SIP Call. Unit level compliance cost estimates are generated using detailed data on
units’ technology and operating characteristics, operating costs, fuel inputs, etc. Two
types of discrete choice models of the compliance strategy choice are estimated: a
conditional logit model, and a random parameter logit model that allows the cost
coefficients in the model to vary across units.
Results from both models suggest that compliance choices do differ significantly
across restructured and more regulated electricity markets. Managers of generators
operating in restructured electricity markets are significantly more responsive to vari-
ation in compliance costs as compared to managers in regulated electricity markets
who are able to pass a significant portion of these costs through to electricity cus-
tomers.
With coefficient estimates from the random parameter logit models in hand, a
logical next step involves deriving conditional distributions for unit specific coeffi-
cients and simulating the compliance decisions that coal plant managers would have
made had the NOx emissions market been designed to reflect spatial heterogeneity in
marginal damages from pollution. A more complicated "exposure based" approach
to designing the permit market would have involved estimating the variability in
marginal damages resulting from increased ozone exposure in different regions of the
regulated area. In order to set "trading ratios" to determine the terms of interregional
permit trading, estimated damages in each region are normalized by the damages in
a designated baseline region (Krupnick et al.). Because pollution permits carry more
currency in low damage areas, the introduction of trading ratios offers additional in-
centives to install pollution controls in relatively high damage areas. The magnitude
of this effect will depend on how responsive firms compliance choices are to changes
in variable compliance costs
My approach will differ from prior work29 on exposure based trading in two im-
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