AN ABSTRACT OF THE THESIS OF
Kiseol Nam for the degree of Doctor of Philosophy in Economics presented
on June 21, 1996. Title: Import Competition and Strategic Group Behav­
ior.
Redacted for Privacy
Abstract approved-
Victor J. Tremblay
This study provides the model that first synthesizes strategic group
theory with the New Empirical Industrial Organization (NEIO) approach in
the international trade analysis, and uses the annual group data (1953 ­
1988) from the U.S. brewing industry with two strategic groups (national
producers and regional producers) in the presence of growing import
competition. The main goal of study is to examine the impact of import
and strategic group competition on strategic group behavior and market
power in the U.S. brewing industry. Using the conjectural variation
technique under the profit maximization assumption, the model estimates
directly conjectural elasticities and the Lerner indexes incorporating
firm behavior in competing with rivals from imports, and inside and
outside each strategic group.
conclusions.
The thesis shows the main following
Inside the group, national and regional brewers behave
like Bertrand-type competitors and regional firms are more competitive
than national firms.
In the cross-group rivalry, national firms expect
a cooperative response from regional brewers and regional firms expect
an aggressive response from national producers. Holding possibly a
sufficient niche market, import competition does not affect the behavior
and market power of national and regional producers. As for over-all
behavior, neither national nor regional firms behave like price-takers.
National firms exert a significantly higher degree of market power than
do regional firms, the market power of which appears to be harmed by
national brewers. However, an average brewer exercises no market power
in the industry as a whole.
IMPORT COMPETITION AND STRATEGIC GROUP BEHAVIOR
By
Kiseol
Nam
A THESIS
Submitted to
Oregon State University
in partial fulfillment of
the requirements for the
Degree of
Doctor of Philosophy
Completed June 21, 1996
Commencement June 1997
Doctor of Philosophy thesis Kiseol Nam presented June 21, 1996
APPROVED
Redacted for Privacy
Major Prof
sor, represen
1g Economics
Redacted for Privacy
Chair of De
rtment of E tiTmics
Redacted for Privacy
Dean of Gra
ate School
I understand that my thesis will become part of the permanent collection
of Oregon State University libraries. My signiture below authorizes
release of my thesis to any reader upon request.
Redacted for Privacy
Kiseol Nam, Author
TABLE OF CONTENTS
Page
CHAPTER I: INTRODUCTION
I.1
1.2
1.3
1
The Purpose of Study
The Significance of Study
The Organization of Thesis
1
4
5
CHAPTER II: MARKET STRUCTURE-INTERNATIONAL TRADE RELATIONSHIP
AND STRATEGIC GROUPS
6
II.1
Market Structure, Performance and International Trade
11.1.1. Theoretical Studies
11.1.2. Empirical Studies
6
6
10
11.2
Strategic Groups
11.2.1. The Concept of Strategic Groups
11.2.2. Empirical Studies of Strategic Groups
12
12
13
CHAPTER III: THEORETICAL CONSIDERATIONS
III.1 The
111.1.1.
111.1.2.
111.1.3.
111.1.4.
17
Theory of Oligopolistic Competition
Oligopolistic Pricing of the Firm
The Conjectural Variation and Market Behavior
Conjectural Elasticities and Market Behavior
The Derivation of Market Power
19
19
21
22
22
111.2
Strategic Groups and Competition
111.2.1. Competition in a Strategic Group Setting
111.2.2. Cross-Group Competition in the U.S. Brewing Industry
111.2.3. Import Competition and Strategic Groups
111.3
The Theoretical Model
111.4 Theoretical Interpretations of Strategic Group Behavior
111.4.1. The Own-Conjectural Elasticity
111.4.2. The Cross-Conjectural Elasticity
111.4.3. The Index of Market Power
CHAPTER IV: THE EMPIRICAL MODEL
IV.1
New Empirical Industrial Organization (NEIO)
IV.2 The Empirical Model
1V.2.1. The Demand Side
IV.2.2. The Supply Side
IV.3
Expected Empirical Results
CHAPTER V: EMPIRICAL RESULTS
V.1
Review of the Empirical Model
V.2 Econometric Concerns and Tests
V.2.1. Contemporaneous Correlation Test
V.2.2. Endogeniety Test of Imports and Advertising
.
23
23
25
26
27
32
32
33
36
37
37
40
41
42
46
50
50
52
52
53
TABLE OF CONTENTS (Continued)
Page
V.2.3. Autocorrelation Tests
V.3 Estimation Results
V.3.1. Firm Behavior inside the Strategic Group
V.3.2. Firm Behavior across Strategic Groups
V.3.3. The Impact of Import Competition on Strategic Group
Behavior
V.3.4. Overall Group Behavior
V.3.5. Market Power by Strategic Group
V.4
Alternative Models
54
56
58
59
60
63
63
67
CHAPTER VI: SUMMARY AND CONCLUSIONS
72
BIBLIOGRAPHY
75
APPENDIX
82
LIST OF FIGURES
Figures
Page
II-1
Relationship between Imports and Monopoly Power
8
11-2
Relationship between Exports and Monopoly Power
9
LIST OF TABLES
Page
Tables
III-1
Import Growth Rates and Shares in the U.S. Beer Market
18
111-2
Various Measures of Market Behavior and Power
24
111-3
Various Measures of Own- and Cross-Group Behavior
35
IV-1
Summary of Expected Empirical Results
49
V-1
Parameter Estimates of Primary Model
57
V-2
The Estimates of Market Power
65
V-3
Alternative Model (T)
69
V-4
Alternative Model (T72)
70
V-5
Alternative Model (D72)
71
TITLE: IMPORT COMPETITION AND STRATEGIC GROUP BEHAVIOR.
CHAPTER I: INTRODUCTION
International trade economists, in both their theoretical and
empirical models, have long attempted to explain why international trade
takes place between countries.
In the traditional Ricardian and the
Heckscher-Ohlin (H-0) models, international trade is driven by differ­
ences in the comparative advantage of production due to the difference
in resources and technology across countries.
In these models, perfect
competition is assumed, so that all profits are always competed away in
the long run.
In practice, however, many industries are characterized by imper­
fect competition where the assumption of price-taking behavior is
inappropriate.
In an imperfectly competitive industry, a few firms can
enjoy monopoly profits by setting the prices of their products.
This
may increase the degree of linkages with international competition.
Therefore, there may exist a significant relationship between market
structure and international trade in an imperfectly competitive setting.
Proper understanding of this relationship has required a new framework
of theoretical analysis and empirical research.
As a result, industrial organization and international trade has
merged into a new field of study, which produces a range of new argu­
ments about international trade and market structure.
During the last
twenty years, great progress has been made in this new field, that has
enriched both areas with new empirical and theoretical insights and has
provided new tools of research.
I.1
The Purpose of Study
One of the interesting issues in this new field is to look at the
relationship between import competition and domestic market power by
2
extending the Structure-Conduct-Performance(SCP) analysis to an open
economy setting.
1
Based on the belief that international linkages can
affect domestic market structure, a large body of empirical work has
introduced measures of international variables in ad hoc reduced form
equations of profits, concentration, and other structural or performance
dimensions.
Examples include works by L. Esposito and F. Esposito
(1971), Pagoulatos and Sorensen (1976), Pugel (1978, 1980), Marvel
(1980), Jacquemin (1982), Melo and Urata (1986), and Rosenbaum and
Reading (1988).
These studies find in general that import competition
places a substantial limit on domestic market power, that simultaneously
provides a powerful incentive to import competition.
The theory of strategic groups has recently emerged to enrich the
conventional theory of entry barriers.2
Numerous empirical studies
demonstrate that strategic groups are present in many U.S. industries
including the brewing: Hatten and Schendel (1977), Tremblay (1985, 1987,
1993), and Carroll and Swaminathan (1992) for the brewing industry, and
Newman (1978), Porter (1979), and Oster (1982) for others.
This theory argues that firms within the same industry may differ
in a wide variety of ways because they may differ in goals and/or con­
straints (i.e. skills, resources, goals or risk posture, and other
market and strategic conditions).
They may face different demand and
supply conditions, which may produce asymmetric rivalry from competi­
Market power may vary by strategic group if protected by differ­
tors.
1
The basic concept of the SCP model suggests that an industry's
performance depends on the conduct of sellers and buyers, which depends on
the structure of the industry. The structure, in turn, depends on basic
industry conditions, such as technology and demand for the product. For
example, the industry structure tends toward monopoly if the firm has
technology such that the average cost of production falls as output
increases or if the demand for the firm's product is relatively inelastic.
This model was developed at Harvard by Edward S. Mason, his colleagues and
students such as Joe S. Bain (Carlton and Perloff (1990), pp. 2-3).
2 The theory of strategic groups is basic to this study and will be
discussed completely in chapter II.
The conventional theory of entry
barriers originates from Joe S. Bain (1956), assumes that firms in the
same industry are homogeneous in strategies and performances, and focuses
on barriers against entrants from outside of the industry.
3
ent levels of mobility barriers [Caves and Porter (1977)].3
This
implies that the impact of competition on market behavior and power may
differ by group.
Thus, the incorporation of strategic group theory into
the SCP analysis will provide for additional implications to the
relationship between the competition and market power.
It will be, therefore, very interesting to examine how import and
strategic group competition affect domestic market power in the strate­
gic group model.
This study is motivated by the fact that there has
been no research on the impact of import competition on market power
when two or more strategic groups exist within an industry.
This thesis
will develop and estimate an empirical model of the U.S. brewing indus­
try which includes growing import competition and the presence of
national and regional strategic groups.4
The primary goal of this thesis is to examine the following:
(1) How do import and strategic group competition affect the behavior
of national and regional U.S. brewing producers?
(2) To what extent do national and regional U.S. brewing producers have
market power?
3
Mobility barriers are defined as economic factors such as economies
of scale, product differentiation, switching costs, cost advantages,
access to distribution channels, capital requirements, and government
policy that deter the movement of firms from one strategic position to
This concept provides the first major reason why some firms in
another.
an industry will be persistently more profitable than others [Porter
(1980), pp. 132-134].
4
Previous research verifies that two or more strategic groups exist
in the U.S. brewing industry. For example, Tremblay (1985, 1987) presents
evidence of two strategic groups, national and regional producers. Hatten
and Schendel (1977) and Hatten and Hatten (1985) find that the brewing
Chapter II reviews more
consists of three or more strategic groups.
Elzinga
extensively the strategic groups in the U.S. brewing industry.
(1992) indicates that imported beer has shown rapid growth and has become
an increasingly important feature of the U.S. brewing industry along with
Therefore, it can no longer be
the changes in beer market structure.
ignored in the market structure of the U.S. brewing: on a volume basis,
imported beers have increased since 1970, growing at an increase rate of
578 % between 1974 and 1988, even though the percent of market share by
During the
imports in U.S. are still small with about 4.8% as of 1988.
Import growth
period, imports maintained an average growth rate of 14%.
climbed to double figures eight out of twelve years between 1975 and 1988.
<Table III-1> shows details.
4
1.2
The Significance of Study
Interindustry studies using the SCP approach have come under
criticism concerning the robustness of their results, the often ad hoc
nature of model specification, variable measurement problems, and the
absence of institutional details at the industry level inherent in a
large cross-section of diverse industries [Pagoulato (1992), p. 37].
As a result, the New Empirical Industrial Organization (NEIO) approach
was developed to eliminate these weaknesses (Bresnahan (1989) and
Perloff (1992)].5
This paper synthesizes the NEIO method with strategic group theory
in order to provide for more accurate empirical results.
That is,
specifying and estimating demand functions and supply relations by
group, the synthesized model can measure market behavior and power by
strategic group that directly involves the degree of competition inside
and outside the group.
Consequently, one can examine more closely over
group level how the import and strategic group competition influence
market behavior and power.
Several studies integrate the NEIO method
into international trade analysis: Yamawaki (1986), Domowitz, Hubbard
and Petersen (1986), Karp and Perloff (1989), Buschena and Perloff
(1991), and Aw (1991, 1992).
However, no previous studies have attempted to synthesize the NEIO
approach with strategic group theory in the study of international
trade.
Thus, the contribution of this paper is that it represents the
first synthesis of the NEIO with strategic group theory to analyze the
impact of import competition on market conduct and power by group in a
particular industry.
5
This method typically uses pooled data at firm level to estimate
structural econometric models based on optimization behavior for the
purpose of directly estimating the market behavior or power. This method
was pioneered by Appelbaum (1979, 1982) and has been surveyed most recent­
ly by Bresnahan (1989). Chapter II describes the concept of the NEIO, and
chapter V introduces the stylized model of Bresnahan (1989).
5
1.3
The Organization of Thesis
Following this introductory chapter, the remaining chapters are
organized as follows.
Chapter II reviews the relevant theoretical and
empirical research on SCP analysis of international trade and the theory
of strategic groups.
this study.
Chapter III provides a theoretical framework for
The concept of strategic groups is incorporated for the
model, and the competition between strategic groups and imports are dis­
cussed.
The model allows for the empirical estimation of market
behavior and power by strategic group.
Chapter IV presents the specifi­
cation of the empirical model, which is based on the theoretical frame­
work developed in Chapter III.
It discusses the estimation techniques
and the main expected empirical results.
Chapter V presents the
econometric results and discusses alternative specifications.
Chapter
VI presents a summary of significant findings and conclusions of the
study.
6
CHAPTER II: MARKET STRUCTURE-INTERNATIONAL TRADE RELATIONSHIP
AND STRATEGIC GROUPS
The preliminary ideas for this study originate from incorporating
strategic group theory into the SCP paradigm of international trade.
The main goal is to examine how import and strategic group competition
affects domestic market behavior and power.
Therefore, this chapter
will provide a complete description of the SCP paradigm as it relates to
international trade and of strategic group theory.
II.1
Market Structure, Performance and International Trade
11.1.1. Theoretical Studies
Several authors show how international trade is interrelated with
domestic monopoly power. 6
They assume that a domestic monopolist faces
foreign competition and that domestic and foreign goods are homogeneous.
For simplicity, the domestic country is assumed to be small, which
implies that the monopolist cannot affect the world price and import
supply curve is perfectly elastic.7
They conclude that exports and
imports can be stimulated by monopoly profits, and simultaneously,
international competition can reduce the market power exerted by a
monopolist in the domestic market.
To illustrate, consider Figure II-1 where DD is the domestic demand
curve, and MC is the industry marginal cost curve which will be the
domestic supply curve if the market is perfectly competitive.
Let P
be
the world price of the goods, and Pc be the domestic equilibrium price
at perfect competition.
With no foreign or domestic competition, the
monopolist would choose the monopoly profit-maximizing level of output
White (1974)
6 See Bhagwati (1965) and White (1974), for example.
extends Bhagwati's (1965) model by considering the presence of uncertain­
ties in import price that may be created by the unexpected changes in
foreign exchange rates, foreign price and costs, and transportation costs.
7 Marvel (1980) presents that the analysis results are the same even
though the country is assumed large enough to affect the world price and
the import supply curve is not perfectly elastic.
7
Qm and price
With
With foreign competition, however, consumers would buy
the cheaper imports, so that the best the monopolist could do would be
to produce at the point where marginal cost is equal to Pw at Qf.
is, the modified MR curve is perfectly elastic along P.
demanded by domestic consumers will be Df.
will import DfQf.
That
The quantity
As a result, the country
Thus, the price charged by the monopolist will be
This implies that imports put a limit on
lower with free trade.
domestic market power.
Alternatively, let us consider the effect of domestic market power
on imports.
In Figure II-1, the country will import QfDf at the world
price (Pw) if the domestic market is perfectly competitive.
But the
country will have the threat of increasing imports if the domestic
market is dominated by a monopolist, since the monopolist charges the-
higher price than Pw and Pc at
This
This implies that the domestic
monopolist will leave more room for imports, and the country will have a
greater likelihood of import competition, the greater degree of market
power exerted by the monopolist.
Thus, imports are more likely to enter
the domestic market under a monopoly than under a competitive regime.
Finally, consider the effect of domestic market power on exports.
In Figure 11-2, if the world price (Pw) is higher than Pc, then the
country will be a net exporter and will export QxDx in the case of
perfect competition.
If the domestic market is dominated by a monopo­
list, then the exports will be increased by the difference of Qm and Dx
at Pm.
However, this situation will be possible only if the monopolist can
discriminate the foreign market from the domestic market.
That is, the
monopolist will charge the higher price, Pm, in the domestic market, but
will charge the lower price, Pw, in the foreign market.
as dumping in the export market.
This is defined
If it fails to discriminate between
markets, the monopolist will be unable to exert monopoly power and will
behave as a perfect competitor.
Thus, the impact of market power on
exports appears less obvious than the case of imports.
8
<Figure II-1>
Relationship between Imports and Monopoly Power
P
MC
D
Pm
Pc
Pw
Qf
Qm
Df
Q
9
<Figure 11-2>
Relationship between Exports and Monopoly Power
MC
P
Pm
POI
Pc
R
Qm Ox
Dx
0
10
11.1.2. Empirical Studies
For over thirty years, the predominant approach in industrial
organization has been the Structure-Conduct-Performance (SCP) paradigm
which holds that market structure influences conduct, which, in turn,
influences market performance.
Initially, the SCP analysis tended to
rely mostly on partial-equilibrium and closed-economy models.
But,
these models are inadequate where foreign competition is important.
Thus, they have been extended to account for foreign trade.
The SCP analysis of international trade focuses on the interaction
of foreign trade with domestic market structure and power.
The empiri­
cal evidence confirms that domestic market structure, conduct and market
power are influenced negatively by foreign competition, and that
domestic market power influences positively foreign entry into a
domestic market.
In an early study, L. Esposito and F. Esposito (1971) examine the
effects of imports on domestic profits in oligopoly markets.
They
observe that imports have a negative impact on domestic profits in both
consumer and producer goods markets.
They conclude that imports are the
most influencing factor in limiting domestic market power in an imper­
fectly competitive market.
Pagoulatos and Sorensen (1976) indicate that
variables of market structure such as market concentration, economies of
scale, and product differentiation influence both import and export
activities.
Pugel (1978, 1980) and Marvel (1980) extend this work by control­
ling for simultaneity.
Pugel (1978, 1980) examines the effects of
international trade on domestic market power.
He observes that import
competition limits domestic market power, and this effect is more
prominent in less competitive markets.
Marvel (1980) estimates the
determinants of both trade flows and market power.
His model predicts
that the elasticity of the residual demand faced by domestic producers,
which depends on the elasticities of both import supply and domestic
total demand for the goods, is an important element in explaining the
11
domestic import share.
His empirical results indicate that imports are
influenced by both domestic profits and market structure.
More specifi­
cally, an increase in market power and concentration affects imports,
and imports have a negative effect on domestic profits which appears
larger in concentrated industries.
Jacquemin (1982) indicates that imports interact, not only with
domestic concentration, but also with the supply elasticity of imports
in reducing domestic profits.
In the monopoly case, domestic costs
affect significantly the level of imports under the assumption of
small open economy.
a
In an oligopoly case, the negative effect of
imports on domestic profits is stronger, the more concentrated the
industry or the less elastic the domestic demand.
But, the relationship
becomes more complicated if the assumption of perfectly inelastic supply
of imports is dropped.
Melo and Urata (1986) examine the effects of trade liberalization
on market structure and performance for Chilean manufacturing.
They
find that trade liberalization substantially increases concentration and
reduces domestic profitability.
Rosenbaum and Reading (1988) use cross-
section, time-series data to analyze the portland cement industry.
They
confirm that import share increases significantly with an increase in
concentration, an increase in capacity utilization, and for higher
marginal costs.
That is, the seller concentration and domestic ineffi­
cient production technology in a single industry have a positive impact
on import share of total domestic production.
On the export side, Pugel (1978, 1980) and Marvel (1980) confirm
that the relationship between exports and market structure is ambiguous.
Pugel (1980) argues that, even in the case of price discrimination
between domestic and export market, the weighted average profits may
increase or decrease, since the profits may fall in one market while the
profits may rise in the other market.
Applying the New Empirical Industrial Organization (NEIO) approach
to international trade issues has been recently popularized because of
12
dissatisfaction with the SCP analysis on both conceptual and empirical
grounds.
The NEIO estimates structural econometric models based on
optimization behavior for the purpose of determining market performance.
This approach evaluates the presence of market power in specific
industries by specifying demand and cost functions, and hypotheses about
strategic interactions among participants in the market.
The indices of
conduct and performance are treated as parameters to be estimated rather
than observed from accounting data.
Several studies attempt to integrate the NEIO approach into
international trade analyses.
For example, Yamawaki (1986) suggests
that foreign market structure, pricing behavior, and exporters' reaction
functions influence export pricing decisions by domestic exporters.
Domowitz, Hubbard and Petersen (1986) provide the evidence that the
relationship between concentration and domestic market power can be
better explained by inclusion of import competition into the model.
Karp and Perloff (1989) also estimate the market power of the rice
export market by using a dynamic oligopoly model.
Buschena and Perloff
(1991) estimate the extent of market power and examine the effects of
legal and institutional changes on the market power of a dominant firm.
Aw (1991, 1992) quantifies the effects of VER (Voluntary Export Re­
straint) on exports and estimates the mark-ups of quality-differentiated
export markets in the Taiwanese footwear industry.
11.2
Strategic Groups
11.2.1. The Concept of Strategic Groups
Strategic group theory extends the conventional SCP model, which
assumes that all firms in the same industry behave in similar ways.
According to Porter (1980, p. 129), a strategic group is defined as
follows:
A strategic group is the group of the firms
in an industry following the same or a similar
strategy along the strategic dimension.
13
Firms in the same industry may differ in goals and/or constraints, so
that the firms' strategies would differ in a variety of ways.
There­
fore, these strategic differences can allow for a mapping of firms
within an industry into one or more strategic groups.
Caves and Porter (1977) show that the stable difference in market
performances of firms in the same industry can be attributed to the
presence of mobility barriers, entry barriers specific to a strategic
group. 8
The firms in the same strategic group generally resemble one
another closely along important strategic dimensions.
In the process,
mobility barriers may grow between the strategic groups and prevent
firms from shifting from one strategic group to another.9
As a result,
the market structure and power may differ by group, depending on the
height of mobility barriers, by which each strategic group is protected.
This implies that there may be a persistent difference in the perfor­
mance among firms in an industry.
Subsequently, the impact of import competition on domestic market
conduct and power may differ by group.
Thus, the strategic group theory
can enrich the conventional SCP analysis of international trade which
assumes that all domestic firms in an industry behave in the same way
against foreign competition.
11.2.2. Empirical Studies of Strategic Groups
There is a large body of literature that shows the conventional
theory of entry barriers is not adequate to explain why performance
differs persistently for different groups of firms within the same
8
There have been other views on the reasons why the performance
For example, Brozen (1971)
argues that the difference in firm performance is due to long-run dis­
equilibrium, and Demsetz (1973) argues that it is due to different success
differs across the firms in the same industry.
rates.
9
Caves and Porter (1977), Porter (1979), and Tremblay (1985, 1993)
argue that the presence of strategic groups will not guarantee the
presence of mobility barriers and will not necessarily cause differences
in firm performance.
For example, Hallagan and Joerding (1983) find that
strategic groups could exist without mobility barriers and performance
But, the presence of mobility barriers will lead to the
differences.
formation of strategic groups and cause performance differences.
14
industry.
For example, Caves and Porter (1977) provide the descriptive
foundation for empirical studies of strategic groups.
They contend that
a single industry contains mobility barriers, barriers specific to a
strategic group, that are not all the same.
Thus, barriers to entry
into an industry are not clear-cut and simple when the concept of
mobility barriers is combined, but are quite sophisticated and specific
to the new firms entering the group in the industry.
Newman (1978) tests hypotheses about the influence of strategic
groups on an industry's profitability over a sample of producer-good
industries.
He verifies the concepts of strategic groups and mobility
barriers by showing that profits vary systematically by group.
Porter (1979) explains why persistent differences exist in firm
profits and corporate strategies in a single industry by presenting the
results of a test that examines the structural determinants of profit­
ability for firms differently situated within their industries.
He
argues that the firm's profit in a single industry is determined by the
interaction of various factors within as well as outside the strategic
group.
Porter (1979) finds several important reasons why the theory of
strategic groups is an indispensable element in the SCP analysis.
First, the low correlation between leaders' and followers' profits
implies that the firm's profit depends on group as well as industry
structure.
Second, concentration ratios, the number of firms, and a
firm's market share are positively related with leaders' profits, but
are negatively related with followers' profits.
Third, growth and
capital requirements are positively related with the followers' profits
and the industry advertising-to-sales ratio is positively related with
the leaders' profits.
Oster (1982) finds that the advertising strategy of high advertis­
ers is easier to change than for low advertisers.
Her proposition is
that mobility barriers affect the difference in variability rather than
the level of profits between groups, such that high advertisers experi­
ence less variable profits than low advertisers.
Finally, she verifies
15
the existence of a difference in profit functions between the groups and
suggests that the strategic group model is superior to the SCP model.
Tang and Thomas (1992) argue that firms competing with one another
in a single industry tend to follow similar strategies and then form
strategic groups.
They indicate that the number and size of strategic
groups depend on the height of strategic differentiation, which would
determine the degree of mobility barriers in the industry.
argue that strategic groups are
And they
more likely to exist when strategic
differentiation and mobility barriers are relatively modest.
There have been many studies discussing the presence of strategic
groups in the U.S. brewing industry.
For example, Hatten and Schendel
(1977) test and find evidence to support the hypothesis that there exist
more than one strategic group in the U.S. brewing industry.
They use a
Chow test and Johnson Cluster techniques to empirically classify firms
into different groups.
They regress firm profitability on market
conduct and structure variables and identify six strategic groups in the
brewing industry.
They argue that, under the assumption of homogeneity,
the regression estimates over a whole industry using pooled cross-
sectional and time-series data might reduce the generality and reliabil­
ity in explaining the firm's profit by market conduct and structure
variables.
Therefore, the strategic group model provides a more
accurate estimate of the relationship between the profit and conduct-
structure variables.
More recently, Tremblay (1985, 1987, 1993), and Carroll and
Swaminathan (1992) verify that the U.S. brewing industry is composed of
two or more strategic groups, although they have different views
concerning the classification of strategic groups in the brewing
industry.
10
Following Caves and Porter (1977), Tremblay (1985, 1987,
1993) classifies U.S. brewers into national and regional groups between
10
Tremblay (1993) argues that Carroll and Swaminathan (1992) mis­
interpret the implications of strategic group theory and ignore several
potentially important variables, such as advertising, technological
changes, and income, in their empirical analysis.
16
1950 and 1980.
The reason is that there are significant mobility
barrlers between the national and regional groups.
During this period,
the number of national brewers (Anheuser-Busche, Miller, Schlitz, and
Pabst) remained constant, while the number of regional brewers drasti­
cally declined.
Tremblay (1985) verifies empirically that demand and
cost structures differ across these two groups, implying that two
strategic groups exist in the U.S. beer industry.
Carroll and Swaminathan (1992) attempt to integrate organizational
ecology theory with the theory of strategic groups.
They use organiza­
tional form to classify brewers into three strategic groups: mass
producers, microbrewers, and brewpubs.
Meanwhile, there have been also several additional empirical
studies on the degree of competition across strategic groups in the U.S.
brewing industry.
Hatten, Schendel and Cooper (1978) and Schendel and
Patton (1978) prove that there exists significant competition between
strategic groups in the U.S. brewing industry; specifically small
regional firms compete in different markets against the national
brewers.
To summarize the results described above, import competition
places a substantial limit on domestic market power, and at the same
time, market power can encourage import competition.
relationship between exports and market power.
Less clear is the
It is also evidenced
that strategic groups are present in many industries and are a key
factor in determining market structure, behavior and power.
These
results imply that if the SCP model incorporates the theory of strategic
group, it provides for more fruitful results of relationship between
imports and market power in theoretical and empirical grounds.
Unfortu­
nately, there has been no research using the incorporated SCP model of
international trade.
17
CHAPTER III: THEORETICAL CONSIDERATIONS
In this chapter, a theoretical model is developed which will be the
cornerstone for the empirical model of the next chapter.
In the U.S.
brewing industry, the number of firms has decreased significantly and a
handful of survivors has grown in size during the post World-war II
period.
For example, about 335 brewing firms exited industry between
1950 and 1983 [Tremblay and Tremblay (1988)].
The main reasons for
these changes can be attributed to horizontal mergers, growing economies
of scale, increasing entry barriers, and product differentiation by
vigorous advertising efforts in the market [Elzinga (1992), and Tremblay
and Tremblay (1988)].
In addition, the quantity of imported beer into the U.S. market has
grown by 578% from 1,386 thousand barrels in 1974 to 9,399 thousand bar­
rels in 1988.
With a 1988 market share of 4.75%, the import sector can
no longer be ignored.
Now that import competition has become a signifi­
cant element of the U.S. beer market, its impact on domestic market
behavior and power seems worthy of study.
In Elzinga's (1992, p.232)
words concerning imported beer,
presently, the most promising source of new
competition is the importation of beer, ..
... Imported beer no longer can be discounted
as insignificant.
The import shares and growth rates in the U.S. brewing industry are
presented in Table III-1.
With these changes in structure, the beer
market is characterized as an oligopolisticly competitive domestic
market with international competition.
The focus of the structural analyses in prior work has been on the
U.S. brewing industry as a whole, and at this level the analysis raises
numerous implications for market structure and competition.
However, a
large body of literature finds that two or more strategic groups exist
in the U.S. brewing industry.
For this reason, the analysis of the
competition and market power for the U.S. brewing should incorporate
18
<Table III-1>
Import Growth Rates and Shares in the U.S. Beer Market
(31
Year
Imports(A)
1,386
1,679
2,386
2,546
3,461
4,443
4,568
5,182
5,755
6,314
7,204
7,917
8,838
9,364
9,399
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
Note) Data are available
(March
16,
1992).
gallon barrels
Total
Output(B)
Import
Share(A/B)
156,147
160,599
163,657
170,508
179,657
184,188
194,086
193,687
194,349
195,123
193,021
193,308
196,499
195,420
198,025
0.89
1.05
1.46
1.49
1.93
2.41
2.35
2.68
2.96
3.24
3.73
4.10
4.50
4.79
4.75
from Brewers
Almanac
(various
in thousands,
%)
Import
Growth Rates
-
19.2
35.1
6.5
30.7
25.0
2.8
13.4
10.5
9.3
13.2
9.4
11.0
5.8
0.3
issues)
and Modern Brewery Age
19
strategic group theory and include import competition.
organized into five sections.
This chapter is
In the next section, the theory of
oligopolistic competition is discussed using a conjectural variation
The second section discusses import and rival group competi­
approach.
tion in a strategic group setting.
The third section develops the
theoretical model to examine the impact of import and strategic group
competition on strategic group behavior and market power.
111.1. The Theory of Oliqopolistic Competition
In this section, the theory of oligopolistic competition will be
briefly discussed before presenting the theoretical model.
In an
oligopoly market where strategic interactions predominate, the firm
makes strategic decisions with respect to pricing, marketing, and
production policies based on explicit consideration of the actions and
reactions of other firms in the market.
The model uses the conjectural
variation method which considers firm i's conjecture about rivals'
behavior.11
It summarizes the strategic interactions among the oligo­
polistic firms.
For simplicity, output is assumed to be the only
strategic variable to develop an oligopolistic pricing equation of the
Regarding output competition, each firm's decision to maximize
firm.
profits depends on the output reaction of other firms in the market.
III.1.1. Oligobolistic Pricing of the Firm
Suppose that we have a market with n firms producing homogeneous
goods and that all input markets are perfectly competitive.
Let us
assume that the goal of firm i is to maximize profit with respect to
output.
Then firm i's profit is defined as:
See Bresnahan (1989), Binger and Hoffman (1988), and Nicholson
The
for the good discussions of conjectural variation theory.
major alternative to conjectural variation models is game theory.
The
conjectural variation approach will be used in this study because it is
easy to apply in empirical research. See Schmalensee (1990) for a just­
ification of this approach and its relation to game theory.
(1989)
20
( 1
Hi
)
Q_
p(qi
( qi )
qi
Ci ( qi )
where ni is firm i's profit, P is market price as a function of (gi +
Q_i) = total industry output where gi is output quantity of firm i, Q., =
the output of all firms except firm i,
is firm i's total cost, and
C1
n firms.
i = 1
The first order condition to this problem is:12
an-
aP
P
aP
a (2-
i
I
MC
qi
-
,
-FcIT
(2)
MR- E P +
aP
MC
7g7i
qi
where MRi is marginal revenue of firm i, MCi is marginal cost of firm i,
aP/agi is the slope of the inverse market demand curve facing firm i, Q_
is the output of all firms except firm i, 8Q_i/8qi is a conjectural
variation, which represents firm i's expectation concerning the output
reaction of its rivals with respect to changes in its own output.
Furthermore, observe from equation (2) that firm i maximizes profit
by equating marginal cost with marginal revenue.
Unlike perfect
competition, however, marginal revenue in equation (2) is composed of
the price and mark-up effect, (OP/8qi + (8P/8Q_0(8Q_i/aqi)]qi.
The
mark-up term can be interpreted as the portion of market price being set
above marginal cost.
If we solve equation (2) for the market price,
then
P =MC­
(3)
= MC-
aP
[-5T
8P
aP
aQ-i
qi
+
aP
qi
12 The second-order condition of profit maximization is assumed to
hold.
21
where 0. = aQ /aq
can be defined as the conjectural variation.
From
i
equation (3), note that the pricing behavior of firm i depends on two
main effects: the marginal cost facing firm i, and the size of the mark­
up effect.
The mark-up effect involves the slope of the inverse market
demand curve facing firm i (aP/aqi) and other firms (aP/aQ_i), the index
of conjectural variation of firm i (00, and the output quantity of firm
i (qi).
111.1.2. The Conjectural Variation and Market Behavior
The size of the mark-up effect equals the portion of the price
above marginal cost and will be affected by changes in the conjectural
variation for price-making firms.
Therefore, the relationship between
conjectural variations and market conduct can be derived.
That is,
O. = 0 implies Cournot behavior, where other firms are assumed to hold
their output level fixed when firm i changes its output level.
If ei =
-1, it implies Bertrand behavior where other firms hold their prices
constant no matter what level firm i sets its price.13
If ei = n-1 (n
= the number of firms), then a cartel solution results where the firms
collude to produce the output level that maximizes joint profits.
Following Bresnahan (1989), the first-order condition [equation
(2)] can be written in the form:
7p
(4)
MR1
laP
aQ)cr
-MC; = 0,
7TS5-2
+l
(7Q
P = MCi
aQ ) qi
MCA
Cqi
gqi
li
= aQ/aqi or is equal to 1 + ei, and Q
where
(1989), p. 1027].
13
Q.1 + qi [Bresnahan
The mark-up effect is now A;(aP/aQ)qi.
Cournot
In the Bertrand model, firms set price rather than output.
Bertrand equilibrium is equivalent to a competitive equilibrium.
The
22
behavior exists when 1i = I, Bertrand behavior exists when Xi = 0 and
cartel behavior exists when X. = n.
111.1.3. Conjectural Elasticity and Market Behavior
In elasticity form, equation
PL1
+
(5)
(4)
can be transformed to:
2fNqi.?
dQ dqi PQ
=MC­
bil
P
1
+
= MCi
EIIJI
where
5,
=
(aQ/aqi)(qi/Q) = Xi(qi/Q) is the conjectural elasticity, and
E = (aQ/aP)(P/Q) is the price elasticity of industry demand.
Note that
the conjectural elasticity is composed of the conjectural variation term
(aQ/aqi) and the market share of the firm i (qi/Q).
Now, Cournot behavior (Xi = 1) implies that the conjectural elas­
ticity equals the market share of firm i.
Under Bertrand competition
(Xi = 0), the conjectural elasticity is equal to 0.
Under pure monopoly
(Q = qi), the conjectural elasticity is equal to 1.
Under cartel
behavior (Xi = n), the conjectural elasticity is equal to n(qi/Q). 14
111.1.4. The Derivation of Market Power
A Lerner-type index of market power can be derived from the first
order condition.
The Lerner index, which is defined as (P - MC)/P where
P is market price and MC is marginal cost, measures the degree to which
firm i elevates price above marginal cost.
Therefore, it will be 0 under Bertrand competition, and it will
increase with an upper bound at 1, the more market power a firm exercis­
es.
Given its definition, the oligopoly Lerner index (Li) can be
writtenasafunctionof&and E from equation (5) as:
14 If all firms are of equal size, then qi/Q = 1/n and the conjectural
elasticity = 1
23
P -MCi
(6)
6;
Lis
P
E
From equation (6), the degree of market power depends on the
combined effects of the conjectural elasticity (5) of firm i and the
price elasticity of market demand (e).
Therefore, one can see how firm
behavior affects exerted market power.
As firms behave more competi­
tively or as the price elasticity of demand increases, the Lerner index
falls, that is, there is less exerted market power.
These different
measures of market power under the three standard behavioral assumptions
(Bertrand, Cournot, and cartel) are summarized in Table 111-2.
111.2
Strategic Groups and Competition
111.2.1. Competition in a Strategic Group Setting
The theory of strategic groups implies that the degree of competi­
tion or market power may vary by group within an industry.
Some
strategic groups may specialize in serving narrowly-defined niches of
customers without competing directly with rival strategic groups.
Others may have more vigorous competition with rivals in serving similar
markets.
For example, Porter (1979, p.218) states:
The impact of strategic groups on industry
rivalry depends on three factors that also
hold the key to the rivalry of particular
groups with each other: the number and size
distribution of groups, the strategic dist­
ance between groups and the market inter­
dependence among groups.
Thus, strategic groups are comprised of firms that may compete for the
same customers in different ways.
A particular market segment could be
served by more than one strategic group.
The products of a group may
sometimes be substitutable for the products of another group as far as a
particular customer is concerned.
Thus, the presence of strategic
groups implies that firms in the industry may face different degree of
competition, depending upon their group affiliation.
In addition to the
intergroup dependence, asymmetric mobility barriers between strategic
24
<Table 111-2>
Various Measures of Market Behavior and Power
Behavioral Assumptions
Bertrand
Cournot
Cartel
The Index of
Conjectural Variation:
01 E aQ_i/aCli
-1
Ai E aWaqi = (0i4-1)
0
Conjectural Elasticity:
6.
0
0
n-1
1
n
n(qi1Q)
qi/c2
2 (aWaqi)(qi/Q)
1
li(qi/Q)
Lerner Index:
0
(cli/(2)/Ei
(n(qi/Q)1/ei
Li E (P-MC)/P = -6i/Ei
Note)
n = the number
firm
i
of firms
in the industry,
and Q, = total
industry
output
except
25
groups may affect the relative competition and market power of firms
from different groups.
Regarding asymmetric mobility barriers, Caves
and Porter (1977, p.254) state:
Group-specific entry barriers not only give
differential protection against the new firms
into the industry. They also protect the
members of one group against entry by a member
of another group.
Thus, the firms in strategic groups with high mobility barriers will
have greater market power than those with lower mobility barriers.
Therefore, the presence of strategic groups complicates the degree
of rivalry faced by a firm.
That is, cross-group and import competition
may have a different impact on the profits for firms from different
strategic groups, depending on the degree of intergroup dependence and
the height of mobility barriers that a strategic group has.
This
suggests that the first order conditions of profit maximization may
differ by strategic group.
111.2.2. Cross-Group Competition in the U.S. Brewing Industry
There are several empirical studies on the competition across
strategic groups in the U.S. brewing industry.
Hatten, Schendel and
Cooper (1978) and Schendel and Patton (1978) conduct studies over the
U.S. beer market and prove that there exists significant competition
across strategic groups.
Elzinga (1992) indicates that the average
geographic market served by one brewer has widened due to economies of
scale in production and marketing.
Also, in a special report, Lyke
(1986, pp.66-67) states:
With a decline in consumption of domestic beers
over the last two years, many brewing managers
are looking toward imported labels to help boost
sales .... new "boutique-style" beers flowing from
small regional breweries can offer a domestic alter­
native to attract today's more discriminating beer
drinkers
Major national brewers may find the
smaller-niche markets now being served the regional
more attractive as sales continue to hold steady for
standard domestic beers.
Regionals should con­
tinue to offer interesting- and profitable
alter­
natives to national brands.
26
Thus, these studies suggest that in the same market segment, some
brewers may actively compete against other member firms classified in
different strategic groups, and specifically, small regional brewers or
imports may compete in different markets against national brewers.
In
this context, it is very interesting to assess the degree of competition
and market power of U.S. brewing industry in the presence of cross-group
and import competition.
111.2.3. Import Competition and Strategic Groups
A large body of literature argues that domestic monopoly profits
appear to provide a powerful incentive to import competition.
These
imports, in turn, may put a constraint on the domestic monopoly profits.
Unfortunately, these studies all ignored the presence of strategic
groups when discussing the relation between imports and domestic market
power.
In many industries, however, strategic groups are present and must
be taken into account.
That is, import competition can be stimulated by
the market power exercised by a specific group rather than by the whole
industry because each strategic group exercises different market power
and because entry may be easier into one group than another.
In turn,
imports could constrain the market power of a particular group.
This
suggests that it may be important to study domestic market power at the
group level of the market rather than over the whole industry.
The SCP studies of import competition and market power verify that
domestic market power encourages import competition.
In particular, L.
Esposito and F. Esposito (1971) find that it may be easier for a foreign
competitor to enter a market than a new firm when entry barriers are
high for the following reasons.
lower factor prices.
First, foreign competitors may face
Second, they may experience lower economies of
scale barriers than potential entrants since they already sell their
products in their home markets or in the world markets.
Third, product
differentiation barriers may be lower for the foreign competitors,
27
unless the image of their goods are inferior to those of domestic
products.
Fourth, the response of foreign competitors to excess profits
may be faster than domestic competitors because they are already selling
in their home or foreign market and can more easily utilize current
capacity.
In this case, importers will enter the market for a strategic
group exercising higher market power.
Alternatively, importers could create a niche segment that provides
a unique price premium for certain product attributes, such as high
quality, which is not being served by existing firms in the market.15
Caves and Porter (1977) indicate that entry can be targeted at an
existing group or it can occur through the creation of new group by
attempting a novel business strategy.
In this case, imports would have
little effect on domestic strategic groups.
These arguments imply that
the degree of exposure to import competition may differ across strategic
groups.
Therefore, it is interesting to investigate the impact of
import competition on national and regional strategic groups in the U.S.
brewing industry where imported beers have grown in importance.
No
previous works have, however, attempted to examine the effect of import
competition on strategic groups.
111.3
The Theoretical Model
In this section, a theoretical model that is consistent with the
key features of the brewing industry will be developed.
It will allow
the degree of market power to vary by group and be affected by import
and cross-group competition.
This will be accomplished by integrating
the impact of cross-group and import competition into a conventional
15 Alchian and Allen (1964, pp. 71) theorem suggests that more
expensive and high-quality goods will be imported from foreign countries
due to the decrease in relative price of imports by transportation costs.
This theory implies that imports could create a specialty niche market for
more expensive and high-quality goods.
28
conjectural variation mode1.16
Following Tremblay (1985, 1987, 1993),
this model classifies firms into two strategic groups, national pro­
ducers and regional producers (hereinafter called group N and group R,
respectively).
Group N consists of several large national brewers,
which generally produce nationally marketed and advertised brands.
Group R consists of relatively small regional brewers, which cover local
or regional markets with regionally advertised or unadvertised
brands.17
He finds that the two strategic groups, national producers (group
N) and regional producers (group R) differ significantly in demand and
cost structures.
Therefore, his work seems most relevant to this study,
which will be conducted by a structural econometric system involving
demand and cost functions.
Consider an imperfectly competitive industry with two strategic
groups N and R that face import competition.
Assume that the behavior
of firm i is influenced by the behavior of rivals from its own group,
other groups, and from foreign countries.
In this setting, group N and
group R inverse demand functions are:
PN =PN(C2NIQR/QMIZN)
PR 'PR (C2R1Q14,QM, ZR)
where QN is the total output of group N, QR is the total output of group
R, QM is the total output of foreign suppliers, and ZN and ZR are the
vectors of exogenous variables that shift the demand functions of groups
N and R.
The total short-run cost function for the representative firm i in
each group is:
16
In this section, the model will follow mostly Appelbaum (1979,
1982), Roberts and Samuelson (1988), Thomas (1989), Schroeter and Azzam
(1990), Azzam and Pagoulatos (1990), and Bernstein and Mohnen (1991).
17
Tremblay (1993, p. 95) shows that national brewers and regional
brewers have significantly different prices, advertising levels, number of
brands, age of plant and equipment, and price-cost margins.
29
CNi = CN,(qN,,WN,,X0,TN,)
CR, = CR, ( qR, ,
, XR, , TR, )
where WN, and WR, are vectors of variable input prices, XNi and
are
vectors of fixed inputs, and TN, and TR, are vectors of variables that
control for changes in the technology of firm i in groups N and R,
respectively.
MCN,
defirleclas-
From equation (9) and (10), the marginal cost function is
=aCNi(gNi, WNi
XNP
TN, ) 0%, for firm i in group N, and
MCR, = 8Cu(qu, Wu, Xu, Tu)/aqu for firm i in group R.
By Shephard's lemma, the input demand function for firm i in each
group (Xu, Xu) equals:
Xu(qu,Wu,V10,Tu) =
acu (
,W0
, To )
awNi
acu ( qu , Wu , Vu ,
(12)
)
XR,(qR,,WR,,VR,,TR,) =
Given the inverse demand and total cost functions, the profit (ilu,
Hu) maximization problem of firm i in each group can be expressed as:
(13)
Max "Ni = PN (
(14)
Max BR, = PR ( ) CIR
where PN
(.) and
)
CN
- CR i
are
the inverse demand functions of firm i in
are
groups N and R, and CNiand CRi are total cost functions of firm i in
groups N and R, respectively.
The first-order conditions of profit maximization for a representa­
tive firm in each group are:18
18 The second-order conditions of this problem are assumed to hold.
30
[apN
(15)
PN
8pN aQR
aPN aQm
aCmi
-3KIR
-2W4 TWi
TW
aQN
ZW4
PR
TC1R-3ZIR; +
acRi
8%)
8%
[8PR ack
(16)
C71,4 T-1--; + T-Q-M -3(7-1Ri
=0
=0
By rearranging terms, equations (15) and (16) can be rewritten in terms
of output conjectural elasticities and price elasticities of demand.
apN aQN qN; QN
(17)
PN [3­
(18)
a
apR 8QR
PR [1
apN aQR
171i
-C
qRi QR
MaTR -Fdli PR CTR
aPN aQm
QN
+
PN Q R TM
aPR aQN qRi QN
1-a274
-aqFZ7 PR
CT4.1
aCmi
QM
N
8PR 8Qm gRi
QM
-FM -a77172
QM/
PR
i
acR,
agRii
Given the aggregation assumption, equations (17) and (18) can be
rewritten in aggregate form as follows:19
(19)
PN
(20)
PR
[1
[1
6NN
1PNR
ONM
ENN
6NR
6NM
6RR
lirRN
ORM
ERR
ERN
ERM
acN
1
-20;
19
Because only group-level data are available in this study, the
If group-wide marginal costs are
aggregation assumption is necessary.
constant and equal for each firm within a group, and if all firms within
a group behave in the same way, then an aggregate marginal cost and a
unique conjectural variation exist [Appelbaum (1982), pp. 289-290)]. This
assumption is relevant to this study because firms are assumed homogeneous
This
within a strategic group if the strategic group assumption hold.
aggregation assumption implies that an empirical estimate of a conjectural
variation or market power parameter provides a measure of average market
conduct and power within a group [Bresnahan (1989), p. 1030 and Schmal­
ensee (1990), p. 150].
31
where,
aCN /aQN
= the marginal cost of group N
acRiaQR = the marginal cost of group R
the own-conjectural elasticity of group N.
NN
= (aQN/agNi ) (c1N; P2N)
5RR
(ac2Riachi ) (c1R; /c2R )
the own-conjectural elasticity of group R.
111NR
(aQR/aciNi ) (go /12R )
the cross-conjectural elasticity of group
N against group R.
6
the cross-conjectural elasticity of group
R against group N.
4RN = (aQN/aCIRI) (CIRINN)
0 NM
(aQM/aCiNi ) (clNi /QM) E the cross-conjectural elasticity of group
0RM
(aQM/aCIRi ) (c1Ri /QM)
ENN
(ac2N/aPN)(PN/QN)
N against imports.
ERR = (aQR/aPR) (PR/QR)
a the cross-conjectural elasticity of group
R against imports.
the own-price elasticities of demand for
products of group N.
the own-price elasticity of demand for
products of group R.
ENR
(aQR/aPN) (PN/QR)
the cross-price elasticity of demand for
the products of group N against group R.
ERN
(aQN/aPR) (PR/QN)
the cross-price elasticity of demand for
the products of group R against group N.
6 NM
(aQM/aPN) (PN/QM)
the cross-price elasticity of demand for
the products of group N against imports.
ERM
(aQM/aPR) (PR/QM)
the cross-price elasticity of demand for
the products of group R against imports.
Finally, equations (19) and (20) can be written as Lerner indexes
of market power for groups N and R (LN, LR):
(21)
LN =
[
aNN
+
LR =
[ a RR
ERR
+
ENR
ENN
(22)
giNR
+
lrRN
ERN
ONM
6NM
+
I
ORM
ERM
I
Equations (21) and (22) measure the market power exercised by group N
and group R in the presence of competition between the two groups and
with importers.
Note that market power depends on various conjectural
elasticities and price elasticities of demand.
32
111.4
Theoretical Interpretations of Strategic Group Behavior
As the theoretical model shows, market power in the presence of
strategic groups and imports is influenced directly by the values of
various conjectural and price elasticities.
In the conventional SCP model, market power is affected only by the
own-conjectural and own-price elasticities implying the presence of only
one group within the industry.
However, with more than one strategic
group, the degree of market power involves additionally the cross-con­
jectural and cross-price elasticities reflecting competition and product
substitutability across groups.
With the strategic group model, it is
possible to show that three forces affect group behavior: own-group
behavior, cross-group behavior, and import behavior.
(5NN/510
(
1/NR/ENR)
For example, if
> (0NN/eNN), then rivalry is greatest between group N
If overall-group behavior is
and imports, and lowest within group N.
competitive, then the whole mark-up term will be equal to 0.
occur, for example, if 6NN = IONN = ONN
This can
0.
111.4.1. The Own-Conjectural Elasticity
The value of the own-conjectural elasticity (5) can be described as
the degree of own-group competition, which is affected by the extent of
mutual dependence among firms within the same group.
It depends on the
degree of own-group competition, and the market share of representative
firm i inside the group, ceteris paribus.
For example, if firms within
the national strategic group exhibit Cournot-type behavior, aQN/aqo =
1, and then the own-conjectural elasticity becomes equal to the market
share of the representative firm (qNi/QN).
For Bertrand-type behavior,
For cartel-
aQN/aqw = 0 and the conjectural elasticity is equal to 0.
type behavior, aQN/aqo = n and the conjectural elasticity equals
n(qNi/QN) where n is the number of firms inside the group.
20
Thus, in
20 If all firms are of equal size, qN/QN = 1/n, where n is the number
of firms inside the group. If there is just one firm in the group, then
QN = qNi, and the conjectural elasticity is equal to 1.
33
this case, 5 ranges between 0 and n(qNi/Q4), and as the value of the
own-conjectural elasticity increases, market power of the group increas­
es, other things being equal.
This implies that the group behaves less
competitively within its own group and may have higher mobility barri­
ers.
21
111.4.2. The Cross - Conjectural Elasticity
The cross-conjectural elasticities (*, 0) measure the responses
from rival groups and imports when a strategic group changes its own
output.
It also reflects the height of mobility barriers that a strate­
gic group possesses against rival groups and imports.
The cross-con­
jectural elasticity is composed of the conjectural variation across
groups (8Qs/aqti, s*t) and the market share of the representative firm i
across groups (qti/Qs), where s and t are indexes for two different
groups, and Qs is the total output of group s.
But, unlike the own-
conjectural elasticity, qti is not contained in Qs.
22
Therefore, one could define Cournot-type behavior across groups as
that which produces 8Qs/aqti = 0, and the cross-conjecture elasticity
Analogously, for Bertrand-type behavior
equals 0, ceteris paribus.
aQs/aqti = -1, and the value of the cross-conjecture elasticity equals
_.(qtfic2s).23
21 The profitability of a specific strategic group will be determined
by the height of mobility barriers protecting it. See Porter (1979, pp.
218).
22 There is an important difference between the own-conjectural
For example, the own-
elasticity and the cross-conjectural elasticity.
conjectural elasticity: 6NN = (aQN/ acki)(q0i/QN) where QN includes qNi,
which means that firm i's output quantity is included in the total output
quantity of its own group. However, the cross-conjectural elasticity:
(aQR/8(aNi)(qNi/QR) where QR does not include qNi.
1IINR
=
23 This holds only if the products are homogeneous across strategic
For example, with two groups N and R that sell different
groups.
products, the Bertrand conjectural variation is derived as follows:
Pm
a0 +aq +aRa
Inverse demand
N N
d'NN = N dq N + a R da
Total differential
-R'
Conjectural variation: aqN/aqR = -aR/aN, which equals -1 only for
homogeneous goods (aR=aN).
:
:
34
Finally, for cartel-type behavior, the value of the cross-con­
jecture elasticity equals n (qti/Qs) where ns is the number of firms in
group s.
Thus, a larger value of the cross-conjectural elasticity means
that cross-group competition is lower and the response from the rival
group or imports is less aggressive when a strategic group changes its
own output level.
These different measures of group behavior inside and
across groups when group N and R are present are summarized in Table
111-3.
According to Caves and Porter (1978) and Porter (1979), the impact
This is because the
of cross-group competition will not be symmetric.
expectation of rival's competitive response may vary across strategic
groups and because the degree of substitutability of products may vary
across strategic groups.
This asymmetric impact of cross-group competi­
tion may cause the degree of market power to differ across strategic
groups.
These arguments imply that values of cross-conjectural elastic­
It is, therefore,
ities may differ across groups N, R and imports.
important to estimate and compare the impact of cross-group and import
competition on strategic group behavior.
There are some important implications about the estimates of cross-
conjectural elasticities.
For example, t,NR > *RN
implies that group R
expects more aggressive response from group N than group N expects from
group R.
In other words, group N expects a more cooperative response
from group R than group R expects from group N.
reverse implication.
*NR
competition across groups.
between them.
*MR < *RN means the
*RN implies that they expect equal mutual
If t, NR
= *RN = 0, they expect no response
The same logic and implications can be applied to the
competition between imports and group N or group R.
Finally, if all conjectural elasticities are equal across the two
strategic groups,
5NN
6RR
*NR = *RN
ONM = ORM '
there are no strategic
differences in the competition between national and regional groups and
imports.
This would support the hypothesis that strategic groups N and
R do not exist in the brewing industry.
35
<Table 111-3>
Various Measures of Own- and Cross-Group Behavior
<Group N>
Behavioral Assumptions
BertrandType
Cartel-
Type
CournotType
5NN
(aQN/aciNi)(clNi/C2N)
clNiNN
nN(ciNiIQN)
14NR
(aQR/aciNi)(c1Ni/C2R)
0
nR(ciNi1C2R)
ONM
(aQM/aciNi)(ciNi/C2M)
0
nOgNi/QM)
<Group R>
Behavioral Assumptions
BertrandType
0
Cartel-
Type
5RR
(aQR/agRi (CIRiP2R
*RN
(5C2N/acIRI
(cIRINN)
(4,/c2N)
0
nN(gRiNN)
(51C2M/aciRi
chi/QM)
(ciR,/Qm)
0
nOgRi/Qm)
ORM
Note)
CournotType
=
n = the number of firms in group N,
nR(gRi/C2R)
R,
and importers.
36
111.4.3. The Index of Market Power
The Lerner indexes of market power for strategic groups N and R are
defined as:
(23)
(24)
M
6NN
itrNR
ONM
NN
E NR
et,IM
612R
*RN
ORM
ERR
ERN
E RM
As shown in equations (23) and (24), the Lerner index by group (LN,
L R
)depends on the combined effects of the own- and cross-conjectural,
and the own- and cross-price elasticities.
That is, the degree of
market power for a strategic group is directly related to the combined
effects of own- and cross conjectural elasticities and inversely related
to the combined effects of own- and cross-price elasticities of the
market demands for the group.
This implies that market power of a strategic group may depend on
the forces of rivalry across groups as well as within the same group and
on the degree of substitutability of products from inside and outside
groups.
These may be determined by the degree of mutual market depen­
dence and the height of mobility barriers between strategic groups.
Thus, the degree of market power that a strategic group exerts in
the industry will be influenced by the combination of strategic interac­
tion among participants inside and outside the group.
For example, the
market power that group N exercises inside its own group ( NN/ENN) would
be offset or enhanced by the strategic impact from the regional group
(11/NR/6NR)
and from importers (ONm/eNm)
group N if LN = 0.
are equal to 0 (b NN
There is no market power for
This can result if all the conjectural elasticities
= 001 = 0).
In other words, group N is compet-
itive in its own group without any responses from group R and foreign
suppliers to own-output variations.
37
CHAPTER IV: THE EMPIRICAL MODEL
The purpose of this chapter is to specify an empirical model that
is based on the theoretical model developed in the previous chapter.
The model extends the New Empirical Industrial Organization (NEIO)
approach by allowing for the presence of strategic groups and imports.
Using a structural econometric model, the methodology specifies a demand
and cost system and involves hypotheses about the degree of competition
between strategic groups and imports and market power by group.
With the conjectural variation approach, we estimate directly con­
jectural elasticities and the Lerner index by group.
The demand
equations and the supply conditions by strategic group will be jointly
estimated by a method of simultaneous equation estimation.
Annual
aggregation group data will be used.
This chapter is organized as follows.
the NEIO approach.
The next section introduces
The second section develops the empirical model when
strategic groups and imports are present.
The third section outlines
important expected empirical results.
IV.1
New Empirical Industrial Organization (NEIO)
The NEIO approach has been surveyed most recently by Bresnahan
(1989).
It was developed in response to several concerns with the
traditional structure-conduct-performance (SCP) paradigm.
According to
Bresnahan (1989, pp. 1012):
The NEIO is partly motivated by dissatisfac­
tion over three maintained hypotheses in the
SCP paradigm: 1) economic price-cost margin
(performance) could be directly observed
in accounting data, 2) cross-section variation
in industry structure could be captured by a
small number of observable measures, and 3)
empirical work should be aimed at estimating
the reduced-form relationship between structure
and performance.
The main accomplishment of the NEIO approach is that it avoids the use
of accounting cost data to estimate marginal cost.
This technique is
38
used to estimate market power by using a structural econometric model,
which specifies the demand function, cost function, and the supply
relation.
Because aggregate group data will be used for this study, the styl­
ized model assumes aggregate data.
Bresnahan (1989) argues that aggre­
gate data can be used under certain assumptions: the firms in the same
group produce homogeneous goods and marginal costs are constant and are
the same across all firms within a group.
In this case, one can inter­
pret estimates of conjectural variations as measures of average industry
conduct and the Lerner index as providing estimates of the average
degree of exerted market power.24
These assumptions seem reasonable
for firms belonging to the same strategic group because they produce
similar products and behave similarly.
Assuming homogeneous goods and ignoring the presence of strategic
groups, the demand function is written in inverse form as:25
Pt =D(Qt,Yt,A, Et)
(25)
where Pt is market price in time period t, Qt is the total quantity
demanded of the industry or group, and these variables are endogenous in
the model.
Y t
is a vector of exogenous demand shifters, A is a vector
of unknown parameters, and et is an additive error term.
The cost function is written as:
(26)
ct
= c(Qt,wt,zt,r, et)
where Qt is the total output of the industry or group at observation t,
Wt is a vector of variable input prices paid by the industry or group,
Zt is a vector of exogenous cost shifters (i.e., technology, fixed
inputs), r is a vector of unknown parameters, and Et is an error term.
24 See Appelbaum (1982) for additional discussion for the aggregation
issue used in this approach.
25
This description closely follows Bresnahan (1989).
39
From the first order condition, the supply relation is written in
the conjectural variation form as:
(27)
Pt =mct(Qt,wt,zt,r,Et)
apt
(1+0)
-a-c-j
( Qt , Yt , A ,
t ) cli t
where MC t can be derived from the cost function [equation (26)], ap /aQ
t
t
is the slope of the inverse demand curve, 0 is the conjectural variation
defined mathematically as aQ_it/aqit where ocLit is the total quantity of
industry or group minus firm i's output (qit).
Bertrand competitors, then 0 is -1.
If the firms behave like
For Cournot behavior, 0 is 0.
If
there is cartel behavior in the industry, then 0 is n-1 where n is the
number of firms.
This supply relation can be rewritten as follows:
(28)
Pt =
mct(Qt,wt,zt,r,Et)
X
aPt
(Qt,Yt,a,Et)qit
Qt
where 1 is the conjectural variation defined mathematically as aczitiaclit
where Qit is the total quantity of industry or group and is equal to
1 + 0.
After some mathematical adjustment, equation (28) can be written in
aggregate form as:
apt
(29)
Pt = MCt(Qt,Wt,Zt,r,et)
5
7C5i
(Qt,Yt,a,et)Qt
where 5 is the parameter for conjectural elasticity and is defined as
(aQt/aqit)(qit/Qt).
Therefore, the final system of equations for estima­
tion is demand function [equation (25)] and supply relation [equation
(29)].
This system of equations can be estimated by a simultaneous
equation estimation method.26
As before, the Lerner index of market power can be derived from the
supply relation in aggregate form, equation (29), as:
26 The cost functions or input demand functions could be included in
the system of equation if the relevant data can be available.
40
aPt
(57i-t-Qt
(30)
Lt=
Pt-MCt
. -
Pt
where
E
45
= -__
Pt
is the price elasticity of demand.
E
This index of market power
can be measured by dividing the conjectural elasticity by the price
elasticity of industry demand.
Empirically, the conjectural elasticity
can be estimated as a parameter of the supply relation, and the price
elasticity can be derived from an estimated parameter of the demand
equation.
Given the conjectural and price elasticities, the Lerner
index can be then estimated.27
This stylized NEIO method can be extended to the estimation of
group behavior and market power in the setting of strategic groups.
This can be accomplished by replacing aggregate data with strategic
group data.
In the econometric system, for example, the market power of
a group can be calculated from the strategic group demand function and
supply relation estimates, which may be affected significantly by other
group or import rivalry.
IV.2
The Empirical Model
It is maintained that the U.S. brewing industry consists of two
strategic groups, national brewers and regional brewers (hereinafter
called group N and group R, respectively).
The firms in these strategic
groups compete with each other in the presence of import competition.
With the introduction of strategic groups, the demand and cost struc­
tures are allowed to differ across groups, and the NEIO approach is used
to build the empirical model.
27 With regard to identification problem, market behavior and power
parameters are identified when marginal cost curve is constant [Appelbaum
(1982), pp. 289-290]. They are also identified when Q interacts with an
exogenous demand variable because the demand curve rotates with the
exogenous demand variable, due to the interaction term, tracing out the
marginal cost curve [Bresnahan (1989) and Perloff (1992)].
41
In the output market, the output of each group is influenced by the
output of rivals in its own group, in the other group, and from foreign
firms.
It is assumed that all domestic input markets are perfectly
competitive.
IV.2.1. The Demand Side
In this model, the demand and cost functions are of particular
importance because their specifications influence price and conjectural
elasticities necessary to the study of strategic competition.
The
inverse demand functions for the national (N) and regional (R) groups
are written as:28
(31)
PN = DON
INNQN
PNRQR
ONMQM
PiNY
RalPoP + p3NADvN + p4NADvR +
(32)
PR = POR
PRRQR
PRNQN
PRMQM
01 RY
132RP0P + p3RADvR + p4RADv, + ER
N
where
PN
(PR) a the average real market price charged by group N (group
R),
QN (QR) a per-capita consumption of group N (group R) beer,
a per-capita consumption of imported beer,
QM
ADVN (ADV R
)
=- the real advertising expenditures of group N (group
R),
a real per-capita disposable income,
a the percent of the population that drinks beer,
POP
E
(ER) 1
a the random error for group N (group R).
N
As consumer theory suggests, the effect of own-output quantity on
the own-price is negative unless beer is a Giffen good, so that the
28 See Hogarty and Elzinga (1972), Tremblay
Tremblay (1992) for a discussion about empirical
U.S. beer industry. The linear demand functions
Time series data are used, and
Tremblay (1985).
subscript, t, will be omitted for simplicity.
(1985), and Lee and
demand functions in the
in this study follow
the time-series
42
signs of
PNN
and 3RR are expected to be negative.29
There are several
cross-price parameters between groups N and R and imports,
and
PRm.
B
.
NR'
ONM'
PRN'
Each is expected to have a negative sign because they are
assumed to be substitute.3°
Evidence on effect of income on the demand
for beer has been conflicting. 31
Demand for beer will increase with
the beer drinking population.
There has been much debate concerning the effect of advertising on
the market demand for beer.
The impact of advertising on the demand for
beer is positive for groups N and R [Tremblay (1985)].
But, it is not
significant at the industry level [Lee and Tremblay (1992)].
In part­
icular, Tremblay (1985) indicates that the advertising of rivals are
important in determining strategic group behavior in the U.S. brewing
industry.
Therefore, the rivals' advertising expenditures are included
in the demand function of each group.
IV.2.2. The Supply Side
Recall from equations (19) and (20) in chapter III that the first
order conditions for profit maximization of group N and R can be solved
for the market price as follows:
(33)
(34)
a;
PN = u-c-rti
PR
acR
--
-F;FR
-1
1
1
+
6 NN +
ENN
1+
_RR
ERR
ilINR
+
ENM
NR
+
111RN
ERN
oNm
+
ORM
ERM
29
Hogarty and Elzinga (1972) and Lee and Tremblay (1992) show that
the demand for beer is inelastic.
30
For example, Elzinga (1992, pp.131-32) indicates that the demand
for an individual brand of beer is quite elastic and consumers substitute
brands in response to price changes.
31 For example, Hogarty and Elzinga (1972), Lee and Tremblay (1992)
find beer to be a normal good, Johnson and Oksanen (1977) find beer to be
neutral good, and Lynk (1984) find beer to be an inferior good.
43
Thus, the pricing behavior of each group depends on two main effects:
the marginal cost facing each group and the size of the overall mark-up
term.
With regard to the composition of the mark-up terms,
.5NN and 5RR are
the respective own-conjectural elasticity of group N and R, 10NR and tRN
,
are the respective cross-conjectural elasticity of group N and R between
each other, and ONm and ORm are the respective cross-conjectural elastic­
ity of group N and R with respect to importers.
As described in chapter III, the value of the own-conjectural
elasticity indicates the degree of competition within each group.
the value increases, competition within a group is lower.
As
The value of
the cross-conjectural elasticity measures the degree of competition
across groups and imports.
As the value increases, the firms behave less competitively across
groups and imports.
The ENN and ERR terms represent the own-price elas­
ticities of groups N and R, ENR and ERN are the respective cross-price
elasticities between groups, and ENm and ERm are the cross-price elas­
ticities of each group against imports.
There are three main inputs that are important to beer production:
labor, materials, and capital.
Therefore, a short-run cost function is
expressed by the following Diewert functional form:32
(35)
Cj
Qj [ Yoi +
+ y2.ipm +
y3 jKi.
pr.,. pm
1/2
1/2)
+ y5j ( PL Kj ) 1/2 + y6i ( PM Kj )
where j = group N or R,
PL E
the real price of labor in the production of beer,
PM E.
the real price of materials in the production of beer,
32
See Tremblay (1987) for a discussion of short-run cost function for
the U.S. beer industry. He suggests that it is more appropriate to
estimate a short-run cost function than a long-run cost function because
firms are likely to be in long run disequilibrium. Diewert functional
form is used because it is flexible functional form [Varian (1984), p.180]
44
KN (KR) E the quantity of capital, a single fixed input, for group N
(group R).33
From Shephard's Lemma, the input-share equations for labor and
materials can be derived from equation (35).
acj
(36)
=
pm \ 1/2
-22 Tr., )
Y4
=
aCj
(37)
X Mi =
Y43(
Qi[Y2,
\ 1
+ -1- W41
y5i K
1/2
+ -2­
Y6i Kj )1/21
+ -2­
where j = group N and R, Xi_j and XMj are labor and material demand
functions, respectively,
The resulting marginal cost functions of each group can be ex­
pressed as follows:
aCN
1/2
= YON + YlNPL + Y2NPM + Y3NI(N + Y4N ( PL PM)
(38)
1/2
+ Y5N(PLKN)
1/2
+ Y6N(PMKN)
aCN
(39)
1/2
-z,TR = YOR + Y1NPL + Y2RPM + YUKR + Y4R ( PL PM)
V2
+ Y5R ( PL KR )
1/2
+ Y6R ( PM
)
Substituting these marginal cost functions for group N and R into
the supply relations [equations (33) and (34)] produces:
33 Although this specification does not control for technological
change, the alternative models in chapter V will include such controls for
technological change.
45
PN
[ YON 4. YlNPL
Y2NPM
Y3NKN
Y4N ( PL PM)
1/2+
p
1/2
(40)
Y6N(PMKN)
PR = IYOR
Y1RPL
1/2
Y2RPM
,
Y3RKR
( 41 )
1/2
4- Y6R(PMKR)
5NN
1P NR
ONM
-NN
-NR
-NM
Y 4R ( PL. PM)
,
1/2
1/2
5RR
lirRN
ARM1-1
ERR
ERN
eRM
After mathematical manipulations, equation (40) and (41) can be rewrit­
ten as:
PN = YON + YlNPL
Y2NPM
Y3NKN
Y4N ( PL PM )1/2+ Y5N ( PL KN )1/2
(42)
v
Y6N (PM "N )
1/2
apNn
a PN
vN
1NR
\dIR
apN
QM
ONM
-c214
PR = YOR
Y2RPM
1RPL
Y3RKR
Y4R (PL PM )1/2 + Y5R ( PL KR )1/2
(43)
Tt_
Y6R ( PM "R /
1/2
A
ap
R
aPR
-2K?Ti
412 +111RN
ZW1 '41 + ORM
aPR "
-QM
v-M
As shown in equations (42) and (43), the overall mark-up term for group
N is:
[ 614),("NgQN)QN
//1NR ( "R "QN ) QR
111NM ( "N"QM ) QM]
It can be seen that the overall mark-up term is composed of the own-
group and cross-group mark-ups.
Therefore, the overall-group behavior
of group N is close to Bertrand if 6NN = 11NR
ORM = 0.
This would imply
that the average national firm behaves competitively in the industry.
We have 10 equations to complete the econometric system for
estimation.
That is, the inverse demand equations (31) and (32), the
46
cost function for each group from equation (35), the input-share
equations (36) and (37) for labor and materials of each group, and
oligopoly behavioral equations or supply relations, equations (42) and
Because of data limitations, however, the cost functions and
(43).
input-share equations are eliminated.
As a result, we estimate four
equations: demand functions (31) and (32) and supply relations (42) and
(43).
From the system of equations (31),
(32),
(42), and (43), we could
estimate price elasticities, conjectural elasticities, and corresponding
market power of each group in the presence of cross-group and import
competition.
In order to estimate them, we treat PN, PR, QN, and QR as
endogenous variables in the model.
An error term is added to each
equation and is assumed to be normally distributed with zero mean.
The
system of equations are estimated using a non-linear three-stage least
square estimator as they are non-linear in parameters and in the
endogenous variables.
The data consist of annual observations of group
data from 1953 through 1988.
See the Data Appendix for a complete
description of measurement issues and data sources.
IV.3
Expected Empirical Results
Competition between groups is expected to differ for several
reasons.
First, it appears that mobility barriers are higher for group
N than for group R.
This is supported by the fact that Tremblay (1993)
finds that from 1950-1988 group N had significantly higher average
profit rates than group R.
Tremblay and Tremblay (1988) find that from
1950-1978 the firm failure rate was much higher for group R than for
group N.
In addition, Elzinga (1992) shows that the market share of
group N rose from 19 percent in 1948 to 88 percent by 1987.
Second, coordination within group N may be relatively easier since
there are generally fewer firms in group N than in group R (depending
upon the region of the country).
Given their superior position,
47
national firms may be better able than regional firms to withstand
outside group competition.
This is supported by several studies that
show that national firms are more successful than regional firms
[Tremblay (1985, 1987, 1993) and Tremblay and Tremblay (1988)].
Given
this evidence, two results are expected.
Expected Result 1: Competition is expected to be more rigorous in group
R than in group N. Thus, äNN > 6RIR.
Expected Result 2: Group N is expected to be more insulated than group R
from outside group competition.
Thus,
,NR > ORN
dr
This research is motivated by the fact that there is no evidence on
the impact of import competition on the market power of groups N and R.
Thus, the impact of import competition is uncertain.
However, imported
beer has continued to hold a strong position in specialty beer market
since it first introduced the specialty beer with high quality to many
Americans.
Therefore, one might anticipate that group N is more insu­
lated from import competition than group R, since regional brewers
produce more specialty or niche beer.
greater competition to group R.
In this case, imports may provide
Then, it is expected that ONm > ORm.
On the other hand, imports may be attracted by the relatively high
profits of national producers.
For example, L. Esposito and F. Esposito
(1971), Pagoulato and Sorensen (1976), Pugel (1978), and Marvel (1980)
demonstrate empirically that a higher degree of domestic market power
provides powerful incentives to import competition.
Besides, national
producers produce the high-quality beers in which importers hold strong
position.
In this case, we can expect that ONm < ORm because imports
compete more rigorously with national firms than with regional firms.
The theory of niche markets suggests that entry can target the cre­
ation of new markets by attempting a novel business strategy.34
This
implies that imported beers would have little or no impact on both group
N and R, since imported beers attempt to target a niche area not
34
For example, Caves and Porter (1977) and Alchian and Allen (1964)
indicate that the imports could create a specialty niche market by
attempting a novel business strategy.
48
perceived by groups N and R in the U.S. beer market.
expected that ONN = Orm = 0.
Then, it is
Thus, the expected empirical results are
uncertain, so that it may be interesting to test this hypothesis.
These
lead to the next expected result.
Expected Result 3: It is uncertain which strategic group is more exposed
to import competition. Thus, either ONm > ORm, ONN < ONN or ONN = ONN = 0
Finally, if group N is better able to collude and is better
insulated than group R from outside group competition, then group N
would have greater market power than group R.
For example, Expected
Result 1 indicates that group N is less competitive in the own-group
than group R.
Expected Result 2 suggests that group N is less vul­
nerable to intergroup competition than group R.
Expected Result 3 says
that the impact of import competition on groups N and R are ambiguous.
However, the impact of import competition on the degree of overall
market power for group N is, if anything, small because the market share
of imported beer is relatively small.
These lead to the following
expected result of the market power for each group.
Expected Result 4: Group N exercises higher market power than group R in
the U.S. brewing market. Thus, LN > LR, where L is the index of market
power.
These expected empirical results can be summarized in Table IV-1.
49
<Table IV -l>
Summary of Expected Empirical Results
Expected Results
1) Competition is expected to be
more rigorous in group R than
in group N
2) Group N is expected to be more
insulated than group R from
outside group competition.
3) It is uncertain which strategic
group is more exposed to import
competition.
4) Group N exercises higher market
power than group R in the U.S.
brewing market
Conjectural Elasticity
Estimates
8
NN
> 5 RR
111NR > *RN
Either ONm > ORm, Ow < oRm,
or Omm = ORm
0
LN > LR
50
CHAPTER V: EMPIRICAL RESULTS
In this chapter, the empirical results will be presented.
The
complete demand and supply models for national and regional strategic
groups (hereinafter called group N and group R, respectively) are
developed in chapter IV.
The system consists of four basic equations:
a demand function and a supply relation for each strategic group in the
U.S. brewing industry.
Using the New Empirical Industrial Organization
(NEIO) approach already reviewed in chapter IV, conjectural elasticities
and the Lerner index for each strategic group are estimated.
This chapter is organized into six sections.
The following section
reviews the demand and supply system that can permit the econometric
identification of the degree of competition.
The second section de­
scribes several specification tests of the primary empirical model.
The
third section presents the estimation results of the structural equa­
tions.
This involves the main inferences from conducting the hypothesis
testings of strategic group behavior and market power for groups N and
R.
The fourth section describes the empirical results based on alterna­
tive models.
V.1
Review of the Empirical Model
From the previous chapter, we have shown that the final empirical
functions of interest include the demand functions and supply relations
by group.
The inverse demand functions are defined below:
(44)
(45)
PN
PR
PON + I3NNQN
130N + PRRQR
PNRQR
PRNQN
13NMQM + PINY + 13200P + 133NADvN + is4NADvR
PRMQM + PUY
132RP°P + I33RADVR + I34RADVN
where P is the average real market price charged by each group, Q is
per-capita consumption of the beer that each group produces, QM is per­
51
capita consumption of imported beer, ADV is the real advertising expen­
diture incurred by each group,
Y is real per-capita disposable income,
and POP is the percent of population that drinks beer.
The supply relations by group equal:
KN)1/2
PN = YON +Y1NPL +Y2NPM
(46)
+Y6N(PMwN)
Y3NKN
Y4N (PL PM)1/2
IaPN
1/2
"NN
Qv
PR = YOR +Y1RPL +Y2RPM +Y3RKR
aPN
RT, t
N
)1/2
Y 4R ( PLPM)1/2
(47)
1/2
aPR
,
aPR
[
'RR
aPN
wN Mw
vR +4TRN
$
aPR+Y6R(PM
7T
From the previous chapter, note that 6NN = (8QN/aqNi)(qNi/QN) is the own-
conjectural elasticity of group N's total output with respect to firm
i's output in group N,
6RR= (a(2RiaciRi )
(qR i /42R )
is the own-conjectural
elasticity of group R's total output with regard to firm i's output in
group R' *Ne(aQR/agNi)(c4i/QR) and ONm=0Qm/8q0(qNi/Qm) are the cross-
conjectural elasticities of group R's total output and total imports
with regard to firm i's output in group N,
( 0 / a
RN= a -N, a -IR;
1
(a
/0-N,
1 and
ONe(aQm/acimi)(qm/Qm) are the cross-conjectural elasticity of group N's
total output and total imports with regard to firm i's output in group
R.
The slopes of inverse demand curves are observable from the demand
equations (44) and (45).
PNR, aPR /aQN
PRN'
That is, apN/aQN = .NN' aPR/aQR
aPN/aQm = PNm, apR/aQm
=P
PRR' aPN/aQR
The 6N,
N
ERR' *NR' *RN' ONM
ONm are the parameter estimates of conjectural elasticities, which can
be identified, given the parameters of supply relations and demand func­
tions for each group.
The Lerner Index by group is defined as follows:
(48)
LN
=
PN -MC11
5NN
4INR
ONRI
PN
ENN
NR
ENM
52
(49)
L R
PR MCR
=
p
5RR
1PRN
ORM)
ERR
ERN
ERM
Note that the degree of market power in this setting is negatively
influenced by the degree of competition from within a group
and from outside groups
(III
NR
111RN
(FNM
'
cPRM
( 5NN'
5RR)
The higher the values of
)
these elasticities, the higher is the degree of market power.
The degree of market power is also negatively influenced by the
price elasticities of demand within groups
(
s
E NN'
ERR) and across groups
(ENR' ERN' ENW ERm)
This means that the degree of market power falls as
the values of these elasticities increase; that is, as the products
become closer substitutes.
V.2
Econometric Concerns and Tests
The system of equations consists of the demand functions [equations
(44) and (45)], and the supply relations [equations (46) and (47)] for
groups N and R.
They are estimated using a non-linear simultaneous
equations estimator.
QN, and
The endogenous variables in the model are PN, PR,
The empirical model is complete with the addition of
additive error terms, the structure of which is discussed in the
followings.
V.2.1. Contemporaneous Correlation Test
The question arises whether or not contemporaneous correlation
exists among the residuals of equations in the structural model.
Zellner and Theil (1962) suggest that if contemporaneous correlation of
residuals is present in the model, then a three-stage least square
estimator is asymptotically more efficient than a two-stage least square
estimator.
That is, using the two-stage least square estimator ignores
relevant information concerning the error covariance matrix.
Thus, it
53
is useful to test whether or not contemporaneous correlation exists
across equations.
An appropriate test for contemporaneous correlation is developed by
Breusch and Pegan (1980): The test statistic is A = T(r212 +r213 +r214
4.r2
..i.r2
23
a2
ij
24
4.r2
)
34
where T = the number of observations, r2ij =a2ij laI-ajj where
is the covariance of equations i and j, a ii
is the variance of
equation i, an is the variance of equation j.
A has an asymptotic x2
distribution with M(M-1)/2 degree of freedom where M = the number of
equations.
The test result shows that the statistic value, A, is 25.47, which
is greater than X20.01,6
16.81.
This rejects the hypothesis that
contemporaneous correlations is absent.
Therefore, given endogeniety
and contemporaneous correlation, a three-stage least squares estimator
is efficient.
V.2.2. Endogenietv Test of Imports and Advertising
In this specification, it is maintained that imports are exogenous.
To test this maintained hypothesis, a Hausman (1978) test is performed:
H o'
0
Ha
p
:
is consistent and efficient (Imports are exogenous)
is consistent (Imports are endogenous)
M,exo
M,er b
where p M,exo
is the vector of coefficient estimates for the imports as an
exogenous variable, and
p
M,ericlo
is the vector of the coefficient esti­
mates for imports as endogenous variables.
These estimates are produced
by three-stage least squares estimation.
For this Hausman test, import quantities were regressed on all
exogenous variables in the demand functions and supply relations and
other exogenous variables affecting import quantities: per-capita
disposable income, the percentage of population drinking beer, real
advertising expenditures of groups N and R, real labor price, real
material price, capital stock of groups N and R, and weighted exchange
54
rate. 35
The test statistic is:
/
( OM,emio
I3M,exo)
[V( 1314,endo)
V( 13M,exo)
1 (I3M,endo- 13f.i,exo)
where V(.) is the covariance matrix of coefficient estimates for imports
as an endogenous and exogenous variable.
A has a x2 distribution with k
degree of freedom (k = the number of restricted parameters).
result shows that A is 7.63 which is smaller than Y
- 20.01,
4
The test
13.28.
This
rejects the alternative hypothesis, supporting the maintained hypothesis
that imports are exogenous.
To test the maintained hypothesis that the advertising of each
group is exogenous, the Hausman (1978) test is performed in exactly the
same way as import endogeniety was tested. 36
The advertising expendi­
ture of each group is regressed respectively on all exogenous variables
in the demand functions and supply relations.
The test results show
that A is 4.52 for the advertising of group N and 5.21 for group R.
Both are smaller than X20.01,
1
= 6.63.
These reject the alternative
hypotheses, supporting the maintained hypothesis that advertising
expenditure of each group is exogenous in this model.
V.2.3. Autocorrelation Tests
When time series data are used in regression analysis, the error
term is frequently correlated over time.
This feature of the regression
disturbance is known as autocorrelation (AR).
When the regression
disturbance is autoregressive, the least squares estimator of the
regression coefficients are unbiased and consistent, but they are not
efficient.
35 The weighted exchange rate is calculated by weighting the exchange
rates in U.S. dollars with the import share of beer from Canada, Germany,
Holland, and Mexico, the major exporters to the U.S.
Over 85% of U.S.
beer imports come from these four countries.
36
For example, Lee and Tremblay (1992) and Tremblay and Tremblay
(1995) assume that advertising is endogenous.
55
Hence, the sampling variances are biased and may be understated.37
To test for the presence of autoregressive errors in the model, two
tests are conducted under the following hypothesis, assuming that the
model has first- or second-order serial correlations.
Ho
H
a
:
:
No autocorrelation
autocorrelation exists
The first test suggested by Greene (1990) is the Lagrange multipli­
er test [Breusch (1978) and Godfrey (1978)].
It is valid for very
general hypotheses about serial correlation of the errors.
This test
was carried out by regressing the ordinary least squares residuals, et,
on Xt, et_1,....et_o, where et_o is the residual with p lags, and Xt is the
matrix of regressors.
The test statistic is 1 = T*R2, where T = the number of observa­
tions, R2 is R-square obtained by regressing the ordinary least squares
residual, et, on Xt, et.1,....et_o.
1 has x 2 distribution with p degrees
of freedom (p = the order of the AR process).
The test results show that the statistic values are 3.28 for
equation (44), 5.43 for equation (45), 5.25 for equation (46), and 2.75
for equation (47).
The critical value is x20.012
greater than these statistic values.
7.38, which is
Therefore, it is concluded that Ho
cannot be rejected for all the equations.
For the second test, a simple t-test [Beach and McKinnon (1978)]
was conducted.
The residuals of each equation including estimated
endogenous variables in the system are estimated by ordinary least
squares.
First, for first-order autocorrelation, et is regressed on et_i
to estimate the coefficient AR1.
et = AR1 *et.1 + v
where v is the error term of estimation.
As a result, the t-ratio for
37 See Kmenta (1986, pp.298-314), Greene (1990, pp.429-439), and
Maddala (1988, pp.192-200) for detailed discussion and theoretical proof
of the estimation problems to be raised by autoregressive errors.
For
example, in the case of positive autoregression and positive correlation
between regressors, the estimated variance of the conventionally
calculated estimator is biased.
56
AR1 for each equation is smaller than the critical values, not rejecting
H
that AR1 = 0.
To test for second-order autocorrelation, the coeffi­
cients AR1 and AR2 are estimated.
e
AR 1 *et.1 + AR2*e
t-2
It is found by t-test that AR1 = AR2 = 0.
+ v
In the same approach, AR3 and
AR4 are additionally estimated and tested, and no significant autocorre­
lation is found in any equation.
Thus, these test results of autoreg­
ressive errors confirm that residuals of all the equations in the system
are not autocorrelated.
V.3
Estimation Results
According to test results conducted to ensure consistent and
efficient estimation, equations (44) through (47) are estimated using a
non-linear three-stage least square estimation technique.
The model is
estimated using annual data for the sample period 1953-1988.
Data Appendix for a complete description of the data.
See the
The endogenous
variables are the prices and quantities of group N and R products, and
all other variables are assumed to be exogenous.
Table V-1 reports the estimates for all the demand and supply
parameters for the strategic groups N and R.
The signs of PNN and
I3RR
are negative, showing that beer satisfies the law of demand and is not
Giffen goods.
All signs of
13
.NR'
ONM'
PRN'
PRm are negative as expected.
As previ­
ous literature indicates, the effect of income on the demand for beer is
conflicting in the model: group N beer is neutral, while group R beer is
normal.
Demand for group N beer increases with the beer drinking popula­
tion, but the effect on group R beer is not significant.
This may be
because the demand for group R beer has not increased persistently as
regional brewers have been less successful and their failure rates have
been much higher than national brewers.
57
<Table V-1>
Parameter Estimates of Primary Model
Parameter
Estimate
Approx.
Std Err
Ratio
Label
0.417
0.184
0.236
1.317
0.00003
0.019
0.00002
8.18E-6
-1.43*
-6.25***
-3.05***
-1.14
1.31
5.32***
1.86**
-1.84**
Intercept
0.380
0.220
0.161
1.181
0.00003
0.017
8.48E-6
0.00002
3.71***
-1.38*
-2.53**
-1.71**
1.89**
-0.94
0.02
1.61*
Intercept
0.447
5.482
3.907
0.007
69.103
0.103
0.037
0.244
0.633
1.262
1.79**
Intercept
-1.68*
PL
PM
-0.49
-3.08***
K.
(pL*A)1/2
0.27
(pL*KN)1/2
3.44***
)1/2
0.72
-0.02
Group N Own-CE
1.91**
Group N Cross-CE to R
-1.30
Group N Cross-CE to M
'T'
Group N Demand
RON
NNN
NNR
N NM
N1N
N2N
N3N
- 0.597
1.152
- 0.721
- 1.502
0.00005
0.104
0.00003
- 0.00001
1-'4N
QN
QR
QM
Y
POP
ADV
N
ADV
R
Group R Demand
OOR
1!RR
NRN
NRM
N1R
N2R
R3R
4R
1.410
-0.304
-0.407
-2.024
0.00006
- 0.016
1.67E-7
0.00003
QR
QM
QM
POP
ADV
R
ADV
N
Group N Supply
YON
YIN
Y2N
Y3N
Y4N
Y5N
16N
aNN
11INR
ONM
0.802
- 9.235
- 1.925
- 0.024
18.802
0.356
0.027
-0.005
1.213
- 1.663
Group R Supply
YOR
Y1R
Y2R
Y3R
Y4R
Y5it
Y6R
5RR
*RN
ORM
3.744
- 6.423
- 14.250
- 0.017
62.200
- 0.083
0.230
-2.003
- 0.837
0.249
Note) ***
1%,
1.474
8.567
8.266
0.013
52.761
0.144
0.141
1.366
0.394
0.433
** 5%,
2.54***
Intercept
-0.75
PL
-1.72**
PM
-1.33*
KR
(pL*pm)1/2
1.18
0.58
(PL*KR)]/2
1.63*
(PM*K0)1/2
-1.47*
Group R Own-CE
-2.12**
Group R Cross-CE to N
0.57
Group R Cross-CE to M
* 10% significance
level
58
As expected, advertising by both group N and R has a positive
impact on the demand for beer, but this effect is not different from
Ofor group R.
This may be because national brewers as large scale
advertisers have marketing advantages over regional brewers.
Rivals'
advertising outside group has a significant negative effect on group N
beer and has a significant positive effect on group R beer.
That is,
group R advertising will decrease the demand for group N products while
These
group N advertising will increase the demand of group R products.
results confirm Tremblay (1985) and suggest that group N advertising has
spillover effects on the demand of group R beer.
A critical motivation for this study is to investigate the market
behavior and power of strategic groups N and R in the presence of import
competition in the U.S. brewing industry.
These can be reflected by the
parameter estimates of the conjectural elasticities,
and
ORm
5NN'
10NR'
ONM'
6RR'
that are presented in Table V-1.
V.3.1. Firm Behavior inside the Strategic Group
This section concerns the investigation of firms' behavior inside
their own group.
Recall that Ne(aQN/agNi)(gNi/QN) measures how the
national firms behave in their own group.
Similarly, 6Ne(aWaciNi)
(gRi/QR) measures how the regional firms behave in their own group.
From Chapter III, recall the following:
Own-Group Behavioral Assumptions
Bertrandtype
C2NN
0
C2NC2R
0
NN
(a/aciNi)(c1Ni/Q) =
RR
(aia ciRi)(c1Ri/)
Note)
Cournottype
CINi/QN
n = the number of firms in group N and R.
Cartel­
type
nN
/0N)
nit(cliti/QN)
59
Therefore, one would expect the own-conjectural elasticities
aNN'
(
aRR) to range from 0 to nOgNi/QN) for group N and from 0 to nR(gRi/QR)
for group R.
For example, the actual bounds on 5NN and 6RR are calculated to be
between 0 and 1, when the data are evaluated at their values of 1970,
the mean year of the sample.
Accordingly, as 6NN and SRR increase in
value, the degree of market power increases, ceteris paribus.
To test for Bertrand-type behavior within the same group, we can
test the null hypothesis that 5NN = 0 for group N,
5RR
= 0 for group R.
As seen in Table V-1, A NN = -0.005 is not different from 0 at the 5%
significance level.
This cannot reject the null hypothesis of Bertrand­
type behavior within group N.
5% significance level.
6RR = -2.003 is different from 0 at the
It is notable that the bRR has a significant
negative sign out of bound.
This implies that there is severe competi­
tion among regional brewers, which may explain the exit of so many
regional producers during this period.
These empirical results are in line with Expected Result 1 in
chapter IV, which says that regional brewers are more competitive than
national firms within the same group.
They are consistent with the
views of Greer (1981) and Elzinga (1992) and the empirical evidence of
Tremblay and Tremblay (1995) who find that the U.S. brewers behave
competitively. In the words of Elzinga (1992, pp. 155),
Even with the increased demand for beer in
the 1960s and 1970s, competition forces the
exit of marginal firms. Moreover, Miller's
increase in productive capacity (imitated by
its rivals) overhangs the industry and now
provokes the larger brewers to battle among
themselves instead of merely competing away
market share from smaller firms.
V.3.2. Firm Behavior across Strategic Groups
The second issue concerns rivalry across groups.
estimates of cross-conjectural elasticities (*. NR '
R.
111RN )
This involves
for groups N and
Recall from chapter III the following definitions and bounds for
*NR
NR
and
41RN:
60
Cross-Group Behavioral Assumptions
Bertrandtype
Cournottype
Cartel­
type
*NR=(aC2R/aCINi) (CINi/4R)
(clNi/C2R)
0
r2R(ciNi/4R)
*RN=(aQN/aciRi) (c1RiNN) =
(gRiP2N)
0
12N(c1Ri/QN)
Note)
n = the number of firms in group N and R.
As the values of cross-conjectural elasticities
(III
NR '
*RN)
increase,
competition is reduced and the degree of market power increase, ceteris
paribus.
For data from 1970, for example, the bound for *NR is -0.15 to
12, and the bound for *RN is -0.02 to 0.08.
The non-zero value of the
cross-conjectural elasticity implies that output strategic choices made
by the representative firm of a strategic group are affected by the
reaction from the rival group.
From Table V-1, the parameter estimates for the cross-conjectural
elasticity (*NR =
1.213 and
significance level.
*RN
0.837) are different from 0 at the 5%
These results suggest that national brewers expect
a cooperative or accommodating response from regional brewers when
national brewers change their output.
Alternatively, regional producers expect an aggressive response
from national producers when regional producers change their output.
The
*
RN
-0.837 has a significant negative
g
sign out of bound.
This
implies that regional brewers are much harmed by the rivalry from
national producers.
These empirical results are consistent with the
Expected Result 2 and support previous research [Porter (1979), Hatten
and Schendel (1977), Tremblay (1985, 1987), and Elzinga(1992)].
V.3.3. The Impact of Import Competition on Strategic Group Behavior.
The question to be examined in this section is how strategic group
behavior is affected by import competition.
The values of conjectural
parameters 00 and ORm measure how imports influence the behavior of
61
groups N and R, respectively.38
Recall from chapter III the following
definitions and bounds for Ow and 6
RN:
,
Behavioral Assumptions (against Imports)
Bertrandtype
ONm=(8QmiaciNi)(clNi/Qm) =
-(clNi/C2m)
ORm=(aQmiaciRi)(c1Ri/Qm)
-(c1Ri/Qm)
Note)
Cournottype
Cartel­
type
0
nm(c10/(20
0
nm(c1Ri/C2N)
n = the number of firms in group N and R.
Thus, as ONm and ORm increase in value, the degree of market power
increases, ceteris paribus.
For instance, data from 1970 indicate that
the bound for ONm is -13.33 to not less than 13.33, and ORm bounds from
-1.18 to not less than 1.18.39
Table V-1 shows that *NM = -1.663 and
*Rm = 0.249 are not different from 0 at the 5% significance level.
These results imply that national and regional producers expect no
response from import producers when national and regional producers
change their output levels.
This supports the theory of niche market
suggested by Caves and Porter (1977).
That is, the import niche is
sufficiently unique, so that little rivalry exists between domestic
groups and imports.
This is supported by Elzinga (1992) who points out
that imports generally compete in the superpremium category.
These empirical results of own- and cross-group behavior can be
summarized as follows, including the actual bounds on conjectural
elasticities for the mean year of sample, 1970:
38
In the case of exogenous imports, there is no reaction from the
imports to strategic decisions of groups N and R. Hence, one can talk
about simply the impact of import competition on strategic output choices
of each group.
39
The actual bound for 0,, and ORm are not concrete because the number
of importers (nm) are not available.
62
The Measures of Firm Behavior
<Group N>
Bounds on Conjectural Elasticities
(The mean year: 1970)
Bertrand
-type
ONM
Cartel
-type
qpn/QN =0.25
0
5NN
IONR
Cournot
-type
Estimated
Conjectural
Elasticities
npl(qpn/QN)= 1
-(q0/QN)= -0.15
0
nR(qNi QR) =12
-(c1Ni/C2m)=-13.33
0
nN(qNi/QN)13.33
-0.005
1.213**
-1.663
<Group R>
Bounds on Conjectural Elasticities
(The mean year: 1970)
Bertrand
-type
5RR
*RN
ORM
Note)
Cournot
-type
Cartel
-type
qNi/c4=0.01
0
Estimated
Conjectural
Elasticities
nN(qpn/QN)=1
-2.003*
-(qrn/QN)=-0.02
0
z2N(qRj/QN)=0.08
-0.837**
-(qNi/QN)=-1.18
0
nm(c4i/QN)1.1.18
0.249
n = the number
significance
of firms
level
in group
N and R, ** 5% significance
level,
and * 10%
63
V.3.4. Overall Group Behavior
A strategic group model can capture the cross-group as well as own-
group behavior and can determine the degree of market power for a
strategic group by combining the own- and cross-group effects.
There­
fore, the overall effect by group can be tested as follows: no market
power exists if 6 NN = *NR = ONm = 0 for group N and (5 RR
group R.
SRN = ONm = 0 for
For example, if we accept these hypotheses, then we conclude
that P = MC in each group (Bertrand behavior), where P is the market
price and MC is marginal cost.
This means that firms behave like price-takers inside the group and
do not expect rival response to own output variations from other com­
The x2 value for a Chi-square test is 15.25
petitors outside the group.
for group N and 20.55 for group R.
7.81.
These are greater than If
^2 0.05,3
Therefore, we can reject the hypothesis of price-taking behavior
and conclude that neither strategic group behaves like Bertrand competi­
tors overall.
V.3.5: Market Power by Strategic Group
The main question in this section is which strategic group exercis­
es higher market power.
This can be answered by comparing the Lerner
index of market power [(P- MC) /P] for each group.
Recall that the Lerner
index of market power for groups N and R (LN, LR) can be expressed as:
(50)
LN
(51)
=
LR = ­
[5NN
11NR
ONR
ENN
ENR
ENM
61212
*RN
ORM
ERR
ERN
E RM
+
Table V-2 shows the degree of estimated market power of groups N
and R (LN, LR), and of the industry as a whole.
The degree of market
power that each strategic group exerts during 1953-1988 can be estimated
at sample means as:
64
LN
-E(SNNieNN)+(*NR/ENR)+(ONN/6NO] =
1.539 (7.092)
LR = -E(bRR/ERR)-1-(1/RN/ERN)+(ORN/ERO]
=
where the number in parentheses are t-ratios.
-1.826 (-4.597)
This shows that LN has
significant positive sign, and LR has significant negative sign at the
5% significance level for a two-tailed test.
Negative market power
(P < MC) for group R can be explained by an unexpected drop in the price
of regional beers and so many exits of the regional brewers from the
industry.
These may be due to growing economies of scale and expansion
in the production of national producers.
Perhaps this also implies that
regional firms expect a predatory or retaliatory response from national
firms to keep them in line."
Thus, they are not static profit maxi­
mizers.
Therefore, one can conclude that national firms have exerted higher
degree of market power than regional firms.
confirm Expected Result 4 of chapter IV.
These empirical results
In addition, mean difference
in market power between groups N and R is significant with t-ratio =
47.56 at the 5% significance level for a two-tailed test.
These results
imply that the strategic groups N and R exert different degrees of
market power and supports the view that mobility barriers are greaterin
group N.
Furthermore, to measure the degree of market power for the
industry as a whole, the weighted average market power (LN +R) can be
calculated by weighting the Lerner index by the market share of groups N
and R:
LN
= MSNLN + MSRLR = -0.724 (-1.214)
where the parentheses show the t-statistics, MSN is the average market
share of group N, and MSR is the average market share of group R in the
U.S. brewing industry.
Table V-2 presents that LN+R is not different
from 0 at the 5% significance level for a two-tailed test.
40
This pro­
For example, the predatory pricing behavior of national brewer can
be seen in the antitrust case between Anheuser-Busche (A-B) and Fallstaff
in 1955.
The Federal Trade Commission (FTC) charged A-B with unlawful
price discrimination and argued that this practice would give A-B market
power by increasing its market share [Elzingar (1992)].
65
<Table V-2>
The Estimates of Market Power
YEAR
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
Variable
LN
LN
L N+R
Note)
LN
LR
1.274
1.185
1.279
1.217
1.216
1.090
1.468
1.376
1.397
1.438
1.446
1.513
1.506
1.547
1.527
1.556
1.663
1.714
1.683
1.657
1.721
1.700
1.646
1.745
1.825
1.730
1.746
1.891
1.899
2.021
1.557
1.507
1.485
1.433
1.366
1.377
Mean
1.539
-1.826
-0.724
** 5% significance
level
-1.593
-1.499
-1.566
-1.462
-1.440
-1.489
-1.721
-1.529
-1.528
-1.268
-1.316
-1.389
-1.568
-1.397
-1.479
-1.499
-1.592
-1.698
-1.702
-1.687
-1.795
-2.105
-1.923
-1.928
-2.042
-2.179
-2.267
-2.471
-2.558
-2.598
-2.529
-2.394
-2.340
-2.425
-2.130
-1.616
LN+R
-1.249
-1.215
-1.276
-1.016
-0.996
-1.044
-1.239
-0.947
-0.924
-0.657
-0.656
-0.669
-0.749
-0.557
-0.553
-0.475
-0.498
-0.468
-0.399
-0.311
-0.270
-0.369
-0.272
-0.345
-0.342
-0.503
-0.551
-0.652
-0.647
-0.875
-1.222
-1.060
-0.955
-0.962
-0.733
-0.410
Std Dev
t-ratio
0.217
0.405
0.596
-4.597
-1.214
7.092 **
66
vides evidence that the average U.S. brewer exercises no market power
and behaves like a price-taking firm.
Finally, the question is how outside group and import rivalry
affects the market power of strategic groups.
The impact of group R and
import rivalry on the market power of group N can be captured from esti­
and 001 /ENm, respectively.
resectively
mates of *q112ENR
/
-
*NR/ENR
1.539 is different
from 0 and ONm/ENm is not different from 0 at the 5% significance level
for a two-tailed test.
These results suggest that regional group
competition is more important than import competition to the national
group and enhances the market power of national group.
On the other hand, group N rivalry significantly reduces the market
power of group R.
In this case, t izN,/ ERN =
1.430 is different from 0,
f
and ORm/ERm is not different from 0 at the 5% significance level.
These
imply that the market power of an average regional brewer has been
harmed by the rivalry from national brewers and has not been affected by
import competition.
These results confirm that the impact of outside competition on
market power differs between groups N and R and that group N has been
more able than group R to withstand outside group competition.
Given a
superior position in technology and marketing, the national brewers may
have increased market share and power at the expense of their smaller
regional competitors.
The national brewers have higher average profit
rates than the regional firms, and the failure rate was much higher for
the regional than for the national firms (Tremblay (1985, 1987, 1993),
Tremblay and Tremblay (1988)].
Besides, it appears that import rivalry has not been an important
factor in determining the market power of domestic brewers, although the
amount of beer imported into the United States has recently been
increasing in the U.S. brewing market.
In 1970, imported beer was a
negligible part of U.S. beer consumption, accounting for less than 1% of
the market.
By 1988, market share had soared to 4.8%.
However, at
least 50% of import volume comes from on-premises consumption, including
67
restaurants, bars, and other public eating and drinking places.
Thus,
imported beer has not affected the direct business of national and
regional brewers, but imports has filled a niche for superpremium beers.
V.4
Alternative Models
The purpose of this section is to provide several alternative
models to analyze the fragility of the results.
This analysis is due to
the work of Edward E. Leamer (1983) who argues:
I believe serious attention to two words
would sweeten the atmosphere of econometric
These are whimsy and fragility.
disclosure.
In order to draw inferences from data as
described by econometric texts, it is necess­
ary to make whimsical assumptions.
The prof­
essional audience consequently and properly
withholds belief until an inference is shown
to be adequately insensitive to the choice of
assumptions.
In an empirical study such as this, it is important to address how the
conclusions are sensitive to alternative model specifications.
Tremblay (1987) finds that technology has changed considerably in
the U.S. brewing industry during the period 1950-1978.
In order to
control for technological change that may affect marginal cost, a linear
time trend T (the sample period 1953-1988=1,2,3...36) is included.
This
variable serves to capture the technological effects of learning by
doing and organizational changes allowing for the more efficient use of
existing inputs.
Table V-3 shows that the time-trend variables are not
significantly different from 0 in the supply relation for both strategic
groups (t-ratio = -0.85 for group N, and 0.94 for group R).
In addit­
ion, the other parameter estimates in the model are fairly insensitive
to the inclusion of this time trend.
Kerkvliet et al. (1993) find a structural break between the 1950-71
and the 1972-1988 regimes in the cost function of the U.S. brewing
industry.
Therefore, a disjointed time trend, T72 (which equals 1 for
the period 1972-1988=1,2,3,..17, and 0 otherwise) is used to capture
68
this possible structural break in technology.
Table V-4 shows that the
variable T72 is not significantly different from 0 in the supply rela­
tion for both strategic groups (t-ratio = 1.08 for group N, and
-1.01 for group R).
The values and signs of other parameter estimates
in the model show little change in general.
A dummy variable D72 that equals 1 for observations that range from
1972-1988 and 0 otherwise is also used to capture this possible struc­
tural break in technology.
Table V-4 indicates that the D72 variable is
not significant for either group.
Other parameter estimates of this
specification are still the same in general.
Thus, the parameters of demand and supply functions appear fairly
insensitive to the assumption of technological changes.
PNN'
PRR'
PNR,
PNM'
ORN'
All signs of
pRm are exactly the same as in the primary model.
The effects of income the beer drinking population, and advertising are
consistent in general.
*RN' and
The conjectural elasticities, 6NN' *NR' ONM'
are e fairly consistent in estimated values and signs.
6RR'
69
<Table V-3>
Alternative Model (T)
Estimate
Parameter
Approx.
Std Err
'T'
Ratio
Label
Group N Demand
- 0.678
- 1.173
- 0.707
3 ON
P NN
PNR
P1N
2N
133N
4N
-1.783
0.00005
0.105
0.00003
-0.00001
Intercept
0.414
0.183
0.235
1.298
0.00003
0.019
0.00002
8.2E-6
-1.64*
-6.40***
-3.00**
-1.37*
1.53*
5.35***
1.88**
-1.77*
0.370
0.216
0.157
1.143
0.00003
0.017
8.3E-6
0.00002
3.90***
-1.52*
-2.56**
-1.69*
1.88**
-0.93
0.05
1.59*
0.470
6.455
5.752
0.008
97.320
0.107
0.040
0.015
0.444
0.721
2.176
Intercept
1.93**
PL
-1.76**
PM
-0.90
-2.80***
"
1/2
(PL*PM)
0.80
pL*K 1/2
3.09***
(pmk)1/2
0.25
-0.85
Group N Own-CE
0.58
1.89**
Group N Cross-CE to R
Group N Cross-CE to M
0.10
2.849
18.998
13.210
0.023
93.773
0.301
0.189
0.018
1.181
1.055
1.623
0.64
0.40
-0.49
-0.05
-0.02
-0.46
0.78
0.94
-1.62*
-1.54*
-0.68
QN
QR
QM
POP
ADV
N
ADV
R
Group R Demand
1.444
O OR
- 0.328
- 0.405
- 1.930
(IP RR
aP RN
,PRM
0.00006
RP 1R
- 0.016
g 2R
4.2E-7
0.00003
a3R
4R
Intercept
QR
QN
QM
POP
ADVR
ADVN
Group N Supply
YON
Y 1N
Y 2N
Y3N
Y4N
Y5N
Y6N
7N
'NN
*NR
'NM
0.907
-11.359
- 5.519
- 0.022
77.978
0.330
0.010
- 0.013
0.256
1.360
0.213
Group R Supply
1.809
7.544
6.468
Y OR
Y 1R
Y 2R
Y3R
Y4R
ity5R
Y6R
Y7R
YRN
'RN
ORM
- 0.001
-1.849
-0.138
0.147
0.017
- 1,910
-1.627
- 1.103
Note)
*** 1%,
** 5%,
* 10% significance
Intercept
PL
PM
(pL*A)1/2
(pL*K)1/2
(pm*KRR) 1/2
Group R Own-CE
Group R Cross-CE to N
Group R Cross-CE to M
Level
70
<Table V-4>
Alternative Model (T72.1
Estimate
Parameter
Approx.
Std Err
'T'
Ratio
Label
Group N Demand
13n0N
1NN
RNR
li;NM
1N
VN
VN
F4N
-0.596
-1.113
-0.674
-1.417
0.00004
0.102
0.00003
-0.00001
0.411
0.179
0.224
1.288
0.00003
0.019
0.00001
7.6E-6
-1.45*
-6.22***
Intercept
QN
QR
Qm
- 3.01**
1.10
1.23
5.33***
1.73**
1.58*
POP
ADV
N
ADVR
Group R Demand
13 OR
,FRR
aPRN
F1R
131R
2R
13F
3R
4R
0.374
1.455
0.210
-0.319
0.157
-0.401
1.154
-1.890
0.00006
0.00003
0.017
-0.017
5.1E-7
8.1E-6
-0.00003
0.00002
3.88***
1.52*
2.55**
1.64*
1.87**
-0.98
0.06
-1.55*
Intercept
QR
QN
Qm
POP
ADV
R
ADVN
Group N Supply
YON
YIN
Y3N
Y4M
Y5N
Y6N
Y7R
.1.5NN
YNR
ONM
0.847
-5.277
-0.034
-0.019
-18.909
0.283
0.027
0.031
-0.111
0.944
-4.404
0.417
5.146
3.608
0.007
65.191
0.095
0.035
0.028
0.241
0.598
3.841
Intercept
2.03**
PL
-1.03
PM
-0.01
K.
-2.75***
"
1/2
(PL*PM)
-0.29
(PL*K )
1/2
2.97***
(pm*4)1/2
0.77
T 72
1.08
Group N Own-CE
-0.46
1.58* Group N Cross-CE to R
Group N Cross-CE to M
-1.15
1.455
8.491
8.121
0.012
52.587
0.149
0.138
0.017
1.101
0.378
1.932
Intercept
2.37***
PL
-0.57
PM
-1.88**
K
-1.11
(pL*6)1/2
1.41*
(pL*K 0/2
0.22
(pm*K:) 1/2
1.75**
T
-1.01
72
Group R Own-CE
-1.65*
Group R Cross-CE to N
-2.02*
Group R Cross-CE to M
0.92
Group R Supply
YOR
11R
Y2R
Y3R
4R
15R
Y6R
Y7R
6RR
4RN
ORM
3.447
-4.830
-15.285
-0.014
74.351
0.033
0.243
-0.018
-1.822
-0.764
1.780
Note)
*** 1%,
** 5%,
* 10% significance
level
71
<Table V-5>
Alternative Model (D72.1
Estimate
Parameter
Approx.
Std Err
'T'
Ratio
Label
Group N Demand
0.619
-1.148
,3,
10N
Fa'NN
- 0.664
a'NR
1.623
0.00005
0.101
0.00003
-0.00001
p.IM
pN
Fa'2N
N3N
P4N
0.411
0.184
0.232
1.308
0.00003
0.019
0.00002
8.1E-6
-1.50*
-6.24***
- 2.85***
- 1.24
1.46*
5.17***
1.82**
-1.79*
Intercept
QN
QR
QM
Y
POP
ADV
N
ADV
R
Group R Demand
0.372
1.455
0.216
0.270
0.159
0.377
1.154
1.916
0.00006
0.00003
0.017
-0.020
8.5E-6
3.4E-6
0.00002
-0.00002
'OR
.
RR
aPRN
aPRM
Pa1R
aP3R
'33R
P4R
3.90***
- 1.25
- 2.37**
1.66*
1.91**
-1.17
0.40
1.31
Group N Supply
YON
YIN
Y2N
Y3N
14N
Y5N
YoN
Y7N
(5NN
IIINR
ONM
Intercept
QR
QN
QM
Y
POP
ADVR
ADVN
0.785
6.401
0.443
-0.021
-16.101
0.303
0.032
0.072
0.090
1.113
1.307
0.440
5.655
3.980
0.007
73.829
0.103
0.038
0.055
0.250
0.676
0.926
1.79**
-1.13
0.11
Intercept
- 2.78**
K,,
3.507
4.978
-17.039
-0.014
87.822
0.028
0.269
-0.086
-2.162
-0.636
0.604
1.395
8.143
7.925
0.012
52.566
0.141
0.134
0.073
1.599
0.378
0.602
Intercept
2.51**
PL
0.61
PM
2.15**
K
1.20
(PL*44)1/2
1.67*
(PL*KR)1/2
-0.20
(pm*KR)1/2
2.01**
D
72
1.17
1.35*
Group R Own-CE
1.68*
Group R Cross-CE to N
1.00
Group R Cross-CE to M
PL
PM
,,i
i,
(PL*PM) '''
-0.22
(PL*KN),1/2
2.94***
(PM*KN)1/`
0.85
D
72
1.30
Group N Own-CE
0.36
Group N Cross-CE to R
1.65*
-1.41*
Group N Cross-CE to M
Group R Supply
YOR
Y112
Y2R
13R
Y4R
Y5R
Y6R
Y 7R
(RR
11JRN
ORM
Note)
***
17.,
** 5%, * 10% significance
level
72
CHAPTER VI: SUMMARY AND CONCLUSIONS
This study provides the first synthesis of strategic group theory
and the NEIO approach in the international trade analysis.
Data from
the U.S. brewing industry are used to analyze the implications of the
model.
This is an imperfectly competitive industry with national and
regional strategic groups in the presence of growing import competition.
The main purpose of this thesis is to examine the following questions:
(1) How do import and strategic group competition affect the behavior
of national and regional U.S. brewing companies?
(2) To what extent do national and regional U.S. brewing companies have
market power?
Using the New Empirical Industrial Organization (NEIO) approach,
the conjectural variation technique is utilized to capture strategic
behavior and measure market power under the assumption that firms
maximize the profits.
This thesis estimates directly the own- and
cross-conjectural elasticities and the Lerner indexes incorporating firm
behavior in competing with rivals inside and outside each strategic
group.
The empirical results show the following conclusions about import
and strategic group competition and market power in the U.S. brewing
industry.
First, national brewers behave like Bertrand-type competitors
inside their own group, and regional firms face more within-group
competition than national firms: the estimated own-conjectural elastici­
ty for group N (SNN = -0.005) is not different from 0, and that for
group R (
5RR
2.003) is different from 0 at the 5% significance level.
Second, national brewers expect a cooperative or accommodating
response from regional brewers when national brewers change their
output.
Alternatively, regional producers expect an aggressive response
from national producers when regional producers change their output.
In
other words, regional brewers are exposed to more competition from
national producers than the reverse: the estimates for the cross-conjec­
73
1.213 for group N and t RN = -0.837 for group
tural elasticities /*
, TNR
R) are different from 0 at the 5% significance level.
Third, neither national nor regional producers expect a response
from import producers when national and regional producers change their
output levels.
It is possible that imported beers serve a niche market.
This may explain why there is little rivalry between imports and
domestic producers: the estimates for the cross-elasticities (tNN =
-1.663 for group N and
111Rm
= 0.249 for group R) are not different from 0
at the 5% significance level.
Fourth, neither national producers nor regional producers behave
like Bertrand competitors overall: the null hypotheses
IIINR = ONM
( 5NN
t RN = ORm = 0 for group R) are both rejected at
0 for group N and 6RR ..
.
the 5% significance level.
In other words, the brewing industry is
imperfectly competitive.
Fifth, national firms exert a higher degree of market power than do
regional firms: the estimated LN = 1.539 and LR = -1.826 are different
from 0 at the 5% significance level.
In addition, the national group
and the regional group exert significantly different degrees of market
power, implying that national brewers have greater mobility barriers
However,
than regional firms.
the average market power of the brewing
industry as a whole is not significantly different from zero.
Sixth, the market power of national firms is not harmed by the
competition from regional firms or imported beers: *NR /ENR
1.539 is
different from 0 and ONN/ENN is not different from 0 at the 5% signifi­
cance level.
On the other hand, the market power of regional brewers is
harmed by the rivalry from national brewers, but it is not affected by
import competition:
not
ID
.
RNI ERN
1.430 is different from 0, and ORm/ERN is
different from 0 at the 5% significance level.
That is, imported
beer does not appear to compete directly with the products of the
national and regional brewers.
Additional research may fruitfully be directed to specifying and
testing the relationship between import competition and market power
74
exerted by strategic groups if the model applies to an industry with
greater import competition.
75
BIBLIOGRAPHY
Alchian, Armen, and Allen, William, 1964, University Economics,
Belmont, CA, Wadsworth Publishing Co. pp. 383-393.
Appelbuam, Elie, 1979, Testing Price Behavior, Journal of Econometrics,
9(3), February, pp. 283-294.
Appelbaum, Elie, 1982, The Estimation of The Degree of Oligopoly Power,
Journal of Econometrics 19(3/2), August, pp. 287-299.
Appelbaum, Elie and Berechman Joseph, 1991, Demand Conditions,
Regulations, and the Measurements of Productivity, Journal of Econometr­
ics, 47(4), pp. 379-400.
Aw, Bee-Yan, 1991, Estimating the Effect of Quantitative Restrictions
in Imperfectly Competitive Markets: The Footwear Case, Empirical
Studies of Commercial Policy, edited by Baldwin, R.E., The university of
Chicago Press, pp. 201-218.
Aw, Bee-Yan, 1992, An Empirical Model of Make-Ups in a Quality-Differen­
tiated Export Market, Journal of International Economics, 33(3/4), Nov.,
1992, pp. 328-344.
Azzam, A.M. and Pagoulatos, E., 1990, Testing Oligopolistic and
Oligopsonistic Behavior: An Application to the U.S. Meat-Packing
Industry, Journal of Agricultural Economics, 41(3), September,
pp. 362-370.
Bain, Joe S., 1956, Barriers to New Competition, Cambridge: Harvard
University Press
Baker, Jonathan B., and Bresnahan, T.F., 1988, Estimating the Residual
Demand Curve Facing a Single Firm, International Journal of Industrial
Organization, 6, pp. 283-300.
Bernstein, J.I. and Mohnen, P., 1991, Price-Cost Margin, Exports
and Productivity Growth: with an Application to Canadian Industries,
Canadian Journal of Economics, 24(3), August, pp. 638-659.
Beverage Industry, 1980 - 1990, Magazines for Industry, Cleveland,
Ohio.
Beach and McKinnon, 1978, A Maximum Likelihood Procedure for Regression
with Autocorrelation Errors, Econometrica, 46, pp. 51-58.
Bhagwati, J., 1965, On the Equivalence of Tariffs and Quotas,
Trade, Growth, and the Balance of Payments, edited by Baldwin, R.E.,
North-Holland, pp. 867-872.
Binger, Brian R. and Hoffman, Elizabeth, 1988, Microeconomic with
Calculus, Scott, Foresman and Company.
Bloch, Harry, 1974, Prices, Costs, and Profits in Canadian Manufactur­
ing: the Influence of Tariffs and Concentration, Canadian Journal of
Economics 7(4), November, pp. 594-610.
Brander, J.A. and Spencer, B.J., 1985, Export subsidies and
International Market Share Rivalry, Journal of International Economics,
18, 1985, pp. 83-100.
76
Bresnahan, Timothy F., 1989, Empirical Studies of Industries with
Market Power, Handbook of Industrial Organization, Richard Schmalensee
and Robert Willig, Amsterdam, North-Holland Publishers, pp. 1011-57.
Breusch and Pegan, 1980, The LM Test and Its Application to Model
Specification in Econometrics, Review of Economic Studies, 47, pp. 239­
254.
Breusch, T., 1978, Testing for Autocorrelation in Dynamic Linear Models,
Australian Economic Papers, 17, pp. 334-355.
Brown, Paul B., 1988, Matters of Import, Incorporate, October, pp. 115­
116.
Browning, K and Browning, M, 1989, Microeconomic Theory and Applica­
tions, Third Edition, Scott, Foresman.
Brazen, Yale, 1971, Bain's Concentration and Rates of Return Revisited,
Journal of Law and Economics, 14, pp. 351-69
Buschena, D.E. and Perloff, J.M., 1991, The Creation of Dominant Firm
Market Power in the Coconut Oil Export Market, American Journal of
Agricultural Economics, 73(4), November, pp. 1000-1008.
Bulow J., Geanakoplos J., and Klemperer P., 1985, Multi-market Oligopo­
ly: Strategic Substitutes and Complements, Journal of Political Economy,
93(3), pp. 488-511.
Carlton, Dennis W. and Perloff, Jeffery M., 1990, Modern Industrial
Organization, Scott, Foresman and Company.
Carroll, Glenn R. and Swaminathan, Ananda, 1992, The Organizational
Ecology of Strategic Groups in the American Brewing Industry from 1975
to 1990, Industrial and Corporate Change, 1(1), pp. 65-97.
Carroll, Glenn R. and Swaminathan, Ananda, 1993, On Theory, Breweries,
and Strategic Groups (A Reply to Tremblay), Industrial and Corporate
Change, 2(1), pp. 99-106.
Caves, Richard E., 1985, International Trade and Industrial Organiza­
tion, European Economic Review 28(3), August, pp. 377-395.
Caves, Richard E. and Porter, M.E., 1978, From Entry Barriers to
Mobility Barriers: Conjectural Decisions and Contrived Deterrence to New
Competition, Quarterly Journal of Economics 91(2), May, pp. 241-261.
Cowling, Keith and Sugden, Roger, 1989, Exchange Rate Adjustment and
Oligopoly Pricing Behavior, Cambridge Journal of Economics 13,
pp. 373-393.
Cubin, John S., 1988, Market Structure and Performance
The Empirical
Research, Fundamentals of Pure and Applied Economics, 28 Harwood
Academic Publishers, pp. 547-552.
Demsetz, Harold, 1973, Industry Structure, Market Rivalry, and Public
Policy, Journal of Law and Economics, 16, pp. 1-9.
DeRosa, Dean A. and Goldstein, Morris, 1981, Import Discipline in the
U.S. Manufacturing Sector, IMF Staff Papers 28(3), September,
pp. 600-634.
Domowitz, I., Hubbard, R.G. and Petersen, B.C. 1986., "Business Cycles
and the Relationship between Concentration and Price-Cost Margins", Rand
Journal of Economics, 17, pp. 1-17.
77
Eaton, J. and Grossman, G.M., Optimal Trade and Industrial Policy under
Oligopoly, Quarterly Journal of Economics, 101, pp. 383-406.
Elzinga, Kenneth G., 1992, The Beer Industry, The Structure of American
Industry, edited by Walter Adams, Macmillan Publishing Co., pp. 218-248.
Esposito, Louis and Esposito, Frances Ferguson, 1971, Foreign Competi­
tion and Domestic Industry Profitability, Review of Economic and
Statistics, 53(4), November, pp. 343-353.
Gasmi,F., Laffont,J. and Vuong, Q., 1990, A Structural Approach to
Empirical Analysis of Collusive Behavior, European Economic Review,
34(2/3), May, pp. 513-523.
Geroski, P.A., 1982, Simultaneous Equations Models of the Structure-
Performance Paradigm, European Economic Review, 19(1), pp. 145-158.
Godfrey, 1978, Testing against General Autoregressive and Moving Average
Error Models When the Regressors include Lagged Dependent Variables,
Econometrica, 46, pp. 1293-1302.
Gollop, Frank M. and Roberts, Mark J., 1979, Firm Interdependence in
Oligopolistic Markets, Journal of Econometrics, 10(3), August, pp. 313­
331.
Greene, William H., 1990, Econometric Analysis, Macmillan Publishing
Co., New York.
Greer, Douglas F., 1971, Product Differentiation and Concentration in
the Brewing Industry, Journal of Industrial Economics, 19(3), July, pp.
201-219.
Greer, Douglas F., 1981, The Causes of Concentration in the US Brewing
Industry, Quarterly Review of Economics and Business, 21 (4), Winter,
pp. 87-106.
Hallagan, William and Joerding, Wayne, 1983, Polymorphic Equilibrium in
Advertising, Bell Journal of Economics, 14(1), pp. 191-201.
Harrigan, Kathryn R., 1985, A Application of Clustering for Strategic
Group Analysis, Strategic Management Journal
6(1), Jan-Mar., pp. 55­
,
73.
Hatten, Kenneth J. and Schendel Dan E., 1977, Heterogeneity within an
Industry: Firm Conduct in the Brewing Industry, 1952-71, The Journal of
Industrial Economics, 26(2), December, pp. 97-113
Hatten, Kenneth J. and Schendel, Dan E. and Cooper, Arnold C., 1978, A
Strategic Model of the U.S. Brewing Industry: 1952-1971, Academy of
Management Journal, 21(4), pp. 592-610.
Hatten, Kenneth J. and Hatten, Mary Louise, 1985, Some Empirical
Insights for Strategic Marketers: The Case of Beer, Strategic Marketing
and Management, John Wiley and Sons Ltd., pp. 275-292.
Hatten, Kenneth J. and Hatten, Mary Louise, 1987, Strategic Groups,
Asymmetric Mobility Barriers and Contestability, Strategic Management
Journal, 8(4), July-Aug., pp. 329-342.
Hausman, J.A., 1978, Specification Tests in Econometrics, Econometrica,
46, November, pp. 1251-1271.
Hogarty, Thomas F. and Elzinga Kenneth G., 1972, The Demand for Beer,
Review of Economics and Statistics, 54(2), May, pp. 195-198.
78
Hwang, Hong, 1984, Intra-industry Trade and Oligopoly: A conjecture
Variations Approach, Canadian Journal of Economics, 17(1), pp. 126-137.
Iwata, G., 1974, Measurement of Conjectural Variations in Oligopoly,
Econometrica, 42(5), September, pp. 947-966.
Jacquemin, Alexis, 1982, Imperfect Market Structure and International
Trade - Some Recent Research, Kyklos, 35, pp. 75-93
Jacquemin, Alexis and Ghellinck, E.D. and Huveneers, Christian, 1980,
Concentration and Profitability in A Small Open Economy, The Journal of
Industrial Economics, 29(2), December, pp. 131-144.
Johnson, J.A. and Oksanen, E.H., 1977, Estimation of Demand for Alcohol­
ic Beverages in Canada from pooled time series and cross sections,
Review of Economics and Statistics, 59, pp. 113-18.
Judge, George J., Hill,R.C., Griffith, W.E., Lutkepohl, H., Lee, Tsoung-
Chao, 1988, Introduction to the Theory and Practice of Econometrics,
Second Edition, John Wiley and Sons.
Karrenbrock, Jeffery D., 1990, The Internationalization of the Beer
Brewing Industry, Review of the Federal Reserve Bank of St. Louis,
72(6), Nov/Dec, pp. 3-13.
Kmenta, Jan, 1986, Elements of Econometrics, Macmillan Publishing Co.,
New York.
Krekvliet J., Nebesky, W., Tremblay, C., and Tremblay, V., 1995,
Technological Change and the Nature of Inefficiency in the U.S. Brewing
Industry: A Reinterpretation, A working Paper, OSU, April.
Krugman, P. R., 1979, Increasing Returns, Monopolistic Competition and
International trade, Journal of International Economics, 9(4),
pp. 469-79.
Krugman, P. R., 1989, Industrial Organization and International Trade,
Handbook of Industrial Organization, Vol.II, edited by Schmalensee, R.
and Willig, R.D., Elsevier Science Publisher, pp. 1179-1223.
Krugman, P. R. and Obstfeld, M, 1991, International Economics: Trade and
Policy, Harper Collins Publisher.
Learner, Edward E., 1983, Let's Take the Con out of Econometrics,
American Economic Review, 73(1) March, pp. 31-43.
Lee, Byunglak and Tremblay, Victor J., 1992, Advertising and the U.S.
Market Demand for Beer, Applied Economics, 24, pp. 69-76.
Leontief, W, 1968, Domestic Production and Foreign Trade:
The American Capital Position Re-examined, Readings in International
Economics, edited by R.E.Caves and H.G. Johnson, Homewood:Irwin, pp.
1002-1013.
Linder, S. B., 1961, An Essay on Trade and Transformation,
New York, Wiley.
Lyke, Rick, 1986, Regional Beers an Alternative to Imports or National
Brands, Hotel and Motel Management, 201, April 28, p. 66.
Maddala, G.S., 1988, Introduction to Econometrics, Macmillan Publishing
Co., New York.
79
Marvel, Howard P., 1980, Foreign Trade and Domestic Competition,
Economic Inquiry, 18(1), January, pp. 103-122.
McGee, John and Thomas, Howard, 1986, Strategic Groups: Theory, Research
and Taxonomy, Strategic Management Journal, 7(2), pp. 141-160.
Melo, Jaime de and Urata Shujiro, 1986, The Influence of Increased
Foreign Competition on industrial Concentration and Profitability,
International Journal of Industrial Organization, 4, pp. 287-304.
Modern Brewery Age, 1960-1989, Business Journal.
Nelson, Randy A., 1984, Regulation, Capital Vintage, and Technical
Change in the Electric Utility Industry, Review of Economics and
Statistics, 66(1), February, pp. 59-69.
Newman, Howard H., 1978, Strategic Groups and the Structure-Performance
Relationship, Review of Economics and Statistics, 60 (3), August, pp.
417-427.
Nicholson, Walter, 1989, Microeconomic Theory: Basic Principles and
Extensions, The Dryden Press, Fourth Edition.
Nicholson, W., 1989, Microeconomic Theory: Basic Principles and Exten­
sions, Fourth Edition, Dryden.
Oster, Sharon, 1982, Intraindustry Structure and the Ease of Strategic
Change, Review of Economics and Statistics, 64(3), August, pp. 376-383.
Pagoulatos, Emilio, 1992, Empirical Studies of Industrial Organization
and International Trade: Selective Survey, Proceedings of a Workshop On
Industrial Organization and International Trade, edited by Sheldon I.M.
and Henderson, D.R., The Ohio State University, pp. 31-51.
Pagoulatos, Emilio and Sorensen, Robert, 1976, Domestic Market Structure
and International Trade: An Empirical Analysis, Quarterly Review of
Economics and Business, 16(1), Spring, pp. 45-59.
Pagoulatos, Emilio and Sorensen, Roberts, 1976, Foreign Trade, Concen­
tration and Profitability in Open Economies, European Economic Review,
8(3), pp. 255-267.
Perloff, Jeffrey M., 1992, Econometric Analysis of Imperfect Competition
and Implications for Trade Research, Proceedings of a Workshop On
Industrial Organization and International Trade, edited by Sheldon I.M.
and Henderson, D.R., The Ohio State University, pp. 58-105.
Pompelli, Gregory K. and Pick, Daniel H., 1990, Pass-Through of Exchange
Rates and Tariffs in Brazil-U.S. Tobacco Trade, American Journal of
Agricultural Economics, 72, pp. 676-681.
Porter, Michael E., 1979, The Structure within Industries and Companies'
Performance, Review of Economics and Statistics, 61 (2), May, pp. 214­
227.
Porter, Michael E., 1980, Competitive Strategy, The Free Press, A
division of MacMillan Publishing Co., Inc., New York.
Pugel, Thomas A., 1980, Foreign Trade and U.S. Market Performance,
The Journal of Industrial Economics, 29, December, pp. 119-129.
Roberts, M. and Samuelson, L., 1988, An Empirical Analysis of Dynamic
Competition in an Oligopolistic Industry, Rand Journal of Economics,
19(2), Summer, pp. 200-220.
80
Rosenbaum, David I. and Reading, Steven L., 1988, Market Structure
and Import Share: A Regional Market Analysis, Southern Economic Journal,
54(3), January, pp. 694-700.
SAS/ETS User's Guide, Version 6, First Edition, SAS institute Inc.
Saving, Thomas A., 1970, Concentration Ratio and The Degree of Monopoly,
International Economic Review, 11(1), February, pp. 139-146.
Scherer F.M., 1971, Industrial Market Structure and Economic
Performance, Rand McNally Co.
Schmalensee, Richard, 1990, "Empirical Studies of Rivalous Behavior"
in Giacomo Bonnano and Dario Brandolini (editors), Industrial Structure
in the New Industrial Economics, Oxford: Clarian Press.
Schroeter, J. and Azzam, A., 1990, Measuring Market Power in
Multi-Product Oligopolies: The U.S. Meat Industry, Applied Economics,
22(10), October, pp. 1365-1367.
Strickland, Allyn D. and Weiss, Leonard W., 1976, Advertising,
Concentration and Price-Cost Margins, Journal of Political Economy,
84(5), pp. 1109-1121.
Tang, Ming-Je and Thomas, Howard, 1992, The Concept of Strategic
Groups: Theoretical Construct or Analytical Convenience, Managerial
and Decision Economics, 13, pp. 323-329
Thomas, J.M., 1989, An Empirical Investigation of Product Differentia­
tion and Pricing Strategy: An Application to the Household Goods
Motor Carrier Industry, Southern Economic Journal, 56(1), July,
pp. 64-79.
Tremblay, Victor J., 1985, Strategic Groups and The Demand for Beer,
The Journal of Industrial Economics, 34(2), December, pp. 183-198.
Tremblay, Victor J., 1987, Scale Economies, Technological Change,
and Firm-Cost Asymmetries in the U.S. Brewing Industry, Quarterly Review
of Economics and Business, 27(2), Summer, pp. 71-86.
Tremblay, Victor J. and Tremblay, Carol H., 1988, The Determinants
of Horizontal Acquisitions: Evidence from the U.S. Brewing Industry,
The Journal of Industrial Economics, 27, September, pp. 21-45
Tremblay, Victor J., 1993, The Organizational Ecology of Strategic
Groups in the American Brewing Industry: A Comment, Industrial and
Corporate Change, 2(1), 1993, pp. 91-97.
Tremblay, Victor J. and Tremblay, Carol H., 1995, Advertising, Price,
and Welfare: Evidence from the U.S. Brewing Industry, Southern Economic
Journal, 62(2), October, pp. 367-381.
Varian, Hal R., 1984, Microeconomic Analysis, W.W.Norton & Company,
Inc., Second Edition.
White, Lawrence J., 1974, Industrial Organization and International
Trade: Some Theoretical Considerations, American Economic Review, 64(6),
December, pp. 1013-1020.
Williamson, Peter J., 1986, Multinational Enterprise Behavior and
Domestic Industry Adjustment Under Import Threat, Review of Economics
and Statistics, 58(3), pp. 359-68.
81
Yamawaki, Hideki, 1986, Exports, Foreign market Structure, and Profit­
ability in Japanese and U.S. Manufacturing, Review of Economics and
Statistics, 68, pp. 618-627.
Yamawaki, Hideki and Audretsch, David B., 1988, Import Share Under
International Oligopoly with Differentiated Products: Japanese Imports
in U.S. Manufacturing, Review of Economics and Statistics, 70(4),
November, pp. 569-579.
Zellner and Theil, 1962, Three Stage Least Squares: Simultaneous
Estimation of Simultaneous Relations, Econometrics, 30, pp. 54-78.
United States Brewers' Association, 1957-1989, Brewers Almanac, United
States Brewers Association, Washinton D.C.
82
APPENDIX
83
THE SAMPLE MEASUREMENT OF VARIABLES AND SOURCES OF DATA
The
The data consist of 36 annual observations from 1953 to 1988.
endogenous variables are PN, PR, QN, and QR.
PN (PR) is the average real
market price of group N (group R) beer per barrel.
They are measured as
the total revenue divided by the number of barrels sold by group N
(group R) and are deflated by the CPI (Consumer Price Index: 1982­
84=100).
The total revenue for group N is measured by aggregating the
average revenue of Anheuser-Busche (A-B) and Pabst for the period of
1953-55,
A-B, Schlitz and Pabst for 1956-81, A-B and Pabst for 1982,
and A-B for 1983-88. 41
The total revenue of the firm is taken from
Moody's Industrial Manual and Moody's OTC Industrial Manual.
Total
revenue for group R is measured by subtracting group N's total revenue
from the industry total revenue.42
QN (QR) is per-capita consumption of group N (group R) beer.
They
are measured in barrels and are put into per-capita terms by dividing
the total output sold by group N (group R) by the U.S. population of 18
years of age and older.
The output sold by group N is taken from Moody­
's Industrial Manual and Moody's OTC Industrial Manual.
The output sold
by group R is measured by subtracting the output by group N from the
quantity of the industry total output that is taken from Advertising Age
(various issues).
The exogenous variables in the demand equations are QM, ADVN
(ADVR), Y, and POP.
QM equals per-capita consumption of imported beer.
It is measured in barrels by dividing the total quantity of imported
beer per year that is taken from Brewers Almanac (Various issues) by the
U.S. population of 18 years of age and older.
ADVN (ADVR
is real
)
41
Miller is excluded since it is a conglomerate firm, so that its
beer revenue data are not available, and the corresponding aggregate
output is used to calculate P. The reason why Schlitz and Pabst exit the
sample data is that Schlitz went out of business in 1982, and Pabst became
a regional producer in 1983.
42 Group N's total revenue is measured as the average revenue for
group N (as defined above) times the total output of all national
producers (including Miller).
84
advertising expenditures in thousand dollar incurred by group N (group
R) and are deflated by the CPI.
The advertising expenditures of group N
(group R) are obtained by summing the total advertising expenditure of
the firms belonging to group N (group R).
The total advertising
expenditure of the firm is obtained from Advertising Age for the period
1953-1984 and from The Beer Industry Update for 1984-88.
Y is real per capita disposable income, taken from U.S. Bureau of
the Census.
POP is the percent of the U.S. population that drink beer,
measured as the percentage of population weighted by index of beer
consumption in various age group (18 years of age and older) over the
U.S. total population.
The index of beer consumption in various age
group is taken from Advertising Age (16 January, 1984).43
The total
population by age group is taken from The U.S. Statistical Abstract.
The explanatory variables in the marginal cost functions are PL,
PM, and KN (KR).
try.
PL is the real price of labor in the U.S. beer indus­
It is measured as the average wage per hour for production workers
in the beer industry and is deflated by the PPI (Producer Price Index:
1982=100).
The average wage per hour is taken from Brewers Almanac
(Various Issues).
try.
PM is the real price of materials for the beer indus­
It is measured by weighted average price of important materials:
malt, corn, rice, sugar, barley, and hops44 and is deflated by the PPI.
The material weights in the production of beer are measured by the
fraction of each material in pounds per barrel, which are taken from
Brewers
Almanac.
The prices of materials are taken from Commodity Year
Book and Agricultural Statistics.
KN (KR) is the capital stock of group
N (group R) in the beer industry.
They are measured as group production
capacity in millions of barrels per year.
Digest, Brewer's Guide and Directory.
They are taken from Brewer's
The CPI and PPI are obtained from
43 The indexes of beer consumption by age group are as follows: 61%
of the 18-24 year-old population drink beer, 58% of the 25-34 age group,
44% of the 35-49 age group, 26% of the 50-64 age group, and 24% of those
65 years and over [Lee and Tremblay (1992)].
44 Following Tremblay (1987), only materials contributing at least 0.1
pounds per barrel of beer are included.