Integrating the Structural Auction Approach and Traditional Measures of Market Power



As was with the auction model, packers’ processing technology is assumed to be
of Generalized Leontief form. For simplification, the conversion factor to convert cattle
into boxed beef is assumed to be one. Thus, y f = y r = y.

The profit maximization problem for packer i is represented as:

(2.6)                    max πi = [Pr - Pf (Yf )]yr - C(yr, v).

yi

where πi is packer is profit, pr is the retail price of beef, and C(yir) is the processing cost
function for a representative packer. The first order condition for maximizing equation

(2.6) is:

d∏^- = P
yir


dpf (Yf )Yf r
dYf    
yir y'


f-∂C(y>) = o.

yr.


Rearranging and re-writing the first order condition yields:

(2.7)


Pr = pf [1 + (1 + θ')s' ] + c( yr ),
εsf

where c(yir) =dC(yir,v)/dyir is packer i’s marginal cost of processing beef,

εsf = (dYf /dpf )(pf /Yf ) is elasticity of cattle supply, si = yrYr processor i’s market

share, and θ = dn yf /dyr is packer i’s conjecture about rivals’ responses to its
i                ij j i

change in purchases of cattle.

Customary with the NEIO model, an industry pricing equation is obtained from
equation (2.7) after multiplying every term of (2.7) by each firm’s market share
si, and
summing across all processors in the industry as:

(2.8)              ∑'^pr =∑,SiP-' +nf(1 + θfs-s` Pf + c(yr).

V ε s         )

Re-arranging (2.8) equation yields the industry pricing equation:

12



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