been. Some incumbents also voluntarily lowered their UNE rates during the application
process in the hope of securing permission to provide long-distance service. If the
incumbents were in fact lowering their UNE rates below the rates that would have
prevailed otherwise, one would expect these voluntary reductions to result in lower UNE
rates. However, the incumbent might have made voluntary reductions that were not as
drastic as would otherwise have been ordered by the state during the application process.
If so, the incumbent might have been able to secure a more favorable UNE rate by pre-
empting action by the state. In such a case, the marginal effect of the voluntary reduction
could be positive.
Lastly, the level of observed UNE entry may affect the UNE rates. If the
commission views the level of entry as relatively low, certes paribus, it may be inclined
to lower UNE rates to encourage additional entry. Thus, one would expect a positive
coefficient on this variable.
Model Specification and Data Used
Model Specification
As noted above, UNE rates changed infrequently in some states. Consequently,
UNE rates often exhibit a high degree of stationarity. However, relatively frequent data
are required to capture the exact timing of the rate decisions. To allow for frequent data
and the stationarity of the lagged dependent variable, the lagged rate is included as an
explanatory variable.21
Including the lagged dependent variable as an explanatory variable in a panel data
regression complicates the econometric analysis. When an OLS fixed-effects estimator is
21 In the econometrics literature this is referred to a dynamic panel data model.