Part IIB Industry Empirical Studies Lecture 2: NEIO and Industry Models of Market Power

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Part IIB IndustryEmpirical StudiesLecture
2 NEIO and Industry Models of Market Power
Dr Christos Genakos
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OUTLINE

• NEIO and the Structural Approach
• Identification
• Estimation and Hypothesis Testing
• Examples Graddy (1995) Genesove and Mullin
  (1998)
• Reduced form and Non-Parametric approaches

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New Empirical Industrial Organization (NEIO)

• Most important weakness of the SCP paradigm was
  the lack of feedback mechanisms emphasized by
  game theory
• Structure, Conduct and Performance are jointly
  determined by underlying primitives,
  institutional details and equilibrium assumptions
• Two important lessons during the 70-80s every
  industry has many potentially important
  idiosyncrasies and these details matter a lot for
  the predicted conduct and performance
• Perhaps we should abandon the hope of finding
  common patterns across industries and instead
  look at each industry more carefully

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New Empirical Industrial Organization (NEIO)

• Key features of NEIO
• No use of accounting data for costs and
  price-cost margins
• Estimate market power fore each industry
  seprately
• Behavior of firms is estimated based on
  theoretical oligopoly models. This allows for
  explicit hypothesis testing on the degree of
  market power.
• The degree of market power is identified and
  estimated. The inference of market power is based
  on the conduct of firms.

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The Structural Approach

• Suppose you had data on the following homogeneous
  goods market
• P industry price
• qi output for each firm and Q the whole industry
• Y variables that shift the demand curve (income,
  weather, price of substitutes)
• W variables that shift the supply curve (price of
  inputs, weather, technology)
• Could you uncover the extent of market power?
• YES! Use the data to simultaneously estimate the
  elasticity of demand, marginal costs and firm
  conduct!

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The Structural Approach
The key aspect of this approach is that it uses
theory to specify the structure of demand and
supply and in the process firm conduct is
identified (pure magic!) Lets see how Demand
function Supply function Profit function
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The Structural Approach
Marginal cost Marginal Revenue ?i is a
parameter which measures conduct ?i0 price
taker, ?i1 monopolist. Optimality Condition
gives us the supply relationship
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The Structural Approach
Two interpretations of ?i parameter (i) measures
the gap between price and marginal cost, and (ii)
an aggregate conjectural variation Problem
with interpretation (i) can justify only few
values, not a continuous index Problem with
interpretation (ii) Corts (1999) critique that
estimation of ?i only unbiased if underlying
method is the result of a conjectural variations
eq. underestimate if firms collude
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OUTLINE

• NEIO and the Structural Approach
• Identification
• Estimation and Hypothesis Testing
• Examples Graddy (1995) Genesove and Mullin
  (1998)
• Reduced form and Non-Parametric approaches

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Identification
Can we identify the market power parameter ?i
given only market level data on P, Q, Y and
W? Remember our supply function
is Identification Problem is that Q and P are
equilibrium values, simultaneously determined by
the interaction of consumers and firms
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Identification
To trace the supply equation we need variables
that shift the demand curve (like income) but not
the supply relationship
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Identification
Similarly, to trace out the demand curve we need
variables that shift the supply (like wages) but
not the demand relationship
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Market Power Identification
Hence to identify demand (supply) function, we
need at least one exogenous variable in the
supply (demand) relationship that does not enter
the demand (supply) function. What about the
market power? Assume demand is given by Assume
also that marginal cost is given by Hence,
supply relationship is
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Market Power is NOT Identified
Shifting only the intercept of the demand curve
does not identify market power
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Market Power IS Identified
Shifting ???? the intercept and the slope of the
demand curve identifies market power
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Market Power Identification
Hence, using econometric estimates of the demand
and supply parameters we can obtain an estimate
of the degree of market power, in our example
here Note identification is based on
(arbitrary?) assumptions on the functional form
of both the demand and marginal cost
functions. Note credible instrumental variables
play a crucial role in the identification.
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OUTLINE

• NEIO and the Structural Approach
• Identification
• Estimation and Hypothesis Testing
• Examples Graddy (1995) Genesove and Mullin
  (1998)
• Reduced form and Non-Parametric approaches

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Estimation and Hypothesis Testing

• Given a set of credible instruments, the
  econometrician estimates the demand and
  optimality condition either separately (2SLS) or
  as a system (3SLS, GMM) of equations
• Two ways to estimate the market power parameter
• Estimate it as a free continuous variable. One
  then tests whether ? equals a value associated
  with a well-known model of competition (Bertrand,
  Cournot, collusion)
• Estimate separate models corresponding to the
  various well-known models by imposing the
  particular value of ? and then use non-nested
  tests to choose among them

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OUTLINE

• NEIO and the Structural Approach
• Identification
• Estimation and Hypothesis Testing
• Examples Graddy (1995) Genesove and Mullin
  (1998)
• Reduced form and Non-Parametric approaches

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Graddy (1995) imperfect competition in the
Fulton fish market
Graddy tests for law of one price in sales of
whiting (type of fish) in a market that has many
characteristics of a perfectly competitive
market She also estimates a structural model of
imperfect competition to estimate market
power Why should an industrial economist care
about the answer?
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The Fulton fish market and Data
The Fulton fish market is the central fish market
in NY Open-air, wholesale person-to-person market
with many dealers and main customers stores and
fry shops Author claims that entry and exit are
easy, but also lots of Mafia activity All dealers
are white, whereas buyers are white, black or
Asian Graddy chose whiting cause more homogenous,
more transactions (and it was the only salesman
to let her watch) Hand-collected data combined
with info from inventories Data on price,
quantities, customer type, fish quality and cash
or credit plus weather data
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Price Discrimination and Market Power
Graddy first estimates a reduced-form model of
transaction prices on various determinants (time,
location in Manhattan or Brooklyn, store dummy,
Asian and black dummy, cash dummy, regular dummy,
average quantity and quality) She finds that the
only consistently significant variable is the
Asian dummy indicating that Asian buyers get
about 7 discount compare to white customers for
the same quality of fish She then sets out to
estimate the degree of market power in the market
for Asian compare to white customers
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Price Discrimination and Market Power
The inverse demand function for Asian and white
buyers are The marginal cost functions for the
Asian and white market are assumed to be the same
and differ only by a random term The
optimality conditions for imperfect competition
gives us
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Price Discrimination and Market Power
Restricting the conduct parameter to be the same
across time and across groups gives us the supply
equation to be estimated Having estimates on
all these parameters, we can back-up the conduct
parameter ?. Because quantity and price
endogenous, need to use exogenous instruments
four measurements of weather and dummy variables
for each day of the week
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Results and Interpretation

• Results from the structural model indicate that
• Asian buyers have more elastic demand than white
  buyers, although difference is not statistically
  significant
• Conduct parameters are all between zero and one,
  but s.e. large, which means cannot reject
  hypothesis of neither competition nor collusion
• Graddy offers three interpretations for the price
  differences
• Market less than competitive and third degree
  price discrimination between two ethnic groups
• Different firm conduct in white and Asian markets
  (many possible combinations)
• Different search behaviour, Asians search more

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Genesove and Mullin (1998) conduct and cost in
the sugar industry, 1890-1914
Genesove and Mullins aim is to test the validity
of the NEIO methodology by comparing the
estimated conduct parameter from a structural
model to the calculated price-cost margins in the
sugar industry The simple production function
together with its volatile history of high
concentration, price wars and court cases at the
beginning of the century make this industry the
ideal test ground Why should an industrial
economist care about the answer?
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The Sugar Industry and Production Technology
The industry during period of study is
characterized by high levels of concentration,
episodes of entry and price wars and later
acquisition by or accommodation with
ASRC Refined sugar is a homogenous good with
common technology
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Demand and Structural Model
The postulate a general demand formula that
encompass as special cases the quadratic, linear,
log-linear and exponential Optimality condition
for a constant marginal cost, c, and conduct
parameter, ?, is given by Instruments used
Cuban raw sugar imports, which are driven by
harvest cycle, weather conditions, Cuban
Revolution, Spanish-American War
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Supply Equation and Results

• Substituting marginal cost function into pricing
  rule gives us
• Genesove and Mullin estimate different versions
  of their model depending on the demand function
  but also cost information availability
• Results
• NEIO methodology does pretty good tracking
  calculated price-cost margins independent of the
  assumed demand function, although ?
  underestimated
• Cost estimates sensitive to the model assumed,
  predictive power improved when add real info even
  if model misspecified
• Estimating a free conduct parameter improves
  estimates

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OUTLINE

• NEIO and the Structural Approach
• Identification
• Estimation and Hypothesis Testing
• Examples Graddy (1995) Genesove and Mullin
  (1998)
• Reduced form and Non-Parametric approaches

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Reduced form and Non-Parametric approaches
An alternative method to a full structural model
is to use comparative statics and be able to
distinguish firm behaviour Good alternatives if
important concerns on specification of structural
model or data limitations Basic idea suppose
that firms face a constant marginal cost a shock
causes the marginal cost to rise. If the market
is competitive, the price will increase by the
same amount as mc. If the market is
oligopolistic, price will not change by the same
amount. Again we need to specify a demand
function and functional form will matter for the
results, but in principle we require less info
than a full structural model However, by imposing
less structure we are able JUST to test whether
the market is competitive or not, cannot measure
the degree of market power
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NEIO and Industry Models of Market Power
References
Bresnahan, T. (1982) The Oligopoly Solution is
Identified, Economic Letters, 10
87-92. Bresnahan, T. (1989) Empirical Studies
of Industries with Market Power, Handbook of
Industrial Organization, 1011-1057. Corts, K.
(1999) Conduct Parameters and the Measurement of
Market Power, Journal of Econometrics,
88227-250. Genesove, D. and Mullin, W. (1998)
Testing Static Oligopoly Models Conduct and
Cost in the Sugar Industry, 1890-1914, Rand
Journal of Economics, 29355-377. Graddy K.
(1995) Testing for imperfect competition at the
Fulton Fish Market, Rand Journal of Economics,
2675-92.
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Next time Differentiated Products Structural
Models
Berry, S (1994) Estimating Discrete-Choice
Models of Product Differentiation, Rand Journal
of Economics, 25242-262. Hausman, J. (1997)
Valuation of New Goods Under Perfect and
Imperfect Competition, in Bresnahan and Gordon
eds., The Economics of New Goods, NBER. Nevo
(2001) Measuring Market Power in the
Ready-to-Eat Cereal Industry, Econometrica,
69307-342. Nevo (2000) A Practitioners Guide
to Estimation of Random-Coefficients Logit Models
of Demand, Journal of Economics and Management
Strategy, 9513-548. Berry, S., Levinsohn J. and
Pakes, A. (1995) Automobile Prices in Market
Equilibrium, Econometrica, 63841-890.