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The use of additional information relatedto the institutional and political specifics of each RF subject permits toexplain the existence of УshakyФ regions (i.e. those which in fact are outsideany qualitative type), and the mentioned above unexplainable (by analysis ofquantitatively measured economic indicators) entry of regions into this or thatclass. Unfortunately, due to its non-measurability (primarily expertevaluations) this information can not be directly used for the building ofanother>

For instance, the analysis of RFregions’ rankingsregularly published by УEkspertФ3 magazine demonstrates thatregions we >

Investment risk	1	2	3	4	5	6	7	8	9
Vladimir obl.	36	0,987	71	74	42	29	36	24	10
Vologda obl.	6	0,858	42	12	3	11	4	10	76
Krasnoyarsk krai	7	0,862	10	23	29	12	14	6	63
Moscow obl.	15	0,918	26	77	12	16	25	46	36
Republic of Sakha	71	1,213	58	41	85	52	76	52	59
Tver obl.	11	0,899	9	52	10	68	60	28	8
Tomsk obl.	32	0,980	52	78	22	17	24	58	58
Chelyabinsk obl.	77	1,336	68	73	63	33	20	45	88

1 – Ranking of risk(2000–2001); 2– Average weightedindex of risk (Russia = 1);
3 – legislative ranking; 4– Political ranking;5 – Social ranking; 6– Economic ranking;
7 – Financial ranking; 8 – Criminal ranking; 9 – Ecological ranking.

As these tables demonstrate, practicallyall regions are characterized by significant dispersion of rankings acrossdifferent categories; however, values from the lower part of the listpredominate as concerns legislative, political, and economic risks,infrastructure potential. For instance, the Vologda oblast demonstrate a lowinvestment risk, however, at the same time, the experts evaluate its potentialas a low one. On the other hand, the high potential of the Moscow oblastis depreciated by relatively high risks (first of all, political and criminal).The Krasnoyarsk krai somewhat stands out. However, the УEkspertФ rankingreflects considerable positive changes occurring in the region over the lasttwo years. It is most probable that at present it may belong to a differenttype.

Investment potential	1	2	3	4	5	6	7	8	9
Vladimir obl.	36	32	45	13	40	22	44	33	69
Vologda obl.	38	55	40	60	16	53	22	28	65
Krasnoyarsk krai	10	4	5	10	11	21	11	8	29
Moscow obl.	3	2	2	4	6	2	4	3	51
Republic of Sakha	17	39	29	85	21	47	18	35	1
Tver obl.	43	36	44	26	42	24	42	49	63
Tomsk obl.	47	33	41	76	44	26	36	40	30
Chelyabinsk obl.	14	8	13	49	10	9	10	7	24

1 – Ranking of potential(2000–2001); 2– Labor ranking; 3– Consumer ranking; 4– Infrastructureranking; 5 –Industrial ranking; 6 – Innovation ranking; 7 – Financial ranking; 8– Institutionalranking; 9 – Naturaland resource ranking.

Let us analyze the possible factors behindother disputable results, in particular, the inclusion of the Sverdlovsk oblastin the type of Уpoor consumersФ and St. Petersburg in the type of Уpoorinvestors.Ф A distinctive feature of the Sverdlovsk oblast is its highpotential observed across the majority of indicators at the background ofextremely high risks. For instance, the oblast is ranked 61st among all RF subjects in terms of thegeneral level of investment risks (76th –legislative risks, 70th– political risks,64th – criminal risks). A weakness ofthe region is its low infrastructure potential (the region is ranked45th ). Such a combinationof factors is determined by the withdrawal of the major part of regionalrevenues from the territory of the Sverdlovsk oblast, what negatively affectsinvestment activity. As a result, the regional living standards are relativelylow, while the region’s economy orients toward the current consumption.

The case of St. Petersburg is morecomplicated. According to the УEkspertФ ranking, in 2000 – 2001 this region wascharacterized by high potential and moderate risks. However, it shall be notedthat in some periods (1995 through 1996 and 1999 through 2000) St. Petersburgwas not included in the number of top 10 regions with lowest risks, whilepolitical risk remains extremely high (80th in 2000 through 2001). Therefore, itmay be assumed that the high investment activity levels observed at thebackground of the lack of external investment (both from abroad and otherregions) and low living standards may be explained by a small share of revenuesallocated for wages, salaries, and other social payments to the population(through the budget), while the share of savings and investment ishigh.

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1 See, for instance, Yenyukov I. S. Metody, algoritmy, programmymnogomernogo statisticheskogo analiza (Methods, Algorithms, Programs ofMultivariate Statistical Analysis). – M.: Finansy i Statistika, 1986;Faktorny, diskriminantny i klasterny analiz (Factor, Discriminative, andCluster Analysis. –M.: Finansy i statistika, 1989; Kulaichev A. P. Metody i sredstva analizadannykh v srede Windows. STADIA 6.0. (Methods and Ways to Analyze Data inWindows Environment. STADIA 6.0.) – M.: Informatika i kompyutery, 1996; SPSS for Windows:Professional Statistics, 6.0. - SPSS Inc., 1993.

2 Moscow city (a Уrich investorФ) is an exclusion due to itsspecial status of the capital. For instance, many all-Russian companies, whichcarry out large investment projects, are registered as legal entities inMoscow. Besides, Moscow is the financial center of Russia, what accounts forthe redistribution of financial flows in its favor.

3 See: УRanking of investment attractiveness of Russia’s regions. 2000 – 2001.Ф // УEkspert,Ф No. 41, 5November, 2001, pp. 97 – 128.

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