began, and whether the magnitude and the direction of these changes are significantly
correlated with firms’ compliance strategy choices. I estimate the following regression
equation using monthly, unit-level ozone season production data from 1997-2004:
) - d _L Dsip m Πsip δ _l Πsip δ I)''pl . fllʌ
4nt — an + Dnt + Dnt ’ δnj + Dnt ■ δnj ■ Dn + εnt t11l
The quantity produced in month t by unit n is Qnt.an is a unit specific fixed effect.
Dnsip is a dummy indicating that the NOx SIP Call market is "on"; this indicator
variable has an n subscript because the program came into effect in different years for
different subsets of plants. The SIP Call indicator variable is interacted with a series
of technology dummies indicating compliance strategy choices; δnj — 1 if the nth
firm chose compliance strategy j, 0 otherwise. A second set of interaction terms are
included that interact the SIP Call indicator and the compliance strategy indicators
with a dummy variable that indicates whether the unit is a non-baseload unit. A
superior specification would include a measure of market area load. Estimation of
this preferred model will be carried out when the load data become available.
This regression equation is estimated separately for restructured and regulated
markets. A significant amount of the variation in the dependent variable is explained
by the unit fixed effects and the SIP Call dummy. The coefficient on the SIP Call
indicator variable is positive in both models, although imprecisely estimated. Both
SCR interaction terms are significant in both models. These results indicate that, on
average, units adopting SCR technology experienced a larger increase their production
on average, once the SIP Call took effect.
There is no way of knowing whether plant managers adjusted their production
expectations upwards when estimating the costs of an SCR retrofit. If they did, the
estimate of variable operating cost I use will be an underestimate, and the added
29
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