Estimates of price markdown estimated with the structural auction model and
traditional NEIO model are shown in tables 3 and 4 respectively. The structural auction’s
average markdown for all bidders shown in table 3 is $3.36 per cwt, and the average
markdown obtained with the traditional NEIO approach is $2.7 per cwt. Both the NEIO
and the structural auction approach seem to overestimate the true markdown because the
average markdown estimated directly from data is nearly zero. Packers profit, given by
the difference between average price spread ($1.22 cwt) minus the average marginal cost
(roughly estimated at $5 cwt), is negative (-$4.78 cwt). Thus, it is unlikely that packers
in the game could have positive markdowns as suggested by the traditional NEIO and the
structural auction approach.
Estimates of price markdowns using the NEIO and structural auction approach are
not consistent regression results from the encompassing equation (2.13). The regression
results suggest much more difference between price markdowns the estimated with NEIO
and structural auction approach that it is actually found. One possible explanation for
this discrepancy in results is failure of the two approaches to account for the winner’s
curse. The price spreads estimated directly from data reveal that packers lost money in
about half of the transactions. Other possible source of bias for the structural auction
approach is use on potential number of dibbers than the actual number of bidders, and
failure to account for refusal to sale.
Conclusion
Recently, there have been many studies evaluating potential market power in the U.S.
cattle procurement markets. These studies used either the NEIO model or the auction
model. However, price markdown measures from these two approaches are not the same.
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