Economics

M.V.Melnichuk

All-Russian State Tax Academy

Inequality in socio-economic development of RF districts over 2000-2006 years

Today in Russia despite the economic growth the problem of inequality in the development of economic regions is rather acute. The inequality in income distribution within different groups of population is increasing. At the same time the phenomenon of differentiation in the development of Russian regions is becoming more striking: two poles (i.e. rich territories – poor territories) continue to move apart. Concentration of wealth in relatively small social groups results in an upset of social and regional equilibrium and in numerous socioeconomic problems. Heavy social and economic differentiation in Russia hampers the innovation progress of production, most of all, of high technology and science intensive areas. Negative tendencies in Russian economy also testify to the fact that scientific and technological security of Russia is jeopardized [1,2].

The issue of particular interest is the relationship between economic growth and inequality in incomes. The problem of interrelation between the economic growth and the income divergence has a great number of various aspects. The phenomenon of economic growth is a typical macroeconomic problem which is described by proper statististical aggregates: gross domestic product (GDP) and gross national product (GNP). Though the high rate of the GDP growth says nothing about how people live. This is connected to the fact that multiple economic entities are non-uniform, and the income produced may be concentrated in a small social group while the remaining part of the population may get nothing. Such effects are originally microeconomic and described by distributed characteristics rather than by aggregates.

The possibility of localization of the whole GDP increment within a small social group (or region) means that the high rate of the economic growth may come into conflict with the enhancement of the well-being of the majority of the population. Thereafter the fast economic growth may provoke further enrichment of the contingent of rich people (or a region) and impoverishment of other social groups. In that case the worth of economic growth in itself may be put in doubt.

An opposite phenomenon when the economic growth contributes to the income leveling may also take place. In that case the social effect resulting from the economic growth is considerably reinforced.

The purpose of this study is to investigate the inequality in economic development of RF federal districts as well as to estimate existing tendencies in population distribution throughout the territory of Russia versus average RUR income per head. The work uses data over the 2000-2006 period provided by State Statistical Agency (GOSCOMSTAT).

To understand movements in the differentiation level for federal districts and to identify changes arising in the country, data for 2000-2006 time interval were chosen. The initial data for model calculations shown in Table 1 represent official figures provided by State Statistical Agency .

Тable 1. Basic characteristics of socioeconomic development for Russian federal districts over 2000 - 2006 period.

Central District
	Y	K	L	I	Salary	L*
2000	1 841 499	4 358 855	22 857	303 918	2 173	38 175
2001	2 243 525	5 199 581	23 003	349 312	3 266	38 068
2002	2 878 665	6 296 105	23 205	435 810	4 433	37 947
2003	3 577 143	8 304 173	23 369	563 111	5 873	37 733
2004	4 617 086	9 280 004	23 418	770 409	7 276	37 546
2005	6 278 359	11 481 926	23 416	964 158	9 622	37 357
2006	7 849 634	13 199 939	23 348	1 152 663	12 117	37 218
Northwestern District
	Y	K	L	I	Salary	L*
2000	578 505	1 789 585	8 742	116 663	2 532	14 199
2001	709 025	2 083 416	8 735	168 114	3 655	14 073
2002	886 843	2 629 404	8 754	199 102	5 068	13 948
2003	1 091 027	3 417 342	8 785	285 159	6 144	13 832
2004	1 474 882	3 663 691	8 775	359 562	7 518	13 731
2005	1 799 780	4 134 214	8 742	483 265	9 487	13 628
2006	2 168 428	4 976 071	8 686	620 814	11 851	13 550
Southern District
	Y	K	L	I	Salary	L*
2000	434 873	1 794 832	13 215	134 904	1 481	22 762
2001	568 950	2 119 572	13 444	167 598	2 159	22 853
2002	693 583	2 503 418	13 650	185 722	2 974	22 892
2003	836 255	2 991 598	13 814	212 183	3 699	22 850
2004	1 042 458	3 243 964	13 938	264 339	4 648	22 821
2005	1 288 126	3 806 157	14 039	338 421	5 800	22 790
2006	1 611 037	4 140 577	14 114	430 483	7 221	22 777
Volga District
	Y	K	L	I	Salary	L*
2000	1 036 789	3 570 321	18 704	206 781	1 783	31 532
2001	1 292 757	4 254 707	18 765	267 845	2 563	31 316
2002	1 483 310	5 137 048	18 906	294 507	3 412	31 104
2003	1 807 987	6 046 752	19 074	350 622	4 235	30 902
2004	2 284 896	6 438 858	19 161	464 094	5 150	30 710
2005	2 799 036	7 462 180	19 207	609 499	6 473	30 511
2006	3 519 037	8 456 510	19 160	757 605	8 118	30 346
Ural District
	Y	K	L	I	Salary	L*
2000	866 133	2 495 342	7 708	250 731	3 487	12 471
2001	1 120 820	3 844 891	7 754	330 984	5 169	12 418
2002	1 335 976	5 069 686	7 818	383 378	6 589	12 362
2003	1 659 322	5 812 297	7 896	445 954	8 086	12 316
2004	2 234 753	6 267 153	7 936	534 467	9 693	12 279
2005	3 091 363	7 935 967	7 954	593 370	11 680	12 244
2006	3 772 731	9 209 054	7 945	770 678	14 307	12 231
Siberian District
	Y	K	L	I	Salary	L*
2000	687 071	2 310 955	12 428	98 647	2 270	20 333
2001	844 142	2 655 055	12 464	135 116	3 191	20 178
2002	991 737	3 215 231	12 532	150 109	4 310	20 031
2003	1 209 597	3 751 440	12 609	193 614	5 325	19 901
2004	1 631 783	3 988 065	12 648	255 399	6 508	19 794
2005	1 951 299	4 458 879	12 648	346 105	8 110	19 677
2006	2 390 625	5 021 477	12 608	442 002	9 878	19 590
Far Eastern District
	Y	K	L	I	Salary	L*
2000	308 802	1 144 282	4 388	53 589	3 114	6 832
2001	391 750	1 338 014	4 350	85 743	4 298	6 743
2002	471 106	1 482 381	4 341	113 779	5 979	6 680
2003	561 094	1 849 684	4 350	135 723	7 555	6 634
2004	678 448	1 991 989	4 343	216 743	9 115	6 593
2005	826 422	2 214 245	4 323	276 291	11 508	6 547
2006	980 959	2 485 870	4 291	313 702	13 711	6 509

Y	GRP (RUR m)
K	Capital Fixed Assets (RUR m)
L	Labor resources (thou prsn.)
I	Investments in Capital Fixed assets (RUR m)
S	Salary (RUR )
L*	Population (thou prsn.)

Obtained results.

Fig.1 Diagrammatic view of GRP trends for Russian federal districts

Fig.2 . Diagrammatic view of capital fixed assets (in value terms) for Russian federal districts.

Fig.3. Diagrammatic view of investments in capital fixed assets for Russian federal districts.

Fig.4. Diagrammatic view of labor resources for Russian federal districts.

Fig.5. Diagrammatic view of labor productivity for Russian federal districts.

Fig.6. Average labor productivity versus average amount of investments for Russian federal districts within 2000-2006 timeframe.

Histograms shown in Figures 1-6 demonstrate various macroeconomic characteristics for Russian federal districts: Gross Regional Product (GRP), key assets, investments in key assets, labor resources and average labor productivity. Regions are placed on a value-decreased basis. As can be seen Central federal district and Ural federal district registered the highest growth rate of macroeconomic characteristics.

Figure 7 illustrates changes in the number of population for Russian federal districts. It is evident that number of population is decreasing throughout all federal districts. The major drops in number can be seen in the most populated areas – Central federal district and Volga federal district.

Fig.7. Movement in the number of population for Russian federal districts.

Figure 8 shows the movement in GRP per head for Russian federal districts. The maximum values are observed for Urals and Central federal districts. The same refers to the value of the GRP per head.

Fig.8. Movement in GRP per head for Russian federal districts.

Fig.9. Klotzvog-Magomedov coefficient of variation for Russian federal districts

Summary: Regulatory imperative statements: “for” and “against” income divergence. At first glance, the revealed income divergence in RF regions and high differentiation value registered by 2007 for clusters of rich and poor regions are grounds to reckon that special regulatory measures should be taken to slow this trend as heavy discrepancies in technological and income characteristics may “cut” underdeveloped regions from the general economic growth resulting in increased disparities and disequilibrium with further slowdown of the economic growth on the country’s scale. Figure 6 showing average labor productivity versus average amount of investments is especially prominent is this respect. The plotted curves demonstrate the strong polarization of Russian regions: actually all foreign and domestic investments are found in Moscow, St-Petersburg and regions of export raw-material production. The remaining regions fail to attract any investments and thus have little chance to speed up their development process.

In the described situation we meet with some positive direct couplings and feedbacks. For example, the increase in differentiation of income per head causes a significant deterioration of investment conditions in several regional groups. And regional differences in the investment climate result in discrepancies in the amount of investments per head. Finally these factors create conditions providing for a different rate of the economic growth and “freezing” and deepening of existing regional distinctions.

BIBLIOGRAPHY

1. Balatsky E.V. Evaluation of fiscal instruments impact on economic growth “Forecasting Issues”, №4, 2004. P.124-135

2. Gusev A.B. Taxes and economic growth: theories and empiric evaluations. M.: Economics and Law. 2003.