Course work: Analysis of the dynamics of Russian foreign trade. Analysis of the possibility of developing the export of goods in conditions of production reduction

20.09.2019

Statistical analysis of the influence of economic factors on indicators foreign trade Russia

Type of work: Dissertation Subject: Statistics Pages: 140

Original work

Excerpt from work

The relevance of the dissertation research topic is determined by the diversity and complexity of the processes of reforming the Russian economy, reflecting their influence on the state and development of foreign trade, the urgent need to analyze the formation of exports and imports of goods in the context of reforms and the use of its results in customs practice in order to solve problems of both foreign trade, and the country's internal economic policy.

The radical economic transformations of recent years have contributed to the formation of a qualitatively new basis for the interaction of the domestic economy with the world economy and have significantly increased the role of foreign economic factors in the development of the country.

The negative consequences of the economic reforms carried out in Russia have led to an extremely unfavorable state in the country's economy and macroeconomic instability. As a result of the sharp drop in production, federal budget revenues from the real sector of the economy decreased significantly. In an effort to make up for the loss of revenue from the country's budget, customs authorities pursue their own policies, often pursuing narrow departmental interests. Customs policy, largely determining the development of foreign trade, as well as relations with trading partners, also influences the economic situation in the country. As S. M. Menshikov notes in his work: “Foreign economic policy must be constantly coordinated with domestic economic policy. Specific steps in foreign economic policy must not be allowed to contradict the priorities of the macroeconomic policy of the state as a whole.”

Thus, the choice of priority in customs policy in the current conditions will determine the possibility economic development country and strengthening its position in the world market.

The state of the country's economy and, above all, production largely determines the volume of foreign trade, as well as the structure of exports and imports of goods. Therefore, the problem of analyzing the influence of such economic factors as the volume of industrial production and domestic consumption, the volume of gross domestic product (GDP) and per capita income, the ratio of domestic and world prices, the real exchange rate of the ruble on foreign trade indicators is very relevant and is of great practical importance in determining foreign trade policy.

Foreign trade processes taking place in Russia during the period of economic reforms have their own characteristics. This fact is confirmed by the growth of exports of goods in the context of a significant reduction in industrial production and the growth of imports in the context of a decline in GDP. At the same time, we can note the presence of specific factors characteristic of the development of Russian foreign trade. Consequently, the identification of economic factors influencing the formation of Russian foreign trade and their reflection in models for analyzing and forecasting the volume of exports and imports of goods has both scientific and practical significance.

The object of the study is Russia's foreign trade in the context of economic reforms.

The subject of the study is the mechanism of formation of export and import of goods under the influence of main economic factors and its formalization.

The purpose of the dissertation is to analyze foreign trade, determine the most important economic factors and reflect them in models for analyzing and forecasting the volume of exports and imports of goods during the transition period of economic development in Russia.

Based on the purpose of the dissertation, the following tasks were set:

- study the dynamics and structure of exports and imports of goods -

- give comparative characteristics foreign trade indicators and the main ones that determine their significance economic indicators Russia and other countries of the world -

- analyze foreign trade policy and methods of customs regulation of export and import of goods in Russia during the period of economic reforms -

— determine the main economic factors influencing the volume of exports and imports of goods;

— build models for analyzing and forecasting exports and imports of goods -

— provide an economic justification for the results of the analysis carried out on the basis of the proposed models.

The set objectives determined the logic of the research and the structure of the dissertation.

The work explores economic conditions that have developed as a result of ongoing reforms, as well as related changes in customs policy.

For a more complete picture of the economic state of Russia and the development of foreign trade, an analysis of indicators of the state and development of foreign trade, industrial production, GDP, price dynamics and inflation processes, volumes and structure of capital investments and other indicators is carried out in comparison with other countries of the world at different levels economic and social development. The position of Russia in modern world trade is analyzed, determined by its position in the world according to the main economic and social indicators.

To conduct a comparative analysis, both Russian and foreign sources of statistical data were used.

The main objective of the dissertation is to determine the economic factors influencing the volume of exports and imports of goods during the period of economic reforms in Russia.

To do this, the work analyzes the dynamics and structure of exports of goods and production, determines the reason for the growth of exports in conditions of a general decline in production, examines the impact on the volume of foreign trade of the relationship between domestic and world prices and the conditions for their formation, and determines the interdependence of demand and supply of exports. A more detailed analysis of exports is carried out using the example of energy resources, which occupy about half of its volume, and a specific product - crude oil. To analyze the main economic factors influencing the export of goods, materials from publications by A. Agalarov, S. Aleksashenko, V. Andrianov, E. Baranova, O. Bogomolov, A. Vavilov, A. Illarionov, A. Mastepanova, V. May are used , S. Menshikov and other economists.

The identified trends are also confirmed in some foreign sources (for example, S. Fischer, R. Dornbusch, R. Schmalenzi. Economics).

Next, an analysis is made of the dynamics and structure of imports of goods in Russia in 1991-1998, the need for imports and the ability to import goods. An analysis of the structure and dynamics of Russia's gross domestic product (GDP) confirms the possibility of increasing the import of goods even in the context of a reduction in GDP. Great importance is given to the analysis of indicators that most influence imports, such as the ruble exchange rate against the US dollar, the real ruble exchange rate, inflation rates and others. When considering issues of customs regulation of imports, relatively cheap imported goods are distinguished, which are highly dependent on customs duties and taxes (food), and expensive ones, accessible to high-income groups of the population (cars).

The theoretical conclusions of the dissertation research were confirmed by the developed models for analyzing exports and imports of goods using the example of specific indicators of economic development in Russia during the transition period from 1991 to 1998.

Models for forecasting exports and imports of goods developed by the IMF were taken as the basis for the study. These models include the main factors influencing the volume of exports and imports of goods, that is, they take into account the main trends in the development of the country’s economy. The models are widely used in forecasting balances of payments in many countries. They can be used in analyzing and forecasting the volumes of exports and imports of goods in Russia with some modification of the influence of the indicators included in them.

To identify trends in the development of exports and imports of goods in the transition period of Russia's development and reflect them in models for analyzing and forecasting foreign trade, the works of Linwood T. Geiger, R. Winn, R. Dornbusch, G. Kassel, V. Leontiev, P. Lindert, M. Todaro, S. Fischer, K. Holden, R. Shmalenzi and other scientists.

Existing publications on the topic of research are devoted mainly to general issues of foreign trade, while the problem of identifying patterns in the formation of exports and imports of goods determined by the economic conditions of Russia's development in the transition period, and reflecting them in models for analyzing and forecasting foreign trade volumes, has not been sufficiently developed.

The theoretical and methodological basis of the dissertation consists of scientific developments of domestic and foreign scientists and scientific organizations in the field of analyzing the influence of economic indicators on the volume of exports and imports of goods, as well as existing experience in modeling foreign trade turnover.

During the dissertation research, methods were used * groupings, analysis time series and structures of indicators, index method, correlation and regression analysis, graphic method and others.

The information base for the study was data from customs statistics of Russia, official publications of the State Statistics Committee of the Russian Federation, Eurostat, and the UN Statistical Commission. When carrying out calculations using the developed models, the BTAteTYUA software was used.

The scientific novelty of the dissertation research is:

Justification of the possibility of increasing the volume of exports and imports of goods in the context of a reduction in industrial production (domestic consumption) and GDP

Russia in the transition period of its development -

Analysis of the impact of the ratio of domestic, export and world prices, as well as changes in the real exchange rate of the ruble on the volume of exports and imports of goods -

Determination of the main economic factors influencing exports and imports in general, individual goods and product groups -

Development on indicators of economic development of Russia in 1991-1998. dependency models:

— export of goods in general and export of crude oil on determining economic factors: production volume, domestic consumption, the ratio of domestic and world prices;

— import of goods in general from the main economic factors: changes in the rate of decline in GDP and the real exchange rate of the ruble;

Assessment of changes in the volume of exports and imports of goods in * 1999, carried out on the basis of developed models -

Justification of the possibility of using the research results in customs practice.

Practical significance. The results of the analysis of the dynamics of foreign trade, the main economic factors determining it and the use of the developed models make it possible to assess development prospects and formalize the mechanism for the formation of exports and imports of goods in Russia for their subsequent consideration when determining foreign trade and customs policy. As a result, it becomes possible to solve management problems at both the strategic and tactical levels:

— adjust the foreign trade and economic situation in the country through customs regulation measures;

— determine and control foreign exchange earnings and income from foreign trade operations.

Thus, changing export and import duties will allow us to adjust the ratio of domestic consumption and export of resources, as well as influence the ratio of imported and domestic goods in Russian markets in order to develop the economy and foreign trade.

Testing and implementation of research results.

The developed models were included in research work carried out in the Russian customs academy(RTA) on the topic “Methodology of statistical analysis and forecasting of the receipt of customs duties in the federal budget of Russia” and in the report on the research work “Methods for forecasting federal budget revenues” of the Research Institute financial institution Ministry of Finance of the Russian Federation.

The provisions and conclusions of the dissertation were presented in the abstracts scientific-practical conference“Problems of improving customs affairs in the Russian Federation”, held on March 18-19, 1999 at the RTA.

The results of the analysis of indicators of the dynamics of exports and imports of goods, as well as the economic factors influencing them, are used in the educational process of the RTA in the course “Customs Statistics”.

1. Methods and models for analyzing and forecasting the export and import of goods // Problems of improving customs affairs in the Russian Federation: Materials of the scientific and practical conference, March 18−19, 1999 - M.: RIO RTA, 1999. - 0.2 pp. .

2. Analysis of the dynamics of indicators of foreign economic activity of the Moscow region // Russian Economy: theory and practice of revival: Interuniversity collection of scientific papers. Vol. 3. -M.: Publishing house Ros. Econ. Acad., 1999. - 0.4 p.l.

3. The influence of inflationary processes on foreign trade indicators // Finance. - 1999. - No. 5 (co-author). - 0.5 p.l.

4. Export forecasting models // Methods for forecasting federal budget revenues. Applied research. Per. No. 01.99.6 715. M.: NIFI Ministry of Finance of the Russian Federation, 1998 (co-authored). - 0.3 p.l.

5. Statistical control and reliability of regional customs statistics // FORUM: Methodological collection. Issue 6. M.: RIO RTA, 1999 (co-authored). - 0.6 p.l.

The results of the study confirmed the presence of a close correlation between the following indicators(tables 2.1 and 2.3 of Appendix 2):

- the volume of imports of goods (in current prices, billion dollars) and the growth of the real exchange rate of the ruble (as a percentage compared to 1992) - R = 0.95-

- the volume of imports of goods and an indicator expressed as the ratio of annual indices of the physical volume of GDP to their average value - K = 0.91.

The mean square errors of the equations are quite small values (8y]=5.36 and 8y2=3.93 with yv=57.1 and ay=11.8), which indicates the adequacy of the models |20, www.site|.

The significance of the regression coefficients a0, b0, b>1 is indicated by the values of the ^criterion.

According to the resulting data in Tables 2.1 and 2.3, the models for analyzing and forecasting the import of goods, depending on the main economic factors, will have the following form: y, = -125.1 + 1.823 x, y2 = 35.8 + 0.042×2,

Graphs of model residuals indicate the absence of autocorrelation (Figures 2.1−2.4).

Between the rest of the functions.y! and y2 there is no correlation dependence, therefore, we can combine the two functions y] and y2 by introducing correction factors: .

Y~ k * y, + (1-k)* y2, where k - correction factor-

Y1 is the volume of imports of goods in current prices, billion dollars, depending on the ratio of the physical volume index of GDP to the average value of the GDP index, expressed as a percentage; y2 is the volume of imports of goods in current prices, billion dollars, depending on changes in the real exchange rate of the ruble ( 1992=100%).

The data in Tables 2.5 and 2.6 of Appendix 2 indicate a fairly accurately selected model that generalizes the influence of two factors on the volume of imports with a value of k = 0.297.

As a result, the model for analyzing and forecasting imports of goods will have the following form: y = 0.3 y, + (1−0.3) y2

The theoretical values of the volume of imports of goods (calculated using the model) deviate from the actual values by an average of 4%, which indicates a sufficient high precision models (Fig. 3.2.5).

1992 1993 1994 1995 1996 1997 1998

In 1999, the volume of imports amounted to $41.1 billion, or 69.8% of the import volume in 1998. As a result of the sharp depreciation of the ruble in August 1998, forced import substitution occurred, which caused an increase in production. Therefore, GDP growth in 1999 relative to 1998 of 103.2% did not affect the growth of imports and the volume of imports changed under the influence of changes in the real exchange rate of the ruble. It is possible to propose a model of the dependence of changes in imports of goods under the influence of changes in the real ruble exchange rate by quarter.

CONCLUSION

The conducted dissertation research allows us to draw the following conclusions.

1. The transition from central planning to a market economy is inevitably associated with the growing openness of the Russian economy. The state monopoly of foreign trade was eliminated, under which all foreign trade operations were carried out by monopoly state associations according to a plan approved by the government. Enterprises received the right to directly enter the foreign market and communicate directly with foreign companies.

However, the state retained some regulatory and supervisory functions. This applies, first of all, to customs regulation (customs duties, currency control system, regulation of the activities of foreign commercial and other structures in Russia) and other aspects of foreign economic activity.

The direction of foreign economic policy must be consistent with domestic economic policy and be carried out in the interests, first of all, of the economy of one’s state.

2. The results of the analysis of the development of the Russian economy during the period of reforms showed that economic situation the country during this period became significantly more complicated.

The strict deflationary measures taken during the reform in conditions of free pricing led to the stratification of property of both individuals and legal entities, reduction or complete elimination of a number of industries in the production and non-production spheres financed from the budget, as well as the redistribution of resources in favor of enterprises with a fast capital turnover period. Ultimately, this led to distortions in the reproductive structure, a drop in production and the elimination of the basis for its restoration.

The problems of macroeconomic stability, which could be achieved, first of all, by reforms of tax and budget policy, were given secondary importance. As a result, the process of privatization and price liberalization was carried out against a backdrop of extreme macroeconomic instability.

Among the main reasons negative consequences The undertaken course of economic reforms should include the ideas contained in it about the minimal role of the state in regulating the economy.

The impact of the ongoing economic reform affected all areas without exception. National economy and foreign trade as well.

And although foreign trade has remained a fairly stable sector of the economy in recent years, last years There is a decrease in the value of exports and imports of goods.

3. The main factors influencing the volume of exports are production and domestic consumption of exported goods.

In Russia, with a general decline in production, the reduction in production in the extractive industries producing export products occurs at a slower pace than in other industries.

As a result, the fall in domestic consumption of exported goods in Russia, caused by the industrial recession, freed up a significant amount of raw materials for export.

4. Between the exchange rate and the volume of exports, as well as export prices, there has always been close relationship. In all countries, an increase in the quotations of the national currency makes exports less effective and, conversely, a decrease in the quotations of the national currency makes export operations more profitable.

In Russia, the opposite situation is observed. In recent years, the price level in Russia for exported goods has been lower than the level of world prices. Therefore, the increase in the growth rate of the real exchange rate of the ruble against the dollar did not have a decisive impact on the decline of the latter. As a result, exports grew.

However, in recent years there has been a tendency for domestic and world prices to converge.

In particular, if oil domestic prices lower than world prices, then Russian prices for processed products exceeded world prices. In 1998, domestic oil prices and world prices, as the latter declined, came closer. Exports were not as profitable in the first half of the year as in previous years. The devaluation of the ruble in the fall of 1998 again made the export of a number of goods, including oil, profitable.

5. Research has shown that the main factors influencing Russia's foreign trade differ from those of developed countries. This was especially evident when analyzing the dynamics of imports.

Statistical analysis of data on imports from Russia and Moscow over a number of years based on standard foreign models showed that only individual factors included in them can be used.

For example, these models quite rightly note that imports increase as real gross domestic product (GDP) increases. The higher the growth rate of the latter, the higher the imports. In Russia, the dynamics of real GDP and imports are different.

Analysis of the structure of GDP and imports proved the possibility of a relationship between imports at current prices and indices of the ratio of annual GDP growth rates to their average value. Consequently, fluctuations in imports correspond to changes in the rate of decline rather than growth of GDP compared to the previous year.

6. A favorable factor for the growth of imports of all types of goods was the increase in the real exchange rate of the ruble. The real exchange rate rose because the nominal depreciation of the ruble was less than the rise in prices in Russia.

Despite the fall in the growth of the real ruble exchange rate, it constantly increased from 1992 to 1997. This contributed to an increase in imports in current prices in this time period, and from 1995 to 1997 in comparable prices. The significant devaluation of the ruble in 1998 affected both the real exchange rate of the ruble and imports, which decreased.

7. When constructing models for analyzing and forecasting the export and import of goods, the discontinuous regression method was used, when in certain economic conditions certain economic factors become the most influential. Based on annual data on the volume of exports and imports of goods and the economic factors influencing them, the following were developed:

— a model for analyzing and forecasting the index of the physical volume of exports of goods (as a percentage of 1991) depending on the index of the physical volume of industrial production (as a percentage of 1991) and changes in the ratio of domestic and world prices for goods (as a percentage of the previous year) —

— model for analyzing and forecasting the volume of oil exports (in million tons) depending on domestic oil consumption (million tons) and the ratio of export and world oil prices (in percent) —

— a model for analyzing and forecasting the volume of imports of goods (in current prices, billion dollars) depending on the growth of the real exchange rate of the ruble (as a percentage of the previous year) and an indicator expressed as the ratio of annual indices of the physical volume of GDP to their average value.

The results of the correlation and regression analysis showed high indicators of the influence of factors and confirmed the presence of the above patterns in the development of Russian exports and imports in 1991-1998:

- index of the physical volume of exports of goods and factor characteristics (index of the physical volume of industrial production / domestic consumption / and changes in the ratio of domestic and world prices for goods) - 11 = 0.998-

- volume of oil exports (in million tons) and domestic oil consumption - 11 = 0.92-

- volume of oil exports (in million tons) and the ratio of export and world oil prices (in percent) - 11 = 0.97-

- volume of imports of goods (in current prices, billion dollars) and changes in the real exchange rate of the ruble (as a percentage of 1992) - 11 = 0.95-

- the volume of imports of goods and an indicator expressed as the ratio of annual indices of the physical volume of GDP to their average value - 11 = 0.91.

8. During 1988−1993. In Russia, the system of foreign trade regulation was reorganized in accordance with the chosen course of creating an open economy and market transformations.

Economic instruments for regulating foreign economic relations are more consistent with a market economic system. However, in the context of the significant deterioration in the state of the Russian economy that is currently taking place, in the interests of mobilization and best use limited resources, one has to resort to administrative instruments for regulating export-import operations.

Customs regulation is becoming an important instrument of foreign trade policy in Russia. With the help of tariff and non-tariff regulation measures, the state exercises control and management of foreign trade operations, up to and including restricting foreign trade.

Knowing the direction of development of exports and imports of goods, with the help of customs regulation measures it is possible to influence the ratio of domestic and world prices for exported and imported goods. Thus, quantitative restrictions and import tariffs reduce the demand for imports. With an increase in prices for imported goods in comparison with goods produced within the country, there is a tendency to replace imported goods with domestic ones. Export tariffs must be determined based on an analysis of domestic and world prices, so that the state can regulate excess profits of exporters, and not cause losses to the development of export industries. Consequently, customs regulation measures not only have a direct impact on the ratio of domestic and world prices, but and indirect effects on output and GDP.

Improper application of customs regulation measures can cause significant damage to the development of production and the country's economy. Consequently, it is necessary to implement customs policy based on an analysis of the prospects for the development of exports and imports of goods, based on the specific economic capabilities of the country.

The proposed models for analyzing and forecasting the export and import of goods contain key points similar research.

CHAPTER 1. Formation of Russian foreign trade in a transition economy

1.1. Assessment of Russia's foreign trade and customs policy

1.2. Comparative analysis of the development of Russian foreign trade with other countries of the world

1.3. Analysis of the possibility of developing the export of goods in conditions of production reduction

CHAPTER 2. Methodological basics and features of modeling and analysis of Russian foreign trade

2.1. Analysis of goods exports in relation to economic development indicators

2.2. Economic and statistical analysis of factors influencing the import of goods

CHAPTER 3. Statistical assessment of the influence of economic factors on the formation of foreign trade

3.1. Using economic and statistical models to analyze the export of goods 86 3.2. Economic and statistical modeling of the dynamics of imports of goods

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Glebkova Irina Yurievna. Statistical analysis of the influence of economic factors on Russian foreign trade indicators: Dis. ...cand. econ. Sciences: 08.00.11: Moscow, 2000 140 p. RSL OD, 61:00-8/758-9

Introduction

Chapter 1. Formation of Russian foreign trade in a transition economy

1.1. Assessment of Russia's foreign trade and customs policy 12

1.2. Comparative analysis of the development of Russian foreign trade with other countries of the world 25

1.3. Analysis of the possibility of developing the export of goods in the context of reduced production 37

Chapter 2. Methodological foundations and features of modeling and analysis of Russian foreign trade

2.1. Analysis of goods exports in relation to economic development indicators 52

2.2. Economic and statistical analysis of factors influencing the import of goods 72

Chapter 3. Statistical assessment of the influence of economic factors on the formation of foreign trade

3.1. Using economic and statistical models to analyze the export of goods 86

3.2. Economic and statistical modeling of the dynamics of imports of goods 108

Conclusion 119

Applications 126

References 138

Introduction to the work

Relevance The topic of the dissertation research is determined by the diversity and complexity of the processes of reforming the Russian economy, reflecting their influence on the state and development of foreign trade, the urgent need to analyze the formation of exports and imports of goods in the context of reforms and the use of its results in customs practice in order to solve problems of both foreign trade and and the country's internal economic policy.

The negative consequences of the economic reforms carried out in Russia have led to an extremely unfavorable state in the country's economy and macroeconomic instability. As a result of the sharp drop in production, federal budget revenues from the real sector of the economy decreased significantly. In an effort to make up for the loss of revenue from the country's budget, customs authorities pursue their own policies, often pursuing narrow departmental interests. Customs policy, largely determining the development of foreign trade, as well as relations with trading partners, also influences the economic situation in the country. As SM notes in his work. Menshikov: “Foreign economic policy must be constantly coordinated with domestic economic policy. Specific steps in foreign economic policy must not be allowed to contradict the priorities of the macroeconomic policy of the state as a whole.”

Thus, the choice of priority in customs policy in the current conditions will determine the possibility of economic development of the country and strengthening its position in the world market.

The object of the study is Russia's foreign trade in the context of economic reforms.

The subject of the study is the mechanism of formation of export and import of goods under the influence of main economic factors and its formalization.

The purpose of the dissertation is to analyze foreign trade, determine the most important economic factors and reflect them

in models for analyzing and forecasting the volume of exports and imports of goods during the transition period of economic development in Russia.

Based on the purpose of the dissertation, the following tasks were set:

explore the dynamics and structure of exports and imports of goods;

give a comparative description of foreign trade indicators and the main economic indicators of Russia and other countries of the world that determine their significance;

analyze foreign trade policy and methods of customs regulation of export and import of goods in Russia during the period of economic reforms;

identify the main economic factors influencing the volume of exports and imports of goods;

build models for analyzing and forecasting the export and import of goods;

provide an economic justification for the results of the analysis carried out on the basis of the proposed models.

The set objectives determined the logic of the research and the structure of the dissertation.

The work examines the economic conditions that have developed as a result of the ongoing reforms, as well as the associated changes in customs policy.

economic and social development. The position of Russia in modern world trade is analyzed, determined by its position in the world according to the main economic and social indicators.

To conduct a comparative analysis, both Russian and foreign sources of statistical data were used.

The main objective of the dissertation is to determine the economic factors influencing the volume of exports and imports of goods during the period of economic reforms in Russia.

The identified trends are also confirmed in some foreign sources (for example, S. Fischer, R. Dornbusch, R. Schmalenzi. Economics).

import of indicators such as the ruble exchange rate against the US dollar, the real ruble exchange rate, inflation rates and others. When considering issues of customs regulation of imports, relatively cheap imported goods are distinguished, which are highly dependent on customs duties and taxes (food), and expensive ones, accessible to high-income groups of the population (cars).

The theoretical conclusions of the dissertation research were confirmed by the developed models for analyzing the export and import of goods using the example of specific indicators of economic development in Russia during the transition period since 1991. to 1998

To identify trends in the development of exports and imports of goods during the transition period of Russia's development and reflect them in models for analyzing and forecasting foreign trade, the works of Linwood T. Geiger, R. Winn, R. Dornbusch, G. Kassel, V. Leontiev, P. Lindert, M. Todaro, S. Fisher, K. Holden, R. Shmalenzi and other scientists.

Existing publications on the topic of research are devoted mainly to general issues of foreign trade, with the problem of identifying patterns in the formation of exports and imports of goods determined by the economic conditions of Russia's development in

transition period, and their reflection in models for analyzing and forecasting foreign trade volumes, has not been sufficiently developed.

Theoretical And methodological basis dissertations consist of scientific developments of domestic and foreign scientists and scientific organizations in the field of analyzing the influence of economic indicators on the volume of exports and imports of goods, as well as existing experience in modeling foreign trade turnover.

During the dissertation research, methods of grouping, analysis of time series and structure of indicators, index method, correlation and regression analysis, graphical method and others were used.

Scientific novelty dissertation research is:

substantiation of the possibility of increasing the volume of exports and imports of goods in the context of a reduction in industrial production (domestic consumption) and Russia's GDP during the transition period of its development;

analysis of the impact of the ratio of domestic, export and world prices, as well as changes in the real exchange rate of the ruble on the volume of exports and imports of goods;

identification of the main economic factors influencing exports and imports in general, individual goods and product groups;

development on indicators of economic development of Russia in 1991-1998. dependency models:

export of goods in general and export of crude oil on determining economic factors: production volume, domestic consumption, the ratio of domestic and world prices;

import of goods in general from the main economic factors: changes in the rate of decline in GDP and the real exchange rate of the ruble;

assessment of changes in the volume of exports and imports of goods in 1999, carried out on the basis of developed models;

substantiation of the possibility of using the research results in customs practice.

Practical significance. The results of the analysis of the dynamics of foreign trade, the main economic factors determining it and the use of the developed models make it possible to assess development prospects and formalize the mechanism for the formation of exports and imports of goods in Russia for their subsequent consideration when determining foreign trade and customs policy. As a result, it becomes possible to solve management problems at both the strategic and tactical levels:

adjust the foreign trade and economic situation in the country through customs regulation measures;

determine and control foreign exchange earnings and income from foreign trade operations.

Approbation And implementation of research results.

The developed models were included in the research work carried out at the Russian Customs Academy (RTA) on the topic "Methodology of statistical analysis and forecasting of the receipt of customs payments to the federal budget of Russia" and in the report on the research work "Methods for forecasting federal budget revenues" Scientific -Research Financial Institute of the Ministry of Finance of the Russian Federation.

The provisions and conclusions of the dissertation were presented in the abstracts of the scientific and practical conference “Problems of improving customs affairs in the Russian Federation,” held on March 18-19, 1999 at the RTA.

Methods and models for analyzing and forecasting the export and import of goods // Problems of improving customs affairs in the Russian Federation: Materials of the scientific and practical conference, March 18-19, 1999 - M: RIO RTA, 1999. - 0.2 pp.

Analysis of the dynamics of indicators of foreign economic activity of the Moscow region // Russian Economy: theory and practice of revival: Interuniversity collection of scientific papers. Vol. 3. -M: Publishing house Ros. Econ. Acad., 1999. - 0.4 p.l.

The influence of inflationary processes on foreign trade indicators // Finance. - 1999. - № 5 (co-authored). - 0.5 p.l.

Export forecasting models // Methods for forecasting federal budget revenues. Applied research. Per. No. 01.99.0006715. M.:NIFI Ministry of Finance of the Russian Federation, 1998 (co-authored). - 0.3 p.l.

Statistical control and reliability of regional customs statistics // FORUM: Methodological collection. Issue 6. M.: RIO RTA, 1999 (co-authored). - 0.6 p.l.

Comparative analysis of the development of Russian foreign trade with other countries of the world

A complete picture of the volumes of Russian exports and imports of goods is given by comparison with the corresponding indicators of countries around the world, taking into account the fact that Russia significantly exceeds most of them in terms of population and territory size.

An analysis of Russian foreign trade indicators in comparison with other countries of the world indicates that its foreign trade turnover clearly does not correspond to the possibilities of Russian exports and the needs for import of goods (Table 1.2.1).

Russia, which is larger in population than any country in Europe, is inferior not only to the leading Western countries, but also to countries such as the Netherlands, Canada, Belgium, Korea and Mexico and ranks only fifteenth among countries in terms of foreign trade turnover.

Our country's share in the trade turnover of its main Western partner, Germany, is only 15%.

China's trade turnover is almost twice as high as Russia's, both in exports and imports of goods.

With a share of world exports of 1.7%, Russia is on par with countries such as Sweden. For the USA, this figure reached in 1997. 12.9%, for Germany - 9.6%. Compared to 1990 Russia's share in world exports decreased by 0.5%.

Russia's share in world imports is 1.0% and has decreased compared to 1990. by 1.3%. For comparison: the US share in world imports in 1997 was . 16.4%, Germany's share - 8.1%.

Russia's trade balance in recent years has shown a constant excess of exports over imports. In 1997 the trade balance amounted to $33.2 billion. Although this gives the country significant foreign exchange earnings, a positive trade balance does not necessarily indicate a prosperous state of the economy.

For a country in crisis, imports, as a rule, are always less than exports. This is explained by the fact that imports of goods depend on the volume of domestic effective demand, which in total is equal to GDP. The crisis level of Russia's GDP determines and comparatively low level import.

Another reason is that debtor countries are always forced to export more in order to have a reserve to pay off the debt and interest on it. This explains why developing countries tend to have trade surpluses, while large creditor countries (the US and UK) have trade deficits.

In order for Russia to take its rightful place in the world economy, its trade with foreign countries must increase significantly, both through exports and imports.

The way to solve this problem lies, first of all, in developing production, changing the structure and increasing the volume of exports, as well as imports of products.

The key issue is improving the structure of Russia's exports in the direction of increasing the share of finished products, and primarily mechanical engineering products, especially high-tech products.

Countries with industrialized economies have a qualitatively higher level of trade and economic relations. Involvement industrial enterprises supplying to the foreign market, to international competition, requires constant organizational and technical improvement of their activities, the technical level and quality of goods produced in the country. Because of this, the highest rates of economic development are characteristic of those countries where foreign trade is rapidly expanding. Among the countries exchanging scientific and technical information, the latest technologies production and high-tech products include the USA, Germany, Great Britain, France, Japan, and in recent years, Asian countries.

As the data in Table 1.2.2 shows, in Russian exports in 1997. 47.7% were products from the mining industry and only 49.4% from manufacturing, while in most countries the share of manufacturing in the commodity structure of exports accounts for more than 90%,

For example, according to 1995 data, in Austria this figure was 98.5%, Germany - 98.4, Italy - 97\7%. Only in some African countries did the share of extractive industry products in the structure of exports exceed this figure in Russia.

By the share of mechanical engineering products and finished products in the structure of exports, one can get an idea of the qualitative side of the state’s participation in world trade, and by the value volume, accordingly, of the importance of a particular country in this trade.

The qualitative side of Russian exports is significantly inferior to industrialized countries: the share of mechanical engineering products in Russian exports in 1997 was . was 8.1% (worth 7D billion dollars), and for the USA this figure was over 51% (worth 353 billion dollars).

Based on the share of the United States (over 14%) and Japan (about 16%) in global exports of engineering products, one can judge their role and place in this market. Specific gravity Russia’s share in global exports of mechanical engineering products does not reach 0.2%,

The production decline has forced Russia in recent years to import significant amounts of food and consumer goods.

According to a recent government report, the optimal share of food in total imports for Russia is 8%. In 1997 this figure was 25.3%, which is unacceptable given the fact that Russia does not provide itself with basic food products, such as grain, sugar, butter, meat, etc. (Table 1.2,3),

Analysis of the possibility of developing the export of goods in conditions of production reduction

The volume and structure of production (especially industrial products) determines the state of the country’s economy in all its spheres. The volume of production determines the size of the country's main economic indicator - GDP, as well as the income and standard of living of the population. The level of production not only shapes domestic yen, but also influences world prices. The production factor is the main factor determining the volume and structure of exports and imports of goods.

In view of the fundamental influence of the production factor and the importance of the development of goods exports, which is one of the main sources of foreign exchange earnings, and therefore the determining condition for the development of imports, the dissertation research provides a detailed analysis of the state and dynamics of goods exports in the context of a reduction in production in Russia.

During the period of the economic crisis in Russia and the general production decline, the value of exports of goods increased 1.7 times in 1997 compared to 1991.

The growth in Russian exports in recent years, which is more than 30% higher than imports, forms a steady increase in the positive balance of foreign trade. In 1997 the value of exports amounted to 32% of industrial output and 19% of GDP.

The value of Russia's exports in 199M997\ was constantly growing, both to non-CIS countries and to the CIS countries (Table 1-3.1). At the same time, in 1997, for the first time in seven years, there was a slight decrease in exports. In 1998, the value of exports decreased by 16% compared to 1997.

While exports decreased in value, the physical volume of exports continued to grow, as evidenced by the data of indices of the physical volume of exports as a percentage of the previous year (Table 1.3.2). The decrease in the value of exports in 1997-1998 was mainly due to the fall in world prices for some exported goods, which in turn influenced the decrease in export prices. At the same time, exports in physical terms declined, and income from the sale of products decreased.

However, the decline in exports does not indicate an emerging downward trend due to falling prices for exported products. IN long term The global market situation will be favorable for Russian exporters, since according to forecasts international organizations An increase in global consumption of oil and other raw materials is expected and, as a result, an increase in prices for them.

Modern publications by Russian economists widely discuss the economic conditions for the development of Russian exports during the transition period and the factors influencing them.

In particular, B, May1 identifies two main groups of goods, the export of which is most influenced by various factors.

Exports of mining industry products depend, first of all, on the volume of production and domestic consumption, as well as the level of world prices for the relevant types of products and on the foreign economic regime of the country. These industries are interested in creating a liberal economic system, the absence of protectionism, and macroeconomic stability as a condition for effective investment activity.

If we consider goods that are products of the manufacturing industry: machinery, equipment, plastics, fabrics, etc., here exports depend, first of all, on their competitiveness in the world market. The most important criteria for competitiveness are quality and prices. Therefore, increasing the utilization of production capacity will not mean that these products will be able to have a sustainable presence on the world market.

Russia exports mainly raw materials. The largest share in sectoral structure Russian exports (Table 1.3.3) are occupied by products of extractive industries. In 1998, mineral products accounted for 39.7% of Russia's total exports to non-CIS countries, metals - 31.7%.

Consequently, the main economic factors influencing Russian exports at present are the volume of production and domestic consumption, as well as the level of world prices for the corresponding types of products.

Economic and statistical analysis of factors influencing the import of goods

Analysis and forecasting of imports of goods is of great importance, since imports provide the main income to the federal budget in the form of revenues from customs authorities and contain reserves for expanding the tax base. Competition caused by the supply of imported goods promotes the development of domestic production and improves the quality of products produced in the country. Import is a necessary condition international exchange, without which the export of domestic products would not find demand. The volume and structure of a country’s imports depends both on the need or necessity for importing goods, which is determined by the state of production, and on the country’s ability to buy these goods, that is, on the demand for imports. The import demand equation proposed by the IMF is as follows: The signs “-b” and “-” indicate the expected direction of influence of the independent variables. The volume of imports increases with an increase in the volume variable, which can be either real income or real domestic expenditure. The price competitiveness variable captures the response of import volumes to changes in relative prices, which reflect both movements in domestic and global pennies in the respective currencies and changes in the exchange rate. The dependence here is inverse, that is, when prices for imported goods rise compared to goods produced within the country, there is a tendency to replace imported goods with domestic ones. Consequently, according to models for analyzing and forecasting imports of goods developed by the IMF and other foreign models, the main economic factors determining the volume of imports are: domestic income or real GDP of the country; price factor expressing the ratio of domestic and world prices for imported goods. Let us consider the possibilities of applying the IMF model in Russian conditions.

According to the IMF model, imports increase as real GDP increases. The greater the growth of GDP, the greater the import of goods. In Russia, the growth of imports occurs against the backdrop of a constant decline in GDP. However, changes in the growth (decrease) rate of GDP have an impact on the volume of Russian imports. The dynamics of Russian GDP growth and import volumes are presented in Table 2.2L. As can be seen from table 2.2.1, the volume of real GDP decreased, and imports in comparable prices increased. This is also true for imports at current prices. Consequently, it is impossible to use standard foreign import forecasting models for Russia at this stage of its economic development. It should be noted that the low level of Russia's GDP also determines the low level of imports; compared to other countries, where these figures are several times higher than in Russia. However, the impact of changes in real GDP on the development of Russian imports has its own characteristics. Let's consider the dynamics and structure of these indicators. Trade liberalization, carried out in the context of market reforms, has contributed to the development of imports of goods in recent years. The value of imported products in 1997 increased, compared to 1991, by 29.1 billion dollars or 1.7 times (Table 2.2.3). The commodity structure of Russia's imports is determined by limited import opportunities (low GDP) and a reduction in production. As a result of the fact that domestic production is not able to provide the population with essential goods, goods such as grain, flour, oil, meat, clothing, shoes, fabrics and others have to be imported.

Imports of mechanical engineering products play a significant role in the Russian economy. Import of machines and progressive technological equipment will contribute to the renewal of production capacities Russian enterprises. This will contribute to increased production efficiency, increased competitiveness of manufactured products, will expand the export of goods, strengthen its position in the world market, and also conquer new markets.

Despite the expansion of measures to promote an increase in imports of mechanical engineering products, primarily related to... preferential customs duties levied on such goods, provision of loans and other measures, import of mechanical and technical products is insufficient due to limited funds to pay for it, due to a significant reduction in domestic capital investment. The share of machinery, equipment and Vehicle in the total volume of imports from Russia amounted to in 1998. 40.1%, and food products - 26.5%.

Economic and statistical modeling of the dynamics of imports of goods

The results of the analysis of the development of imports of goods under the influence of economic factors allowed us to draw the following conclusions. 1. The growth in the value of imports in the context of a decline in GDP is explained by an increase in GDP indices (the decline in GDP decreases). In conditions of production reduction, there is a decrease in final consumption and accumulation of domestic goods. Moreover, the reduction in production, and therefore the consumption of domestic goods, exceeds the reduction in GDP, thereby freeing up funds for additional imports of goods. A relationship is found between imports at current prices and the ratio of annual GDP growth (decrease) rates to their average value. Analysis of the structure of GDP confirms this dependence. 2. A favorable factor for the growth of imports of all types of goods was the increase in the real exchange rate of the ruble. The real exchange rate rose because the nominal depreciation of the ruble was less than the rise in prices in Russia. The situation when internal currency depreciation occurs faster than external one, that is, if the exchange rate falls slower than internal growth, is beneficial for importers, as it frees up funds for imports and promotes their growth. Based on the results of a study of the influence of main economic factors on the volume of imports of goods, it is proposed to include the following variables in the model for analyzing and forecasting imports of goods: 1. Volume of imports of goods in current prices, billion, dollars; 2. Change in the real exchange rate of the ruble, % compared to 1992 -x); 3. The ratio of annual indices of the physical volume of GDP to their average value, % - x?; Let's build a model for analyzing and forecasting imports of goods subject to a decrease in the volume of real GDP and changes in the real exchange rate of the ruble: The dependent variable is the value of imports of goods in Russia in 1991-1998 41].

Analyzing the graphical forms of changes in the value of imports and the ratio of indices of the physical volume of GDP to their average value (Figure 3.2.1 and Figure 3.2.2) it is clear that they are very similar (especially in 1994-1998), that is, with an increase in the ratio per annum Indices of the physical volume of GDP to their average value, the value of imports increases and vice versa. The graph of changes in the real ruble exchange rate indicates the presence of a direct relationship between changes in the studied indicators. The table of paired correlation coefficients shows that there is a strong correlation between changes in the real ruble exchange rate and the ratio of the physical volume indices of GDP to their average value (the correlation coefficient is 0.89), that is, it is not possible to include these indicators in the model at the same time. Consequently, we will construct two functions of the dependence of imports of goods: where Vj is the volume of imports of goods in current prices, billion dollars, depending on the ratio of the physical volume index of GDP to the average value of the GDP index, expressed as a percentage; y2 is the volume of imports of goods at current prices, billion dollars, depending on changes in the real exchange rate of the ruble (1992=100%); a0, ai s bo, b - model parameters. The results of the study confirmed the existence of a close correlation between the following indicators (tables 2.1 and 23 of Appendix 2): - the volume of imports of goods (in current prices, billion dollars) and the growth of the real exchange rate of the ruble (as a percentage compared to 1992) - R = 0.95; - the volume of imports of goods and an indicator expressed as the ratio of annual indices of the physical volume of GDP to their average value - R = 0.91. The mean square errors of the equations are quite small values (Sv] = 5 36 and Sy2 = 3.93 with usr = 57.1 and Oy = U.8), which indicates the adequacy of the models. On the significance of the regression coefficients u, a, bo, bi indicate t-test values. According to the resulting data in Tables 2.1 and 2.3, the models for analyzing and forecasting imports of goods, depending on the main economic factors, will have the following form:

Graphs of model residuals indicate the absence of autocorrelation (Figures 2L-2.4). There is no correlation between the remainders of the functions і and y2, therefore, we can combine the two functions y3 and y2 by introducing correction factors: . where k is the correction factor; Vі is the volume of imports of goods at current prices, billion dollars, depending on the ratio of the physical volume index of GDP to the average value of the GDP index, expressed as a percentage; y2 - volume of imports of goods at current prices, billion dollars depending on changes in the real exchange rate of the ruble (1992-100%), Data from tables 2.5 and 2.6 of Appendix 2 indicate a fairly accurately selected model that generalizes the influence on the volume of imports of two factors at a value of k =0.297. As a result, the model for analyzing and forecasting imports of goods will have the following form: y = 0.3 Ui+ (1-0.3) y2 The theoretical values of the volume of imports of goods (calculated according to the model) deviate from the actual values by an average of 4%, which indicates about the fairly high accuracy of the model (Fig. 3.2.5).

International trade- traditional and most developed form of international economic relations – 80% the entire volume of IEO.

The economic success of any country in the world is based on foreign trade.

International trade ( MT) is form of communication between producers different countries arising on the basis international division of labor, and expresses them mutual economic dependence.

Since the second half of the 20th century, world trade has been developing at a rapid pace. In the period 1950-1998. world exports increased 16 times. Since the mid-90s, there has been a high and stable growth rate of world exports - an average of 6% per year.

International trade is growing faster than production. This creates more favorable conditions for its development. For every 10% increase in global production, there is a 16% increase in the volume of MT. There is an increase in the capacity of world markets

For stable, sustainable growth international trade influenced a number of factors:

· development of the international division of labor and internationalization of production and capital;

· scientific and technological revolution, promoting the renewal of fixed capital, the creation of new sectors of the economy, accelerating the reconstruction of old ones;

· regulation (liberalization) of international trade through GATT - WTO measures;

· liberalization of international trade, the transition of many countries to a regime that includes the abolition of quantitative restrictions on imports and a significant reduction in customs duties - the formation of “free economic zones”;

· development of trade and economic integration processes: elimination of regional barriers, formation of common markets, free trade zones;

· active activity of transnational corporations in the world market;

· obtaining political independence of former colonial countries. Singling out from among them “newly industrialized countries” with an economic model oriented toward the foreign market.

« international trade" - trade of a country with other countries, consisting of paid imports ( import) and paid export ( export) goods.

Foreign trade activities divided by product specialization on the:

· trade in finished products,

· trade in machinery and equipment,

trade in raw materials

· trade in services.

Main competitors in the global market

The modern structure of the world economy can be conveyed through the concepts “center”, “semi-periphery” and “periphery”.

Center - developed Western countries.

TO semi-periphery most can be attributed countries with economies in transition. It also includes the most “advanced” developing states – “newly industrialized countries” (NICs).

Periphery - developing countries (except NIS).

The industrial states of the West play the main role. They account for more than 70% world exports. Wherein about 70% of exports from developed Western countries account for mutual trade turnover .

Largest exporters are: USA, Germany, Japan, France.

The exports of these countries are dominated by capital-intensive industrial goods (machinery and equipment). In Germany – more 80% , V Japan – more than 90%(1st place in the world).

1/3 Japanese exports go to the United States.

Western Europe is the main center of international trade. Its exports are almost 4 times higher than US exports.

Currently, the highest rates of economic development and export growth are observed in China.

Sustained high rates of international trade are supported by expanding trade within OECD (Organization for Economic Co-operation and Development) countries. Since the mid-90s share of OECD countries(these are mainly developed countries) in world trade 73% .

According to expert forecasts, in 2030, three countries are expected to be among the most competitive countries - the USA, Japan and China. Next in this long-term forecast are Germany, Singapore, South Korea, India, Taiwan, Malaysia and Switzerland.

Share developing countries(including China) in global exports is more than 27%. Their foreign economic relations are focused on developed capitalist countries. On mutual trade accounts for only approximately 35% exports of developing countries.

For now, developing countries remain largely suppliers raw materials and food and comparatively simple products finished products to the world market.

Among industrial goods, exports are dominated by labor-intensive(cheap labor), resource-intensive.

Capital-intensive products are present mainly in NIS exports - 2/3 of the volume of manufacturing exports. In other countries only 1/5.

Developing countries play a leading role only in world exports clothing and fabrics.

The share of services exports has increased financial and cultural services with a reduction in the share of transport and tourism.

In the exports of OPEC countries, oil and petroleum products account for more than 30%. (Kuwait,Saudi Arabia)

The desire of developing countries to diversify their exports through industrial goods often encounters some form of resistance from industrialized countries.

In general, exports from developing countries (with the exception of NIS) are growing unevenly, both across groups of countries and across industries.

For developing countries, foreign economic relations are of great importance. They contribute to the expansion and modernization of fixed capital, allow the acquisition of new technologies (ec. development), and help mitigate social and economic problems that arise during the transition to a market economy.

“Analysis of the influence of factors on the results of foreign trade activities is the least studied problem of foreign trade statistics. The study of stochastic relationships in foreign trade is currently sporadic. On the one hand, this is due to the “youth” of customs statistics as a science. On the other hand, the reason is the lack of statisticians involved in the study of stochastic relationships on the ground. Thirdly, the information base for studying the influence of various factors on the results of foreign trade activities goes beyond the scope of the State Customs Committee-FTS database. There is a need to attract additional information, for example information Federal service State Statistics Russia, which requires well-established mechanisms for the interchange of information, or the search for other opportunities for obtaining the necessary data.”

“One of the most general laws of the objective world is the law of universal connection and dependence between phenomena. Naturally, when studying phenomena in a variety of fields, statistics inevitably encounter dependencies between both quantitative and qualitative indicators and characteristics. Its task is to detect (identify) such dependencies and give them a quantitative description.

Among the interrelated characteristics (indicators), some can be considered as certain factors influencing the change of others ( factorial), and the second ( productive) – as a consequence, the result of the influence of the former.

There are 2 types of relationships between individual characteristics: functional and stochastic (statistical), a special case of which is correlation.

Relationship between two variables x And y called functional, if a certain value of the variable x strictly matches one or more values of another variable y, and with a change in value x meaning y changes strictly definitely. Such connections are usually found in exact sciences. For example, it is known that the area of a square is equal to the square of its side ( S = a 2). This ratio is typical for each individual case (square), this is the so-called strictly deterministic connection. Such connections can also be found in customs affairs. For example, the relationship between the amount of ad valorem customs duty ( y) and customs value of the goods ( x), taxed at a fixed ad valorem rate of customs duty, for example 5%, can easily be expressed by the formula y = 0.05x. To study functional connections it is used index method which is discussed in topic 8.

There are other types of connections where many factors interact mutually, the combination of which leads to variations in the values of the resulting characteristic (indicator) with the same value of the factor characteristic. For example, when studying the dependence of the amount of customs payments received by the federal budget on the number of goods transported across the customs border of the state (or on the value of trade turnover), the latter will be considered as a factor characteristic, and the amount of customs payments - as a resultant one. There is no strictly determined connection between them, i.e. with the same number of goods moved across the customs border (or the value of trade turnover), the amount of customs duties listed by different customs offices will be different, since in addition to the number of goods moved across the customs border of the state (or the value of trade turnover), the amount of customs duties is influenced by many other factors (different range of goods for which different customs duties, fees and benefits are applied; different customs regimes for moving goods across the customs border, etc.), the combination of which causes variations in the amount of customs duties.

Where many factors interact, including random ones, it is impossible to identify dependencies by considering a single case. Such connections can only be detected through mass observation as statistical patterns. The connection revealed in this way is called stochastic.

Correlation connection is a narrower concept than stochastic connection; it is its special case. It is correlations that are the subject of the study of statistics.

Correlation– this is a relationship that manifests itself with a large number of observations in the form of a certain relationship between the average value of the resulting characteristic and the characteristic factors. In other words, a correlation can be conditionally considered as a kind of functional connection between the average value of one characteristic (resultative) and the value of another (or others). Moreover, if we consider the relationship between the average value of the effective indicator y with one sign-factor x, the correlation is called steam room, and if there are 2 or more factor characteristics ( x 1 , x 2 , …, x m) – multiple.

By the nature of the changes x And y in pair correlation there are direct And reverse connection. With a direct connection, the values of both characteristics change in the same direction, i.e. with increasing (decreasing) values x the values also increase (decrease) y. With feedback, the values of the factor and resultant characteristics change in different directions.

The study of correlations comes down to solving the following problems:

1) identifying the presence (absence) of a correlation between the studied characteristics;

2) measuring the closeness of the connection between two (or more) characteristics using special coefficients (this part of the study is called correlation analysis);

3) determination of the regression equation - a mathematical model in which the average value of the resulting characteristic at is considered as a function of one or more variables - factor characteristics (this part of the study is called regression analysis).

34. Correlation and regression analysis of connections between foreign trade indicators.

General term « correlation and regression analysis"implies a comprehensive study of correlations (i.e. solving all three problems).

3. Sign correlation coefficient (Fechner)– the simplest indicator of the closeness of a connection, based on a comparison of the behavior of deviations of individual values of each characteristic ( x And y) from its average value. In this case, not the magnitudes of deviations () and (), but their signs (“+” or “–”) are taken into account. Having determined the signs of deviations from the average value in each row, consider all pairs of signs and count the number of their matches ( WITH) and mismatches ( N). Then the Fechner coefficient is calculated as the ratio of the difference in the numbers of pairs of matches and mismatches of signs to their sum, i.e. To total number observed units:

. (1)

Obviously, if the signs of all deviations for each characteristic coincide, then K F = 1, which characterizes the presence of a direct connection. If all the signs do not match, then K F =– 1(feedback). If åС=åН, That K F = 0. So, like any indicator of connection closeness, the Fechner coefficient can take values from 0 to 1. However, if K F = 1, then this should in no way be taken as evidence of a functional relationship between X And at.

The average values of the factor and resultant characteristics are determined using the simple arithmetic average formula Error! Link source not found.:

; .

The last two columns of Table 2 show the signs of deviations of each X And at from its average value. The number of sign matches is 10, and the number of mismatches is 2, then we determine the sign correlation coefficient (Fechner) using the formula. (1):

K F =

Table 2. Auxiliary table for calculating the Fechner coefficient

Month number	x	y	x –	y –
	27,068	172,17	–	–
	29,889	200,90	–	–
	34,444	231,83	–	–
	33,158	232,10	–	–
	37,755	233,40	+	–
	37,554	236,99	+	–
	37,299	246,53	+	+
	40,370	253,62	+	+
	37,909	256,43	+	+
	38,348	261,89	+	+
	39,137	259,36	+	+
	46,298	278,87	+	+
Total	439,229	2864,09

Typically, this value of the connection closeness indicator characterizes a noticeable direct relationship between x And y however, it should be borne in mind that since K F depends only on the signs and does not take into account the magnitude of the deviations themselves X And at from their average values, then it practically characterizes not so much the closeness of the connection as its presence and direction.

4. Linear correlation coefficient– the most popular meter of the closeness of a linear relationship between two quantitative characteristics x And y. It is based on the assumption that when complete independence of features x And at deviations of the values of a factor characteristic from the average () are random in nature and must be randomly combined with various deviations (). If there is a significant predominance of coincidences or discrepancies of such deviations, an assumption is made about the existence of a connection between x And y.

Unlike K F the linear correlation coefficient takes into account not only the signs of deviations from the average values, but also the values of the deviations themselves, expressed for comparability in units of standard deviation t:

Linear correlation coefficient r represents the average value of the products of normalized deviations for x And at:

, (2) or . (3)

Numerator of the formula. (3) divided by n, which is the average product of deviations of the values of two characteristics from their average values, is called coefficient of covariance is a measure of joint variation of the factor x and effective y signs:

The disadvantage of the covariance coefficient is that it is not normalized, unlike the linear correlation coefficient. Obviously, the linear correlation coefficient is the quotient of the covariance between X And at by the product of their standard deviations:

By means of simple mathematical transformations, you can obtain other modifications of the formula for the linear correlation coefficient, for example:

, (6) , (7)

, (8) . (9)

The linear correlation coefficient can take values from –1 to +1, and the sign is determined during the solution. For example, if , then r according to formula (6) will be positive, which characterizes the direct relationship between X And at, otherwise ( r< 0) – feedback. If , then r= 0, which means none linear dependence between X And at, and when r= 1 – functional relationship between X And at. Therefore, any intermediate value r from 0 to 1 characterizes the degree of approximation of the correlation between X And at to functional. There is a rule of thumb (Chaddock scale) for assessing the strength of a relationship, presented in Table 3.

Table 3. Chaddock scale

Thus, the correlation coefficient for a linear dependence serves both as a measure of the closeness of the connection and as an indicator characterizing the degree of approximation of the correlation dependence between X And at to linear. Therefore, the proximity of the meaning r to 0 in some cases may mean there is no connection between X And at, and in others indicate that the relationship is not linear.

In our calculation problem r Let's build auxiliary table 4.

Table 4. Auxiliary calculations of the linear correlation coefficient

No. of the month	x	y			t x	t y	t x t y		xy
	27,068	172,17	90,897	4422,782	-1,993	-2,408	4,799	634,049	4660,298
	29,889	200,90	45,064	1426,875	-1,403	-1,368	1,919	253,577	6004,700
	34,444	231,83	4,657	46,840	-0,451	-0,248	0,112	14,769	7985,153
	33,158	232,10	11,861	43,217	-0,720	-0,238	0,171	22,641	7695,972
	37,755	233,40	1,329	27,815	0,241	-0,191	-0,046	-6,081	8812,017
	37,554	236,99	0,906	2,836	0,199	-0,061	-0,012	-1,603	8899,922
	37,299	246,53	0,486	61,717	0,146	0,284	0,041	5,476	9195,322
	40,370	253,62	14,198	223,383	0,788	0,541	0,426	56,317	10238,639
	37,909	256,43	1,708	315,276	0,273	0,643	0,176	23,207	9721,005
	38,348	261,89	3,049	538,983	0,365	0,841	0,307	40,535	10042,958
	39,137	259,36	6,426	427,911	0,530	0,749	0,397	52,439	10150,572
	46,298	278,87	94,012	1615,718	2,027	1,455	2,950	389,740	12911,123
Total	439,229	2864,09	274,594	9153,353			11,241	1485,066	106317,681

In our problem: = = 4.784; = = 27.618.

Then the linear correlation coefficient according to formula (2): r = 11,241/12 = 0,937.

We obtain a similar result using the formula. (3):

r = 1485,066/(12*4,784*27,618) = 0,937

Or according to formula (6):

r = (106317,681/12 – 36,602*238,674) / (4,784*27,618) = 0,937.

The value found indicates that the relationship between the value of foreign trade turnover and the amount of customs payments to the federal budget is very close to functional (strong on the Chaddock scale).

Checking the correlation coefficient for significance (materiality). When interpreting the value of the correlation coefficient, it should be borne in mind that it is calculated for a limited number of observations and is subject to random fluctuations, like the values themselves x And y, on the basis of which it is calculated. In other words, like any sample indicator, it contains a random error and does not always clearly reflect the actual relationship between the indicators being studied. In order to assess the materiality (significance) of the r and, accordingly, the reality of the measurable connection between X And at, it is necessary to calculate the mean square error of the correlation coefficient σ r. Assessment of materiality (significance) r based on value comparison r with its mean square error: .

There are some calculation features σ r depending on the number of observations (sample size) – n.

1. If the number of observations is large enough ( n>30), then σ r calculated using the formula. (10):

Usually, if >3, then r is considered significant (essential), and the connection is considered real. Given a certain probability, we can determine confidence limits (boundaries) r =(), Where t– confidence coefficient calculated using the Laplace integral (see Appendix 11).

2. If the number of observations is small ( n<30), то σ r calculated using the formula (11):

and significance r checked based on t- Student's t-test, for which the calculated value of the criterion is determined by the formula. (12) and is compared with t TABLE.

. (12)

Table value t TABLE is found according to the distribution table t-Student's t-test (see Appendix 9.) at the significance level α=1-β and number of degrees of freedom ν=n–2. If t CALCULATION > t TABLE, That r is considered significant, and the relationship between X And at– real. Otherwise ( t CALCULATION< t ТАБЛ ) it is believed that the connection between X And at is missing and the value r, different from zero, was obtained by chance.

In our problem, the number of observations is small, which means we will evaluate the significance (significance) of the linear correlation coefficient using formulas (11) and. (12):

= 0,349/3,162 = 0,110; = 0,937/0,110 = 8,482.

From Appendix 9 it is clear that with the number of degrees of freedom ν = 12 – 2 = 10 (in the 10th line) and probability β = 95% (significance level α =1 – β = 0.05) t table = 2.2281, and with a probability of 99% ( α =0,01) t table = 3.169 means t CALCULATION > t TABLE, which makes it possible to calculate the linear correlation coefficient r= 0.937 significant.

5. Selection of regression equation is a mathematical description of changes in mutually correlated quantities based on empirical (actual) data. The regression equation must determine what the average value of the resulting characteristic will be at at one or another value of the factor characteristic X, if other factors influencing at and not related to X, not taken into account, i.e. abstract from them. In other words, the regression equation can be considered as a probabilistic hypothetical functional relationship of the value of the resulting characteristic at with the values of the factor characteristic X.

The regression equation can also be called theoretical regression line. The values of the resulting characteristic calculated using the regression equation are called theoretical.They are usually designated or (read: “Y, aligned by X") and are considered as a function of X, i.e. = f(x).

Find in every specific case type of function with which one can most adequately reflect one or another relationship between characteristics X And y, - one of the main tasks of regression analysis. The choice of theoretical regression line is often determined by the shape of the empirical regression line; the theoretical line seems to smooth out the kinks of the empirical regression line. In addition, it is necessary to take into account the nature of the indicators being studied and the specifics of their relationships.

For analytical connection between X And at the types of equations given in the table can be used (see section analysis of dynamics series) (subject to replacement t on x). Usually the dependence expressed by the equation of a straight line is called linear(or rectilinear), and everyone else - curvilinear dependencies.

Having chosen the type of function), the parameters of the equation are determined using empirical data. In this case, the searched parameters should be such that the theoretical values of the resulting characteristic calculated by the equation would be as close as possible to the empirical data.

There are several methods for finding the parameters of a regression equation. Most commonly used least square method(MNC). Its essence lies in the following requirement: the sought theoretical values of the resultant attribute must be such that would ensure minimum amount squares of their deviations from empirical values, i.e.

By placing this condition, it is easy to determine at what values a 0, a 1 etc. for each analytical curve this sum of squared deviations will be minimal. This method we have already used in topic 6 “Statistical study of the dynamics of foreign economic activity”, therefore, we will use the formula to find the parameters of the theoretical regression line, replacing the parameter t on x:

(13)

Expressing from the first equation of the system (13) a 0 , we get:

. (14)

Substituting. (14) into the second equation of system (13), then, dividing both parts by n, we get:

Applying the arithmetic mean formula 3 times, we get: .

Opening the brackets and moving the terms without a 1 to the right side of the equation, we express a 1:

. (15)

Parameter a 1 in a linear regression equation is called regression coefficient, which shows how much the value of the resulting attribute changes y x per unit.

We present the initial data and calculations for our example in Table 5.

Table 5. Auxiliary calculations for finding the regression equation

No.	x	y	x 2	xy
	27,068	172,17	732,677	4660,298	187,124	223,612	2657,453
	29,889	200,90	893,352	6004,700	202,377	2,181	1317,497
	34,444	231,83	1186,389	7985,153	227,006	23,274	136,153
	33,158	232,10	1099,453	7695,972	220,052	145,147	346,774
	37,755	233,40	1425,440	8812,017	244,908	132,441	38,864
	37,554	236,99	1410,303	8899,922	243,821	46,669	26,495
	37,299	246,53	1391,215	9195,322	242,443	16,706	14,202
	40,370	253,62	1629,737	10238,639	259,048	29,459	415,076
	37,909	256,43	1437,092	9721,005	245,741	114,256	49,940
	38,348	261,89	1470,569	10042,958	248,115	189,761	89,122
	39,137	259,36	1531,705	10150,572	252,381	48,710	187,871
	46,298	278,87	2143,505	12911,123	291,100	149,580	2748,498
Total	439,229	2864,09	16351,437	106317,681	2864,115	1121,795	8027,945

According to the formula. (15): = 5,407.

According to the formula. (14): a 0 = 238,674 – 5,407*36,602 = 40,767.

From here we get the regression equation: =40.767+5.407x, substituting into which instead x empirical values of the factor characteristic (2nd column of Table 5), we obtain theoretical values of the resultant characteristic aligned along a straight line (6th column of table 5). To illustrate the differences between empirical and theoretical regression lines, let's plot a graph (Figure 6).

Fig.6. Graph of empirical and theoretical regression lines

From Figure 6 it can be seen that small differences between the empirical and theoretical regression lines exist, so it is necessary assess materiality regression coefficient and connection equation, for which the average error of the parameters of the regression equation is determined and compared with this error.

The calculation of errors in the parameters of the regression equation is based on the use of residual variance, which characterizes the discrepancy (deviation) between the empirical and theoretical values of the resulting characteristic. For linear equation regressions ( ) average parameter errors a 1 And a 2 are determined by formulas (16) and (17), respectively:

, (16) , (17) . (18)

The significance of the parameters is checked by comparing its value with the average error. Let us denote this relationship as t

And using the same formula for the parameter a 1: =8,46.

Since the sample is small, setting the standard significance α=0.05 we find in the 10th line of Appendix 9 table value t α=2.23, which is significantly less than the obtained values of 13.3 and 8.46, which indicates the significance of both parameters of the regression equation.

Along with checking the significance of individual parameters, testing the significance of a regression equation in general or, what is the same, checking the adequacy of the model using the Fisher test according to Appendix 8. We have already used this method to check the adequacy of the trend equation in the previous topic, so using the formula in our example we get:

Comparing the calculated value of Fisher's criterion F r= 71.56 with tabular F t= 4.96, determined according to Appendix 8 with the number of degrees of freedom ν 1= k– 1 = 2 –1 = 1 and ν 2= n– k= 12 – 2 = 10 (i.e. 1st column and 10th row) and the standard significance level α = 0.05, we can conclude that the regression equation is significant.

6. Elasticity coefficient shows by what percentage the average effective sign changes y when a factor characteristic changes x by 1%. It is calculated based on the regression equation:

where is the first derivative of the regression equation y By x.

The elasticity coefficient is a variable value, i.e. changes with changing factor values x. So, for a linear relationship:

In relation to the considered regression equation, which expresses the dependence of the amount of customs payments to the federal budget on the value of foreign trade turnover ( = 40.767 + 5.407x), elasticity coefficient according to the formula. (21): .

Substituting into this expression different meanings x, we get different values E. So, for example, when x= 40 elasticity coefficient = 0.84, and at x= 50 respectively = 0.87, etc. This means that with an increase in foreign trade turnover x from 40 to 40.4 billion dollars. (i.e. by 1%), the amount of customs duties will increase by an average of 0.84% of the previous level; with increasing x from 50 to 50.5 billion dollars. (i.e. by 1%) y will increase by 0.87%, etc.” .

Ad valorem (lat.) – “from value”

The manifestation of stochastic relationships is subject to the law of large numbers: only in a sufficiently large number of units individual characteristics will be smoothed out, the accidents will cancel each other out and the dependence, if it is significant, will appear quite clearly

The term "stochastic" comes from the Greek. "stochos" - target. Shooting at a target, even good shooter rarely hits its center; shots land in some proximity to it. In other words, a stochastic relationship means the approximate nature of the characteristic values

The term “correlation” was introduced into statistics by the English biologist and statistician F. Galton at the end of the 19th century, which meant “a connection, as it were,” i.e. communication in a form other than functional. Even earlier, this term was used by the Frenchman J. Cuvier in paleontology, where by the law of correlation of animal parts he understood the possibility of reconstructing the appearance of the entire animal from parts found in excavations

Multiple correlation is studied in an econometrics course based on the application computer programs(for example, a special add-on to Excel, SPSS etc.), in the statistics course only pairwise correlation is studied

When measuring the strength of the connection between rows of dynamics this is equivalent to the absence of autocorrelation between the levels of the series, i.e. Before assessing the closeness of the relationship between time series, it is necessary to check each series for autocorrelation - see guidelines

Do it yourself

The term “regression” was introduced into statistics by F. Galton, who, having studied a large number of families, found that in a group of families with tall fathers, sons are on average shorter than their fathers, and in a group of families with short fathers, sons are on average taller than their fathers, i.e. .e. the deviation of growth from the average in the next generation decreases - regresses

Options a 0 And a 1 can be obtained not only by the substitution method as given below, but also by the method of 2nd order determinants (do this task yourself)

The sum of the empirical (2864.09) and aligned along a straight line (2864.115) values should coincide, but in our case this does not happen due to rounding of calculations to 3 decimal places

The numerator is the sum of the last column, and the denominator is the sum of the penultimate column of table 5