Statistical indicators of differences in structure: absolute and normalized. Absolute and relative indicators of the structure of the structure of the Ryabtsev structural shifts

Kk Belgibaeva - Ph.D., Associate Professor of the Department, NEU named T.Riryskulov

Annotation. This study identified features of the formation of financial resources of the sectors of the economy. Used methods of statistical analysis. Applied index V.M. Ryabtseva for the first time. The information database of the study is the official statistical materials of the financial account of the Republic of Kazakhstan.

Keywords: Economy, Sector, Financial Account, Structural Shifts, Index, Scale.

Introduction Accelerating changes in the global economy, growing disproportions determine the need for the study of structural shifts. Under the structural shift in the economy it is understood as the change in the "relationship between parts and all production in time and space" or a qualitative change in the relationship between the elements of the socio-economic system, due to the dynamics of quantitative characteristics.

In the financial balance of the country, economic operations are recorded between the institutional units of the country and the rest of the world ( foreign countries). Information on the activities of institutional units is grouped by six sectors of the country's economy: non-financial corporations (NFC); Financial corporations (FC); government bodies (OGU); non-profit organizations serving households (NKOCh); Households (DC); The rest of the world (OM). Of these, five resident sectors are internal economy (VE) of the country.

The value of the financial account is as follows:

1) it lines the results of the functioning of the economy at all stages of the economic cycle and foreign economic activity with financial results, completes the consistent range of accounts;

2) examines the composition and financial proportions in financial assets and obligations in the economy as a whole, as well as in each sector of the economy;

3) shows a mechanism for the redistribution of financial resources between credit sectors and borrower sectors. Volume financial resources It is composed of gross savings and balance of capital transfers.

Formulation of the problem. For the quantitative measurement of structural shifts in the economy, scientists in the field of statistics have developed a system of indicators. . Convenient for estimating structural differences are indices or coefficients K. Gatev and V.M. Ryabtseva. They are determined by the formulas:

where, and - specific weights (values) of the gradations of two structures, in our study two parts of the financial account balance: the acquisition of net financial assets and the adoption of pure financial obligations.

Dignity of the index V.M. Ryabtseva is that the results obtained can be interpreted on the score scale. It is shown in Table 1.

Table 1 - Estimation scale Measures of materiality differences in criteria

Results. Taking advantage of the above formula (2) and the recommended scale apply them to the structural and dynamic study of the financial account of Kazakhstan on official data published in the press. . As comparisons, we will accept the structure for 2009-2011. Accordingly, for two parts of the financial account balance. The results of the shif assessments we produced in the financial account stream structure are presented in Table 2.

* Note: Calculated based on the source.

According to the "Rest World" sector in 2010 compared with 2009, the values \u200b\u200bof the index V.M. Ryabtseva (0.955 and 0.893) indicate the opposite type of structures. In terms of changing financial assets, the share of securities acquisitions is significantly reduced, except for shares (on -350.8%) and the share of loans increased (by 408.8%). The following structural shifts occurred in terms of net liabilities: the share of currency and deposits decreased (on -107.7%), the share of loans increased (by 20.9%).

Internal economy in 2010 compared with 2009. Indices V.M. Ryabtseva amounted to 0.886 and 1.072 (Table 2), indicating the full opposite type of structures in two parts of the balance. During this period of time, the share of currency and deposit acquisitions (by -30.7%), loans (on -44%) were significantly reduced and the share of shares acquisitions was dramatically increased (34%). In terms of the commitments taken, the share on shares (by 40.5%) and securities by 35.3% increased. In Development Concept financial Sector RK noted that "in the post-crisis period from the beginning of 2010, the global economy is in a state of extreme instability." According to the "Rest World" sector in 2011 compared with 2010, the values \u200b\u200bof the index V.M. Ryabtseva, equal to 0.962 and 0.783, confirm the complete opposite of the structures. According to the explanation, we present the established structures of financial instruments in each part of the balance.

According to the "Other World" sector in terms of changing financial assets, a significant reduction in the share of acquisition of loans (at -391.5%) and other derivatives (by 25.5%), as well as an increase in the share valuable papers (by 377.9%), shares (by 38.3%).

In terms of the adopted net liabilities, the share of securities increased by 65.4%, the share of shares and other forms of participation in capital decreased (at -18.7%), the proportion of other receivables decreased (at -17.8%).

According to the internal economy in 2011 compared with 2010. The values \u200b\u200bof the index V.M. Ryabtseva (0.619 and 1,052, Table 2) indicate a very significant level of differences in terms of assets and the complete opposite of structures in terms of liabilities. In terms of the acquisition of financial assets there has been a significant decrease in the share of securities, except for shares (by 10.7%), an increase in the share of loans (by 22.8%). Parts of the adopted obligations decreased shares on securities (at -33%), other receivables (by 16.7%), the share of shares and other forms of capital participation increased to 43.3%.

According to the "Nefinancial Corporation" sector in 2010 compared with 2009. The values \u200b\u200bof the coefficient V.M. Ryabtseva (0.854 and 0.796, Table 2) indicate the opposite type of structures. In two parts of the balance, there has been a significant decrease in loans and loans. Despite high percentages Banks for loans, non-financial corporations concluded loan transactions for large amounts of money for the formation and expansion of their business. Thus, banks increased lending real sectors Economy. In addition, the assets of non-financial enterprises sharply increased the share of shares, other receivables.

In 2011 compared with 2010. The values \u200b\u200bof the index V.M. Ryabtsev indicates a significant level of differences in terms of assets changes and the opposite type of structures in terms of liabilities. The proportion of securities in two parts of the balance has significantly decreased. In addition, in terms of assets, the proportion of currency and deposits has increased dramatically. The share of loans increased in obligations, the share of other receivables decreased.

According to the "Financial Corporation" sector in 2010. compared with 2009. The values \u200b\u200bof the index V.M. Ryabtseva (0.725 and 0.861, Table 2) characterize the opposite type of structures. In terms of assets, a significant impact of a decrease in the share of securities, except for shares, other receivables. The proportion of currency and deposits increased dramatically. In terms of financial obligations, on the contrary, the share of currency and deposits, insurance technical reserves, has decreased, while increasing the share of other receivables and borrowings. Negative for banks The dynamics of growth of debts on loans is due to a number of reasons: a) in the pre-crisis years, the foreign loans denominated in freely convertible currency were uncontrolled in the pre-crisis years. Currency risks on the loan are completely transferred to borrowers; b) During the global financial crisis, the high growth rates of lending volumes, high competition, reduced the requirements of banks to borrowers, and high appetite increased risks. .

In 2011 Compared to 2010 The values \u200b\u200bof the index V.M. Ryabtseva is equal to these two parts of the balance of 0.975 and 1.372. They reflect the complete opposite of the structures (Table 2). In terms of balance assets, structural shifts occurred. The proportion of currency and deposits significantly decreased. The share of securities, except for shares increased dramatically. In terms of the adoption of financial liabilities, the proportion of loans, other receivables has significantly decreased. The proportion of obligations under the insurance technic reserve, currency and deposits increased.

By the state administration authorities in 2010 compared with 2009. The values \u200b\u200bof the index V.M. Ryabtseva 0, 987 and 0.351 indicate the complete opposite of the structures in terms of assets and a significant level of differences in the obligations (Table 2). In terms of balance assets, the share of other receivables and loans has significantly decreased. State bodies Provided loans in a smaller volume than non-financial corporations. Significantly decreased by the share of other receivables. At the same time, the share of acquired securities acquired, except for shares, as well as the adoption of obligations on them. In 2011 compared with 2010. Index V.M. Ryabtseva, equal to 0, 059 and 0.557, indicates a very low level of differences in terms of the acquisition of assets and a very significant level of differences in the acquisitions of financial liabilities. This condition is associated with a slight decrease in the share of shares and other forms of participation in capital. At the same time, the share of acquired securities, except for shares. In terms of commitment, the share of other receivables increased, the share of loans has decreased.

According to the "non-profit organizations serving households" in 2010 compared with 2009, the values \u200b\u200bof the index V.M. Ryabtseva (0.012 and 0.826) indicate the identical level of differences in the assets and the opposite type of structures in terms of the acquisition of financial liabilities. Compared to other sectors of the economy, non-profit organizations have a limited set. financial instruments: currency and deposits, other receivables and loans. In 2011 compared to 2010, the values \u200b\u200bof the index V.M. Ryabtseva 0,013 and 1,206 confirm the same type of structure as in previous years.

By the sector, households in 2010 compared to 2009. Index V.M. Ryabtseva, equal to 0.315 and 0.737, indicates a significant level of differences and the opposite type of structures. Such differences are caused by a decrease in the acquisitions of currency and deposits, as well as improving insurance technical reserves. In another part of the balance, the share of commitments to loans has sharply decreased and the share of other receivables increased.

In 2011 compared with 2010. The values \u200b\u200bof the index V.M. Ryabtseva (0.179 and 0.166) estimate a significant level of differences. During this period of time, the share of currency and deposit acquisitions has increased significantly and the share of insurance technical reserves has decreased. In terms of financial obligations, the share of loans has decreased and the share of other receivables increased.

Conclusions. The proposed and approved method of assessing structural shifts in the financial account of Kazakhstan for the period 2009-2011. allowed to obtain the following conclusions:

1. Structural shifts that occurred in the economy of the country do not have a clear focus: following the growth of indicators in one year there is a drop in the other, as well as the growth of the share of sectors on one financial asset accompanied by a drop on another asset.

2. Structural shifts in the sectors of the economy are negative.

3. Summarizing the indicators of structural shifts characterized differences in the structure of the sectors of the economy. The highest patterns of structural differences are observed in sectors: "Financial Corporations" and "Restaurants".

References:

1. Sivelkin V.A., Kuznetsova V.E. Statistical analysis of the structure of socio-economic processes and phenomena: Tutorial. - Orenburg: GOU VPO OGU, 2002. - 99С.

2. Ivanov Yu.N. Basics of the national office 2005 - 480s.

3. Statistical Collection National Accounts of the Republic of Kazakhstan 2008-2012 - Astana 2014 - 99c.

4. Resolution of Board National Bank Of the Republic of Kazakhstan dated April 23, 2014 No. 68 "On approval of rules for the application of early response measures and a methodology for determining factors affecting deterioration financial situation Second Level Bank.

5. Markarov T.V. Modern condition banking system RK and prospects for its development. - Astana: Bulletin of the Financial Academy, 2011, №1, p.52-57.

The development of a statistical aggregate is manifested not only in quantitative growth or decrease in the elements of the system, but also in changing its structure. Structure - This is the structure of the aggregate consisting of individual elements and connections between them. For example, the export of the country (the totality) consists of various types of goods (elements), the cost of which is varied by types and countries. In addition, there is a constant change in the export structure in the dynamics. Accordingly, the task of studying the structure of the aggregates and their speakers is arising, for which special methods have been developed to be discussed below.

In the topic 2, the structure of the structure calculated by formula (6) was considered, which characterizes the proportion of individual elements as a result of the absolute sign of the aggregate. In the subject 3, the system of indicators and methodology for analyzing the distribution of a set by the values \u200b\u200bof a separate feature (variational range of distribution) are considered. Here are indicators characterizing the change in the structure as a whole, i.e. "Structural shift". Practical use We consider these indicators on two examples presented in tables 19 and 20 (the first 4 columns isolated by bold, the initial data, and the remaining - auxiliary calculations).

Table 19. Distribution of the population of Russia largest per capita cash income (DDD)

Table 20. Distribution of the number of unemployed Russia in terms of education in 2006

The generalizing absolute indicator of the change in the structure can serve the sum of the absolute change modules of the sharedefined by formula (50):

, (50)

where d.1j. - share of the J-O group of elements in reporting period; d.0j. - The share of the J-O group of elements in the base period.

According to the table 19 in the 5th column, the column was calculated by formula (50): \u003d 0,212, that is, the total change in the share in the distribution of Russians for income was 21.2%. Similarly, according to the same formula, according to the table 20: 0.276, the difference in the structure of the unemployed among women and men in terms of education is 27.6%.

The calculation of the average absolute change, which occurs on one share (group, the element of the aggregate) does not give any for more information. But it is possible to determine how strong the change in the structure in comparison with the maximum possible value of the amount of modules, which is equal to 2. For this, the indicator is used. the degree of intensity of the absolute shift(or hangby), which is determined by the formula (51): the object as a general result of the indicator under study; k. - Number of objects.

According to the table 19 in the 6th and 7th columns, a calculation of the coefficient of herfindal by formula (52) was calculated: H.2005 \u003d 0.142 and H.2006 \u003d 0.1687, that is, the level of concentration in the distribution of Russians for revenues increased in 2006 compared with 2005. Similarly, according to the same formula according to the table 20: H.husband \u003d 0.2455 and H.women \u003d 0.2177, that is, the level of concentration in the distribution of unemployed in terms of men's education is higher than among women (the impact of the level of education on the status of the unemployed among men is higher than among women).

The reverse index of the Gerfindal value is the size of effective number of groups In a structure that shows the number of groups without taking into account groups having insignificantly small shares is determined by formula (53):

E \u003d.1/ H.. (53)

According to Table 19, the effective number of groups according to formula (53): E.2005 \u003d 1 / 0,142 \u003d 7.0 and E.2006 \u003d 5.9, that is, the effective number of groups in the distribution of Russians for revenues decreased from 7 in 2005 to 6 in 2005, which indicates the need to revise the intervals of the distribution of Russians in revenues next year. Similarly, according to the same formula according to the table 20: E.husband \u003d 1 / 0,2455 \u003d 4.07 and E.women \u003d 1 / 0.2177 \u003d 4.59, then the effective number of groups in the distribution of the unemployed in terms of the formation among men is higher and among women - 4 in men and 5 in women.

Another option to evaluate the degree of structuring of the phenomenon as a whole - zrafman index (54), which represents the sum of the absolute change modules of the shares per effective group:

. (54)

According to the table 19 V using formula (54): \u003d 0,212 * 0.142 \u003d 0.030, that is, the change in the shares per effective group in the distribution of Russians in incomes is insignificant (3.0%). Similarly, according to the same formula, according to the table, 20: 0.2455 * 0.276 \u003d 0.068, that is, the difference in the structure based on one effectary group among unemployed women and men in terms of education is weak (6.8%).

To assess changes between the two largest fractions (dominant shares) applies liphart index (55):

. 55)

where d.1m. and d.0m. - Share m.a group of elements in the reporting period and base periods; m. - Maximum share in the aggregate.

According to the table 19 by formula (55): \u003d 0.5 * (0.083 + 0.023) \u003d 0.053, that is, the average change in the share in two dominant groups of distribution of Russians by income was 5.3%. Similarly, according to the same formula, according to the table 20: \u003d 0.5 * (0.060 + 0.051) \u003d 0.056, that is, the difference in the structure in two dominant groups among unemployed women and men in terms of education is 5.6%.

The considered indicators are based on the middle arithmetic in various versions, and due to their linearity by deviations, they equally take into account large and small deviations. Quadratic indexes Allowed to compare various structures that are indistinguishable from the point of view of the amount of change.

Quadic Structural Shift Index Kazinta (56):

. (56)

According to the table 19 by formula (56): \u003d\u003d 0.035, that is, the average change in the fraction in the distribution of Russians for income was 3.5% (insignificant). Similarly, according to the same formula according to the table 20: \u003d\u003d 0.049, there is a difference in groups in the structure of unemployed among women and men in terms of education is 4.9% (insignificant).

Similar to Kazinz index the index of the smallest kids (or gallahher index), when calculating which, in contrast to formula (51), small differences in fractions are weaker influence the index than large, determined by formula (57) \u003d 0.117, that is, the difference in the structure of the unemployed among women and men in terms of education according to the MONRO formula is 11.7%.

The integral coefficient of the structural shifts of Gateva (59), which distinguishes structures with equal depths of deviations (takes higher values \u200b\u200bwhen groups have about the same shares):

. (59)

According to the table 19, according to formula (59): \u003d\u003d 0.179, there is, the intensity of changes in the share in the distribution of Russians by income according to the Gateev method was 17.9% (insignificant). Similarly, according to the same formula, according to the table 20: \u003d\u003d 0.192, the difference in the structure of the unemployed among women and men in terms of education according to the Gatev technique is 19.2% (insignificant).

Index Ryabtsevadiffering from (59) only by the denominator, it usually takes lower values, calculated by formula (60):

. (60)

According to Table 19, according to formula (60): \u003d \u003d 0.127, that is, the intensity of changes in the distribution of Russians by revenues according to the Ryabtsev technique was 12.7% (insignificant). Similarly, according to the same formula according to the table 20: \u003d \u003d 0.137, that is, the difference in the structure of the unemployed among women and men in terms of education according to the Ryabtsev technique is 13.7% (significantly).

Index of structural differences Salay (61), whose specialty is that the larger j Atkinson's index, index of generalized entropywhich will be discussed in the course of socio-economic statistics in the topic "Statistics of the standard of living".

There are the following conditional data on the structure of the monetary income of the population of the region, as a percentage:

It is necessary to conclude changes in the structure of monetary incomes of the population.

Decision.

According to the above indicators, it can be concluded that in the composition of the population of the population, the share of wages decreased (from 60% in the base period to 42% - in the reporting) with increasing swelling revenue from property and business activities (respectively, from 24% to 44%).

The generalizing characteristic of structural changes is given integral indicators of structural differences, the calculation of which is illustrating in the table:

The value of the calculated indicators of structural differences indicates significant changes in the structure of the monetary income of the population of the region.

Tasks 5-6. Invite the study of the dynamics of indicators, i.e. The intensity of changes in the time in time, which are carried out using the following indicators: absolute gains, growth rates, growth rates, the absolute value of one percentage of growth, as well as medium-sized indicators.

Depending on the research task, the indicators may be calculated with the comparison base variable (chains) and with a constant comparison base (basic).

1. Absolute increase - This is the difference between the compared level and the previous or basic:

chain absolute increase:

basis absolute increase :.

The amount of chain absolute increases is equal to the basic absolute increase for the corresponding period of time.

2. Growth rate - relative indicator characterizing the intensity of the development of the phenomenon; It is equal to the ratio of the studied level to the previous or basic and expressed in coefficients or percentages.

chain growth rates: 100;

basis growth rate: .

The product of the corresponding chain growth rates calculated in the coefficients is equal to the basic.

3. Rate of increase Determine in two ways:

a) as an absolute increase in the previous level (chain) or base level (basic):

chain growth rates:

basic growth rate: .

b) as a difference between growth rates and 100%:

T PR \u003d T R -100%.

4. The absolute value of one percent of the increase It is defined as the ratio of the chain absolute increase to the chain rate of growth (%) or for each subsequent level - as 0.01 of the previous level of speakers:

5. Medium absolute increase It is calculated on the middle arithmetic simple, that is, the division of the amount of chain absolute gains by their number

Middle growth rate Find an average geometric formula:

Average rapid growth Find out of subtraction from the average growth rate of 100%:

Methods of calculation medium level A number of speakers depend on its type and completeness of information.

1) B. interval Rows At equal time intervals average level Determined by the middle arithmetic formula:

2) in interval rows with unequal intervals of time - according to the formula of the average arithmetic suspended (by the size of the intervals):

3) in torquers with comprehensive data on changes in the moment indicator, the calculation is made according to the average arithmetic levels of the row levels that remained unchanged for certain periods of time suspended by the magnitude of the corresponding intervals;

4) In the torque rows of dynamics with equidal levels, the formula of the average chronological simple is used.

Analysis of disproportion in the employment of the population in municipalities The region as a whole and in the context of large and medium, small and micro enterprises was carried out with the help of the Ryabtsev index, the main advantage of which to other methods for measuring shifts in the number of employed population in the regions of the republic is that its value does not depend on the number of gradations Structures, that is, from the number of municipalities, therefore, there is no highlighting of structural changes, as well as in the presence of an assessment scale of the materiality of the differences in the index structures. Comparison of the structural indicators of the average number of employed on large and medium showed that the processes of phased reduction of employees of large and medium-sized enterprises had similar dynamics in each territorial education of the Republic of Mari El, while the system of small businesses not only does not cease its existence, but also constantly expanding, although Certainly, the level of development of small businesses in the Republic of Mari El is still extremely low. The formation of it is slowed down due to the established concentration of production, unstable economic Regulations, imperfections of existing tax legislation, weak state supportwhat makes it necessary to increase economic efficiency municipalities.

regional Employment Structure

employment of the population of municipalities

the index Ryabtsev

the level of differences in the structures

1. Bredneva L.B. Study of the structure and structural differences in the economy Khabarovsk Region // Bulletin HGEP. - 2011. - № 1 (52). - P. 4-10.

2. Substrators N.G. Analysis of the effects of factors on the volume and structure of gross regional Product Republic of Mordovia [Electronic resource]. - URL: http://sisupr.mrsu.ru/2010-1/pdf/podzorov3.pdf.

3. Republic of Mari El: Statistical Yearbook "Republic of Mari El" / territorial body Federal Service State statistics in the Republic of Mari El. - Yoshkar-Ola, 2011. - 464 c.

4. Statva A.L. Geographical Employment Analysis Omsk region: Author. dis. ... Cand. geogr. science - Barnaul, 2005. - 24 s.

5. Ution S.S. Employment and labor market in transformation russian economy: Author. dis. ... dot. ECON. science - M., 2003. - 48 p.

One of the main and most complex tasks of market transformations is the formation of an efficiently functioning, dynamic and civilized labor market. The state ceased to be the only guarantor of employment, and in the current conditions, each person himself decides, to work or not. The idea of \u200b\u200bthe employment role has changed radically. The results and consequences of the transformation of socio-labor relations were reflected in the change in the occupied population and its structure, which under the action macroeconomic factors Subjected to further distortion that reduces the economic activity and quality of life. First of all, this is due to the restructuring of employment due to the change in the structure.

It is advisable for studying the employment of the population and the processes of its regulation in the region to hold the typology of the areas of it, since the Republic of Mari El acts as a single monolith, but as a totality of districts with specific features Employment, priorities and development prospects.

To analyze employment in 17 administrative units of the republic (3 city districts and 14 municipal districts) were used in two time periods - 2000 and 2010. - values \u200b\u200bof the following indicators:

• the number of employed population (total), people, calculated on the ILO methodology according to selective surveys on employment issues at the end of the year;
• the average annual number of employees in large and medium-sized enterprises, people, calculated according to organizations and enterprises for the year;
• the average annual number of employees in small and microenterprises, people, calculated according to organizations and enterprises for the year.

Analysis of the total number of employed has shown that most of the total population and 2000, and in 2010. accounted for urban districts: 63.4 and 60.5%, respectively. In 2000, the proportion of employed population in the total number of employees was 53.7% - G. Yoshkar-Ola; 6.6% - Volzhsk, 3.0% - Kozmodemiansk. A large proportion in the total number of busy population belonged to the period of the Okomarysky (4.5%) and Zvenigovsky districts (3.5%).

In 2010, still on the city of Yoshkar-Olu accounted for the largest share of employees - 46.2%. But if for the period under study, the number of people employed in the capital of the Republic of Mary El decreased by more than 18 thousand people., T. Volzhsk and Kozmodemyansk for the time period studied not only expanded their shares in the distribution of employees to 8.2 and 3.8 % Accordingly, but also increased the absolute values \u200b\u200bof the total number of employed on its territory by 28.2 and 32.0%, respectively. Among the municipal regions in the number of people engaged in it in 2010, the Medvedev district was among the leaders, which was already 9.3% of the occupied population of the republic, and the Zvenigovsky district, where 5.9% of employed worked. Such disproportions in employment are primarily associated with the geographical distribution of enterprises in the republic, which are predominantly located in the cities of the region, which, of course, serves as an additional factor in increasing the role of cities in the development of society - urbanization.

Analysis of the average number on large and medium-sized enterprises has shown that the reduction of employees of this group in the period under study everywhere. Paraginsky, Mariy-Turkish, Kuzherth and Novoshlyalsky districts are especially allocated, where the growth rates of the analyzed indicator amounted to 34.8, 39.0, 40.2 and 40.7%, respectively. In general, the Medvedev region is significantly allocated, in which the reducing the average number of employed in the enterprises of this group has been only 9.0%. In 2000, 54.9% of the average number of employees in large and medium-sized enterprises accounted for cities (Yoshkar-Ola - 42.4%, Volzhsk - 8.3%, Kozmodemiansk - 4.2%). Among the areas of the number of employed in large and medium-sized enterprises, Zvenigovsky was allocated (6.2%) and Medvedev (9.6%). A similar situation was observed in 2010

As for small businesses, here the picture here is somewhat different. If in 2000, 16,013 people were employed in urban districts of the republic and this was 86.3% of the total number of employed this group (76.4% worked in Yoshkar-Ola), by the end of 2010 Despite the impressive increase in the number of employees of this group, only 68.8% of those employed remained behind the cities (58.6% of Yoshkar-Ola). Especially significant success in the development of small business, Medvedev and Morkinsky districts were achieved. If in 2000 their cumulative contribution to the average number of small and microenterprises workers was a little more than one percent, then by 2010, Medvedev region has already provided 6.0% of jobs, and Morkinsky - 2.2%.

Figure 1 shows the growth rates under investigators for 2010/2000. The largest growth rates for all employment indicators were distinguished by Medvedevsky district. Here, the increase in the total number of employed reached 275.6%, which is primarily caused by the formation and development of small businesses, the average number of employed in which increased 16.4 times. The YURINIS DISTRICT, on the contrary, against the background of a reduction in total employment by 51.9% in the development of small businesses has reached the most minor success. The growth rate of the average number at the enterprises of this group was the most minor in comparison with other administrative units of the republic - only 262.4%.

Fig. 1. The growth rate of the average annual number of employedin the context of municipalities.

The growth rates of the average number of people employed in large and medium-sized enterprises of the republic did not exceed 90.9% (Medvedevsky district). Only in urban districts, the average growth rate of this indicator was only 73.0%.

The negative dynamics of this indicator is due primarily to the reduction of the number of large and medium-sized enterprises and organizations in the territory of the Republic of Mari El, which in turn is due to the artificial fraction of larger enterprises in order to obtain benefits or lightweight tax regime, as well as the redistribution of the forms of ownership of enterprises of the region. Number of enterprises state form The property in the study period decreased from 861 to 746, of which the republican form of ownership - from 565 to 431.

The problems of the development of small businesses both in the country as a whole and in the republic five times are given quite close attention: the decrees of the President of the Russian Federation, the Government Decision and the Solutions of Local Authorities are issued, various specialized Funds And other elements of infrastructure to support small businesses, since it is small enterprises that take a prominent place in the market of goods and services, they are most susceptible to changing conditions, to the introduction of new techniques, the use of progressive technologies. With the help of individual entrepreneurship, social problems are solved as the creation of new jobs and other local problems. Only over the past ten years, the number of small businesses has grown by 542 units, while the average number of people employed here for the same period increased 2.4 times.

Transition to market relations He led to the transformation of the economy, the objective reflection of which is largely determined by the presence of generalizing information on structural changes. The priority of the study of the indicators of the structure, their dynamics are due to the need to submit an objective, high-quality, most complete information, adequately reflecting the analyzed areas in employment, authorities leaders for the adoption of effective management decisions.

At the same time, for the adjacent periods of the discrepancy in the structure of the total number of the working population, they were interpreted for mostly as "identity of structures" in the employment of the population in the context of municipalities, the index V.M. Ryabtseva - integral coefficient of structural differences - criterion,:

(1)

where and are specific gradations of two structures; - The number of gradations.

The advantage of this index to other techniques for measuring shifts in the number of employed population in the regions of the republic is that its value does not depend on the number of gradations of structures, that is, from the number of municipalities, therefore, the structural changes does not exist, as well as the stock assessment scale Significance of differences in the structures of the index (Table 1).

Table 1 - Scale Assessment Measurement Measures of differences in the number of people employed in the Ryabtsev index

In order to assess the materiality of differences in the structure of employment of municipalities of the Republic of Mari El, calculations were made by the values \u200b\u200bof Ryabtsev indexes by year over the time interval from 2000 to 2010 for each of the employment indicators under consideration: the number of employed population (total), people; the average annual number of employees on large and medium-sized enterprises, people; The average annual number of employees in small and micro enterprises, people.

Table 2 - Assessment of the materiality of structural differences in employment in the municipalities of the RME

As follows from Table 2, the value of the criterion when comparing the structural indicators of the number of employed population for the entire observation period (from 2010 and 2000) amounted to 0.098, which indicates a low level of differences in the structure of employed population in the municipalities of the republic.

For adjacent periods of discrepancies in the structure of the total number of the working population, they were interpreted for mostly as "identity of structures", which suggests that transformation in the distribution of the number of employed in administrative units in a very slow pace (Fig. 2).

Fig. 2. Dynamics of structural changes in the employment of the republic.

The most significant structural transformation during the period under study was characterized by a small business of urban districts and municipal districts.

"A significant level of difference in structures" occupied in a small business was celebrated in 2003-2004, when the growth rate of the average number of employed on small and large enterprises republics amounted to 125.4%. Especially strongly on a general background was allocated for that period the Okrugarysky district, in which only for the year the average number of employees of this group increased more than 8 times, while in the urban districts of the republic, the small business was in stagnation.

In the last decade, most administrative units of the region occurs an unusually rapid increase in the number of small enterprises. Validation all the time (small businesses quickly appear, but they can and quickly break), the system of small businesses not only does not stop its existence, but also constantly expanding, although, of course, the level of development of small businesses in the Republic of Mari El is still extremely low. The formation of it is inhibited due to the established concentration of production, an unstable economic situation, the imperfection of the current tax legislation, weak state support.

The need to increase the economic efficiency of municipalities sets new tasks before the territories, primarily associated with the choice of a competitive model. regional economyallowing you to maximize the existing potential.

Reviewers:

• Katkov Nikolai Semenovich, Doctor of Economics, Professor, Professor of the Department of Economic Cybernetics FGBOU VPO "Mary State University", Yoshkar-Ola.
• Schvetsov Mikhail Nikolaevich, Doctor of Economics, Professor, Rector of ANO VPO "Interregional Outdoor Social Institute", Yoshkar-Ola.

Bibliographic reference

 [Email Protected] Irina Alexandrovna Echina,

postgraduate student of the Department of Economic Informatics and Management, UDC 338 (470) Volgograd State University

Structural shifts and structural differences in economic systems in Russia

The article presents the results of calculations of structural changes in the regions of Russia for the period from 2004 to 2011. in terms of gross value added by type economic activity. Calculations were obtained on the basis of the Ryabtsev index, the choice of which is explained by the estimated scale of the materiality of structural differences and the possibility of obtaining adequate estimates on any set of statistical data. Based on the obtained index values, the author identified six groups of regional economic systems, characterized by the identical structure, very low, low, significant, significant and very significant levels of structural differences. To determine the industries, due to the changes in which structural shifts occurred, the mass, speed, structural shifting indices for the federal districts of Russia were calculated. Negative dynamics of the specified characteristics of structural shifts are characterized by industries agriculture and manufacturing. Calculated indexes of structural differences of the economic system of Russia for a longer time interval (1990 - 2011), covering the ascending and downward phases of the fifth long wave Economic cycles confirm the presence of structural shifts in the economic systems of the Russian economy.

Keywords: structural shift, structural differences, economy of regions of Russia, sectoral structure, gross value added.

Structural Shifts and Structural Differences of Economic Systems in Russia

The Paper Presents The Results of the Statistical Survey of the Structural Changes in The Russian Regions for The Pereiod from the 2004 to 2011 in Terms of Gross Value Added According to the Type of Economic Activity. The Calculations Were Obtained using the Riabtsev Index Which Was Chosen for Having A Rating Scale for Measuring The Level of Structural Difference and The Ability to Obtain Adequate Estimates of Any Set of Statistical Data. Having Obtained The Values \u200b\u200bof The Relevant Indices The Author Identifies Six Groups of Regional Economic Systems: With Verylow, Low, Substantial, Significant and Very Significant Level Of Structural Differences. In Order to Determine The Sectors That Caused The Structural Shifts, The Author Calculates Mass, Velocity, and Indices of Structural Changes in The Federal Districts of Russia. The Author Reveals That There Is a Negative Dynamics In These Characteristics of Structural Changes in The Agricultural Sector and the Manufacturing Industry. The Calculated Indices of the Structural Difference For A Longer Time Period (1990 - 2011) Cover The Ascending and Descending Phases of The Fifth Long Wave Of Economic Cycles and Confirm the Presence of Structural Changes in the Economy of the Russian Federation.

Keywords: Structural Shift, Structural Differences, Regional Economy in Russia, Sectoral Structure, Gross Value Added.

The development of convergent technologies and the formation of a new technological direction has a significant impact on the functioning of economic economic systems and the level of socio-economic development of the regions. New technologies involved in the creation of a product of regional production determine the structure of the economy, the predominance of certain industries. In order to determine the presence of transformational processes in regional economic systems, it is necessary to evaluate structural shifts and structural differences. For this, there are a number of indices: the Herfindelle - Hirschman index, the entropy index, the relative concentration index, the dispersion indicator of market fractions, the integral coefficient of structural differences K. Gateva, the index of structural shifts A. Salay, the index V.M. Ryabtseva.

Each of the indicators has advantages and disadvantages. Herfindal index - Hirschman traditionally

it is used to measure the concentration of production, but it is not allowed for structures with different number of elements. The entropy index is the opposite concentration indicator and is less common. The dispersion of market fractions is a coarse analogue of the above indexes, is used as auxiliary means. The relative concentration index does not have clearly defined limits for its interpretation. The Gateev coefficient, the Salaya index and the Ryabtsev index are the most accurate and convenient tools to solve the objectives of the objectives.

The main problem of using indices from socio-economic statistics is the lack of an intuitive understanding and, as a result, the complexity of choice between them. Ryabtsev and Gateev indexes differ only by the denominator, but the lack of clear interpretation does not allow to allocate the best.

Gatev Index:

Table 1

Salaya index:

Ryabtsev index:

Scale Estimation Measurement of the materiality of structural differences in the Ryabtsev index

Interval of values \u200b\u200b1 "Characteristics of structural differences

0,000 - 0.030 identity structures

0,031 - 0,070 Extremely low level difference in structures

0,071 - 0,150 Low level differences in structures

0.151 - 0,300 significant level of differences in structures

0,301 - 0,500 Significant level of differences in structures

0,501 - 0,700 Very significant level of differences in structures

0,701 - 0,900 opposite type of structures

0,901 and above the complete opposite of the structures

where the BU - the specific gravity of the signs in the aggregates; ¡- the number of gradations in the structures.

Testing the methodology for calculating structural changes in industry Structure Federal Districts of the Russian Federation for the period 2004 - 2011 Based on the indexes Ryabtsev, Gatev and Salay makes it possible to conclude about the presence of structural changes in the regions (Fig. 1).

The accuracy of calculations is confirmed by the implementation of inequality developed by V.M. Ryabtsev:

the index Ryabtsev< индекс Гатева < индекс Салаи.

As follows from the results of the dynamics of the indices presented in Fig. 1, the author's calculations are true.

For further assessment of the materiality of structural shifts in the gross value added (VDS) by type of economic activity in the regions of Russia, the Ryabtsev index is used due to a number of reasons: 1) the indices of Salay and Gateva cannot be calculated in the event of equality of the specific gravity of the industry zero; 2) The Ryabtsev index has an assessment scale of the materiality of structural differences (Table 1).

Conducting an appraisal study of the structure of the DVS federal districts of the Russian Federation by type of economic activity for the period from 2004 to 2011. Allowed to identify only three levels of differences in structures (Table 2).

Table 2

Estimation of the materiality of structural differences

in the gross value added of federal districts for the period 2004 - 2011.

Volga Federal District 0.048 Extremely low level differences

Russian Federation 0,060

Central Federal District 0.062

Southern Federal District 0.075 Low Differences Structures

Ural Federal District 0.077

Northwest Federal District 0.085

North Caucasus Federal District 0.149

Siberian Federal District 0,168 significant level of differences in structures

Far Eastern Federal District 0.219

Fig. 1. The schedule for the dynamics of structural changes in the Russian economy in the indexes of Salay, Gatev and Ryabtsev for the period 2004 - 2011. (Sost. Author based on sources)

The average Russian economy structure, the structure of the Central and Volga federal districts are characterized by quite low level Differences of structures. Low level of differences in the structures of economic systems distinguishes the North-West, South, North Caucasian and Ural Federal Districts. A significant level of distinction for the seven-year period is characteristic of the Siberian and Far Eastern Federal Districts.

To assess the degree of difference in the structures of the economic systems of federal districts, the calculation of the Ryabtsev index in relation to the structure of the economy of the Southern Federal District (Table 3) was carried out.

T a b l and c and 3

Assessment of the materiality of structural differences in the gross value added of the Southern Federal District to the Federal Districts of Russia in 2011

Region index Ryabtsov Interpretation

SFO - RF 0,218 significant level of difference in structures

SUFO - CFO 0,298 significant level of differences in structures

SFO - SPO 0,224 Significant level of differences in structures

SMFO - SCFO 0,165 Significant level of differences in structures

SFO-PFO 0.246 Significant level of differences in structures

SFO - UFO 0,524 is a very significant level of differences in structures

SFO-SFO 0,264 Significant level of differences in structures

SUFO - DVFO 0,462 significant level of differences in structures

Based on the obtained data of the Ryabtsev index for federal districts, it can be concluded that the sectoral structure of the Southern Federal District of the Russian Federation has a significant level of difference in the structure of the industry on average in Russia. In comparing the structures of the Southern and Ural federal districts, the Ryabtsev index matters 0.524, which indicates a very significant level of the sectoral difference in compared structures. A significant level of sectoral difference with the index Ryabtseva 0.462 SWFO has with the Far Eastern Federal District. When compared with the central, northwestern, North Caucasus, Volga and Siberian federal districts, the calculated Ryabtsev index indicates a significant level of difference in structures. The North Caucasus Federal District is closest to the South Federal District in the sectoral structure, which is explained by the territorial geographical features and history of the administrative division of Russia to the federal districts.

An analysis of the calculated values \u200b\u200bof the indexes of structural differences for the regions of Russia for 2011 compared to 2004 allows to distinguish 6 groups of regions,

the identical structure, a very low, low, significant, significant and very significant level of structural differences.

Among the 92 constituent entities of the Russian Federation (including the federal districts and the city of federal significance), the identity of the 2011 economy structure in relation to 2004 is noted in the Khanty-Mansi Autonomous District.

The group of subjects with a very low level of structural differences includes the structure of the economy on average in the Russian Federation, as well as 5 regions (Nenets Autonomous Okrug, Nizhny Novgorod region, Tyumen region, Novgorod and Vologda region) and 2 federal Districts (Volga and Central).

The most extensive group constitutes regions with a low level of structural differences - 49 subjects, including the overall structure of the economy of the Southern, Urals, North-Western and North Caucasus federal districts. Low level of structural differences is characterized by the structure of the cities of federal significance - Moscow and St. Petersburg.

A significant level of structural difference distinguishes 30 constituent entities of the Russian Federation, including Siberian and Far Eastern Federal Districts with their regions, with the exception Altai Region, Tomsk Region, Novosibirsk Region and the Republic of Sakha (Yakutia). In addition, this group includes the regions of the Volga Federal District: Kirovskaya (with the Ryabtsev index of 0.153) and Penza (0.159) regions; Regions of the Central Federal District: Kaluga (0.158), Kostroma (0.169) and Lipetsk (0.244); Regions of the Southern Federal District: Krasnodar Territory (0.159) and the Astrakhan region (0.187); Three regions of the North-West Federal District: Arkhangelsk region (0.165), the Republic of Komi (0.167) and the Republic of Karelia (0.189); Four subjects of the North Caucasus Federal District: Stavropol Territory (0.158), Republic of Dagestan (0.185), Chechen Republic (0.189), Kabardino-Balkarian Republic (0.216).

A significant level of differences in the structures for the seven-year period was obtained in two regions: the Republic of Ingushetia - 0.329 and the Jewish Autonomous Region - 0.398.

In general, in the regions of the Russian Federation for 2011, the most significant structural changes were noted in the regions of the Far Eastern Federal District: Sakhalin Oblast - 0.539 And the Chukchi Autonomous District - 0.580. They are included in the group of regions with a very significant level of differences in structures throughout the entire period from 2004 to 2011.

In order to identify industries, due to changes in which transformations in the industry structure of gross value added are observed, the mass, speed and indexes of structural shifts from 2004 were calculated. According to the Federal Districts of the Russian Federation.

The calculated data of the mass of the structural shift to produce the sectors of the federal districts of the federal districts is that for all federal districts and the average Russian value, the mass shift in the agricultural industry is negative, which indicates a decrease in the share of the industry in the overall structure of the gross regional product. Also reduced the proportion of processing production. Reducing the speed and index of structural shifts in the branches of the rural

the saint and the manufacturing industry confirms the decrease in the specific gravity of these industries in the structure of regional economic systems and their stagnation.

Positive dynamics are available branches of construction, hotel and restaurant business, operations with real estate, Government and military security, health care. In a number of federal districts, an increase in the share of the mining sector is noted, with the exception of the Central and Ural federal districts and the south of Russia.

In general, the calculation of the characteristics of structural shifts by industry for the period 2004 - 2011. Does not reveal significant structural differences. However, the assessment of the structures of the economic system of Russia for the period 1990-2011. Resets a significant level of structural shifts (Fig. 2).

6 groups of regional economic systems of Russia, characterized by the identical structure, are highly low, low, significant, significant and very significant levels of structural differences;

Based on calculating the mass, speed and index of structural shifts, determined negative dynamics in the industries of agriculture and manufacturing;

For the period 1990 - 2011. The structure of the Russian economy is characterized by significant structural differences determined by the affiliation of economic systems to different phases economic cycleWhat confirms the impact of new key factors of development on an existing system of economic activity.

1. Aralbaeva G.G., Afanasyev V.N. Prediction of structural shifts in the Senenburg Economic Structure

Fig. 2. Histogram of the dynamics of the values \u200b\u200bof the Ryabtsev index on VDS by the types of economic activity of Russia for the period 1990 - 2011. (Sost. Author on the basis of sources).

The presence of significant structural differences in the economy for the 20-year period under consideration is due to the comparison of structures relating to different phases of the fifth "post-kontrayev" long wave: ascending and downward phase. The 2011 economy is included in the downstream phase, the 1990s economy. - in ascending, which determines the presence of a significant level of structural differences of compared economic systems.

Thus, summarizing the calculations of structural shifts and structural differences in the Russian economy, we obtained the following results:

The structure of the economic systems of the federal districts of Russia in 2011 compared with 2004 has changed slightly: only two federal districts are distinguished by a significant level of structural differences, the average Russian economy structure is characterized by a very low level of the differences in structures;

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