes de Figueiredo and Edwards (2007), which assesses the relationship between firms’ campaign contributions and regulated state-level rates in the U.S. telecommunications industry. Hiatt and Park (2013) examine the effect of supportive stakeholders on the regulatory approval of genetically-modified organisms by the U.S. Department of Agriculture.
2 Complementary tactics include lobbying and building coalitions of aligned interest groups (for examples see de Figueiredo and Silverman 2006, Hillman and Hitt 1999, Lord 2003).
3 As de Figueiredo et al. (1999, p. 285), note, “One of the central properties of administrative procedures is to … aid the participation of a number of previously excluded groups.” State-level administrative procedures also facilitate the participation of previously excluded groups (de Figueiredo and Vanden Bergh 2004). Section 3 of the Massachusetts code on administrative procedure, for example, ensures that “prior to the adoption, amendment, or repeal of any regulation … the agency shall give notice and afford interested persons and opportunity to present data, views, or arguments … .” (General Laws of Massachusetts, Chapter 30A, Section 3).
4 Similar requirements exist for regulations promulgated by state agencies. For example, the South Carolina code on administrative procedures states that the regulator shall “issue a written report which shall include findings as to the need and reasonableness of the proposed regulation based on an analysis of the factors … and may include suggested modifications to the proposed regulations in the case of a finding of lack of need or reasonableness … .” (South Carolina Code of Laws, Title 1, Chapter 23, Section 1-23-111).
5 We acquired campaign contribution data from the National Institute for Money in State Politics (NIMSP), an independent research organization that tracks the amounts and dates of political campaign contributions made by individuals, organizations and political action committees to election candidates for state government office. For individuals’ campaign contributions, NIMSP identifies employer organizations. NIMSP data covers all states from 1999 onwards. Utility merger and acquisition transaction data were obtained from SNL Financial.
6 The panel consists of 25,066 firm-month observations. The number of observations is 1,286 less than the potential maximum of 26,352 (12 months × 12 years × 183 firms) due to missing data for one utility that operates in the District of Columbia and also due to the elimination of some firms following merger and acquisition events.
7 In 10 states, PUC commissioners are elected rather than appointed by the state government. Because state governments still control PUC budgets and jurisdictional authority through appropriations and legislation, PUCs in these states have an incentive to account for political preferences in their regulatory decisions. Our empirical results are nonetheless robust to excluding elected PUC states from the data set.
8 Prior research on corporate political campaign contribution strategy has typically included only PAC contributions. Here we additionally include contributions by the top management team since recent studies have found they complement PAC contributions (Fremeth et al. 2013, 2016). In addition, some states limit PAC contributions but not individual contributions, while other states limit the latter but not the former. Names of each utility’s top management team were gathered from annual editions of Platt’s UDI Directory of Electric Power Producers and Distributors, and verified against FERC Form 1 filings. We implemented an extensive name and organization matching process to identify in the NIMSP data which of these executives had made political campaign contributions.
9 Compared to federal level campaign contributions, state level contributions are much smaller in magnitude, reflecting the lower cost of state election campaigns. To illustrate, average political campaign contributions from all sources to all state-level House and Senate candidates in a typical state were $11 million per annum for the four-year period from 2007 to 2010.
10 We obtained regulatory approval documents from each state Public Utility Commission for each of 1,753 rate reviews that occurred from 1980 to 2010. Each rate review document lists the identities of participating intervenors. Approximately 13,260 interventions were made during this period, including 4,580 unique intervenor organizations.
11 To construct this variable we gathered the names and appointment dates of all PUC commissioners in each state from 1960 to 2010 from Internet and archival sources. 427 commissioners held office from 1999 to 2010.
12 In robustness checks we additionally included measures of the historic stability of Democratic and Republican party control of state government. Including these measures had no effect on the results for our variables of theoretical interest in either economic or statistical terms (available upon request).
13 We assess the robustness of our model in two ways. First, we estimate a Tobit model instead of a linear regression model since our dependent variable is truncated at zero (Angrist and Pischke 2009). Second, we use logged campaign contributions as our dependent variable to mitigate the impact of skewness. In both cases the patterns of statistical significance remain and coefficient estimates provide support for the hypotheses.
14 The 2008 proposed acquisition of the Energy East electricity company in New York by Iberdrola, a Spanish utility, provides just one example of state political pressures that can be exerted on Public Utility Commission M&A approval decisions. As the local newspaper commented, “State Senate Majority Leader Joseph Bruno, R-Brunswick, and U.S. Sen. Charles Schumer, D-NY, were upset when an administrative law judge overseeing the case recommended that the PSC not approve the merger except with significant restrictions. Bruno actually called on the judge to be dismissed … and said that the PSC and the DPS are ‘the most ponderous, difficult bureaucratic agencies in this state,’ … Governor Paterson also issued a statement in support of the merger, saying the PSC shouldn’t let the perfect be the enemy of the good when it comes to ratepayer benefits. The judge in the case says Iberdrola should have to give consumers more than $640 million in benefits, while Iberdrola has only been willing to give up $201 million” (Rulison 2008).
15 For example, in the 2000 merger between Xcel Energy and New Century, organized consumer groups including a consortium of industrial customers and a state-funded public consumer advocate lobbied the regulatory agency for a $50 million rate reduction and a six-year rate freeze, both of which were included by the agency in its merger approval conditions.
16 An identification advantage of focusing the empirical analysis around M&A events is that it helps address concern about potential endogeneity of intervenor opposition: it is possible that firms that develop greater political support through their nonmarket strategies may elicit greater stakeholder opposition (for instance, through more frequent participation in regulatory hearings). In this case, the maintained assumption of stakeholder opposition being exogenous would not be valid. Endogeneity is unlikely to be an issue in the period before public announcement of a utility merger or acquisition since intervenors will not be aware of the event (and firms’ campaign contributions and lobbying activities are generally reported only once a year; that is, with a considerable lag after they have actually occurred). This gives utilities a strategic advantage in developing political support before M&A announcement as their private knowledge rules out an endogenous opposition stakeholder response. We thank an anonymous reviewer for raising this issue.
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Adam R. Fremeth is an assistant professor in the Business, Economics, and Public Policy group at the Ivey Business School, University of Western Ontario. He received his Ph.D. from the University of Minnesota. His work focuses on the intersection of firm strategy and public policy making. He is primarily concerned with how firms both shape and respond to public policy, specifically in regulated settings such as the electric utility and oil and gas sectors.
Guy L. F. Holburn holds the Suncor Chair in Energy Policy and is an associate professor in the Business, Economics, and Public Policy group at the Ivey Business School, University of Western Ontario. He received his Ph.D. in business and public policy from the University of California, Berkeley. His research focuses on the relationship between political, regulatory, and stakeholder environments and firms’ nonmarket and market strategies.
Richard G. Vanden Bergh is a professor of strategy at the Grossman School of Business, University of Vermont. He received his Ph.D. in business and public policy and earned his MBA from the Haas School of Business, University of California, Berkeley. His areas of research include firm strategy in the political environment, the design of political and regulatory institutions, and the effects of political institutions on business investment.
