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155,4%

137,9%

Regions with an unsteadysituation, annual fluctuations of living standards without a clear trend toeither side

28,9%

166,0%

142,4%

Regions with a steady low povertylevel, but steadily low level of population’s incomes andspending

21,1%

174,8%

160,0%

Figure 3.1.1.

Table3.1.7 presents mean values of the three parameters of living standards underconsideration for >

3.2. >

It is the study of investment processes, thenature and forms of economic agents’ investment activity that constitutes one of the crucial tasks inthe course of the evaluation of the current economic situation and prospects ofthe national economy’sdevelopment. However the building of a single investment function for the wholenational economy is a complicated or even impossible problem both because ofdeficiencies of the data available and due to the difference between the typesof investment processes in different Subjects. In the frame of>

We assume that investment activity in theregion can be characterized by three indicators:

  1. The ratio of investment in capital assets to GRP
  2. Relative growth rate in investment in capital assets against theaverage nationwide level
  3. The ratio of foreign investment to GRP

To select method of clusterization of Russianregions by investment activity indicators we applied the procedure analogous tothe one employed in the course of clusterization of regions by livingstandards. Form the formal perspective, the best method has proved to be WardLinkage with the distance Squared Euclidian Distance. Below we provide resultsof the clusterization according to the best method by the noted threeindicators. The clusterization was built using the data for the whole periodbetween 1995 to 1999, 78 regions. Annex 2 provides results of theclusterization by years.

Original data. Letus first consider thedistribution pattern of Russian regions across clusters on the basis ofnon-adjusted investment activity values. Starting from the 378th iteration, the speed of growth in thedistance between united clusters begins to exceed exponential growth. Thisleads to the conclusion that the general integrity of regions breaks down into12 clusters. Annex 2 presents the respective>

The comparison of the results of thisclassification related to 1995 with the>

Adjusted data.Indicators used for clusterization appear non-homogenous, that is why let usadjust them and build>

The comparison of the results of thisclassification related to 1995 with the>

Classification of regions by investmentactivity. Qualitative analysis of results related toadjusted indicators using Ward Linkage Method and Squared Eucledian Distance ofclusters (see Annex 2) shows that as far as investment activity is concerned,the clusters can be attributed to several economically sufficiently homogenousgroups. Such groups were singled out on the basis of the comparison and ranking(across all the clusters) of adjusted values of all three indicators inquestion. Specifically, there may be five groups of clusters (regions) singledout:

  1. Regions with a low investment activity by all the parameters(clusters 1, 4,5, 7).
  2. Regions with a high investment activity by all the parameters(clusters 8,10,11)
  3. Regions with a high investment activity, predominate domesticinvestments (clusters 2 and 6)
  4. Regions with a high investment activity, predominate foreigninvestment, while domestic investments are small (cluster 3)
  5. Regions with a low investment activity, while the volume of foreigninvestment is high (cluster 9)

Movement of RF Subjects between 1995 to1999across the noted groups of regions is presented in Table 3.2.1.

Table 3.2.1. Movement of RF Subjects acrossthe noted groups of clusters resulted from clusterization according to WardLinkage methods on the basis of adjusted data for 1995 – 1999.

Regions

1995

1996

1997

1998

1999

Republic of Karelia

1

1

1

1

4

Republic of Komi

3

3

1

1

1

Arkhangelsk oblast

4

1

1

1

5

Vologda oblast

4

1

1

1

4

Murmansk oblast

1

1

4

1

4

Saint-Petersbourg city

1

1

4

4

4

Leningrad oblast

3

3

3

3

2

Novgorod oblast

4

3

1

4

3

Pskov oblast

1

1

1

1

1

Bryansk oblast

1

1

1

4

1

Vladimir oblast

1

3

1

5

1

Ivanovo oblast

1

1

1

4

1

Kaluga oblast

2

1

4

1

9

Kostroma oblast

1

3

1

4

4

Moscow city

3

3

4

4

5

Moscow oblast

3

3

1

4

1

Oryol oblast

1

3

1

4

4

Ryazan oblast

1

1

1

1

1

Smolensk oblast

1

1

1

1

2

Tver oblast

4

1

1

4

3

Tula oblast

1

3

1

1

1

Yaroslavl oblast

1

1

4

1

2

Republic of Mariy El

1

3

4

1

1

Republic of Mordovia

1

3

1

1

1

Table 3.2.1. cont`d

Regions

1995

1996

1997

1998

1999

Chuvash Republic

3

1

3

1

1

Kirov oblast

1

1

1

4

1

Nizhny Novgorod oblast

1

3

1

1

1

Belgorod oblast

3

3

3

3

1

Voronezh oblast

1

3

1

1

1

Kursk oblast

1

3

4

1

1

Lipetsk oblast

4

3

1

1

1

Tambov oblast

1

3

1

1

1

Republic of Kalmykia

3

1

4

3

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