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INVESTMENT ACTIVITIES OF RUSSIAN REGIONS

INVESTMENT ACTIVITIES OF RUSSIAN REGIONS
Марина Мельничук, преподаватель, доктор экономических наук, доцент

Алан Караев, преподаватель, доктор технических наук, профессор

Всероссийская государственная налоговая академия министерства финансов Российской Федерации, Россия

Участник первенства: Национальное первенство по научной аналитике - "Россия";

Открытое Европейско-Азиатское первенство по научной аналитике;

УДК 330.322.21

The article deals with the problem of increasing divergence against the background of sustainable economic growth. Running a sensible investment policy which is based on the qualitative evaluation of the investment efficiency of regions is considered to be an effective instrument for decline in spatial economic differentiation.
Keywords: economic differentiation, investment activity, investment policy, production functions, Keynesian multipliers.

The Russian economic  space is characterized by extraordinary non-uniformity and unevenness of development caused to a considerable extent by nature differences, the geographic evolution of the Russian state, phases of the country’s current territory development.

In the framework of this spatial non-uniformity, the principal state economic policies tend to efficiently combine regional diversity, preservation of the national space integrity and its effective integration into the globalizing world. Therefore, “Russia’s way in the 21st century is to reject the regional uniformism in the social-economic policy and focus on making use of advantages of every region and interregional cooperation, harmony of regional society interests, implementation of the equal opportunities principle for all citizens irrespective of their residence”[1].

The historically developed unevenness of the economic space of Russia has a significant impact on the structure and effectiveness of the economy, the strategy and tactics of institutional reforms and the social-economic policy. The differentiation of regions increased dramatically in the 1990ies.  It was due to a number of reasons: development of the market competition mechanism, disruption of national economic links, different market adaptability of regions with different structures of the economy and different mentalities of the population and authorities, reduction of government investments into regional development, etc. A positive feature of the economic dynamics in 2000-2010 is that the economic growth enveloped the major part of the Russian space leading to higher real incomes and consumer spendings of the population in every and all subjects of the Russian Federation. However, even the wide-spread and sustainable economic growth is so far unable to overcome the tendency to the increasing differentiation (divergence) of regions by their economic development levels.

The non-uniformity general to the structure of the Russian economic space may increase through emergence of new points of growth, development poles, effective regional clusters leading to further aggravation of negative non-uniformity effects such as appearance of depressed and non-competitive areas lagging more and more behind regional leaders and falling out of the common and humanitarian space, which impedes thereby a uniform and successful state social-economic policy. Though lagging regions receive significant government support, financial mechanisms applied solve, for the most part, just current social tasks (fiscal capacity equalization) rather than provide incentives for accelerated economic development of regions as the basis for social task solution on the regional level.

To smooth the spatial economic differentiation substantially, more effective instruments of the economic policy are needed, primarily enhancement of the investment and innovation activities. Running a regional economic policy in a situation of economic restructuring traditionally leads to concentration of investments in one or several regions, with loss of the economic potential and investment attractiveness on the rest territory of the country. In this regard, one of the most important measures of the state influence on the spatial distribution of production factors is an active investment policy based on the qualitative evaluation of the investment efficiency of regions where the contribution of investments into the gross regional product is determined.

The starting point in investigation of investment processes in the economy of Russia is to analyze the dynamics of social-economic indicators of the Russian Federation and individual regions for the recent decade. Changes in macroeconomic proportions of the Russian economy make it possible to expose a number of principal factors that have had a substantial effect on the nature and dynamics of transformation shifts at all levels of the economy, which, in turn, allows a better insight into the role and contribution of separate areas and subjects of the Russian Federation into the country’s GRP and helps to reveal specifics of the investment policy run in given regions.

The most popular instrument in the study of the production-factors-to-GRP relationship, including the regional frame of reference, also needed for forecasting GRP dynamics of regions is the production function apparatus and, above all, the standard multiplicative Cobb-Douglas function:, where Y – gross regional product (GRP); А– residual or technological parameter; K – fixed assets input; L – annual average labor input; ?– GRP fixed assets elasticity.

However, certain complications arise in building up production functions of the Russian region economy. First, time series are so far quite short since the transition to the market economy has begun comparatively recently. Secondly, the available data are not sufficiently accurate due to the transient nature of processes going on in the country. One of the reasons for data inaccuracy in evaluation of fixed assets and the GRP may be inaccuracy in price measurements resulting from considerable price volatility: price leaps in the Russian economy exceed by far slow changes occurring in developed countries of the West. The third, and maybe the main reason that impedes formulation of the production function, is extreme inaccuracy in measuring the capital used in production. There are several factors contributing to this:

- with the beginning of the transformation downturn, fixed assets ceased to be used in the full extent, therefore fixed assets data do not correspond to their actually used portion;

- in transition from resource limitations to demand limitations fixed assets have become redundant, which, on the one hand, diminishes their significance as a factor capable of determining the GRP performance dynamics, and, on the other hand, makes impossible their market-based assessment.

One of the solutions to the problem of missing or inadequate fixed assets data is to use fixed capital investment data rather than fixed assets data[2]. The advantages of this approach are determined by high efficiency of investments assigned both for involvement of idle assets into circulation and acquisition of new assets; thereby the share of the efficiently used capital increases. A fact of no small importance is that there are statistical data reflecting the dynamics of investments into fixed assets and the dynamics of paid labor; therefore production functions of the type Y=F(I,W) were used in the work, where I is investments into fixed assets, and W is investments into labor or paid labor.

As a result of the author’s investigation based on the linear multivariate regression analysis using macroeconomic indicators of regions as the model inputs (observed variables), production functions of Russian regions were built. By way of illustration, data on Central, Northwestern, Volga and Urals federal districts are provided (see the Table below). The analysis of the Table makes it possible to conclude that the production functions obtained for RF region economies meet principal statistical criteria (R2 – determination factor and DW – Durbin-Watson factor) and may be regarded quite operable and fit for practical use.

Parameter values of production functions

for the RF region economy (2000-2010)

нализтаблицы1оссии(см.табл.1

 

Region

A

?

?

?+?

r

R2

DW

1

2

3

4

5

6

7

8

Central Federal District

BelgorodArea

23.4637

0.4338

0.5662

1

0

0.978

2.235

BryanskArea

28.5708

0.5006

0.3994

0.9

0

0.979

2.044

Vladimir Area

69.5877

0.3427

0.3583

0.7

0

0.96

3.182

VoronezhArea

86.6149

0.3417

0.546

0.90

0

0.935

2.403

IvanovoArea

222.4745

0.2818

0.5532

0.83

0

0.954

1.707

KalugaArea

49.6854

0.3569

0.5913

0.95

0

0.990

2.773

KostromaArea

12.5826

0.3244

0.5756

0.9

0

0.973

1.965

KurskArea

47.3473

0.349

0.5013

0.85

0

0.979

1.763

LipetskArea

24.3307

0.3507

0.6493

1

0

0.923

1.851

MoscowArea

14.9924

0.4071

0.5929

1

0

0.985

2.885

OrelArea

168.3605

0.239

0.7216

0.96

0

0.978

2.136

RyazanArea

88.2451

0.1238

0.6968

0.82

0

0.958

2.300

SmolenskArea

82.1269

0.2688

0.5155

0.78

0

0.980

2.476

TambovArea

213.2946

0.1394

0.5604

0.7

0

0.989

2.955

Tver Area

14.0426

0.3365

0.6635

1

0

0.926

2.139

TulaArea

50.4406

0.3452

0.623

0.95

0

0.940

1.994

YaroslavlArea

19.5029

0.1907

0.8093

1

0

0.982

2.181

MoscowCity

4.5113

0.9155

0.0845

>1

0

0.962

2.545

MoscowCity

9.3744

0.8805

0.1195

1

0.018

0.937

2.516

Northwestern Federal District

Republicof Karelia

48.7695

0.2323

0.6291

0.86

0

0.938

2.414

KomiRepublic

20.3274

0.3935

0.5559

0.95

0

0.968

1.732

ArkhangelskArea

97.391

0.261

0.5302

0.79

0

0.951

1.494

VologdaArea

121.7085

0.3658

0.3906

0.76

0

0.902

1.445

KaliningradArea

99.2605

0.254

0.5068

0.76

0

0.962

2.521

LeningradArea

22.9929

0.3391

0.5988

0.94

0

0.996

2.069

MurmanskArea

73.4754

0.137

0.7093

0.85

0

0.960

1.974

NovgorodArea

65.0786

0.189

0.6543

0.84

0

0.966

2.276

PskovArea

15.2595

0.326

0.6731

1

0

0.951

2.356

Saint-PetersburgCity

56.9446

0.6502

0.3498

1

0

0.959

2.386

VolgaFederal District

BashkortostanRepublic

9.773

0.5775

0.4225

1

0

0.957

1.813

Mari El Republic

82.6947

0.2173

0.5543

0.77

0

0.968

2.935

Republicof Mordovia

69.777

0.1799

0.5269

0.71

0

0.891

1.300

Republicof Tatarstan

6.277

0.7917

0.2083

1

0

0.929

2.449

UdmurtRepublic

13.8069

0.4425

0.5575

1

0

0.992

2.235

ChuvashRepublic

29.3765

0.6737

0.1452

0.82

0

0.963

2.042

PermKrai

16.6735

0.3394

0.6606

1

0

0.943

2.607

KirovArea

241.9934

0.2081

0.4618

0.67

0

0.895

1.457

Nizhny NovgorodArea

70.1515

0.5049

0.4951

1

0

0.976

2.645

OrenburgArea

13.6921

0.4809

0.5191

1

0

0.953

2.222

PenzaArea

116.2327

0.2409

0.5526

0.80

0

0.969

2.411

Samara Area

11.1188

0.6005

0.3995

1

0

0.944

2.791

SaratovArea

8.9634

0.4638

0.4862

0.95

0

0.861

2.398

UlyanovskArea

131.7153

0.3413

0.5566

0.9

0

0.934

1.647

Urals Federal District

KurganArea

86.5498

0.3415

0.5221

0.86

0

0.994

3.133

SverdlovskArea

45.6314

0.6799

0.2478

0.93

0

0.919

1.435

TyumenArea

0.0614

0.8758

0.1439

>1

0

0.928

1.439

TyumenArea

2.324

0.8623

0.1377

1

0.015

0.981

2.486

ChelyabinskArea

48.2681

0.3747

0.5932

0.89

0

0.978

1.811

 

Source: The author’s calculations based on data of the statistical yearbook “Regions of Russia. Social-Economic Indicators”. Moscow, Rosstat Publishers, 2011.

It should be noted that the factors of investment into fixed assets and paid labor predetermine over 90% of all GRP changes. Moreover, for the majority of regions the value of the GRP investment elasticity coefficient for the entire time interval considered is significantly less than 1, which means the future need for the savings rate growth and, respectively, the consumption rate reduction in order to increase the production efficiency or the labor productivity.

To substantiate conditions required for Russian regions to enter the path of balanced economic growth, the author successfully established the interrelationship between production dependency parameters and Keynesian Multipliers (static and dynamic). The expression 1 connecting the GRP growth rates with the investment growth rates was taken as the basis, where c and c* are the average and the maximum consumption rates, respectively, the expression in parentheses is the GRP investment elasticity (let it be E) representing a combination of the average and the maximum propensities to consume.

Assuming c and c* as values of the same magnitude (), the elasticity coefficient value, E, ranges from zero to one. Two maximum values of the GRP investment elasticity coefficient  are consistent with two asymptotic trajectories: the stable balanced economic growth path   and the negative economic growth path   

For the GRP investment elasticity coefficient values close to 1 (), a situation is observed when relative changes of the consumption volume, the savings volume, investments and the GRP are equal: . In this case we may talk about the balanced model of endogenous stable economic growth since we have an optimized breakdown of the GRP to the current consumption and savings as potential investments for the subsequent GRP growth, that is, the availability of savings ensures the availability of investments as well as the availability of a positive feedback for a cumulative economic cycle.

If the GRP investment elasticity coefficient is close to 0 (), a situation occurs when the whole GRP volume of the previous stage is spent on the current consumption and in this case the value of the consumption volume does not depend on the GRP value since the scale of the GRP value is by far less than the potential consumption volume scale, that is, there are no savings and hence no investments required for a stable economic growth.

References:

1. A. Granberg. Modeling Spatial Development of National and World Economy: Evolution of Approaches, “Region: Economics and Sociology” Journal, No.1, 2007

2. V. Bessonov. Problems of Building Production Functions in the Russian Transitional Economy. – Moscow: The Institute of Transition Period Economy, 2002

3. Regions of Russia. Social-Economic Indicators. Moscow, Rosstat Publishers, 2011


[1]A. Granberg. Modeling Spatial Development of National and World Economy: Evolution of Approaches, “Region: Economics and Sociology” Journal, No.1, 2007, pp.87-106.

[2]V. Bessonov. Problems of Building Production Functions in the Russian Transitional Economy. – Moscow: The Institute of Transition Period Economy, 2002, p.46.

 

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Ваша оценка: Нет Средняя: 6.9 (8 голосов)
Комментарии: 4

Сороченко Ольга Анатольевна

Очень интересный подход к оценке инвестиционной деятельности. Очень жаль, что не все формулы и функции отображаются. К сожалению, представлены данные не по всем федеральным округам. в частности меня интересует Дальневосточный федеральный округ, которые не исследовался авторами.

Мельничук Марина Владимировна

Позвольте поблагодарить Вас за проявленный интерес к статье.Должна заметить,что анализ проводился по всем федеральным округам и данные по Дальневосточному округу есть. К сожалению, они не приведены из-за ограниченности страниц доклада.

Хачпанов Гия Вячеславович

Работа написана неплохо. Проведены исследования, осуществлены расчёты и сделаны выводы по инвестиционной деятельности в регионах.

Самбурская Наталия Ивановна

С невероятным интересом изучала доклад. Поразил комплексный подход к инвестиционной политике с учетом географических и социально-экономических особенностей регионов. Проведена огромная аналитическая работа. К сожалению, не увидела многих функций и формул, но с нетерпением буду ждать сборник материалов конференции.
Комментарии: 4

Сороченко Ольга Анатольевна

Очень интересный подход к оценке инвестиционной деятельности. Очень жаль, что не все формулы и функции отображаются. К сожалению, представлены данные не по всем федеральным округам. в частности меня интересует Дальневосточный федеральный округ, которые не исследовался авторами.

Мельничук Марина Владимировна

Позвольте поблагодарить Вас за проявленный интерес к статье.Должна заметить,что анализ проводился по всем федеральным округам и данные по Дальневосточному округу есть. К сожалению, они не приведены из-за ограниченности страниц доклада.

Хачпанов Гия Вячеславович

Работа написана неплохо. Проведены исследования, осуществлены расчёты и сделаны выводы по инвестиционной деятельности в регионах.

Самбурская Наталия Ивановна

С невероятным интересом изучала доклад. Поразил комплексный подход к инвестиционной политике с учетом географических и социально-экономических особенностей регионов. Проведена огромная аналитическая работа. К сожалению, не увидела многих функций и формул, но с нетерпением буду ждать сборник материалов конференции.
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