Regional differentiation in the Russian federation: A cluster-based typification

The economic zoning of over 30-year long standing would hamper the progress of
transition towards market economy. Some zones are too large and cumbersome in
their structure. The inequality of economic potentialities in some zones is
remarkably measured by a factor of 4 to 5. The other are noted for multi-industry
economic structure involving up to seven or eight major industries and dozens of
primary-industry plants (businesses). Thus, a zone's specialization is becoming
rather doubtful. Moreover, the economic zones have no bodies of power of their
own and are outside the administrative structure system.

Transition to market economy calls for the objectives of economic management of
a given territory being radically changed. This is reflected in the setting up in the
1990's of a number of interregions in RF, whose status revealed a fundamental
difference from that observed in the network of economic zones. These
associations can be illustrated as follows:

Central Russia             Northern Caucasus

Black-soil belt               Greater Volga

North-Western Russia      Siberian accord

The Urals                   Far-East

Interregional associations of the RF subjects will be formed on their own initiative
keeping in view their common socio-economic targets and ecological problems.
Once recognized, they would boost the association members into coordinating
their activities, strategies and policies, and into pooling their resources to ensure
their more efficient use. «The Siberian Accord» may well illustrate the case, being
an interregional association created on the basis of Siberian republics, krays and
oblasts. The concurrence of borders formed by interregional associations and
economic zones is not altogether ruled out.

2.2. Problem regions' salient features

The problem regions categorization involves not only the subjects of the Russian
Federation as a whole, but certain portions of the oblasts, krays, republic or
contiguous areas of the neighbouring spatial entities. Furthermore, taking into

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