Industrial Organization
The central research question in industrial organization is:
“How can the behavior and performance of firms and markets
be explained and predicted with observable data?”
IO economists apply microeconomic theory and econometrics
to study firms and markets – theoretical and empirical
work are both important
There are several implications for business strategy and
public policy – public policy is often the focus of the
analysis
Industrial Organization
• The main goal in industrial organization is to understand
how firms strategically interact in well-defined markets
• Ideally, we want to be able to use observable variables to
predict firm behavior, profits, and social welfare at the
level of particular markets
• IO is particularly concerned with how government
intervention influences firm behavior and market
performance
• Antitrust policy, regulatory policies, patent policies, etc.,
are all important
Main Approaches
• The typical approach in theoretical IO is to use a formal
game theoretic model with profit maximizing firms
• The firm as a strategic agent is the unit of analysis; the
implications for market performance are critical outcomes
• IO approaches often downplay differences in resources and
capabilities at the firm level and focus on the implications
of “pure” strategic interaction
• This is in contrast to the strategy literature, where much of
the focus is on how differences in resources and
capabilities influence strategic choices
Key Concepts: Defining the Market
• Most theoretical models in IO focus on strategic
interaction in a well defined market (in contrast to
Strategy, where the choice of which industries to operate in
is a key issue of interest)
• In a model, it is easy to define the boundaries of a market;
in reality it is more difficult to do so
Market Boundaries
1. What is the relevant product?
• Most large firms produce several different products
• Even if we focus on a particular product it is difficult to
draw industry boundaries
• For example, should desktop computers be in the same
industry as laptops?
• In practice, we need to determine how substitutable the
products are and how similar the production processes are
• The boundaries are often determined by data availability
Market Boundaries
2. What is the relevant geographic area?
• Often data is available only within the U.S. at the national
level, and it may include only domestic firms
• This is problematic for several reasons:
• First, in many industries the largest U.S. firms sell
products all over the world – their market is not confined
to the U.S.
• For example, many banks argue that they need to be large
in order to compete effectively in the international market
for loans
Second, some industries have natural regional boundaries
within the U.S.
• For example, how many movie theater chains operate in
the Inland Empire?
• Edwards, AMC, not many others, yet nationally there are
many more firms
Third, imports are often obtain a high share of the domestic
market, as in the automobile industry
• Neither business strategists nor public policy makers
would analyze the domestic automobile industry without
considering Honda, Toyota, and the other foreign
automobile manufacturers
Market Boundaries
3. What about dynamics?
• Suppose we follow an industry over time
• There may be substantial turnover in the leading firms, the
products sold, the product processes employed, etc.
• Consider video games or computers
• Even in non high-tech industries the environment evolves
over time
Most Real-World Industries are Oligopolies
It is unusual to observe an industry with no large firms or only one large firm
Typically some firms are larger and more profitable than most of their competitors
Firms differ along many dimensions:
products, production processes, organizational forms, brand names, location,
distribution networks, etc.
Those that are able to sustain profits above the norm in their industry are said to
have a “competitive advantage”
The source of a competitive advantage is typically some resource or capability that
is difficult to imitate (particular technologies, trade secrets, brand names, etc.)
Industry Structure
Because oligopolies vary substantially, it is important to describe the structural
features of these industries
Key aspects of industry structure include:
The number and relative size of large firms
The degree of product differentiation
The barriers to entry and expansion
How much production processes vary
Structure-Conduct-Performance
Industrial Organization emerged as a distinct field of economics in the late
1930s, beginning with case studies of industries
The SCP paradigm led economists to make comparisons across industries;
it continues to influence economists and policy makers
The basic idea of SCP is that industry Structure determines Conduct (how
the firms behave, particularly with respect to pricing), and Conduct
determines Performance (measured using rates of return or price-cost
mark-ups)
In practice, the main link explored was between structure and performance
Barriers to Entry
• Barriers to entry are important in the SCP paradigm
because it takes an essentially static view of an industry:
perfect competition is ideal and monopoly is associated
with the largest welfare losses
• If entry and exit can occur easily, then it is difficult for the
established firms to collude or maintain prices above
marginal costs
• A barrier to entry is a cost of producing which is borne by
new entrants but not by established firms
• Determining whether something is a barrier to entry can be
tricky; assessing the welfare implications of a particular
barrier is even more tricky (consider patents)
Some Examples of Barriers to Entry
1.
2.
3.
•
Absolute Cost or Quality Advantages (trade secrets, cost
advantages due to learning, location)
Capital Requirements (new entrants may lack a
reputation and face high costs of raising funds)
Economies of Scale (new entrants may have to enter as
small, high cost firms or enter large and face the
difficulty of acquiring sufficient customers to sell their
output)
Innovation and Product Differentiation may be used to
get around entry barriers
Criticisms of SCP
Empirical studies have as a whole been inconclusive: at best there is weak
evidence of a link between market structure and performance
Game theory establishes that conduct is not determined completely by structure:
firm behavior must be considered independently of industry structure
Further, structure and performance both change over time
Causation is not just one-way:
High performance encourages entry through innovation or differentiation, which
affects structure
Low performance encourages exit or capacity reduction
Problems with Measuring Performance
There are several problems with measuring performance
Ideal measures of performance would be economic profits or the
difference between price and marginal cost
Unfortunately, measuring economic profits is extremely difficult
Several adjustments to accounting data must be made to measure assets
using replacement values, value investments and intangible assets, and
adjust for risk
Similarly, measures of marginal cost are typically unavailable, and
average cost must be used instead
Correlation vs. Causation
Even if a statistical link between performance and concentration is discovered, it
does not imply that concentration causes the performance
It could be that a third variable causes both high mark-ups and high concentration
The differential efficiency hypothesis is that large firms are large and profitable
because they are more efficient – they have cost advantages or better products
Thus, high concentration and high profits are observed together because
differential efficiency causes some firms to become large and profitable
Implications of Differential Efficiency
If the differential efficiency hypothesis is correct, breaking up firms in highly
concentrated industries is not a good idea
Breaking up these firms would punish them for being efficient and discourage
investments that improve efficiency
Empirical tests strongly support the differential efficiency hypothesis: a firm’s
profit is strongly correlated with its market share
In contrast, there is typically only a weak positive association between industry
profit and concentration
Dynamics
• The most interesting current approaches to industry
analysis focus on dynamics
• In a dynamic world, innovation becomes important, and
providing profit incentives for innovation is critical
• In a dynamic world, it is no longer the case that perfect
competition is ideal; it is essential for firms to obtain
profits above the norm when they innovate in order for
them to have the incentive to innovate in the first place
• Analyses of the links between market structure (or any
observable variables) and conduct and performance
become more difficult and more complex
Entry and Exit
• In a dynamic framework, it is critical to consider entry and exit
• Dunne, Roberts and Samuelson (1988) summarize the patterns of firm
entry, growth, and exit in 387 4-digit SIC Code U.S. manufacturing
industries
• Their data is census data, so they only observe each industry every five
years: 1963, 67, 72, 77, 82
• This implies that they underestimate turnover, because if a firm enters
and exits within the five year interval they never observe it
• The data is constructed from plant-level data collected in the Census of
Manufactures
• The data has the complete list of 7-digit products produced in each
plant, so even though the 4-digit categories change over time, it is
possible to group goods in a consistent way (just reconstruct from the
7-digit data)
Types of Entrants
They distinguish between three types of entrants:
1.
2.
3.
New firms
Existing firms that diversify into an industry by opening
a new plant
Existing firms that enter by altering the mix of outputs
they produce in their existing plants
Most entrants are new firms, and most are small
Diversifying firms are larger
Key Results
• On average, 93.4% of firms are single-plant firms, but they
account for only 17.1% of the value of production
• After deleting the smallest firms (those that together
produce 1% of the industry’s output), the average entry
rate varies from .31-.43; the exit rate varies from .31-.39
• On average, 38.6% of firms are new to the industry each
census year
• Entrants and exiting firms are small: entrants account for
15.8% of output, and the market share of exiting firms
varies from .144 to .191
• An entrant produces 35.2% of what an incumbent does on
average
Entry by Type
New firm, new plant entrants are
55.4% of the number of entrants
50.0% of entrant output
28.4% as large as incumbents
Diversifying firm, new plant entrants are
8.5% of the number of entrants
14.4% of entrant output
87.1% as large as incumbents
Diversifying firms who are changing their product mix in an old plant are
36.1% of the number of entrants
35.6% of entrant output
34.9% as large as incumbents
Exit by Type
Of entrants that exit, new firms that construct new plants are
the largest group of exiters
A relatively high proportion of diversifying firms who
constructed new plants survive over time
On the whole, entrants and exits tend to be smaller than
continuing firms
New firms that entered with new plants in the period 19631977 period were the majority of exits during 1963-1982
Variation
• There is a lot of variation in entry and exit rates within 2-digit sectors
and between 2-digit sectors: industries differ
• We can characterize how industries differ. It is not random, but
systematic:
• High entry rates today imply high entry rates tomorrow (the same
relationship holds for exit rates; high exit rates persist)
• Further, entry and exit rates are positively correlated
• This implies that there are high entry/exit industries and low entry/exit
(turnover) industries
• After correcting for industry effects by looking at deviations from
mean entry/exit rates, periods with above average entry are associated
with below average exit
Entry Cohorts
• The market share of an entry cohort is highest when it first
enters; then it declines
• Survivors tend to grow and failures are small
• The average size of survivors relative to the average size of
firms in the industry rises over time
• So the trend in market share is due to exit
• Exit rates for entry cohorts are quite high, with most of the
exit occurring in the first 5 years after entry
The Role of Small Firms
• It is important to clarify the role of small firms in evolving
industries
• Are small firms just stragglers that are likely to fail? Are
they innovators at the frontier? How do success and failure
probabilities depend on strategic choices and luck?
• The static perfect competition paradigm suggests that
entrants are important for maximizing welfare – they
depress prices and increase output
• The results of Dunne, Roberts, and Samuelson (1988)
suggest that while entrants might play this role, they do not
often become important firms in the industry
Small Firms in Evolving Industries
• In Filson and Gretz (2004), we consider the role of small
firms in high-tech industries
• Small firms enter to compete in innovation races; if a small
firm wins an innovation race it can either market the
innovation or license/sell it to an existing firm
• Thus, in this model, small firms can grow (if they market
their innovation successfully), profit through selling
technology, or simply fail
• The nature of the innovation and the nature of
environmental shocks are important for determining which
path occurs
Alliances
• Alliances are an important phenomena in modern high-tech
industries and in other industries where globalization is
important
• In the biotechnology industry there are complex webs of
alliances
• So far, few authors have attempted to study these
overlapping networks of alliances
• For example, research on biotechnology alliances could
clarify the roles that small biotechnology firms and large
pharmaceutical firms play in these networks
Additional Topics
• IO is too broad to summarize the various topics,
approaches and results in a simple way; corporate finance,
strategy, and the theory of the firm are relatively narrow
pursuits by comparison
• Instead, I will briefly review some of the main topics and
some interesting open questions; the list is by no means
exhaustive
• We have already talked about market structures and the
importance of understanding dynamic competition; I will
emphasize other topics
Pricing
• IO is concerned with pricing behavior; much of the
analysis is based on microeconomic price theory
• Price discrimination, nonlinear pricing, tie-in sales, pricing
durable goods, predatory pricing, and limit pricing have all
received attention in the literature
• Much of this work is quite mature and dates back to the
1950s and 1960s
• Recent research on pricing has focused on new
environments like the Internet that raise new issues:
bundling information goods (like software or music),
designing subscription models, considering
micropayments, etc.
Information and Advertising
• For those interested in behavioral economics, advertising
would make a useful application
• Traditional neoclassical approaches are poorly suited for
understanding advertising
• In standard microeconomic analysis, the utility function is
taken as given – you can inform a consumer about a good
but you cannot change his taste for it
• In reality, most advertising is persuasive, not informative:
it is designed to change consumer tastes
• We lack a good understanding of how this occurs
A Structural Model of Advertising
• Economists who study advertising typically assume it
shifts the consumer demand curve in some fashion, but this
is a “reduced form” model
• A structural model would allow a researcher to assess how
advertising works at the micro level (in the brain, perhaps)
• Such a model might allow firms to better optimize their
advertising strategies, and it would inform policy makers
about the potential impacts of alternative advertising
policies
Technological Change
• Much of modern IO is particularly concerned with
technological change and policies that influence
technological change
• Patents, copyrights, and trademarks are important objects
of analysis
• Joint ventures and alliances
• The effects of regulatory policies on technological progress
Antitrust Policy and Regulation
• Antitrust policy in the U.S. is based on Acts passed in the
late 1800s and early 1900s
• Since then we have learned a great deal about how
industries evolve, and many new devices that affect
competitive behavior (such as overlapping networks of
alliances) did not exist before
• Exploring what modern dynamic analysis can teach us
about appropriate antitrust and regulatory policies is likely
to be a fruitful research agenda
Theory vs. Empirical Work
• The ratio of theory to empirical work in industrial
organization is generally too high
• Small changes in assumptions in game theoretic models
often produce substantial changes in results (for example,
firms may do too much of x under one set of assumptions
and too little of x under another, where x can be just about
any strategic choice, such as product differentiation,
advertising, etc.)
• This would be ok if we could measure and quantify to
assess which set of assumptions is valid, but often this is
impossible because the models are too abstract (for
example, Cournot vs. Stackelberg? Neither is the truth)
Reaction
• One reaction to this problem is to simply abandon the
study of strategic interaction, but this is too extreme
• A useful approach is to combine theory with empirical
work
• Avoid theories that depend heavily on specific assumptions
about intricate strategic thinking and concentrate on those
that can be tied to observable data
• It is also important to try to verify assumptions as much as
possible – talk to industry participants if possible
• Few economists have produced useful insights in the
absence of data to guide them
Problems with Talking to Industry
Participants
There are several problems with talking to industry
participants that should be noted:
1. People may distort the facts to protect their interests
2. Practices and strategies often evolve over time; current
participants are often not deep thinkers or theorists who
continually evaluate standard industry practices, and
they may not be able to articulate why they do what they
do (Friedman’s example of the pool player is relevant)
3. Industry participants often use terms such as “risk”
“variable cost” and so on in different ways than
economists – it can be difficult to communicate
Problems with Industry Participants
4. Economists often rely on historical data, and it may be
difficult to find participants who recall industry events
with a high degree of accuracy
5. Participants may not want to talk to you at all; it is often
easier to get information from a disinterested party such as
a retired executive or consultant, but they may not have the
most relevant and up-to-date information
Trade journals and historical studies are alternative
information sources for learning about firms and markets