Besides the variables of the termination rate equation I include termination rates and
a post-paid dummy into the quantity equation. From the theoretical model one should
expect a negative coefficient of the termination rate term. Also a positive coefficient of
the post-paid term is expected.
Equations (11) and (12) will be used in line with the first hypothesis on own investment
effects.
For the second hypothesis I aggregate the data with regard to investments. Although it
was not necessary to consider multiple investors simultaneously in the theoretical model
it is important to take this aspect into account in the empirical analysis. As an individual
investment effect of one provider cannot be isolated from those of others, I use a weighted
average measure of investments as an explanatory variable for the analysis of a potential
externality. In order to make comparisons with the results of the first equation system
easier we take the perspective of a competitor and consider how aggregated investments
affect termination rates and incoming traffic.12 Thus, we get for the termination rate
equation and the incoming traffic equation:
2 t2 t2 investmentj l z t2
log(ti,l,z) = αl,z + βinvlog (N - 1)z J + β log(si,l,z)
t2 t2 t2 (13)
+βmt2sizelog(msizel,z)+βut2rbpoplog(share upopl,z)+regulation0i,l,zβrt2eg
+β1t2800GSM1800i,l,z + it,2l,z
log Xqj2,i,l,z = αlq,2z + βiqn2vlog X
jj
investmentj,l,z
(N - 1)l,z
+ βtq2log(ti,l,z)
+βsq2log(si,l,z) + βmq2sizelog(msizel,z) + βpqo2stposti,l,
(14)
+βuqr2bpoplog(share upopl,z) +regulation0i,l,zβrqe2g + iq,2l,z
where log(Pj∙ invesstmentj,l,z ) is the logarithm of the average investment of all MNPs except
for i. All other variables are equal to those of the first empirical model. Due to lags
in the data employing a time dependent approach would heavily suffer from the low
number of observations. I therefore pool the data and use similar estimation approaches
as in Dewenter and Haucap (2005).
12 Alternatively, one could also take the perspective of an investor and look at how investments affect
outgoing traffic and the competitors’ termination rates.
16
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