computed from the average AC codes used in scoring the
parties for the seats they held in each year of the period.
For example, if we were sure about the proportions of seats
the party held in half the years--assigning an AC of 9 to
each year, but less confident about the proportions for the
other half of the period-assigning only an AC of 7 to those
years, the AC105 code for that party would average to 8.
That average AC value for scoring each party on legislative
representation became the AC105 code for legislative
instability. In no instance did the average AC code for any
party drop below a value of 4, indicating that relatively
good legislative representation data existed to provide
anchor points in calculating BV105.
Basic Variable 1.06: Electoral
Instability
Political parties interact with the citizenry by
contesting elections. The stability of these interactions
should be reflected by the fluctuations in the percentages
of votes received by a party over time. If a party never
participated in an election during our time period--because
of prevention or boycott--it cannot be credited with
building electoral relations with the citizenry. Indeed, it
is argued that the party's repeated absence in elections
contested by other parties further disadvantages it relative
to those which conducted campaigns. Thus, absence from two
elections should reflect more instability than absence from
one and so on, with the increment. in instability
diminishing with each missed election. Of course, those
parties which compete in some elections, but not all, should
gain more credit for their participation than those absent
from all the elections.
Operational Definition. Two different formulas are
used to compute electoral instability, BV106. For parties
which participated in at least two elections, BV106 is
expressed by the coefficient of relative variation in
percentage of votes (Yi) won in elections
for the lower house of each of K elections during our
time period as given by the formula
Electoral Instability =
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Coefficient of Relative Variation
=
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Wherever possible, elections for the lower house of
the legislature were used in applying this formula. In
certain cases, however, we substituted votes cast for the
parties' candidates in presidential elections. (The source
of votes is identified in the country printouts.)
If this formula were applied to parties which did not
contest any elections during our time period, the resulting
instability score would be zero--for there would be no
variation in the parties' "votes" not received. For these
parties, therefore, an alternative formula is used to
calculate BV106:
Electoral Instability =
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where K again is equal to the total number of
elections during our time period. Thus a party that missed
the only election held would receive a score of 1; missing
both elections when two were held would produce a score of
1.5; missing three out of three would produce a score of
1.83; and so forth.
If a ruling party consistently won large proportions of
the vote in elections due to restricting competition by
other parties, it would obtain a low electoral instability
score according to our formula. In contrast to our policy
for treating legislative instability, however, we do not
credit such a party with a low electoral instability score.
We regard a low electoral instability score in this
situation to be markedly more artificial in character. While
these electoral results are widely recognized as fiction,
the percentage of seats that the party wins is clearly
accepted as fact. Moreover, such a party is certain to be
rewarded for its electoral policy by a low score on
legislative instability (BV105) and to give it a low
electoral instability score as well results in a form of
doublecounting. Therefore, we omit computing BV106 for any
party that obtains more than 90 percent of the vote averaged
over all elections. This figure effectively filters out the
parties as desired.
Coding Results. The scores computed for BV106
ranged from 0 to 2.08. They are grouped into categories for
presentation in Table 3.8. As the "missing" data count
shows, our success in coding parties on BV 106 was only
slightly less than that enjoyed for BV105. While roughly 8
percent of the parties failed to be coded for both
"electoral instability," and "legislative instability,"
these tended not to be the same parties. Parties that were
banned throughout our time period and thus were not
"eligible" for a legislative instability score were still
coded on electoral instability if the country held
elections, as described in the conceptual and operational
definitions. But, when a party was assigned an electoral
instability score for failing to participate in its
country's elections, rigged or not, the resulting BV 106
score was always automatically given an AC score of 3--the
lowest that can be assigned to any variable. Partly as a
consequence, the mean AC code for BV 106 is considerably
lower than that for BV 105. The lower confidence in coding
electoral instability as opposed to legislative instability
was also due to less attention paid in the literature to
electoral success in comparison with legislative
representation. There were thus two conse-
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