sort are available only for one year - 1962. In addition, the numbers of bosses and their
average salaries by republic (without separation into hierarchical levels) are available for
1964. My approach is based on the assumption that changes in territorial structure are the
major source of changes both in the number of bosses (due to change in the total number of
units) and in average salaries (due to change in the hierarchical level mix). An advantage of
this approach is that it relies on the data on territorial structure that are easily verifiable and
hardly could be subject to any deliberate distortion unlike many other series of policy-related
data.
I use two methods to impute missing data on the salaries and the size of party
bureaucracy. Under the first method, assuming constant republic differentials in pay and
office size (the number of bosses per unit) by level (from 1962 data) and applying common
trend in these variables (from the annual national data), I calculate the numbers for each level
for each republic and aggregate them to obtain republican average salaries and the total
numbers of bosses. The second method is to regress average republican salary and office size
data for 1962 and 1964 against territorial structure data and national averages for these years,
and use predictions of these models. The numbers of PPOs and the salaries of their personnel
exhibit relatively high variation across republics and are strongly correlated with the total
number of urban settlements by republic. Moreover, higher numbers of these units and
salaries are characteristic of more urbanized and industrial republics. For these reasons, I use
a common “all cities” variable, as well as republic-specific coefficients, in the regressions.
Regression models for imputing salaries and boss numbers are reported in Table 1. Aggregate
dynamics calculated on the basis of thus imputed salaries and boss numbers is in good
31
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