View
240
Download
1
Category
Preview:
Citation preview
1
Regulation, Institutional Logics and
Capital Structure: An Assessment
Sumit K. Majumdar
University of Texas at Dallas
majumdar@utdallas.edu
October 1, 2015
2
Regulation, Institutional Logics and
Capital Structure: An Assessment
Abstract
The impact of transition from a rate of return to incentive regulation on firm leverage
levels in the United States telecommunications industry has been examined for the years
1988 to 2001. Overall, price cap regulated firms have had 43 percent lower leverage levels
than firms regulated by the rate of return method. Diffusion of price cap regulation between
1996 and 2001 has had larger negative impact than between 1988 and 1995. Price cap
regulated firms have had 23 percent lower leverage between 1988 and 1995, while price cap
regulated firms have had 78 percent lower leverage between 1996 and 2001. Leverage decline
after price caps introduction would be motivated by efficiency considerations, but after TA
1996 firms would not only cut costs but send signals that low leverage would provide
financial muscle to fight competitive battles and aggressively protect markets.
Key words: capital structure; debt; incentive regulation; institutional logics; leverage; price
caps; rate of return regulation; strategic behavior.
3
Introduction
There are three sets of issues, from several literatures, that matter for understanding
of firm behavior. First, in the regulation and firm behavior literature, financing questions
have been important. Regulated entities, such as electricity, financial services and
telecommunications firms, in the United States, have had high leverage (Barclay, et al 2003;
Besley and Bolten, 1990; Bowen, et al 1982; Bradley, et al 1984; Hagerman and Ratchford,
1978; Taggart, 1981). In regulated industries, with regulated output prices, that firms subject
to rate of return regulation would choose high leverage, because interest costs would be
included in the rate base for calculating firms’ allowable returns (Dasgupta and Nanda, 1993;
Meyer, 1976; Rao and Moyer, 1994; Sherman, 1977; Spiegel, 1996), has been an idea holding
sway.
The business environment that regulators create permits high leverage, because
regulators are not going to let firms die (Taggart, 1985). Regulators have had incentives to
set high regulated prices to lower the probability of regulated firms becoming financially
distressed, allowing interest costs to pass-through to customers and permitting higher
leverage (Spiegel and Spulber, 1994). Limited empirical work (Klein, et al 2002; Taggart,
1981, 1985) has highlighted the existence of price regulations in output markets as providing
regulated firms with incentives to utilize higher debt to finance their operations. Recent
evidence (Bortolotti, et al 2011; Cambini and Rondi, 2012) has examined causality between
regulation and leverage, finding that leverage positively affects regulated rates but causality
the other way around is not established.
4
An important dimension of contemporary business environments has been the world-
wide occurrence of regulatory changes. With such changes in the institutional environment, a
shift in risk, from a firm’s customers to its shareholders, can follow from changes in pricing
regulations, such as from a rate of return to an incentive regulation scheme such as price cap
regulation (Laffont and Tirole, 1993; Lewellen and Mauer, 1993; Majumdar, 2011a).
These institutional changes alter the nature of agency costs regulators face, and
trigger changes in firms’ incentives for reducing costs (Majumdar, 1997; Sappington, 2002),
as a result of which firms may reduce debt to reduce interest burdens. Hence, a shift away
from a rate of return regime, to alternative incentive regulation schemes, can influence debt
levels in affected firms. This issue is relatively unexplored, and only one work (Ovtchinnikov,
2010) has shown the introduction of regulatory innovations to have induced firms to lower
leverage.
Second, in the corporate finance and strategy literature, financing and strategic
behavior questions have been closely interrelated,1 given the relationships between a firm’s
capital structure and strategy,2 because types of financing of firms impacts their strategic
behavior (Hall, 2002Majumdar, 2011b; Mayer, 1990).3 Capital structure has been measured
as the ratio of debt to total capital (Zingales, 1998). Debt is an important type of funds
1 The literature (Balakrishnan and Fox, 1993; Barton and Gordon, 1987; Bettis, 1983;
Bromiley, 1990; Oviatt, 1988) finds numerous such interrelationships. 2 The literature (Brown, et al 2009; Campello, 2003; Kochhar and Hitt, 1996;
Kovenock and Phillips, 1997) has described the possible cause and effect linkages.
3 The additional literature (Bencivenga and Smith, 1991; Cantor, 1990; Hao and Jaffe,
1993; King and Levine, 1993; Lang, et al 1996; O’Brien, 2003) supports evidence that
different financing types influence strategic behavior.
5
source (Corbett and Jenkinson, 1997); the defining feature of two components in a firm’s
capital structure, debt and equity, are the differential rights of providers (La Porta, et al
1998), relative levels debt impact firms’ behavior and increased debt held by firms softens
aggressive strategic behavior.4
The financial structure decision is equally strategic (Myers, 1977).5 Because of agency
(Jensen and Meckling, 1976), signaling (Ross, 1977) and information asymmetry issues
(Myers and Majluf, 1984), considerable heterogeneity exists between firms in financing
decisions (Cantillo and Wright, 2000; Denis and Mihov, 2003; Houston and James, 1996;
Krishnaswami, et al 1999). The issues of whether to have debt, and how much, are important
(Grundy, 1996; Grinblatt and Titman, 2001), and the taking-on of debt is an important
endogenous strategic choice firms make (McKay and Phillips, 2005; Parsons and Titman,
2008; Titman and Wessels, 1988).
Third, in the strategy literature, the role of institutional logics is important
(Thornton, 2004; North, 2005). Firms are embedded within an institutional context that
prescribe appropriate responses (North, 2005; Thornton and Ocasio, 2008). Strategic actions
are responses to institutional features (Greenwood, et al 2014). Institutions are generative
context-defining forces for firms (de Figueiredo, 2002), and influence strategic decision-
making because their logics shape behavior via effects on individuals’ perceptions (Thornton
4 The literature (Anderson and Makhija, 1999; Chevalier, 1995; Chirinko and Elston,
2006; David, et al 2008; Khanna and Tice, 2000; Lambrecht, 2001; Phillips, 1995; Titman,
1984) establishes this.
5 While an early piece (Modigliani and Miller, 1958) had showed that debt to equity
ratios did not matter, a literature has emerged that shows these postulates to be irrelevant
(Parsons and Titman, 2008).
6
and Ocasio, 2008; North, 2005). Yet, there is inadequate evidence as to how institutional
changes affect the actual strategies of firms (Short and Tofell, 2010).
Government regulators exercise power over key economic sectors (Earle, 1997), and,
in regulated environments, government agencies use institutional rules to intervene in and
constrain day-to-day firm operational activities (Evans, 1995). Such contextual constraints
influence social interactions by providing incentives for regularity of behavior (Greif, 1998).
Institutional changes alter incentives, such as on property rights (North and Thomas, 1973),
and variations in firms’ behavior and strategy occur due to the influences of different
institutional regimes (Fukuyama, 2011).
Motivations of firms differ across time (Nelson, 2007), and firms scan the environment
(Nelson and Winter, 1982). Strategic behavior is influenced by incentives, and these vary
according to institutional contexts (North, 1990). Institutional changes alter institutional
logics, and motivate firms to change strategic behaviors, as scanning, searching and sense-
making outcomes impact incentives (Thornton, et al 2012). Altered institutional logics lead
to changes in interpretations of environmental contingencies (Ocasio and Joseph, 2005),
engender new approaches to address these contingencies (Rao, et al 2003), and strategic
changes occur in rapidly-changing environments (Teece, et al 1997; Teece, 2007).
Issue Assessed: Summing up briefly, first literature highlights that regulatory
considerations have an impact on leverage levels or the strategic leverage decision. The
second literature highlights leverage decisions to be a strategic choice of firms. The third
literature highlights the role of institutional changes as influencing strategic decisions.
Putting the key ideas from the three literatures together, this paper evaluates the question as
7
to whether, as institutional environments change, leading to changes in institutional logics,
and how regulatory norms can be interpreted within these different eras, firms decisions on
leverage levels are affected by the explicit regulatory changes that may have occurred in
each era when a differing institutional logic might have prevailed.
Specifically, the article reports on an evaluation of the impact of the transition from a
rate of regulation scheme to an incentive regulation scheme on the leverage strategy of firms
in the United States telecommunications industry. A form of detailed operational regulation
in the telecommunications sector has been over pricing behavior, so that the monopoly
incumbent local exchange companies (ILECs) do not compromise consumer welfare through
high prices (Sappington, 2002).
Price regulation has been based on two extremes (Sappington and Weisman, 1996).
The standard approach has, historically, been rate of return (ROR) based pricing regulation.
Firms have been allowed to set prices allowing them to earn a pre-determined return on their
capital base. This has been a, by now famous, “cost plus” model of regulation.
Given disquiet about the “cost plus” approach, incentive-based approaches, such as
the price cap regulation (PCR) model, have been derived (Sappington, 2002). The PCR
approach has been a “price minus” model of regulation. Introduced in the United States
telecommunications sector in 1990, by 2001 over 40 states had implemented price cap
regulations. In 1985, there were 50 states with rate of return regulatory schemes. By 2001,
the number was 6. The other states had variants of the two schemes.
Hypotheses Examined: How changes in pricing regulations affect the leverage of
telecommunications firms is examined over the years 1998 to 2001, and for two specific eras
8
in that overall period. The assessment is contextualized and conducted for two unique
institutional eras in which sector regulatory and competitive conditions changed. The
institutional environments have differed before and after passage of the Telecommunications
Act of 1996 (TA 1996) in the telecommunications industry. Differences in pre- and post-
legislation periods will have differently impacted firms’ leverage strategies.
The first period data are for the years 1988 to 1995, when a ‘regulated public utility’
logic was in place before TA 1996. A ‘competitive entity’ logic came into play after TA 1996.
The second period data relate to the 1996 to 2001 period. Two hypotheses are examined with
the data. First, a hypothesis relates the relative extent of l everage as a function of pricing
regulation regime changes. Second, a hypothesis posits that the relative impact of how
pricing regulation changes influence the extent of leverage will be a function of changing
institutional logics over the two time periods evaluated.
This article makes important contributions to the literatures by integrating ideas
across literatures to present a framework with which to assess how regulatory changes may
affect firm behavior, because of changes in institutional logic across time periods. While there
is now an emerging body of writing on the topic of institutional logics (North; 2005;
Thornton and Ocasio, 2008; Thornton, et al 2012), there is no articulation as to how, as
historical contingencies and institutional logics alter, and firms strategic pre-dispositions
change, changing regulations also affect firms’ strategic decisions differently over time.
Pricing Regulations and Leverage
In regulated environments, where a ‘cost plus’ mental framework, underlying the rate
of return regulatory regime, had driven the regulatory approach, the cost figure for a firm’s
9
operations, would be considered as constant or it could rise. Lack of cost and market
pressures would lead to inefficient strategic choices (Weisman, 1993). The regulated firm
would not need to appreciate market conditions as its focus would be on internal or political
matters. Such a firm would be concerned about just producing the mandated output. Given
the available outputs, whether customers might demand them or not would be
inconsequential.
Specifically, a rate of return culture would lead firms to inflate their capital base with
inappropriate items and waste resources (Averch and Johnson, 1962; Bailey and Coleman,
1971; Baumol and Klevorick, 1970), limit innovation on cost reduction activities (Biglaiser
and Riordan, 2001), and obfuscate costs as risks were transferred to consumers because of
‘cost pass-through’ by inefficient firms (Joskow, 1974). In such circumstance, regulated firms
would inflate their debt base because interest costs would be included in the rate base for the
passing-through of all costs to consumers within the structure of regulated prices (Dasgupta
and Nanda, 1993; Spiegel, 1994; Spiegel and Spulber, 1994).
An impact of price cap introduction would be cost reductions, as this would be a
“price minus” regulatory regime. In such a regulatory environment, with capped prices, a
firm’s question would be that given a price ceiling, being the maximum received sum for
service provision, how would it make a profit? In a price-capped environment, the price
figure would be constant; while the cost figure would have to be variable. If the profit per
unit were to rise, then the cost per unit would have to move down. That would imply cost
savings coming from all possible sources, including making savings on interest costs. In such
10
a setting, the incentives would be to lower debt levels so as to save on the costs of financing
borrowed funds.
The “price minus” approach of a price cap scheme would focus the firm’s attention on
the market, because it would have to establish the market for a service with a specific price,
and it would not be in the firm’s interest to argue for a higher price during a review. Lower
prices, generally, would lead to higher volumes, and marginal cost reductions would provide
larger reductions in total cost and larger increases in profit. With output prices fixed, the
lowering of costs, including that of interest costs through lowered borrowings, would trigger a
downward, and not upward, revisions of prices that would then further enhance demand for
firms’ outputs.
Regulated firms would also be free to put in the relevant capability packages to help
generate the required volumes of services. In addition, firms would have the full freedom and
flexibility to implement whatever organizational mechanism would be necessary to meet
internal profit volume targets. Hence, an important characteristic of the price cap model
would be enhanced autonomy for strategic actions and flexibility in organizational routines
for implementation.
The enhanced demand for outputs could also trigger increases in the level of demand
for other types of capital, such as human capital and other technological capital that would
augment firms’ dynamic capabilities (Majumdar, 2013). Hence, a transition to a price caps
regime would, in general, be associated with a decline in relative debt levels. Accordingly, it is
hypothesized that:
11
Hypothesis 1: A transition from a rate of return regulatory regime to a price caps regulatory
regime will be associated with relative lower levels of debt in the firms that have made the
transition.
Institutional Change in the United States Telecommunications Industry
Historical Background: The Communications Act of 1934 had formalized the United
States telecommunications industry as a collection of regulated public utilities. Given
institutional logics, local telephone companies acquired a regulated public utility mindset.
The 1934 Act directed the newly created Federal Communications Commission (FCC) to
regulate interstate communications to provide telecommunications services at "just, fair and
reasonable prices." The Act, however, did not specify as to how to obtain the goal. The means
to do so were left open.
In addition, the Act presumed the existence of a monopoly supplier of long distance
services, and the fostering of competition was not a stated goal of the 1934 Act (Spiller,
2005). The ethos then was of universal access and cheap service. In the late 1950s, the FCC
started a process of partially and selectively deregulating the long distance and customer
equipment industry segments. The deregulatory process eventually led to the break-up of the
Bell system in 1984.
The main change of the 1980s, the break-up of the Bell system, came about as a result
of a settlement of a Department of Justice antitrust suit against AT&T, rather than
legislation or regulation. The regulated public utility monopoly model, in which the ILECs
were regulated monopolists, was not dismantled for many more years. A decade later, the
1982 AT&T litigation settlement, the Modified Final Judgment (MFJ), was likely to be
12
reversed by the Supreme Court. In the early 1990s, the United States Congress codified many
restrictions of the settlement into legislation while opening local exchange markets for
competition and providing ILECs’ owners the ability to enter into long distance markets.
This legislation became TA 1996.
Telecommunications Act of 1996: Historical contingencies altered as fundamental
structural changes occurred in the telecommunications sector after TA 1996. After the issue
of a MFJ in 1982, and pursuant to a consent decree, in 1984 the Bell system had divested its
ILECs, called the Bell Operating Companies (BOCs), and retained long distance services. In
1984, 22 BOCs owned by 7 Regional Holding Companies (RHCs) were in existence, and 161
local access and transport areas (LATAs) were created. The BOCs were permitted to carry
calls originating and terminating in one LATA. Between 1984 and 1996 regulatory fiat was
still the prevalent logic.
Twelve years after the 1984 divestiture, the promulgation of TA 1996 (Public Law
104-104, 110 Stat. 56, codified at 47 U.S.C. 151, et seq.), recast industry structure to make it
competitive (Cave, et al 2002). The TA 1996 legislation was intended to change industry
structure and bring in competition. Convergence, inter-modal facility provision and
competition became norms. The emergence of inter-modal competition, from alternative high
speed and wireless carriers, within local markets of the firms studied, was profound (Loomis
and Swann, 2005). In this milieu, the institutional logics altered completely. Firms would be
guided by a competitive entity mindset as a character archetype (Thornton and Ocasio,
2008), driven by the making of continuous adaptations to changing market conditions and
providing customers with numerous choices.
13
Institutional Logic Changes, Pricing Regulations and Leverage
Institutional logics encompass assumptions about meaningful firm actions (Thornton,
et al 2012), and changes in logics perpetrate changes in individuals’ perceptions to influence
their actions on strategic decisions (Glynn, 2008). If the institutional logics of an era defined
by a regulated utility mindset transitioned to a an era where a competitive entity mindset
was to be in place, then perceptions about how to act in an era of different institutional
logics, and interpret environmental signals, would also alter.
The objectives of TA 1996 were: ‘To promote competition and reduce regulation in order
to secure lower prices and higher quality services for American telecommunications consumers and
encourage the rapid deployment of new telecommunications technologies.’ This structure-
changing legislation was intended to bring contestability and competition into a monopol ized
sector. The impact of this legislation would be vital in altering institutional logics of
incumbents from a regulated public utility to a competitive entity mindset.
The TA 1996 deregulated the industry make it competitive (Cave, et al 2002). The
policies after 1996 involved creating a new industry structure, encouraging the deployment of
alternate infrastructures and enhancing customer choices. The structure-changing legislation
would have induced competition in incumbents’ markets and made the environment
dynamic and unpredictable (Hazlett, 2000). The institutional ethos would have shifted from
maximizing universal access to enhancing customer choices.
Enhanced market contestability would increase customer choosiness (Fernandes,
2006). In the presence of competitor entry, with progressively increasing choices available to
customers, higher demand elasticities would result as customers’ consumption patterns would
14
change and switching between alternate suppliers become possible because of open markets.
The rewards or penalties for price changes would rise. Efficient firms could capture a greater
market share through price decreases, while high cost levels, and substantial high prices,
could lead to a substantial market share loss for the firms concerned, and the presence of
organizational slack in firms would be equally costly for inefficient firms (Scharfstein, 1988).
In the process of strategic adaptation to institutional change, because of changes in
the institutional logics, market-opening and structure-changing policies could trigger
important behavioral changes in firms (Barley and Tolbert, 1997). The presence of high costs
would lead to lower profits, increase fiscal distress, act as an inducement to improve internal
efficiencies (Schmidt, 1997) and motivate search for cost reductions (Majumdar, 1995). Even
if firms had hitherto been cost-conscious, such levels of cost-consciousness would rise and all
feasible sources of slack in firms would be cut. Firms would reduce their levels of leverage
further, so as to further reduce the quantum of borrowed funds on which interest would have
to be paid.
As noted earlier, a transition from a “cost-plus” to a “price-minus” regulatory
framework would, in general, be associated with a lower level of leverage; however, the
intensity of the relationship associated with such a transition to a lower level of leverage
would be greater in an era where a competitive entity mindset prevailed , since the need for
cost savings, in such a setting, would have increased by an order of magnitude because of of
emergent market contestability, over a regulated public utility mindset. Hence, it is
hypothesized that:
15
Hypothesis 2: While a transition from a rate of return to a price caps regulatory regime will
be associated with relative lower levels of debt in the firms that have made the transition, the size of
such an impact will be larger in an institutional era characterized by a competitive entity mindset
relative to an institutional era characterized by a regulated public utility mindset.
Empirical Analysis
Data and Dependent Variables: The forty ILECs studied have been the unit of
analysis, for the empirical assessment, with each of them having operations in one or more
states. The impact of regulatory change on relative leverage patterns has been evaluated for
each of the ILECs over the course of the 1988 to 2001 period, and separately for the two
different eras: 1998 to 1995 and 1996 to 2001.
Data for the firms have been obtained from the Statistics of Communications Common
Carriers (SCCC) for the period 1988 to 2001. These companies have accounted for ninety nine
percent of the United States telecommunications fixed-line infrastructure. The data have
been extensively used for other similar analyses (Majumdar, 2011a, 2013; Majumdar, et al
2010, 2014). A balanced panel data model has been used, with the dependent variable
measuring leverage, or debt ratio, denoted as Debt. It has been measured as the long term
debt over total assets ratio (Cornett and Tehranian, 1992). The primary explanatory variable
is changes in the nature of price regulation faced by each of firms over time.
Background Details of Price Cap Schemes: In the telecommunications sector, starting
with the United Kingdom, where price caps were implemented to regulate British Telecom in
1984, the implementation of price caps have become ubiquitous. Almost all of the States
within the United States have adopted some form of incentive regulation, the most popular
16
being price caps. The popularity of price caps have seen them being adopted world-wide.
Price cap regulation has been employed in recent years in Belgium, Bolivia, France,
Germany, Honduras, Hong Kong, Ireland, Italy, Japan, Mexico, The Netherlands, Panama
and Peru (Weisman and Pfeifenberger, 2003).
For the United States telecommunications sector, after the first studies providing
evidence for the ideas that price caps lead to higher technology diffusion (Taylor, et al, 1992;
Greenstein, et al, 1995) and increased efficiency (Majumdar, 1997), a number of pieces (Ai
and Sappington, 2003; Gasmi, et al, 2002; Sappington, 2002) have borne out the positive
behavioral and performance consequences of price caps.
Principal Regulation Explanatory Variable: The regulation variable, Regulation, is a
dummy variable; 1 denotes the presence of price caps or another form of incentive regulation;
0 denotes the presence of rate of return regulation. The diffusion of price caps scheme has
varied over time. Introduced in 1990, by 2001 over 40 states had implemented price cap
regulations. The decline in rate of return regulation has been steady. In 1985 there were 50
states with rate of return schemes. By 2001, it was 6. There was no straight transition from
rate of return to price cap regulation. There were other schemes, falling under the rubric
incentive regulation, also implemented (Sappington, 2002).
The data on regulatory changes in the United States telecommunications industry
have been used in other work (Majumdar, 2011a). For the firms, the regulatory regime in
each period, an incentive scheme or rate of regulation, has been coded as a 1, 0 variable. Over
time, if the regulatory regime an observation experiences has changed, the 1 and 0 coding
17
picks up the change. Hence, relative to itself, a comparison of regulatory regimes for each
observation has been feasible.
Estimation Approach: To evaluate the first hypothesis, treatment effects modelling of
the relationship between regulatory transition and leverage is undertaken for all of the firms
for the full period between 1988 and 2001. Subsequently, the data are split into two parts:
the first part for the years 1988 to 1995, and the second part for the years 1996 to 2001.
Models are estimated for each such separate data set. The differences between the estimates
for the Regulation variable for each part are statistically evaluated to enable a reaching of a
conclusion on the second hypothesis.
Also, a firm- and location specific regulatory change will be endogenous because
regulators will have taken numerous firm-specific factors into account while putting through
the change regime. In addition, there will be an element of self-selection by firms into a price
cap regime, from a rate of return regulation situation, as, in many cases, they would have
attempted to influence regulators to make the transition. Hence, the regulatory change
variable is treated as endogenous and modeled appropriately using a treatment effect model.
Treatment Effects Modeling: The literature has dealt with issues of endogeneity. The
analysis of historical micro-econometric causality helps ascertain factors influencing higher a
transition to price cap regulation, given that regulatory change can influence leverage. In
historical micro-econometric causality analysis, endogeneity concern is tackled using the
treatment effects approach, in which a dummy explanatory variable denotes the existence,
or otherwise, of the endogenous phenomenon the impact of which is evaluated on an outcome
18
variable (Abbring and Heckman, 2008; Angrist and Krueger, 2001; Dehejia and Wahba,
1999; Heckman, 2005; Heckman and Vytlacil, 2005).
Firms that experience price cap regulation subject themselves to a treatment. The
treatment occurrence is given by the transition from the rate of return scheme to price cap
regulation. Its outcome is evaluated in terms of resulting relative leverage levels. The
prospect of experiencing a treatment is endogenous, involving a selection bias, since not all
firms will have engaged in such a regulatory transition but just a selected set of firms. The
treatment effects approach (Heckman, 1976; 1979) helps assess how regulatory transition
influences firms’ subsequent leverage, and a treatment effect is the average causal effect of a
variable on an outcome such as leverage.
A treatment effects model consists of an outcome and a selection equation. The price
cap variable is a covariate influencing leverage, in an outcome equation, after the price cap
variable has been modeled as a dummy endogenous variable influenced by other exogenous
variables, in a selection equation. Selection bias arises because treated firms differ from non-
treated firms for reasons other than the treatment status, per-se. The process of regulatory
transition affecting a particular firm, in a particular territory and in a particular time, can be
conditioned by several factors, as self-selection into treatment may be at play.
Treatment effect models (Heckman, et al 1998; Hirano, et al 2003; Rubin, 1974)
permit natural experiments to be assessed (Angrist, 1998), where a response function,
identifying strategic behavior, in this case of firms leverage outcome, embodies the effect of
interest after the onset of an internal decision or institutional policy (White, 2011). Natural
19
experiments are identifiable discrete shifts in within- or outside-firm environments such that
there is a behavior change (Angrist and Krueger, 2001).
The treatment effects modeling approach is described in Cameron and Trivedi (2005),
Guo and Fraser (2010) and Wooldridge (2010). The selection models permit treatment effects
modeling and pre- and post-event evaluations of variables of interest. Given a binary
dependent variable, selection models are easier ways of dealing with sample selection bias
than instrumental variable regressions (Bascle, 2008; Hamilton and Nickerson, 2003).
Firm- and Industry-Related Variables in the Outcome Equation: The literatures cited
have dealt with the importance of debt in capital structure, and why debt is an important
strategic variable. The extent of firms’ leverage indicates expectations about earnings
capacities and the abilities to repay debts. Yet, on what factors actually drive leverage levels,
there is no universal set of covariates determining leverage (Myers, 2003). Factors relevant in
explaining leverage variations are contingent on time and place specificities (Simerly and Li,
2000), industry factors (Vincente-Lorente, 2001), and firm-specific attributes (Kayhan and
Titman, 2007; Kochhar, 1996; Morellec, 2004).
Three relevant surveys on the determinants of leverage (Harris and Raviv, 1991;
Rajan and Zingales, 1995; Frank and Goyal, 2009) highlight the key covariates that
influence leverage. Leverage increases with fixed assets, non-debt tax shields, growth
opportunities, and firm size; it decreases with volatility, spending on intangible assets and
superior economic performance (Harris and Raviv, 1991). Others (Rajan and Zingales, 1995)
highlight firm size, profitability, possession of tangible assets and firm growth opportunities
as variables significantly impacting leverage. Frank and Goyal (2009) find that: firms in
20
industries where the median firm has high leverage have high leverage; firms with greater
tangible assets have higher leverage; firms with higher profits have lower leverage; larger
firms have higher leverage; and firms with higher market-to-book ratios have lower leverage.
Based on the literature, along with the regulation variable, Regulation, the following are
included as firm-related explanatory variables in the selection equation for Leverage: sales
growth (Growth), firm size (Size) measured as the log of total assets, financial performance
(Performance) which is an asset utilization ratio, an important profitability driver, measured
as the ratio of operating revenues to total tangible assets, and the ratio of total long term
assets to total assets (Assets). To control for industry-related factors, an intensity of relative
competition (Relative Competition) variable is used. The variable is the number of possible
competitors given a license to operate in each firm’s specific territory relative to the average
number of competitors per territory in the industry as a whole. The competition data are
collected from the FCC Competition in Telecommunications Industry reports.
Financial Market Variables in the Outcome Equation: The structure of interest rates
predicts real economic activity (Fama, 1986). An issue is, do the levels of interest rates
influence borrowings by firms? Monetary policies influence real sector activities (Friedman
and Schwartz, 1963), and short-term interest rates have been used to influence the cost of
capital and fixed investment spending (Bernanke and Gertler, 1995). Monetary policy
changes lead to balance sheet restructuring, including that of leverage (Adrian and Shin,
2010; Kashyap, et al 1993). Financial policies propagate shocks. These constraints affect
firms’ leverage decisions (Gomes, 2001; Korajczyk and Levy, 2003). In assessing macro-
economic factors impacting firm level financial decisions, financial market controls are used
21
and the variable used is the interest rate on 30-year long term U. S. Treasury bonds (Interest
Rate).
Variables in the Selection Equation: The price caps literature (Sappington, 2002;
Majumdar, 2011a; 2013) highlights key variables that can determine a transition from a rate
of return to a price caps regime. The size (Size) variable is the log of total output, a standard
measure in the literature. A control for the nature of interconnection regimes is necessary,
since they have been important, for fiscal reasons, in the sector (Armstrong, 2002). In the
absence of a finer or granular measure over the full time period, the relative access cost,
computed as the ratio of access costs to total operating revenues (Access), proxies for
interconnection regimes.
Key environmental factors are urbanization and the extent of business lines (Sharkey,
2002). The urban population ratio (Urban) is the weighted average ratio of urban population
to total population in each firm’s territory. This ratio is weighted by the fraction of lines that
the firm has operating rights to in specific states. The business lines construct (Business) is
measured by the ratio of total business lines to total access lines for each firm.
A technology investment measure used as a control has been the ratio of total fiber
kilometers to total cable kilometers (Fiber), as fiber has been an important technology
providing connectivity and generating efficiency. An advertising variable used has been the
ratio of advertising expenses to total expenses (Advertising). A market share variable
(Market Share) has been constructed by taking the ratio of a firm’s lines in its operating
territory relative to the total lines in the territory. The use of market share constructs as
22
controls proxy for market presence, though in regulated industries a high market share does
not imply monopoly power (Spulber, 2002).
Four measures of firms’ economic performance have been used. Following Christensen
and Montgomery (1981) and Cornett and Tehranian (1992), the following variables, cash flow
over assets (Cash Flow) and growth in sales (Growth), have been used as measures of
financial performance. The cash flow over assets variable has been calculated as the ratio of
total operating revenues to total assets (Cornett and Tehranian, 1992). An efficiency measure
has been a plant efficiency ratio (Efficiency); while a relative performance used has been the
ratio of the cash flow to total assets for each firm relative to the average cash flow to total
assets for all the firms as a whole (Industry Performance).
Results
Mean Values: The mean values for the Debt and Regulation variables are given in
table 1. The average ratio of long term debt to total assets has been 0.23, in proportion terms,
or 23 percent, for the entire period. When the data are split into two separate periods, the
ratio for the 1988 to 1995 period has been 0.24, and over time there has been a decline since
the ratio has been 0.21 for the 1996 to 2001 period. Over time, equity financing has become
slightly more important for the firms.
The values of the Regulation variable are also given in table 1; recollect that this has
been a 1, 0 variable, with 1 denoting the presence of a price caps regime. For the entire
period, between 1998 and 2001, the ratio has been 0.46 denoting that the regulatory change
had occurred in just under half of the observations. That would, however, portray a
somewhat inaccurate picture since the diffusion of the regulatory innovation has been
23
steadily rising over the time period. The average value of the variable for the 1988 to 1995
period was about 0.16, denoting that the regulatory change had occurred in just under a
sixth of the observations. For the 1996 to 2001 period, the mean value of the variable of 0.87
has denoted that the regulatory change had occurred in about six-sevenths of the
observations.
1******************** INSERT TABLE 1 HERE ********************
Tests for Hypothesis 1: The results of the estimations are given in table 2. Results for
the entire period, between 1998 and 2001, and for when the data are split into two separate
periods, the 1988 to 1995 period, when a regulated public utility entity mindset was in place,
and the 1996 to 2001 period, when a competitive entity mindset came into effect, are also
given in table 2. The estimates for the Regulation variable in the outcome equations for Debt
are -0.100, -0.057 and -0.167 for the entire period, for the 1988 to 1995 period and for the
1996 to 2001 period, respectively. All of the estimates are significant, at values of p < 0.01.
Hence, a transition from rate of return to price caps regulation has led the firms experiencing
such a transition to lower their levels of indebtedness, as measured by the Debt variable.
The impact of a transition in regulatory regimes on leverage levels is evaluated next.
Given average leverage ratios of 0.231, 0.244 and 0.213 for the Debt variable for the entire
period, and the 1988 to 1995 and 1996 to 2001 periods, the Regulation size estimates imply:
first, for the entire period, a transition to a price caps regulatory regime has been associated
with 43 percent lower leverage for the firms experiencing the regulatory transition; for the
period between 1998 to 1995, a transition to a price caps regime has been associated with 23
percent lower leverage for firms experiencing the transition; and for the period between 1996
24
to 2001 a transition to a price caps regime has been associated with 78 percent leverage ratio
for firms experiencing the regulatory transition.
Overall, these results support the first hypothesis that the transition away from a rate
of return regulatory regime to a price caps regulatory regime will be associated with relative
lower levels of debt. Additional unreported results suggest consistency across specifications.
The results for the 1988 to 1995 and 1996 periods show that, in both periods assessed
separately, the impact of a price caps regulatory scheme is to lower debt levels in firms. The
second hypothesis, however, has posited that the relationship for the 1996 to 2001 period, an
era characterized by a competitive entity mindset among the firms, will be larger than that
for the 1998 to 1995 period, an era characterized by a regulated public utility mindset.
******************** INSERT TABLE 2 HERE ********************
Tests for Hypothesis 2: A test to statistically establish the validity of the second
hypothesis is to apply a standard test comparing the estimates from two specifications. The
results of such a procedure, significant at p < 0.01, show that the negative relationship
between Regulation and Debt is of larger magnitude for the 1996 to 2001 period relative to the
1988 to 1995 period.
Such a test validates the second hypothesis that, given a negative relationship
between price cap regulation and debt, the size of such a relationship will be larger in an
institutional era characterized by a competitive entity mindset relative to an institutional era
characterized by a regulated public utility mindset.
Discussion
25
Contribution: The article is a contribution across several streams of literature in that a
theoretical framework of how institutions, via their underlying logics, have shaped the
heterogeneous action of firms in responding to regulatory changes and impacted on a key
dimension of strategy, the leverage choice, has been developed. Structures of financing, such
as the leverage ratio, significantly impacts firms’ strategic behavior (Hall, 2002; Hao and
Jaffe, 1993; King and Levine, 1993; Mayer, 1990; O’Brien, 2003). In many industries, the
types of regulation firms experience significantly impact their leverage decision (Dasgupta
and Nanda, 1993; Spiegel, 1996). Such impacts may further vary across unique institutional
time periods, because historical contingencies have altered (Thornton and Ocasio, 2008).
The data analysis results support the two hypotheses. Further discussions of the
results are based on applying institutional logics ideas to the context as well as extending
them. Institutional logics incorporate assumptions about what might be meaningful firm
actions (Glynn and Lounsbury, 2005; Thornton, et al 2012). While these are embedded in
individuals’ perceptions, influencing actions (Pahnke, et al 2015) and responses to
environmental stimuli (Almandoz, 2014), such institutional logics fit together (Glynn, 2000)
for firms to develop norms (Thornton, et al 2012) influencing strategy choices (Glynn, 2008).
Within each of the two epochs assessed, the extant regulated public utility and
competitive entity institutional logics have had central roles in influencing firm behavior.
The cost-reduction reasons as to why a change from rate of return regulation to price cap
regulation would be associated with lower leverage, and vice-versa, have been articulated.
There have been standard arguments in the literature on firm regulation on this issue, but
evidence has not been forthcoming so far.
26
Additionally, though, even within a regulated public utility environment, there could
be intra-organizational consequences arising from the particular regulatory transition
evaluated. A characteristic of such transitions are enhancements of autonomy and flexibility,
as regulatory micro-management is removed and firms are free to meet goals and targets
(Majumdar, 2013). This permits firms to put in relevant capability packages to achieve goals.
Firms have the freedom to implement necessary strategies. The impacts of such autonomy
and flexibility would result in superior performance. In such circumstances, managers and
shareholders would seek to enhance their ownership investments in increasingly-profitable
ventures and, to do so, reduce the proportion of debt in the firm’s financial structure.
Institutional Influences: The additional context-specific for cost-cutting, motivated by
institutional logics changes are discussed next. The TA 1996 impacted competitive entry.
After 1996, a number of possible competitors entered the territories of the ILECs. These
competitive local exchange carriers (CLECs) were defined as incumbents' rivals that entered
local phone markets after divestiture. The TA 1996 and the 1996 FCC Report and Order led
such firms to enter the local telecommunications market in three ways. First, CLECs could
purchase a local service at wholesale rates and re-sell it to the end users. These CLECs were
classified as resellers. Second, they could lease various unbundled elements of ILECs’
network through co-location. These CLECs were classified as service providers. Third, they
could set up their own networks as facilities-based competitors.
The TA 1996 mandated that parts of the ILECs’ infrastructure, including the last
mile of copper wires that ran to homes and businesses, be accessible to competitive providers
of services. These parts were called the unbundled network elements (UNE), and the ILECs
27
were to open their network in exchange for a chance to offer long distance services. The
legislation required that the firms classified as Regional Bell Operating Companies (RBOCs)
meet requirements, under Section 271 of the TA 1996, before they could enter inter-state long
distance markets. After TA 1996, competition in the sector dramatically increased.
A CLEC could even lease an entire network at unbundled rates, this being known as
the UNE platform, or UNE-P. By exploiting UNE-P, entrants could purchase downstream
services for a fraction of the incumbents’ retail prices. Details of how CLECs could lease
elements of an incumbents’ infrastructure, piece by piece, on very favorable terms would be
important as these factors will have influenced ILECs’ behavior. These rules disaggregated
ILECs’ upstream capital elements, and allowed entrants to make or buy each piece of their
network infrastructures as they saw fit with the aid of these elements.
The UNE rates were derived from total element long-run incremental costs
(TELRIC). The TELRIC method, which the incumbents had protested against, was upheld
by the United States Supreme Court in 2002. The approach estimated efficient long-run unit
costs for each network element, assuming that the latest technologies were in place,
effectively ignoring the fact that ILECs possessed legacy networks, built up expensively over
many years, which might have had different cost structures.
Introducing UNE and TELRIC into the downstream market was intended to
encourage entry and induce ILECs to upgrade networks. Yet, the costing and pricing rules
would easily motivate cost reductions in various areas, such as interest costs by the reduction
of debt levels, so as to generate financial savings and resources if the CLEC entrants were to
28
gain access to ILECs’ networks at a fraction of the cost incurred by the ILECs. These cost-
cutting necessities would motivate lower leverage levels after TA 1996 went into force.
Impact on Emergent Strategic Logic: In a strategic sense, the extent of leverage in a
firm would be dependent on what the future competitive and strategic impact of such
leverage might be. The impact of leverage on aggressiveness in strategic behavior is based on
the long purse argument (Telser, 1966). Per this argument, having ready access to capital
would allow a firm to sustain losses until it succeeded in eliminating competition. A firm with
low leverage levels could raise more debt, as it would have slack capacity to undertake grater
leverage. This contingency would enable it to behave aggressively, vis-à-vis its rivals, leading
to eventual competitive success.
Conversely, a firm with higher leverage could be vulnerable to competitors’ aggressive
behavior, and increased debt held by firms would soften aggressive strategic behavior
(Anderson and Makhija, 1999; David, et al 2008). The presence of high leverage in incumbent
firms would provide opportunities for rivals to weaken them financially by aggressive
strategies. Highly-leveraged firms would not respond similarly, since the resulting financial
outcomes could be quite negative. The converse would be true.
It was apparent that after TA 1996 the competitive environment had altered ,
exposing the ILECs to substantial threats (Economides, 1999; Koski and Majumdar, 2002).
Given a negative relationship between price cap regulation and leverage, motivated in part
by desires to augment endogenous capabilities in a price cap environment, post-TA 1996
competitive entity institutional logics would enhance the intensity of this relationship. Firms
would not only be motivated to cut costs, and use the savings to build capabilities, but also
29
send clear signals to competitors that they had the financial muscle, engendered by low
leverage levels, to fight strenuous and intense competitive battles and engage in aggressive
strategies to protect their markets and retaliate to competitors’ actions.
Conclusion
Leverage decisions being strategic choices of firms, regulatory considerations have a
major impact on the leverage levels of firms, and institutional changes influence strategic
decisions. In this paper, the question assessed has been whether, given dramatically-changing
institutional environments, with changes in institutional logics leading to interpretation
differences in regulatory norms, firms decisions on leverage levels have been affected by the
regulatory changes occurring in each era when differing institutional logics prevailed.
Specifically, the impact of the transition from a rate of regulation to an incentive
regulation scheme in the United States telecommunications industry on firm leverage levels
has been examined for the years 1998 to 2001, and within that period for two separate unique
eras in which competitive conditions changed, with the institutional environments differing
before and after passage of the Telecommunications Act of 1996 (TA 1996). Between the
years 1988 to 1995, a ‘regulated public utility’ logic prevailed, while a ‘competitive entity’ logic
prevailed for the years 1996 to 2001. Overall, the introduction of price cap regulation has led
to a decline in leverage.
Firms regulated by the price cap method have had 43 percent lower leverage than
firms regulated by the rate of return method. When data for two separate periods have been
analyzed, the diffusion of price cap regulation in the 1996 to 2001 period has had a larger
negative impact, on leverage, than the diffusion of price cap regulation between 1988 and
30
1995. Firms regulated by the price cap method have had 23 percent lower leverage than
others, in the 1988 to 1995 period, while firms regulated by the price cap method have had 78
percent lower leverage than others in the 1996 to 2001 period.
The results support the idea of the institutional logics literature that as institutional
logics alter, firms strategic pre-dispositions change, and hence changing regulations also
impact strategic decisions differently over time. The overall decline in leverage after price
caps introduction might be motivated by efficiency considerations, but after TA 1996 firms
would not only be motivated to cut costs, and build capabilities, but also send signals to
competitors that low leverage levels would provide the financial muscle and depth to fight
intense competitive battles and engage in aggressive market-protection strategies.
31
References
Abbring, J. H. and Heckman, J. J. (2008): Dynamic Policy Analysis, in L. Matyas and P.
Sevestre, Eds., Econometrics of Panel Data, Dordrecht: Kluwer, Third Edition.
Adrian, T. and H. S. Shin (2010): Liquidity and Leverage, Journal of Financial
Intermediation, 19, 418-437
Ai, C. and Sappington, D. (2002): The impact of state incentive regulation on the U.S. telecommunications industry. Journal of Regulatory Economics, 22, 2, 133-159.
Almandoz, J. (2014): Founding Teams as Carriers of Competing Logics: When Institutional Forces Predict Banks’ Risk Exposure, Administrative Science Quarterly, 59, 442-473.
Anderson, C. W. and Makhija, A. K. (1999): Deregulation, disintermediation, and agency costs of debt: Evidence from Japan. Journal of Financial Economics, 51, 309-339.
Angrist, J. (1998): Using Social Security Data on Military Applications to estimate the effect of Voluntary Military Service on Earnings, Econometrica, 66, 249-288
Angrist, J. and Krueger, A. (2001): Instrumental variables and the search for identification: from supply and demand to natural experiments. Journal of Economic Perspectives, 15,
4, 69–85.
Armstrong, M. (2002): The Theory of Access Pricing and Interconnection, in Handbook of
Telecommunications Economics, M. E. Cave, S. K. Majumdar and I. Vogelsang, Eds.,
Amsterdam: North Holland.
Averch, H. and Johnson, L. (1962): Behaviour of the firm under regulatory constraint, American Economic Review, 52, 1053-1069.
Bailey, E. and Coleman, R. (1971): The effect of lagged regulation in an Averch-Johnson model, Bell Journal of Economics, 2, 278-292.
Balakrishnan, S. and Fox, I. (1993): Asset Specificity, Firm Heterogeneity and Capital
Structure. Strategic Management Journal, 14: 3-16.
Barclay, M. J., L. Marx and C. Smith (2003): The Joint Determination of Leverage and Maturity, Journal of Corporate Finance, 9, 149–167.
Barley, S. R. and Tolbert, P. S. (1997): Institutionalization and Structuration: Studying the Links between Action and Institution, Organization Studies, 18, 1, 93–117.
32
Barton, S. and Gordon, P. (1987): Corporate Strategy: Useful Perspective for the Study of Capital Structure? Academy of Management Review, 12, 67-75.
Bascle, G. (2008): Controlling for endogeneity with instrumental variables in strategic management research. Strategic Organization, 6, 3, 285-327
Baumol, W. and Klevorick, A. K. (1970): Input Choices and Rate of Return Regulation: An Overview of the Discussion, Bell Journal of Economics and Management Science, 1:2
169-190.
Bencivenga, V. R. and B. D. Smith (1991): Financial Intermediation and Endogenous Growth, Review of Economic Studies, 58, 195-209.
Bernanke, B. S. and M. Gertler (1995): Inside the black box: The credit channel of monetary
policy transmission, Journal of Economic Perspectives, 9, 4, 27–48.
Besley, S. and E. Bolten (1990): What Factors Are Important in Establishing Mandated Returns? Public Utilities Fortnightly, 125, 26–30.
Bettis, R. A. (1983): Modern Finance Theory, Corporate Strategy and Public Policy: Three Conundrums. Academy of Management Review, 8, 406-415.
Biglaiser, G. and Riordan, M. (2001): Dynamics of price regulation, RAND Journal of
Economics, 31, 4, 744–767.
Bortolotti, B., C. Cambini, L. Rondi and Y. Spiegel (2011): Capital Structure and Regulation: Do Ownership and Regulatory Independence Matter? Journal of
Economics and Management Strategy, 20, 2, 517-564.
Bowen, R. M., L. A. Daley and C. Huber (1982): Evidence on the Existence and
Determinants of Inter-Industry Differences in Leverage, Financial Management, 1, 4,
10–20.
Bradley, M., Jarrell, G. A. and Kim, E. H. (1984): On the Existence of an Optimal Capital Structure: Theory and Evidence, Journal of Finance, 39, 3, 857-878.
Bromiley, P. (1990): On the Use of Financial Theory in Strategic Management, in P. Shrivastava and R. Lamb, Eds. Advances in Strategic Management, 6, 71-98.
Brown, J. R., S. M. Fazzari and B. C. Petersen (2009): Financing innovation and growth:
Cash flow, external equity, and the 1990s R&D boom. Journal of Finance, LXIV, 1,
151-185.
33
Cambini, C. and L. Rondi (2012): Capital structure and investment in regulated network utilities: Evidence from EU Telecoms, Industrial and Corporate Change, 21, 1, 31-71.
Campello, M. (2003): Capital Structure and Product Market Interactions: Evidence from Business Cycles. Journal of Financial Economics, 68, 353-378.
Cantillo, M. and Wright, J. (2000): How Do Firms Choose Their Lenders? An Empirical Investigation, Review of Financial Studies, 13, 155-189.
Cantor, R. (1990): Effects of Leverage on Corporate Investment and Hiring Decisions, Federal Reserve Bank of New York Quarterly Review, 15, 31-41.
Cave, M. E., Majumdar, S. K. and Vogelsang, I. (2002): Structure, Regulation and
Competition in the Telecommunications Industry, in M. E. Cave, S. K. Majumdar and
I. Vogelsang, Eds. Handbook of Telecommunications Economics, Amsterdam: North-
Holland, 1-40.
Chevalier, J. A. (1995): Capital structure and product-market competition: Empirical evidence from the supermarket industry. American Economic Review, 85, 415-435.
Chirinko, R. and J. A. Elston (2006): Finance, Control and Profitability: The Influence of German Banks. Journal of Economic Behaviour and Organisation, 59, 1, 69-88.
Christensen, H. and C. Montgomery (1981): Corporate Economic Performance:
Diversification Strategy versus Market Structure, Strategic Management Journal, 2,
327-343
Corbett, J. and Jenkinson, T. (1997): How is investment financed? A study of Germany, Japan, the United Kingdom and the United States, Manchester School, Supplement,
69-93.
Cornett, M. M. and Tehranian, H. (1992): Changes in Corporate Performance Associated with Bank Acquisitions, Journal of Financial Economics, 31, 211-234
Dasgupta, S. and Nanda, V. (1993): Bargaining and Brinkmanship: Capital Structure Choice
by Regulated Firms, International Journal of Industrial Organization, 11, 475-497
David, P., O’Brien, J. and Yoshikawa, T. (2008): The implications of debt heterogeneity for R&D investment and firm performance, Academy of Management Journal, 51: 165-
181.
de Figueiredo, J. M. (2002): Lobbying and Information in Politics, Business and Politics, 4, 2,
125-129.
34
Dehejia, R. and Wahba, S. (1999): Causal effects in nonexperimental studies: reevaluating the evaluation of training programs. Journal of the American Statistical Association,
94, 1053–1062.
Denis D. J. and Mihov, V. T. (2003): The Choice among Bank Debt, Non-bank Private Debt, and Public Debt: Evidence from New Corporate Borrowings, Journal of Financial
Economics, 70, 3-28
Earle, T. (1997): How Chiefs Come to Power. Stanford: Stanford University Press.
Economides, N. (1999): The Telecommunications Act of 1996 and its Impact, Japan and the
World Economy, 11, 4, 455-483
Evans, P. (1995): Embedded Autonomy: States and Industrial Transformation, Princeton:
Princeton University Press.
Fama, E. (1986): Term premiums and default premiums in money markets, Journal of
Financial Economics, 17, 175-196.
Fernandes, L. (2006): India’s New Middle Classes: Democratic Politics in an Era of Economic
Reform, Minneapolis: University of Minnesota Press
Frank, M. Z. and V. K. Goyal (2009): Capital structure decisions: Which factors are reliably
important? Financial Management, 38, 1-37
Friedman, M. and A. J. Schwartz (1963): A Monetary History of the United States, 1867-1960.
Princeton, N.J.: Princeton University Press.
Fukuyama, F. (2011): The Origins of Political Order, New York: Farrar, Straus and Giroux
Gasmi, F., Kennett, D. M., Laffont, J-J and Sharkey, W. W. (2002): Cost Proxy Models and
Telecommunications Policy, Cambridge, MA: MIT Press.
Glynn, M. A. (2000): When cymbals become symbols: Conflict over organizational identity
within a symphony orchestra, Organization Science, 11, 3, 285–298.
Glynn, M. A. (2008): Beyond Constraints: How Institutions Enable Identities. in R. Greenwood, C. Oliver, K. Sahlin-Andersson, and R. Suddaby, Eds., Handbook of
Organizational Institutionalism, Thousand Oaks, CA: Sage, 413-430
35
Glynn, M. A. and M. Lounsbury (2005): From the Critics’ Corner: Logic Blending, Discursive Change and Authenticity in a Cultural Production System, Journal of Management
Studies, 42, 5, 1031–1055.
Gomes, J. F. (2001): Financing investment, American Economic Review, 91, 1263-1285
Greenstein, S., McMaster, S. and Spiller, P. (1995): The Effect of Incentive Regulation on
Infrastructure Modernisation: Local Exchange Companies' Deployment of Digital
Technology, Journal of Economics and Management Strategy, 4, 187-236
Greenwood, R., C. R. Hinings and D. Whetten (2014): Rethinking Institutions and Organizations, Journal of Management Studies, 51, 7, 1206-1220
Greif, A. (1998): Historical and comparative institutional analysis, American Economic
Review, 88, 2, 72-74.
Grinblatt, M. and Titman S. (2001): Financial markets and corporate strategy, New York:
McGraw-Hill.
Grundy, A. (1996): Corporate strategy and financial decisions, London: Kogan Page.
Hagerman. L. and B. T. Ratchford (1978): Some Determinants of Allowed Rates of Return on Equity to Electric Utilities. Bell Journal of Economics, 9, 46-55.
Hall, B. H. (2002): The Financing of Research and Development, Oxford Review of Economic
Policy, 18, 1, 35-51.
Hamilton, B. H. and Nickerson, J. A. (2003): Correcting for Endogeneity in Strategic Management Research. Strategic Organization, 1, 1, 51-78
Hao, K. Y. and A. B. Jaffe (1993): Effect of Liquidity on Firms’ R&D Spending, Economics
of Innovation and New Technology, 2, 275-282.
Harris, M. and A. Raviv (1991): The theory of capital structure, Journal of Finance, 46, 297-
356.
Hazlett, T. (2000): Economic and Political Consequences of the 1996 Telecommunications Act, Regulation, 23, 3, 36-45
Heckman, J. (1976): The common structure of statistical models of truncation, sample
selection, and limited dependent variables and a simple estimator for such models. Annals of Economic and Social Measurement, 5, 475–492.
36
Heckman, J. J. (1979): Sample selection bias as a specification error. Econometrica, 47, 153–
161.
Heckman, J. J. (2005): The scientific model of causality, Sociological Methodology, 35, 1-97
Heckman, J. J., H. Ichimura and P. Todd (1998): Matching as an Econometric Evaluation Exercise, Review of Economic Studies, 65, 261-294.
Heckman, J. J. and E. Vytlacil (2005): Structural Equations, Treatment Effects, and Econometric Policy Evaluation, Econometrica, 73, 669-738
Hirano, K. G., G. Imbens and G. Ridder (2003): Efficient Estimation of Average Treatment Effects using the estimated Propensity Score, Econometrica, 71, 1161-1189
Houston, J. and James, C. (1996): Bank Information Monopolies and the Mix of Private and Public Debt Claims, Journal of Finance, 51, 1863-1889.
Jensen, M. and W. Meckling (1976): Theory of the firm: managerial behaviour, agency costs
and ownership structure. Journal of Financial Economics. 3. 305-360.
Joskow, P. (1974): Inflation and environmental concern: Structural change in the process of public utility price regulation, Journal of Law and Economics, 17, 291-327.
Kashyap, A. K., Stein, J. C. and Wilcox, D. W. (1993): Monetary Policy and Credit Conditions: Evidence from the Composition of External Finance. American Economic
Review, 83, 1, 78–98
Kayhan, A. and S. Titman (2007): Firms' histories and their capital structures, Journal of
Financial Economics, 83, 1-32.
Khanna, N. and Tice, S. (2000): Strategic Response of Incumbents to New Entry: The Effect of Ownership Structure, Capital Structure and Focus, Review of Financial Studies, 13,
749-779.
King, R. G. and R. Levine (1993): Finance and Growth: Schumpeter Might be Right. Quarterly Journal of Economics, 108, 3, 717-737.
Klein, R., R. Phillips, and W. Shiu (2002): The Capital Structure of Firms Subject to Price Regulation: Evidence from the Insurance Industry, Journal of Financial Services
Research, 22, 1–2, 79–100.
37
Kochhar, R. (1996): Explaining firm capital structure: the role of agency theory vs. transaction cost economics. Strategic Management Journal, 17, 9, 713–728.
Kochhar, R. and Hitt, M. (1998): Linking corporate strategy to capital structure: diversification strategy, type and source of financing, Strategic Management Journal,
19, 601-610
Korajczyk, R.A. and A. Levy (2003): Capital structure choice: Macroeconomic conditions
and financial constraints,” Journal of Financial Economics 68, 75-109.
Koski, H. A. and S. K. Majumdar (2002): Paragons of Virtue? Competitor Entry and the Strategies of Incumbents in the US Local Telecommunications Industry, Information
Economics and Policy, 14, 4, 453-480
Kovenock, D. and G. M. Phillips (1997): Capital structure and product market behavior: An examination of plant exit and investment decisions. Review of Financial Studies, 10,
767-803.
Krishnaswami, S., Spindt, P. A. and Subramaniam, V. (1999): Information Asymmetry,
Monitoring and the Placement Structure of Corporate Debt, Journal of Financial
Economics, 51, 407-434.
Laffont, J-J. and Tirole, J. (1993): A Theory of Incentives in Procurement and Regulation.
Cambridge, MA: MIT Press.
Lambrecht, B. (2001): The Impact of Debt Financing on Entry and Exit in a Duopoly, Review of Financial Studies, 14, 765-804.
Lang, L. H. P., Ofek, E. and R. M. Stulz (1996): Leverage, Investment, and Firm Growth, Journal of Financial Economics, 40, 3-29.
La Porta, R., F. Lopez-de-Silanes, A. Shleifer and R. W. Vishny (1998): Law and Finance. Journal of Political Economy, 106, 6, 1113-1155.
Lewellen, W. G. and Mauer, D. C. (1993): Public Utility Valuation and Risk under Incentive
Regulation. Journal of Regulatory Economics, 5, 263-287.
Loomis, D. G. and C. M. Swann (2005): Inter-modal Competition in Local Exchange Markets. Information Economics and Policy, 17, 97-113.
MacKay, P. and Phillips, G. M. (2005): How Does Industry Affect Firm Financial Structure? Review of Financial Studies, 18, 4, 1433-1466
38
Majumdar, S. K. (1995): X-efficiency in Emerging Competitive Markets: The Case of U.S. Telecommunications, Journal of Economic Behavior and Organization, 26, 1, 129-144
Majumdar, S. K. (1997): Incentive Regulation and Productive Efficiency in the U.S. Telecommunications Industry, Journal of Business, 70, 4, 547-576 (1997)
Majumdar, S. K. (2011a): Does Incentive Compatible Mechanism Design Induce Competitive Entry? Journal of Competition Law and Economics, 7, 2, 427-453
Majumdar, S. K. (2011b): Retentions, Relationships and Innovations: The Financing of R&D in India, Economics of Innovation and New Technology, 20, 3, 233-257
Majumdar, S. K. (2013): Appropriate Mechanism Design, Regulations and Wages, Industrial
and Corporate Change, 22, 5, 1373-1408
Majumdar, S. K., R. Moussawi and U. Yaylacicegi, (2010): Mergers, Jobs and Wages in the United States Telecommunications Industry, Human Relations, 63, 10, October, 1611-
1636
Majumdar, S. K., R. Moussawi and U. Yaylacicegi, (2014): Do Incumbents’ Mergers Influence Entrepreneurial Entry? An Evaluation, Entrepreneurship Theory and Practice, 38, 3,
601-633
Mayer, C. (1990): Financial Systems, Corporate Finance and Economic Development, in R.
G. Hubbard, Ed. Asymmetric Information, Corporate Finance and Investment, Chicago:
University of Chicago Press.
Meyer, R. A. (1976): Capital Structure and the Behavior of the Regulated Firm under Uncertainty. Southern Economic Journal, 42, 600-609.
Morellec, E. and A. Zhdanov (2005): The dynamics of mergers and acquisitions, Journal of
Financial Economics, 77, 649–672
Myers, S. C. (1977): Determinants of Corporate Borrowing, Journal of Financial Economics,
5, 147-175.
Myers, S. C. (2003): Financing of corporations, in G. Constantinides, M. Harris, and R. Stulz, Eds., Handbook of the Economics of Finance: Corporate Finance Vol 1A, Amsterdam:
North Holland, 215-253
Myers, S. and N. Majluf (1984): Corporate Financing and Investment Decisions when Firms Have Information Investors Do Not Have, Journal of Financial Economics, 131, 187-
221.
39
Modigliani, F. and Miller, M. (1958): The Cost of Capital, Corporation Finance and the Theory of Investment. American Economic Review, 48, 3, 261–297
Nelson, R. R. (2007): Universal Darwinism and Evolutionary Social Science, Biology and
Philosophy, 22, 73-94
Nelson R. R. and S. G. Winter (1982): An Evolutionary Theory of Economic Change.
Cambridge, MA: Harvard University Press:
North, D. C. (1990): Institutions, Institutional Change and Economic Performance, New York:
Cambridge University Press.
North, D. C. (2005): Understanding the Process of Economic Change, Princeton: Princeton
University Press
North, D. C. and R. P. Thomas (1973): The Rise of the Western World, New York: Cambridge
University Press.
O'Brien, J. (2003): The capital structure implication of pursuing a strategy of innovation. Strategic Management Journal, 24: 415-431.
Ocasio, W. and J. Joseph (2005): Cultural adaptation and institutional change: The evolution of vocabularies of corporate governance, 1972–2002, Poetics, 33, 163-178
Oviatt, B. M. (1988): Agency and Transaction Cost Perspectives on the Manager–Shareholder Relationship: Incentives for Congruent Interests. Academy of
Management Review, 13, 214–225.
Ovtchinnikov, A. (2010): Capital Structure Decisions: Evidence from Deregulated Industries,
Journal of Financial Economics, 95, 2, 249-274.
Pahnke, E. C., Katila, R. and Eisenhardt, K. M. (2015): Who Takes You to the Dance? How Funding Partners Influence Innovative Activity in Young Firms, Administrative
Science Quarterly, forthcoming
Parsons, C. and Titman, S. (2008): Capital Structure and Corporate Strategy, Handbook of
Corporate Finance: Empirical Corporate Finance, Volume 2, Ed. B. Espen Eckbo,
Amsterdam: North-Holland, 203-234
Phillips, G. M. (1995): Increased debt and industry product markets: An empirical analysis. Journal of Financial Economics, 37, 189-238.
40
Rajan, R. G. and L. Zingales (1995): What Do We Know about Capital Structure? Some Evidence from International Data, Journal of Finance, 50, 5, 1421–1460.
Rao, H., P. Monin and R. Durand (2003): Institutional Change in Toque Ville: Nouvelle Cuisine as an Identity Movement in French Gastronomy, American Journal of
Sociology, 108, 4, 795–843
Rao, R. and Moyer, C. R. (1994): Regulatory Climate and Electrical Utility Capital Structure
Decisions, Financial Review, 29, 97-124
Ross, S. (1977): The determination of financial structure: the incentive signaling approach, Bell Journal of Economics, 8, 1-32
Rubin, D. (1974): Estimating Causal Effects of Treatments in Randomized and Non-
randomized Studies, Journal of Educational Psychology, 66, 688-701
Sappington, D. (2002): Price Regulation, in Handbook of Telecommunications Economics, M.
E. Cave, S. K. Majumdar and I. Vogelsang, Eds., Amsterdam: North Holland
Sappington, D. and Weisman, D. (1996): Designing incentive regulation for the
telecommunications industry, Cambridge, MA: MIT Press.
Scharfstein, D. (1988): Product-market Competition and Managerial Slack. RAND Journal
of Economics, 19, 147-155.
Schmidt, K. (1997): Managerial Incentives and Product Market Competition, Review of
Economic Studies, 64, 191-213.
Sharkey, W. W. (2002): Representation of Technology and Production, in Handbook of
Telecommunications Economics, M. E. Cave, S. K. Majumdar and I. Vogelsang, Eds.,
Amsterdam: North Holland.
Sherman, R. (1977): Ex-Ante Rates of Return for Regulated Utilities, Land Economics, 53,
172-184
Short, J. L and M. W. Toffel (2010): Making Self-regulation more than Merely Symbolic: The Critical Role of the Legal Environment, Administrative Science Quarterly, 55, 361-396
Simerly, R. L. and Li, M. (2000): Environmental dynamism, capital structure and performance: a theoretical integration and an empirical test. Strategic Management
Journal, 21, 1, 31–49
41
Spiegel, Y. (1996): The Choice of Technology and Capital Structure under Rate Regulation, International Journal of Industrial Organization, 15, 191–216.
Spiegel, Y. and Spulber, D. F. (1994): The Capital Structure of a Regulated Firm, Rand
Journal of Economics, 25, 424-440
Spiller, P. T. (2005): Institutional Changes in Emerging markets: Implications for the Telecommunications Sector, in Handbook of Telecommunications Economics, Volume
2, S. K. Majumdar, I. Vogelsang and M. E. Cave, Eds., Amsterdam: North Holland
Spulber, D. (2002): Competition Policy in Telecommunications, in Handbook of
Telecommunications Economics, M. E. Cave, S. K. Majumdar and I. Vogelsang, Eds.,
Amsterdam: North Holland
Taggart, R. A. (1981): Rate of Return Regulation and Utility Capital Structure Decision, Journal of Finance, 36, 2, 383-393.
Taggart, R. A. (1985): Effects of Regulation on Utility Financing: Theory and Evidence, Journal of Industrial Economics, 33, 257-276.
Taylor, W., Zarkadas, C. and Zona, J. D. (1992): Incentive regulation and the diffusion of
new technology in telecommunications, Mimeo, National Economic Research
Associates.
Teece, D. J. (2007): Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28, 1319-1350.
Teece, D. J., G. Pisano and A. Shuen (1997): Dynamic capabilities and strategic management. Strategic Management Journal, 18, 509-533.
Telser, L. G. (1966): Cutthroat competition and the long purse. Journal of Law and
Economics 9, 259–277.
Thornton, P. (2004): Markets from Culture: Institutional Logics and Organizational Decisions
in Higher Education Publishing. Stanford, CA: Stanford University Press
Thornton, P. and W. Ocasio (2008): Institutional Logics, in R. Greenwood, C. Oliver, K. Sahlin-Andersson, and R. Suddaby, Eds., Handbook of Organizational
Institutionalism, Thousand Oaks, CA: Sage, 99-129.
Thornton, P., W. Ocasio and M. Lounsbury (2012): The Institutional Logics Perspective: A
New Approach to Culture, Structure and Process. Oxford: Oxford University Press.
42
Titman, S. (1984): The effect of capital structure on a firm's liquidation decision, Journal of
Financial Economics, 13, 137-151.
Titman, S. and Wessels, R. (1988): The Determinants of Capital Structure Choice, Journal of
Finance, 43, 1-19.
Vincente-Lorente, J. D. (2001): Specificity and opacity as resource-based determinants of
capital structure: evidence for Spanish manufacturing firms. Strategic Management
Journal, 22, 2, 157–177
Weisman, D. (1993): Superior regulatory regimes in theory and practice, Journal of
Regulatory Economics, 5, 355-366.
Weisman, D and J. Pfeifenberger (2003): Efficiency as a Discovery Process: Why Enhanced Incentives Outperform Regulatory Mandates, Electricity Journal, 16, 1, 52-68.
White, H. (2011): Time Series Estimation of the Effects of Natural Experiments, Journal of
Econometrics, 135, 527-566
Zingales, L. (1998): Survival of the fittest or the fattest? Exit and financing in the trucking industry. Journal of Finance, 53, 905-938.
43
Table 1: Mean Values for the Debt and Regulation Variables
Overall Period:
1988 to 2001
Period Prior to
TA 1996:
1988 to 1995
Period After TA
1996:
1996 to 2001
Debt Equity 0.231 0.244 0.213 Regulation 0.463 0.158 0.870
44
Table 2: Treatments Effects Estimation Results
Outcome Variable: Debt Equity
Model (A) Model (B) Model (C)
Overall Period:
1988 to 2001
Period Prior to TA
1996:
1988 to 1995
Period After TA
1996:
1996 to 2001
Constant 0.421***
(0.075)
0.256***
(0.028)
0.508***
(0.145)
Regulation -0.100***
(0.012)
-0.057**
(0.020)
-0.167***
(0.019)
Growth 0.018
(0.040)
-0.001
(0.030)
0.053
(0.141)
Size -0.009***
(0.003)
-0.006***
(0.002)
-0.022***
(0.006)
Performance -0.398***
(0.101)
-0.195**
(0.101)
-0.368**
(0.198)
Assets 0.158***
(0.047)
0.062
(0.054)
0.244***
(0.080)
Relative Competition 0.011***
(0.002)
0.007**
(0.002)
0.032***
(0.007)
Interest Rate -0.003
(0.004)
0.012***
(0.004)
0.011
(0.011)
Wald χ2 142.50 49.27 119.35
Selection Equations for Regulation Treatment Variable
Constant 10.519***
(2.392)
24.069*
(17.613)
5.469**
(3.040)
Size -0.013
(0.065)
-0.130
(0.131)
-0.119
(0.105)
Access 3.753*
(2.237)
5.095
(3.740)
5.107
(5.061)
Urban -2.926***
(0.734)
-3.412**
(1.465)
-3.680**
(1.268)
Business 3.028**
(1.098)
0.875
(2.629)
3.833**
(1.871)
Fiber 0.138***
(0.034)
0.206**
(0.102)
0.060*
(0.0390
Advertising 11.151**
(6.037)
22.083**
(12.784)
3.414
(8.236)
Market Share -1.337***
(0.234)
-1.161**
(0.571)
-1.222***
(0.293)
Cash Flow 6.406***
(1.024)
7.598***
(2.094)
5.881***
(1.874) Growth 1.192 8.366** 0.178
45
(1.258) (3.810) (2.028)
Efficiency -39.406***
(5.231)
-82.271***
(15.119)
-31.820***
(5.941)
Industry Performance -26.796***
(6.067)
-53.760
(47.504)
-4.653
(6.967)
Atanh ρ 1.096 0.665 1.604
Log σ -2.479 -2.893 -2.264
Ρ 0.799 0.581 0.922
Σ 0.084 0.055 0.104 Λ 0.067 0.032 0.096
LR Test χ2 20.42 1.64 17.80 N 519 285 234
*** p < 0.01, ** p < 0.05, * p < 0.10; standard errors in parentheses.
Recommended