Introduction…………………………………………………………………………………........4

Section 1. Theoretical part……………………………………………………………6

1.1. Goals and objectives of forecasting socio-economic development as a special type of planning at the municipal level………………...…6

1.2. Methods for forecasting the socio-economic development of a territory………………………………………………………………………………….11

Section 2. Analytical part……………………………………………17

2.1. General characteristics of the territory…………………………………….17

2.2. Analysis of the organizational structure of the Territory Administration…..19

2.3. Analysis of methods used in forecasting the socio-economic development of a territory……………………………………….22

2.4. Analysis of the socio-economic development of the territory according to forecast indicators………………………………………………………..23

2.4.1. Analysis of demographic indicators…………………………….24

2.4.2. Analysis of employment and income of the population……………………………24

2.4.3. Analysis of the economic base……………………………………………………..26

2.4.4. Analysis of the financial base………………………………………………………...26

2.4.5. Analysis of small business development………………………..27

2.4.6. Analysis of investment activities…………………………….28

2.4.7. Analysis of housing construction and housing provision of the population…………………………………………………………………………………28

2.4.8. Analysis of housing and communal services………………………...29

2.4.9. Analysis of the social sphere…………………………………………29

Conclusion…………………………………………………………………………………..30

List of references……………………………………………………….32

Application

Introduction

The conditions for the socio-economic development of municipalities in our country have changed significantly in recent years. In general, in relation to modern Russia, we can talk about qualitative changes in the field of local economic development. The Constitution of the Russian Federation of 1993, which separated local self-government from state power, and the Federal Law “On the General Principles of Local Self-Government in the Russian Federation” define the basic principles of local self-government. Municipalities received independence based on the delimitation of the competence of different levels of government, the definition of subjects of joint jurisdiction and the transfer of some powers from top to bottom. The economic basis of local self-government in Russia was the right to independently manage municipal property and local finances. Municipal authorities received the opportunity and responsibility to develop their own economy in the interests of people living on their territory.

In order to somehow present the “picture” of socio-economic development for the coming years, a socio-economic forecast is developed and implemented in the territory of education. Using the example of the Sunsky municipal district of the Kirov region, we will analyze the development of the region from a socio-economic point of view, based on the forecast “Socio-economic development of the Sunsky municipal district of the Kirov region for 2012-2014”.

Currently, not a single sphere of social life can do without forecasts as a means of knowing the future. Particularly important are forecasts of the socio-economic development of society, justification of the main directions of economic policy, and anticipation of the consequences of decisions made. Socio-economic forecasting is one of the decisive scientific factors in shaping the strategy and tactics of social development.

The relevance of this topic is that the level of forecasting processes of social development determines the effectiveness of planning and management of the economy and other areas.

The purpose of this course work is to consider methods of socio-economic forecasts to determine the essence, areas of application and the most effective forecasting methods. To do this, it is necessary to solve the following problems: determine the essence of socio-economic forecasting methods and the areas of their application in the course of studying the fundamentals of forecasting methodology; characterize the methods of socio-economic forecasting.

Section 1. Theoretical part

Goals and objectives of forecasting socio-economic development as a special type of planning at the municipal level.

The socio-economic development of a municipality is understood as a controlled process of changes in various spheres of life of the municipality, aimed at achieving a certain level of development of the social (including spiritual) and economic spheres in the territory of the municipality, with the least damage to natural resources and the highest level of satisfaction of collective needs population and state interests. In this direction, the following actions are carried out: local target programs are approved and implemented, municipal orders are issued, forms of participation of enterprises and organizations in the development of the municipality are agreed upon, contracts are concluded, etc. The socio-economic development of municipalities is included in the powers of local self-government by the Federal Law “On the General Principles of the Organization of Local Self-Government in the Russian Federation”.

Forecasting, as one of the forms of government regulation, serves as the initial stage and precedes the development of programs, plans, main directions, the development of a strategy for socio-economic development, and so on. In all types of social activities, it is necessary to foresee development prospects, the future consequences of currently taken decisions, as well as phenomena that may arise regardless of the measures envisaged.

The task is to take into account the interaction of many objective and subjective factors (internal and external), to ensure that foresight, as an element of managing social development, is truly scientific and reliable.

The purpose of forecasting is to create scientific prerequisites, including: scientific analysis of economic development trends; variant prediction of the upcoming development of social reproduction, taking into account both existing trends and intended goals; assessment of the possible consequences of decisions made; justification of directions of socio-economic and scientific-technical development for making management decisions.

The main goal of forecasting territorial socio-economic development is to ensure coordination of national and regional interests in the development and implementation of regional economic policy.

Territorial forecasts are developed for the long-term, medium-term and annually (current forecasts).

Currently, forecasting the SER of a territory includes:

Development of options for SER of the territory, taking into account the probabilistic impact of internal and external political, economic and other factors;

Providing materials for differentiating industry and interregional forecasts;

Clarification of the need for funds to finance various target programs, supply of products, provision of services and performance of work for state regional needs, support of certain sectors of the economy.

The SER forecast is a necessary prerequisite for sub-federal authorities to make various optimal management decisions, including in the field of integrated SER of the territory. The forecast is carried out by comparing the actual indicators of the analyzed period with the planned and actual indicators for previous years.

In order to develop SER forecasts, a comprehensive analysis of the situation in the territory is carried out in the following areas (3, 57)

· demographic situation (birth rate, mortality rate, life expectancy, migration);

· natural environment (minerals, climate, water and land resources, soil composition, flora and fauna);

· social sphere (state of education, health care, culture, science, crime rate);

· regional finances (budget state, tax potential of the territory, financial state of business entities);

· standard of living of the population (average per capita income, wages, cost of living, consumer basket);

· production sector (total production volumes, industry structure, production dynamics);

· ecology (volumes of harmful emissions, implementation of environmental measures).

In forecasting theory, there are many bases on which forecasts are classified. However, the most appropriate approach to socio-economic forecasts will be the classification of socio-economic forecasts according to the time criterion. From the point of view of this criterion, SER forecasts are divided into long-term, medium-term and short-term

Long-term forecasts SER are developed by executive authorities of a constituent entity of the Russian Federation once every 5 years for the 10th period. Data from such forecasts are used in the development of medium-term forecasts of the regional economic development system, as well as the concept and programs of the economic development system. In long-term socio-economic forecasting, it is necessary to take into account one set of indicators that characterize the potential of the region: land resources, minerals, labor, fixed and working capital, scientific and technical achievements. In medium-term forecasting, these factors are no longer sufficient to explain the dynamics of production volume. Data from regional economic development forecasts for the long term are subject to publication in the press.

Medium-term forecasts SER are developed by the executive authorities of the constituent entities of the Russian Federation for a period of 3 to 5 years with annual data adjustments. In medium-term forecasting, indicators of effective demand of the population and other agents of reproductive activity (region, entrepreneurs, population) come to the fore. Data from regional economic development forecasts for the medium term are subject to publication in the press.

Short term forecasts SER are developed by the executive authorities of the constituent entities of the Russian Federation annually. Data from such forecasts serve as the basis for drawing up a draft budget. When constructing a short-term forecast model, the first place goes to indicators characterizing the financial situation in the economy as a whole and for individual groups of economic entities: households, small and medium-sized businesses, the business sector, and the population. SER forecast data for the short term are subject to publication in the press.

Planning and forecasting complement each other. A socio-economic development plan is a document that contains a system of indicators and a set of various measures to solve socio-economic problems. It reflects goals, priorities, resources, sources of their provision, order and deadlines for implementation.

Thus, planning is a process of scientific substantiation of goals, priorities, determination of ways and means of achieving them. In practice, it is implemented through the development of plans. Its distinctive feature is the specificity of indicators, their certainty in time and quantity.

The forms of combination of forecast and plan can be very different: a forecast can precede the development of a plan (in most cases), follow it (forecasting the consequences of a decision made in a plan), be carried out in the process of developing a plan, or independently play the role of a plan, especially in large-scale economic systems ( region, state), when it is impossible to ensure an accurate determination of indicators, that is, the plan becomes probabilistic in nature and practically turns into a forecast.

Planning is aimed at justifying the adoption and practical implementation of management decisions. The purpose of forecasting is, first of all, to create scientific prerequisites for their implementation. These prerequisites include: scientific analysis of trends in socio-economic development; variant foresight of upcoming development, taking into account both existing trends and intended goals; assessment of the possible consequences of decisions made. The rationale for the directions of socio-economic forecasting is, on the one hand, to find out the prospects for the near or more distant future in the area under study, guided by real economic processes, to formulate development goals, and on the other hand, to contribute to the development of optimal plans, based on the compiled forecast and assessment of the decision made in terms of its consequences in the forecast period. (9.51).

Methods for forecasting the socio-economic development of a territory.

Forecasting methods should be understood as a set of techniques and ways of thinking that allow, based on the analysis of retrospective data, exogenous (external) and endogenous (internal) connections of the forecast object, as well as their measurements within the framework of the phenomenon or process under consideration, to derive judgments of a certain reliability regarding it (the object). future development (4, 29).

Forecasting methods are expressed in methods and techniques for developing forecast and planning documents and indicators in relation to their various types and purposes.

In the wide variety of forecasting methods, the following groups can be distinguished:

1. Methods of expert assessments;

2. Extrapolation methods;

3. Modeling;

4. Normative method;

5. Target method.

Extrapolation- this is a method in which the predicted indicators are calculated as a continuation of the dynamic series for the future according to the identified pattern of development. The method allows you to find the level of a series beyond its limits in the future. The extrapolation method is used when the system is stable, the phenomena are stable, when the dynamics of processes and indicators in the future are determined by the trends of their changes in the past period. Extrapolation is effective for short-term forecasts if the time series data are clearly and consistently expressed.

One of the methods of extrapolation can be regression lines, the reliability of which increases when constructing multiscale correlation models that make the predicted indicators dependent on several variables. Therefore, work on the forecast of socio-economic development of a municipality should begin with the study of factors (variables) influencing socio-economic development. These factors include:

1. Availability of own financial resources;

2. Demographic changes;

3. Development of economic sectors and others.

The method of expert assessments is used mainly in long-term forecasts; this method helps to establish the degree of complexity of the problem, identifies important factors and the relationships between them, and selects the most preferable alternatives. However, the method of expert assessments is not without drawbacks, because it has some subjectivity.

The method of expert assessments is more often used in cases where it is difficult to quantify the forecast background, and experts do this based on their understanding of the issue. This method has several types: individual expert assessment, collective expert assessment, interview method, expert commission method.

In practice, it is possible to use extrapolation methods and expert assessments, using objective development trends and expert opinions.

With the normative forecasting method, the ways and timing of achieving possible states of the phenomenon, taken as a goal, are determined. In this case, we are talking about predicting the achievement of desired states of a phenomenon based on given norms and goals. The normative method is most often used for program or target forecasts. Both a quantitative expression of the standard and a certain scale of capabilities of the evaluation function are used. The normative forecasting method helps to develop recommendations to increase the level of objectivity, and therefore the effectiveness of decisions.

The normative method in planning socio-economic development can also be called the method of technical and economic calculations. It uses rules and regulations developed on a legislative or departmental basis. The presence of norms and standards makes it possible to determine forecast and planned indicators based on direct calculation. In forecasting, more general norms are used, and in planning, more specific norms are used.

With the help of standards, both market and non-market, mainly non-productive spheres are regulated. For example, in the non-production sphere, standards are used for the minimum pension, expenses for education, healthcare, housing and communal services, and others, serviced by federal and local budgets.

A variety of regulations are standards and limits. They are used, for example, in planning the minimum amount of municipal budget funds allocated to cover the expenses of enterprises and housing and communal services organizations.

The balance sheet forecasting method is one of the main methods for developing plans for socio-economic development; it has universal significance as a method of linking needs with resources. Using the balance method, imbalances that regulate national economic proportions are identified and the necessary relationships between sections and indicators of the plan are substantiated; reserves are identified; economic equilibrium is established.

The experimental-statistical forecasting method is characterized by an orientation towards the results actually achieved in the past, from the extrapolation of which the plan for the desired indicator is determined.

Forecasting methods are not limited to those listed above. There are also specialized methods:

1. Morphological analysis;

2. Forecast scenario;

3. Correlation and regression analysis;

4. Factor analysis;

5. Spectral analysis;

6. Game theory.

The program-target method, compared to other methods, is relatively new and underdeveloped.

The program-target method is closely related to the normative, balance sheet and economic-mathematical methods and involves the development of a plan starting with an assessment of final needs based on the goals of economic development with the further search and determination of effective ways and means to achieve them and resource provision.

The essence of the program-target method is the selection of the main goals of social, economic, scientific and technical development, the development of interrelated measures to achieve them within the scheduled time frame with a balanced provision of resources, taking into account their effective use.

The program-target method is used in the development of targeted comprehensive programs, which are a document that reflects the goal and complex of research, production, organizational, economic, social and other tasks and activities, linked by resources, performers and implementation deadlines.

Within the framework of the above classification, two large homogeneous groups can be distinguished: intuitive and formalized forecasting methods. These groups are fundamentally different in their essence. Within the framework of scientific research, the methods classified in the second group are of greatest interest, however, in recent years, attempts have been increasingly made to study intuitive methods.

Thus, we can conclude that forecasting socio-economic development is a complex multi-stage process. In this case, it is necessary to solve many diverse problems, both theoretical and practical. To successfully solve many of the problems, it is necessary to have extensive forecasting and planning tools. The basis of the forecasting tools are forecasting and planning methods. Today, many different methods have been developed, each of which has its own area of ​​application and its own characteristics. Any method allows you to make forecasts and plans with the maximum degree of reliability in some conditions, and is absolutely inapplicable in others. In the process of improving the system of planning and forecasting socio-economic development, one of the directions should be to expand the base of methods used. To do this, you should clearly understand the features, advantages and disadvantages of specific methods.

The most common forecasting methods include extrapolation, normative calculations, including interpolation, expert assessments, analogy, and mathematical modeling (10, 234).

Related information.

Socio-economic forecasting: functions, principles and methods

To plan the development of the national economy, a system of various forecasts is used, which include social, economic, demographic, etc. The forecast is an important part of the economic policy planning process. It makes it possible to outline the results of economic development of the national economy. In general, the forecast provides information about the development of the object in the future. Forecasts are developed by government and non-government organizations in the form of qualitative characteristics of development and quantitative assessments of economic indicators. Forecast Based on qualitative and quantitative parameters. The forecast covers the following stages: formation of an information base; object analysis; analysis of the external environment; determination of the predicted trajectory of the object; making decisions; assessment of forecast quality. The essence of economic forecasting lies in scientifically based prediction of the dynamics and structure of economic and social phenomena and processes that have an alternative, probabilistic nature and manifest themselves at the national, sectoral and other levels. The purpose of such a prediction is to improve the quality of decisions and avoid mistakes when developing short-term and long-term public policy projects.

Forecasting the economic and social development of the national economy involves studying the economic and social, scientific and technical, industrial, agricultural, and social potential. Sources of information are: accumulated knowledge and experience, factual and statistical information, economic and mathematical models.

In practice, there are the following forecasting methods: expert, characterized by a survey of specialists regarding a specific object; extrapolation, characterized by the collection of information about the development of an object in the past and the transfer of patterns to the future; modeling is characterized by the construction of models with changes in the future.

The main objects of forecasting are the national economy, the economy of intersectoral and industrial complexes, the economy of individual regions and administrative-territorial units, and the economics of enterprises. The subjects of forecasting are the state represented by government bodies of a certain level, economic services of local governments, and economic divisions of enterprises.

The unity of various methods and models for developing forecasts is ensured by the principles of socio-economic forecasting. Reflecting various aspects of forecast development, these principles create a single whole. There are such principles of forecasting the national economy as purposefulness, adequacy, alternativeness, consistency, efficiency and scientific validity.

The most important principle of socio-economic forecasting is the principle of purposefulness. It consists in a meaningful description of the object of research, which is carried out on the basis of the tasks assigned to the study. The principle of adequacy of forecasts characterizes the assessment of relationships in the development of the national economy and the creation of a theoretical analogue of real economic processes with their complete imitation. That is, during forecast development, forecasting methods and models must first be validated. The principle of alternative forecasting follows from the possibility of economic development and socio-economic processes in different directions. The principle of systematicity means that the economy is considered as a single object of forecasting. The principle of efficiency presupposes the effectiveness of the forecast in determining the cost of its analytical preparation. The essence of the principle of scientific validity of forecasts lies in forecasting, which requires comprehensive consideration of the operation of objective economic laws and laws of social development.

Socio-economic forecasting is manifested through its functions:

1. normative function, makes it possible to implement a predictive model and warns governing bodies against subjectivity in their activities;

2. the orientation function is expressed in the determination by the subject of management of the goals of society's development in a more realistic direction and a selective approach to information;

3. warning function, the task of which is to inform management authorities about possible and real deviations of the object from the predictive model.

One of the most important characteristics of socio-economic forecasting is the classification of forecasts according to various criteria (Fig. 21.4). In turn, forecasts are also classified according to various criteria and characteristics.

Rice. 21.4. V

Depending on the scope of application, forecasting can be socio-economic and scientific-technical. Socio-economic forecasting provides an assessment of possible future changes in the economic and social conditions of society. Scientific and technical forecasting is aimed at developing scientific, technical and technological means for implementing plans for socio-economic development.

Depending on the level of management, forecasting is divided into national economic, sectoral (or regional) and forecasting of enterprise development. National economic forecasting takes into account the possibilities of optimally achieving production goals and fulfilling the tasks of economic development. Industry forecasting is carried out taking into account the proposals of various industries and regions. Forecasting the development of firms, corporations, and enterprises is carried out taking into account new trends in the economic and social aspects and the latest achievements in technology and production technology.

According to the degree of justification, forecasting is divided into search (research) and normative. Search forecasting evaluates promising trends in economic development, while normative forecasting is associated with determining the ways and timing of achieving the desired state of economic and social development of the country based on the results achieved. Regulatory forecasting is carried out on the basis of a predetermined goal. Its task is to determine the ways and timing of achieving a possible state of the economy in the future based on given standards.

Forecasting is a type of activity of government bodies, one of the functions of public administration. In a market economy, when economic relations are formed horizontally, and administrative methods of influence on commodity producers have limited effect, the role of forecasting becomes of paramount importance.

Economic forecasting is implemented based on the use of both general scientific methods and research approaches, and specific methods inherent in scientific forecasting of economic phenomena. Among the general methods, the following can be distinguished: historical, complex, systemic, structural, system-structural.

The historical approach consists of considering each phenomenon in the interconnection of its historical forms. Forecasting is based on the transfer of laws and trends that exist in the present beyond its borders, in order to recreate on this basis a model of the future that does not yet exist. The connection between various historical forms of existence of the same phenomenon means that the current state of the object under study is a natural result of its previous development, and the future state is a natural result of development in the past and present.

An integrated approach includes consideration of phenomena in their connection and dependence on each other, using research methods not only of this science, but also of other sciences that study this phenomenon. The theoretical basis for developing scientific ideas about future development is political economy. For the same purpose, the scientific apparatus of other social sciences is widely used in the theory and practice of economic forecasting.

The systems approach involves the study of quantitative and qualitative patterns of probabilistic processes in complex economic systems. It plays an important role in economic forecasting. Each phenomenon of reality can be considered as a system. This means that it consists of a number of interconnected parts, elements that generally provide certain properties and functions. Knowing these properties and functions, one can predict how the object under study will behave.

The structural approach plays an important role in the study of forecasting objects, since the purpose of the study is a causal explanation, that is, to establish the cause of the phenomenon under study.

The systemic-structural approach involves, on the one hand, consideration of the economic system as a whole, dynamically developing, and on the other hand, the division of the system into its constituent structural elements in their interaction, since in real conditions each structural element affects both all other elements and the system generally. This creates the opportunity to reveal the patterns of connections between the elements of the system, as well as their relationship and subordination.

Socio-economic forecasting involves the use of various methods, which can be understood as a set of ways of thinking. They allow, on the basis of data, to derive definite and reliable judgments regarding the future state of the object under study.

In general, intuitive and formalized methods of forecasting the national economy are distinguished (Fig. 21.5).

Rice. 21.5. V

Intuitive forecasting methods are used when it is impossible to take into account the influence of many factors due to the complexity of the forecast object, and in this case, expert opinions regarding the behavior of the forecast object are used. They can be individual (questionnaires, interviews, analytics, script writing) and collective (decision of a collective expert commission, collective generation of ideas, brainstorming, Delphi method, matrix method).

Formalized forecasting methods are based on analytical grids expressing both aggregate demand and aggregate supply. The group of formalized methods includes extrapolation and modeling methods.

Forecast extrapolation can be carried out using methods of least squares, exponential smoothing, moving averages, and adaptive smoothing. When forming forecasts using extrapolation, they proceed from trends in changes in certain quantitative characteristics of an object that have statistically developed. However, the degree of reality of the forecast compiled using these methods is much lower, since the economic phenomenon is influenced by several variables that are not subject to extrapolation. In addition, extrapolation focuses on the past and present, and forecast parameters may depend on factors that did not operate in the past.

Forecast modeling methods include structural, network, matrix and simulation modeling.

Structural models describe the connections between individual elements of a single whole (inter-industry balance).

Network models enable optimization of predictive decisions using mathematical programming techniques.

Matrix modeling involves the compilation of an expert matrix based on a survey of experts.

Simulation models reproduce the development of the forecast object in accordance with the expected situation or similar phenomenon.

Using the above forecasting methods, conclusions can be drawn about the development of the national economy in the future.

Forecasting economic and social development of Ukraine

The legislative basis for socio-economic forecasting in Ukraine is the Constitution of Ukraine, the Law of Ukraine “On State Forecasting and Development of Programs for Economic and Social Development of Ukraine”, other laws of Ukraine and by-laws.

According to this legal framework, the main principles on which state forecasting of economic and social development of Ukraine is based are the following: the principle of integrity, objectivity, scientific character, transparency, independence, equality and respect for national interests.

Conducting economic and social forecasting involves studying the overall potential of the country (region, industry, enterprise). Participants in state forecasting and development of programs for economic and social development of Ukraine are government bodies that develop, approve and implement forecast and program documents for economic and social development, namely: the Cabinet of Ministers of Ukraine, the authorized central executive body on economic policy issues, other central bodies executive power, the Council of Ministers of the Autonomous Republic of Crimea, local state administrations and local government bodies.

The long-term state forecast of economic and social development of Ukraine is developed for 10-15 years and is updated every five years. It should contain: an assumption about the foreign economic situation and domestic economic policy; analysis of the economic and social development of the country over the past years; forecast macroeconomic indicators (GDP, inflation rate, real wages, unemployment rate, budget deficit as a percentage of GDP, foreign trade balance, external debt); conclusions about the main trends in economic development in the long term.

The forecast for the economic and social development of Ukraine for the medium term is being developed for 5 years.

The state forecast of economic and social development of Ukraine for the short-term period is developed annually for the next year. The indicators of this forecast are used to assess revenues and formulate indicators of the state budget of Ukraine.

Tagiev M.Kh.

Forms and methods of regulating socio-economic development of regions: existing practice and development prospects

In modern economic conditions, there is a fairly broad classification of forms and methods of state regulation of socio-economic development of regions.

When considering management systems for regional structures, you need to pay attention to the management of socio-economic development of regions. As is known, socio-economic development includes the following components:

Increased production, income and, as a result, increased well-being of the population;

Significant changes in the social, institutional, administrative structures of society;

Changes in public consciousness;

Changes in traditions and habits;

Increasing the level of education and improving health, etc.

To implement these components in modern conditions, a system of methods for regulating the socio-economic development of the country's regions is necessary.

As is known, under a planned economy, the set of methods for managing the development of Russian regions was limited primarily to administrative methods, i.e. Administrative instructions actually carried out the redistribution of resources between regions, as a result of which a relatively uniform level was achieved.

But in the transition to market relations, naturally, such a set of methods is not entirely suitable for solving this kind of problem. In the extensive arsenal of modern instruments of state regulation of the regional economy, a number of forms and methods can be distinguished. State regulation is carried out in the following forms:

1) legislative;

2) tax;

3) credit;

4) subvention.

The legislative form of regulation means that special legislative acts are adopted that provide relatively equal opportunities for competition, expand the boundaries of competition, and prevent the development of monopolized production and the establishment of exorbitantly high prices.

Tax and credit forms of regulation represent the use of taxes and credits to influence national output. By changing tax rates and benefits, the government influences the contraction or expansion of production and investment decisions. By varying lending conditions, the state influences the decrease or increase in production volumes. By selling securities, it reduces bank reserves, while increasing

Interest rates rise and, accordingly, production declines, and vice versa. By purchasing securities, the state increases bank reserves, while interest rates fall and production expands.

The subvention form of regulation involves the provision of government subsidies and tax benefits to certain industries and enterprises (mainly such industries as agriculture, mining, shipbuilding, and transport).

Among the methods of state regulation can be distinguished: administrative and legal regulation, direct and indirect regulation.

Administrative methods include various measures for rationalization and allocation, licensing and quotas, control over prices, income, exchange rates, accounting interest, etc. These measures have the force of an order and are not based on economic interests and the incentives that implement them. State legal regulation is carried out within the framework of economic legislation through a system of norms and rules established by it.

Particular attention, in our opinion, should be paid to economically weak regions.

The state should provide various support to such regions: in the form of developing production infrastructure, stimulating the influx of private investment, providing a number of tax and credit benefits, selective subsidies to enterprises that provide minimal employment, supplementing transfers, etc. But the main direction, the main path is the self-development of regions based on the use of one’s own socio-economic potential.

Direct regulation involves managing development through fiscal policy, direct financing, investing in individual regions or industries to curb decline or increase the pace of development. This is one of the methods of targeted regulation (microtool). The most typical example of such state activity in the regions is the implementation of investment projects of federal significance: construction and reconstruction at the expense of the federal budget of railways, highways, scientific, educational and medical centers, etc. The state should also finance projects that have a strong positive impact on employment growth, increasing the tax base, and the quality of social services in specific regions. Currently, a significant number of investment projects are carried out on a shared basis using funds from regional budgets and private investors (the so-called “revolving” principle of financing). The federal targeted investment program, included in the structure of the federal budget for 2003, contains hundreds of candy facilities and provides for the allocation of 23.8 billion rubles for investments, including 7.0 billion rubles for production complexes, and for the social complex - 16.8 billion rubles.

The state should provide selective support to existing enterprises in the form of subsidies for the products they produce. First of all this

refers to public sector enterprises. From the point of view of regional economic policy, it is important where such enterprises are located and in what regional situation. Financial support is particularly useful when it prevents greater economic and social costs to the region from reduced production, employment or business failure.

Placement of government orders for the supply of products for national needs. The state, as the largest buyer, should strongly influence production capacity utilization, employment and income in different regions, implementing certain objectives of regional economic policy. In conditions of economic recession, it is especially important to provide city-forming enterprises with orders in order to reduce unemployment and other negative socio-economic consequences. Placing government orders can stimulate economic recovery in the relevant regions and cities.

Organizational, legal, information support for regions in special areas of activity. This kind of support for regions is most important in those activities where the capabilities and competence of regional authorities are limited or insufficient. First of all, this is foreign economic activity. The state should provide assistance to regions in establishing contacts with foreign trade partners and foreign investors, in obtaining international loans and borrowings, in distributing regional securities on world financial markets, in including in international programs and technical assistance projects. As a rule, these forms of international participation of regions are implemented on the basis of agreements concluded by the Government of the Russian Federation; it also acts as a guarantor of loan repayment and project completion.

The above measures taken by the state in modern conditions are predominantly direct in nature. Today, the importance of methods of indirect (mediated) regulation, carried out through financial and tax regulators, supported by regional benefits and economic incentives in various fields of activity that influence the course of development of the regional economy in Russia, is sharply increasing.

Based on the above, we can say that there is a set of general methods and forms of regulating the development of regions, with which the state influences their economic functioning. But at the same time, modern domestic and foreign literature provides a set of territorially oriented economic regulators operating on the territory, among themselves and the newly created mechanism for regulating the economy regarding the attraction of foreign investors, foreign economic activity, the development of free economic zones, large, small and medium-sized businesses.

The system of economic regulators must maintain a balance between social justice and economic feasibility, and be formed in the territory not spontaneously, as is currently happening, but strictly in accordance with their compatibility and consistency. For each type of area there are three

attempts to justify economically compatible sets of economic regulations and benefits, highlighting a block in them dedicated to supporting certain types of business activities.

The mechanism for the territorial development of regions of various types should naturally fit into the emerging system of state regulation of territorial development and be implemented at the federal, interregional, regional and local levels in accordance with the developed strategy for the territorial development of the economy in Russia and the main priority directions of its regional economic and social policy.

In modern domestic and foreign economic literature, there are four blocks of territorially oriented economic regulators that influence the real process of regional development: social, economic, environmental and interethnic.

In the social sphere it is:

A mechanism for facilitating the employment of demobilized military personnel, migrants, refugees from neighboring countries and regions of military conflicts, people leaving the Far North and equivalent areas;

Formation of social funds for the national revival of small peoples and ethnic groups;

Allocation of financial assistance to low-income categories of the population from the fund for social support of the population in specific regions;

Changes in regional wage coefficients in problem regions.

In the economic sphere:

For old industrial areas:

Exemption from taxation of part of the profit allocated for technical re-equipment and reconstruction of enterprises, conversion of military production and R&D;

Introduction of a preferential depreciation system;

Subsidizing the costs of retraining workers released as a result of rationalization of production, re-profiling of enterprises and declaring some of them bankrupt;

Providing tax incentives and insurance guarantees to foreign investors promoting major structural and technological changes;

Allocation of preferential government and commercial loans;

Introduction of a competitive contract system;

Implementation of a set of economic incentive measures to support priority areas of entrepreneurship;

For crisis (depressed) regions:

Allocation of government domestic and foreign investments and subventions within the framework of federal and regional programs;

Use of special budgetary and extra-budgetary regional funds;

The use of preferential regional tax deduction standards (for income tax, VAT and others) in order to increase the financial base of the budgets of problem or priority regions;

Attracting private domestic and foreign capital, as well as special funds to solve major regional economic problems.

For free economic zones and border areas:

Reduction or abolition of customs duties, export-import controls over goods entering the zone and re-exported from it (in free trade transit zones);

Introduction of preferential trade and customs regime, preferential financing and taxation, stimulation of foreign investment in the manufacturing sector (in export industrial zones);

Providing tax, registration benefits and information services for domestic and foreign firms, special regime for insurance and banking operations, preferential taxation for certain types of income and special lending conditions (in banking and insurance zones);

Supporting innovative companies by insuring commercial loans, promoting domestic developments to the foreign market by reducing the taxation of profits, indexing depreciation charges and other measures to influence the economic situation (in technological zones);

For regions in extreme situations:

Granting the right to enterprises to freely sell a certain share of their products (oil, gas, gold, diamonds) on the world market;

Increasing the share of foreign currency earnings left in the regions (Dagestan, Kabardino-Balkaria, etc.);

Use of special regional funds and federal regional development programs;

A mechanism of guarantees against political risks in the form of collateral in areas with an unstable situation;

Sanctions against regions that have stopped transferring funds to the republican budget of the Russian Federation (cessation of financing of all federal expenditures in the territory, termination of customs clearance of all foreign trade cargo, revocation of previously issued quotas and licenses for the export of strategic types of raw materials, termination of the issuance of centralized loans) will have a negative impact on economic activity in the regions.

In the environmental field:

Introduction of territorially differentiated fees for land use in urban and rural areas, resort areas;

Implementation of the state land monitoring program, creation of a multi-level forecasting system for eliminating negative environmental processes (financial

financing from the federal budget and funds from land fees);

Granting the preferential right to conclude contracts and obtain licenses for the use of renewable natural resources to tribal communities, families of individual representatives of small peoples of the North in their places of traditional residence;

Creation of a special regime of residence in areas of environmental disaster;

Introduction of preferential conditions for the privatization of environmental facilities;

In the field of national and interethnic relations:

Providing preferential loans and the opportunity to purchase housing for “repressed peoples” and those displaced due to interethnic conflicts;

Reducing payment rates for loans aimed at enhancing the development of farms, employment of migrants, refugees from areas of military conflicts, neighboring countries and victims of repression;

Promotion of free privatization of objects and territories of traditional forms of economic management of small peoples.

The above system of territorially-oriented methods for regulating the economic development of regions of the country differs from the previous ones in a more specific focus on achieving a particular goal, taking into account the specifics of a particular region. Based on this, we can say that before using one or another method for a specific region, a thorough multifaceted study and identification of its features is necessary.

In addition to the above methods, in modern conditions program-targeted methods of state regulation of territorial development are becoming increasingly known and applied in domestic economic practice.

The use of program-targeted methods is caused, on the one hand, by the inability to solve one or another major interregional or intersectoral problem using traditional methods, and on the other hand, by the need to link goals (subgoals), multi-purpose resources and a large number of performers.

Solving large-scale intersectoral (sectoral) and regional problems, as a rule, is associated with the development and implementation of federal target programs, which should be considered as one of the means of structural and regional policy of the state.

Program-targeted methods of regulating the socio-economic development of the country's regions are an effective tool in the hands of government authorities when solving one or another important problem of its regulation.

Thus, the set of methods and forms of regulation of the socio-economic development of the region presented above includes a large number of specific activities and methods for solving certain problems in the management process.

development of the region. Currently, in our opinion, it is necessary to most fully study all the factors affecting the effectiveness of using each of them to create and develop an effective mechanism for regulating regional development.

Alikberli M.M.. Gadzhiev M.M.. Naurkhanov H.Ya.

The place and role of investment in the simplest models of economic growth

Effective development of the industrial complex presupposes a systematic increase in the technical and technological level of the enterprise, as a consequence of the requirements generated by both the internal and external environment. Striving for leadership, enterprises introduce new technologies and equipment, improve existing technical and technological potential, in order to increase competitiveness and create prerequisites for sustainable development. This process is systemic in nature and requires a well-functioning mechanism for financing capital investments. The development of the financial market significantly expands and diversifies sources of funds: along with internal investments, there is a real opportunity to attract external funds. Thus, significant capital investments are made by attracting funds from both domestic and foreign investors, represented by the state, investment companies, banks, entrepreneurs, and so on.

Attracted investments aimed at developing technical and economic potential lead to increased efficiency of capital investments. But the higher the return on invested capital, the greater the opportunity for enterprises to radically re-equip, intensify processes and, as a result, achieve diversification goals.

Any business can be represented as an interconnected system of movement of financial resources caused by management decisions. It follows that since entrepreneurial activity is based on the advance of capital by investing and reinvesting it at all stages of the enterprise’s life cycle, the effectiveness of enterprises is related to the management, evaluation and analysis of the effectiveness of investments.

The construction of most models of economic growth is based on isolating individual factors from the economic environment and determining the degree of their influence on the results of the functioning of the economy. Despite the generality and simplicity of economic models, they make it possible to determine the main trends in the dynamics of economic development, identify the key factors that influence these dynamics, and also assess the nature of the impact of these factors.

It seems appropriate to consider the main models of economic growth.

Theoretical and methodological foundations of socio-economic forecasting methods. The essence of forecasting methods using the example of the USA. Possibilities of using experience in applying forecasting methods in modern Ukraine.

Methods of socio-economic forecasting

The coursework was completed by Denis Nazarenko

Introduction

Currently, not a single sphere of social life can do without forecasts as a means of knowing the future. Of particular importance are forecasts of the socio-economic development of society, justification of the main directions of economic policy, and anticipation of the consequences of decisions made. Socio-economic forecasting is one of the decisive scientific factors in shaping the strategy and tactics of social development.

The relevance of this topic both in a developed market economy and in a transition economy is determined by the fact that the level of forecasting processes of social development determines the effectiveness of planning and management of the economy and other areas.

The purpose of this course work is to consider the methodology and techniques for developing socio-economic forecasts to determine the essence, areas of application and the most effective forecasting methods. To do this, it is necessary to solve the following problems: determine the essence of socio-economic forecasting methods and the areas of their application in the course of studying the theoretical and methodological foundations of forecasting methodology; characterize the methods of socio-economic forecasting in economically developed countries and identify the features of their application in modern Ukraine.

In the process of writing this course work, textbooks edited by V.O. were used. Mosina, K.L. Triseeva, V. Tsygichko, V.V. Deniskin, as well as scientific articles on the problem under study in the periodicals “USA: Economics, Politics, Ideology”, “World Economy and International Relations”, “Problems of Forecasting”, “Russian Economic Journal”, “Problems of Forecasting”, “Russian Economic Journal”, “Economy of Ukraine”, “Bulletin of Moscow State University”.

Theoretical and methodological foundations of socio-economic forecasting methods

Socio-economic forecasting of the main directions of social development involves the use of special computational and logical techniques that make it possible to determine the functioning parameters of individual elements of the productive forces in their interrelation and interdependence. Systematized scientifically based forecasting of the development of socio-economic processes on the basis of specialized ones has been carried out since the first half of the 50s, although some forecasting techniques were known earlier. These include: logical analysis and analogy, extrapolation of trends, polling the opinions of specialists and scientists.

In the development of the methodology for forecasting socio-economic processes, the scientific developments of domestic and foreign scientists A.G. played a major role. Aganbegyan, I.V. Bestuzhev-Lada, L. Klein, V. Goldberg. The works of these scientists examine the meaning, essence and functions of forecasting, its role and place in the planning system, explore issues of methodology and organization of economic forecasting, and show the features of scientific forecasting. The development of works covering forecasting issues is carried out in the following main directions: deepening the theoretical and applied developments of several groups of techniques that meet the requirements of different objects and different types of forecasting work; development and implementation in practice of special methods and procedures for using various methodological techniques in the course of a specific forecast study; searching for ways and means of algorithmizing forecasting techniques and implementing them using a computer.

Forecasting methods should be understood as a set of techniques and ways of thinking that allow, based on the analysis of retrospective data, exogenous (external) and endogenous (internal) connections of the forecast object, as well as their measurements within the framework of the phenomenon or process under consideration, to derive judgments of a certain reliability regarding it (the object). future development.

According to estimates of domestic and foreign scientists, there are currently over 20 forecasting methods, but the number of basic ones is much smaller (15-20). Many of these methods refer rather to individual techniques and procedures that take into account the nuances of the forecast object. Others are a set of individual techniques that differ from the basic ones or from each other in the number of private techniques and the sequence of their application.

Existing sources present various classification principles for forecasting methods. One of the most important classification features of forecasting methods is the degree of formalization, which quite fully covers forecasting methods. The second classification feature can be called the general principle of operation of forecasting methods, the third is the method of obtaining forecast information. In Fig. 1.1 presents a classification scheme for forecasting methods.

As evidenced by the diagram presented in Fig. 1.1, according to the degree of formalization (according to the first classification criterion), economic forecasting methods can be divided into intuitive and formalized. Intuitive forecasting methods are used in cases where it is impossible to take into account the influence of many factors due to the significant complexity of the forecast object. In this case, expert assessments are used. At the same time, a distinction is made between individual and collective expert assessments.

Individual expert assessments include: the “interview” method, in which direct contact between an expert and a specialist is carried out using a “question-answer” scheme; analytical method, in which a logical analysis of any predicted situation is carried out, analytical reports are compiled; a method of writing a script, which is based on determining the logic of a process or phenomenon over time under various conditions.

Methods of collective expert assessments include the method of “commissions”, “collective generation of ideas” (“brainstorming”), the Delphi method, and the matrix method. This group of methods is based on the fact that with collective thinking, firstly, the accuracy of the result is higher, and secondly, when processing individual independent assessments made by experts, at least productive ideas can arise.

The group of formalized methods includes two subgroups: extrapolation and modeling. The first subgroup includes methods: least squares, exponential smoothing, moving averages. The second includes structural, network and matrix modeling.

The considered classes of intuitive and formalized methods are similar in composition to expert and factual methods. Factual methods are based on actually available information about the forecast object and its past development, expert methods are based on information obtained from the assessments of specialist experts.

Rice. 1.1

The class of expert forecasting methods includes the heuristic forecasting method (heuristics is a science that studies productive creative thinking). This is an analytical method, the essence of which is the construction and subsequent truncation of a “search tree” of expert assessment using some kind of heuristic. With this method, specialized processing of forecast expert assessments obtained through a systematic survey of highly qualified specialists is carried out. It is used to develop forecasts of scientific and technical problems and objects, the analysis of the development of which either completely or partially cannot be formalized.

The studied literature presents a significant number of classification schemes for forecasting methods. The main error of such schemes is a violation of classification principles, which include: sufficient completeness of coverage of forecasting methods, unity of the classification attribute at each level of division (with multi-level classification), non-overlapping sections of the classification, openness of the classification scheme (i.e. the possibility of adding new methods) .

In most classification schemes, forecasting methods are divided into three main classes: extrapolation, expert assessment and modeling methods. With this division, extrapolation methods are opposed to modeling methods as an independent class.

On the one hand, the construction of models aims to reveal the pattern of development of the object or process being studied in a certain retrospective area. And if the model is built correctly and adequately reflects the connections and properties of a real object, it can serve as the basis for extrapolation, i.e., for transferring some conclusions about the behavior of the model to the object. This is predicting the behavior of an object by extrapolating trends identified in the model.

On the other hand, extrapolation methods are nothing more than the use of theoretical and empirical models to find variables outside the retrospective observation section based on the data of the relationships between them in the retrospective section. Thus, the use of extrapolation in forecasting always involves the use of some kind of model. Therefore, any modeling is the basis for extrapolation.

Constructive classification allows you to visually depict a set of forecasting methods in the form of a hierarchical tree and characterize each level with its own classification feature. (Fig. 1.2)

At the first level, all methods based on the “information basis of the method” are divided into three classes: factual, combined and expert.

Factual ones are based on factual information about the forecast object and its past development. Expert methods use information provided by specialist experts through systematic procedures for identifying and summarizing their opinions. In turn, classes of expert and factual methods are divided into subclasses based on information processing methods.

Expert methods are divided into two subclasses. Direct expert assessments are based on the principle of obtaining and processing the independent generalized opinion of a team of experts (or one of them) in the absence of influence on the opinion of each expert by the opinions of another expert and the entire team. Expert assessments with feedback in one form or another implement the principle of feedback based on the impact on the expert assessment

group (one expert) with opinions previously received from this group (or from one of the experts).

The class of factual methods combines the following three subclasses: analogy methods, anticipatory and statistical methods.

Analogy methods are aimed at identifying similarities in the patterns of development of various processes. These include methods of mathematical and historical analogies. Methods of mathematical analogies use objects of a different physical nature, other fields of science and technology, which have a mathematical description of the development process and coincide with the object of prediction, as an analogue for an object.

Anticipatory forecasting methods are based on certain principles of special processing of scientific and technical information, taking into account its ability to outstrip the progress of science and technology. These include methods for studying the dynamics of scientific and technical information, using the construction of time series based on various types of such information, analysis and forecasting on this basis the development of the corresponding object (for example, the envelope method). Advanced methods also include methods for researching and assessing the level of technology, based on the use of special methods for analyzing quantitative and qualitative scientific and technical information to determine the characteristics of the quality level of existing and designed equipment.

Statistical methods are a set of methods for processing quantitative information about a forecasting object, united by the principle of identifying the mathematical patterns contained in it for changing the characteristics of a given object in order to obtain forecast models.

The difficulty in choosing the most effective method of economic forecasting lies in determining the characteristics of each method regarding the classification of forecasting methods, the list of requirements for retrospective information and the forecast background.

In this regard, there is a need to dwell in more detail on the main classes of economic forecasting methods.

In cases of extreme complexity of the system, its novelty, uncertainty in the formation of some essential features, insufficient completeness of information, and finally, the impossibility of complete mathematical formalization of the process of solving the problem, one has to turn to the recommendations of competent specialists. Their solution to the problem, argumentation, approach, the formation of quantitative assessments of the results, and the processing of the latter by formal methods are called the method of expert assessments. This method includes three components: intuitive-logical analysis of the problem or its fragment; decision and issuance of quantitative or qualitative characteristics (assessment, decision result); processing of decision results – received from experts – assessments.

One of the varieties of the expert assessment method is the method of collective generation of ideas (“brainstorming”), which allows one to determine possible options for the development of a forecast object in a short period of time. Brainstorming methods can be classified based on the presence or absence of feedback between the leader and the brainstorming participants in the process of solving a certain problem situation. The current situation required the development of a “brainstorming” method—destructive referenced evaluation (DRA), capable of evaluating options efficiently and quickly enough, without limiting their number.

The essence of this method is to actualize the creative potential of specialists during a “brainstorming” of a problem situation, which first involves the generation of ideas and the subsequent destruction (destruction, criticism) of these ideas with the formation of counter-ideas. Working with the DOO method involves the implementation of the following six stages.

The first stage is the formation of a group of brainstorming participants (in terms of size and composition). The optimal size of a group of participants is determined empirically: groups of 10–15 people are recognized as the most productive. The composition of the group of participants involves their targeted selection: 1) from people of approximately the same rank, if the participants know each other; 2) from persons of different ranks, if the participants do not know each other (in this case, each participant should be leveled by assigning him a number and then addressing the participant by number). The second stage is drawing up a problem note from a brainstorming participant. It is compiled by the problem situation analysis group and includes a description of the ECE method and a description of the problem situation. The third stage is the generation of ideas. The duration of brainstorming is recommended to be at least 20 minutes and no more than 1 hour, depending on the activity of the participants. It is advisable to record the ideas expressed on a tape recorder so as not to “miss” any idea and to be able to systematize them for the next stage.

The fourth stage is the systematization of ideas expressed at the generation stage. The problem situation analysis group carries out systematization of ideas in the following sequence: a nomenclature list of all expressed ideas is compiled; each of the ideas is formulated in commonly used terms; duplicate and complementary ideas are identified; duplicate and (or) complementary ideas are combined and formed into one complex idea; signs are identified according to which ideas can be combined; ideas are combined into groups according to selected characteristics; a list of ideas is compiled into groups (in each group, ideas are written down in order of their generality from more general to specific, complementing or developing more general ideas).

The fifth stage is the destruction (destruction) of systematized ideas (a specialized procedure for assessing ideas for practical feasibility in the process of a brainstorming session, when each of them is subjected to comprehensive criticism by the brainstorming participants).

The basic rule of the destruction stage is to consider each of the systematized ideas only from the point of view of obstacles to its implementation, that is, the participants in the attack put forward conclusions that reject the systematized idea. Particularly valuable is the fact that in the process of destruction a counter-idea can be generated that formulates existing restrictions and suggests the possibility of removing these restrictions.

The sixth step is to evaluate the criticisms and compile a list of practical ideas.

The method of collective generation of ideas has been tested in practice and allows one to find a group solution when determining possible options for the development of a forecast object, excluding the path of compromise, when a single opinion cannot be considered the result of an impartial analysis of the problem.

In 1970-1980 Separate methods have been created that allow, to a certain extent, to organize statistical processing of the opinions of expert experts and achieve a more or less agreed upon opinion. The Delphi method is one of the most common methods of expert assessment of the future, i.e. expert forecasting. This method was developed by the American research corporation RAND and is used to determine and assess the likelihood of certain events occurring.

The Delphi method is built on the following principle: in inexact sciences, expert opinions and subjective judgments, by necessity, must replace the exact laws of causality reflected by the natural sciences.

The Delphi method allows you to summarize the opinions of individual experts into a consensus group opinion. It has all the shortcomings of forecasts based on expert assessments. However, the work carried out by the RAND Corporation to improve this system has significantly increased the flexibility, speed and accuracy of forecasting. The Delphi method is characterized by three features that distinguish it from conventional methods of group interaction between experts. These features include: a) anonymity of experts; b) using the results of the previous round of the survey; C) statistical characteristics of the group response.

Anonymity lies in the fact that during the procedure of expert assessment of the predicted phenomenon or object, the participants of the expert group are unknown to each other. In this case, the interaction of group members when filling out questionnaires is completely eliminated. As a result of such a statement, the author of the answer may change his opinion without publicly announcing it.

The statistical characteristic of a group response involves processing the results obtained using the following measurement methods: ranking, paired comparison, sequential comparison and direct assessment.

In the development of the Delphi method, cross-correction is used. A future event is represented as a huge number of connected and transforming paths of development. When cross-correlation is introduced, the value of each event, due to the entered certain connections, will change either in a positive or negative direction, thereby adjusting the probabilities of the events in question. For the purpose of future compliance of the model with real conditions, elements of randomness can be introduced into the model.

The disadvantage of this method is that the problem of correlating scientific and technological changes is very complex, since in real life the magnitude of the correlation is very difficult to measure, the correlations are unclear and vary widely depending on the achievements in question.

The essence of forecast extrapolation methods is to study the dynamics of changes in an economic phenomenon in the pre-forecast period and transfer the found pattern to a certain period in the future. A prerequisite for the use of an extrapolation approach in forecasting should be considered knowledge and an objective understanding of the nature of the process under study, as well as the presence of stable trends in the development mechanism.

However, the degree of reality of such forecasts and, accordingly, the degree of confidence in them are largely determined by the reasoning of the choice of extrapolation limits and the stability of the correspondence of the “measurers” in relation to the essence of the phenomenon under consideration. It should be noted that complex objects, as a rule, cannot be characterized by one parameter.

The extrapolation operation in general can be represented as determining the values ​​of the function

The simplest method of forecasting is considered to be an approach that forms a forecast estimate from the actually achieved level using the average increase or growth rate.

In accordance with it, the forecast for steps forward at a point in time

This method has certain advantages, including the low complexity of the computational algorithm and universal calculation schemes. In addition to these advantages, it has several significant disadvantages. Firstly, all actual observations are the result of regularity and chance, therefore, it is inappropriate to rely on the last observation. Secondly, there is no way to assess the legality of using the average increase in each specific case. Thirdly, this approach does not allow us to form an interval in which the predicted value falls. In this regard, the extrapolation method does not give accurate results over a long forecast period, because this method is based on the past and present, and thus the error accumulates. This method gives positive results for the short term forecasting of certain objects - for 5-7 years.

Various techniques are used to improve the accuracy of extrapolation. One of them is, for example, to adjust the extrapolated part of the general development curve (trend) taking into account the real experience of the development of an industry analogue of research or an object that is ahead of the predicted object in its development.

A common technique for predicting certain processes and phenomena is modeling. Modeling is considered a fairly effective means of predicting the possible occurrence of new or future technical means and solutions. For the first time, for forecasting purposes, the construction of operating models was undertaken in economics. The model is constructed by the subject of the study so that the operations reflect the characteristics of the object that are significant for the purpose of the study. Therefore, the question of the quality of such a mapping - the adequacy of the model to the object - can only be legitimately decided in relation to a specific goal. Construction of a model based on preliminary study and identification of its essential characteristics, experimental and theoretical analysis of the model, comparison of results with object data, and adjustment of the model constitute the content of the modeling method.

One of the modeling methods is the method of mathematical modeling. An economic-mathematical model is understood as a technique for bringing to a complete description of the process of obtaining, processing initial information and assessing the solution of the problem under consideration in a fairly wide class of cases. The use of mathematical apparatus to describe models (including algorithms and their actions) is associated with the advantages of a mathematical approach to multi-stage information processing processes, the use of identical means of forming problems, finding a method for solving them, fixing these methods and converting them into programs designed for the use of computer technology .

The use of mathematical methods is a necessary condition for the development and use of forecasting methods, ensuring high requirements for the validity, effectiveness and temporality of forecasts.

Regression analysis methods are of great practical importance in forecasting. Regression analysis is used to study the forms of communication that establish qualitative relationships between random variables of the random process being studied. In other words, the relationship between random and non-random variables is called regression, and the method of analyzing such relationships is called regression analysis. The advantage of the regression method should be considered its universality, a wide selection of functional dependencies, and the possibility of including the time factor in a statistical model as an independent variable.

A specific forecasting method is a scenario forecast - this is a kind of method of describing a logically sequential process, an event based on the current situation. The scenarios are described taking into account time estimates. The main purpose of the scenario is to determine the general goal of development of the predicted object, phenomenon and to formulate criteria for assessing the upper levels of the “tree of goals.” Scenarios are usually developed based on preliminary forecast data and source materials on the development of the forecast object. The starting materials should include technical and economic characteristics and indicators of the main processes of the production and scientific base for achieving the goal.

A scenario is a picture that displays a consistent, detailed solution to a problem, identification of possible obstacles, and detection of serious deficiencies in order to prejudge the issue of a possible termination of work begun or completion of ongoing work on the projected object. The scenario according to which a forecast for the development of an object or processes should be drawn up must contain issues of the development of not only science and technology, but also the economy, foreign and domestic policy. Therefore, scenarios must be developed by highly qualified specialists of the appropriate profile of the predicted object. The scenario, in its descriptiveness, is an accumulator of initial information, on the basis of which all work on the development of the predicted object should be built. Therefore, the finished script must be subjected to careful analysis.

Consequently, in the process of systematized scientifically based forecasting of the development of socio-economic processes, the development of forecasting methodology took place as a set of methods, techniques and ways of thinking that, based on the analysis of retrospective data, exogenous and endogenous connections of the forecast object, as well as their measurements within the framework of the phenomenon under consideration, or process to derive judgments of a certain reliability regarding its future development.

The study of various classification schemes of forecasting methods allows us to identify factual, expert and combined methods as the main classes, the specialization of which is determined by the specifics of goals and objectives, the quantity and quality of initial information, and the forecast lead time. The next chapter will examine the problems of selecting adequate forecasting methods and their application in developed economies.

The essence of socio-economic forecasting methods using the example of the USA

In the process of creating a market-type economy, an objective need arises to take into account the experience of highly developed countries in forecasting socio-economic phenomena, objects and processes. In developed countries, the practice of contract orders for predictive developments carried out for government agencies and large companies is widespread. In the United States, the centers of such research are the REMD Corporation, the Hudson Institute, and the Zorton Corporation, which specializes in economic forecasting. The most famous international forecasting organization is the Club of Rome; its main line of activity is to stimulate and coordinate research into global problems.

In its development in the post-war period (1950-1990), forecasting went through different forms, corresponding to different types of government regulation of a mixed economy. Historically, the first form of economic forecasting was the opportunistic one, associated with the increasing influence of the budget on the rate and proportions of economic growth as government spending increases in GDP. In the conditions of structural restructuring of the economy and their accelerated development, it became necessary to coordinate budgets with the indicators of economic forecasts, on which estimates of tax revenues and the size of budget revenues were based

This has led to the development of medium- and long-term forecasts, examples of which are the "Choosing Paths for Economic Growth" (1976-1985) in Canada, the Department of Labor Forecast 1986-1995. in the USA, “Ten Year Plan for Doubling National Income” (1961-1970) in Japan.

As forecasting activities improved and became more complex, they began to be separated from the budget both methodically and organizationally: if at the first stage national economic forecasts were compiled in the Ministries of Finance, then in the 60s of the 20th century special forecasting and planning bodies began to be created in economically developed countries ( General Commissariat for Planning in France, Economic Advisory Council in Japan, Central Planning Bureau in the Netherlands, etc.)

The essence of forecasting in a developed market economy lies in the scientific prediction of the development of all forms of management, in the subsequent identification of patterns and trends in scientific, technical, economic and social progress. Economic forecasts are compiled taking into account factors with a long-term impact on the dynamics of the economy: the volume and quality of fixed capital, the presence of a working population, the latest technologies, the unemployment rate, the amount of investment, export growth, and the inflation rate.

The global experience of market reforms has demonstrated the importance of balanced banking, credit, financial and budgetary policies of the state. Forecasting budget revenues is one of the most important problems that arise during its formation. Calculation methods in stable market conditions are based on a preliminary forecast of the nominal values ​​of the main macroeconomic indicators: GDP volume, consumption and investment. The stability over time of the most important budget standards and tax rates in countries with developed market economies, the availability of homogeneous statistical samples of sufficient length make it possible to widely use methods of applied statistics and economic-mathematical models for such forecasting.

In foreign developed countries, forecasting is based on a diagram of the main relationships in the national economy, formed from statistical information, called the system of national accounts (SNA).

The SNA is based on the balance sheet method and represents national accounting adequate to a market economy, which at the macro level ends with a set of indicators characterizing the results of economic activity, the structure of the economy, operations carried out in the process of economic activity, the resources available in the country and their use. The SNA is built in the form of balance sheets and accounts that create a model of the functioning of the units of the national economy.

The SNA can be characterized as a macrostatistical model of the economy and as a mechanism that ensures the unity of developing forecasts and plans and monitoring their implementation. With the help of the SNA, management and planning bodies develop forecasts, draft programs and plans, evaluate the results of the impact on the economy, and monitor the implementation of plans.

The primary elements in the national accounting system are economic transactions and economic agents. An economic transaction is a process in which one of the parties involved transfers or sells, and the other receives or buys, material and financial assets and services. Legal entities and individuals carrying out economic transactions are economic agents.

Economic transactions are recorded in accounts built on the principle of double entry, according to which each transaction is recorded twice - in the “resources” section and in the “use” section. For each account, a balancing balance is displayed - the difference between resources and their use. If there is an excess of resources, the balance is recorded in the “use” section; if there is a shortage, the balance is recorded in the “resources” section.

Accounts are prepared for both economic transactions and economic agents. In order to use data for analysis, forecasting accounts are combined into groups by type of activity and institutional sectors of the national economy.

The central place in the system of SNA indicators is occupied by the gross national product indicator, which is the value equivalent of the market values ​​of all goods produced during the year - products and services.

Macroeconomic forecasting is based on a model of circular flows or GNP turnover. In its elementary form, this model includes only two categories of economic agents - households and firms - and does not imply government intervention in the economy, as well as any connections with the outside world (Fig. 2.1)

Circular flow model in a closed economy

From the diagram presented in Fig. 2.1, it is clear that the economy is a closed system. The flows of “income - expenses” and “resources - products” are carried out simultaneously in opposite directions and are endlessly repeated. The main conclusion from the model is the equality of the total volume of production in monetary terms to the total value of household cash income.

In a real market economy with government intervention, the model of circular flows becomes somewhat more complicated (Appendix 1). When other groups of economic agents are introduced into the model - the government and the outside world - this equality is violated, since a leakage is formed from the income-expenses flow in the form of savings, taxes and imports. At the same time, additional funds are poured into this flow - investments, government taxes and exports.

Consequently, real and cash flows are carried out under the condition that the total income of households, firms, the state and the outside world is equal to the total volume of production.

Thus, the income and expenditure model is based on the basic macroeconomic identity:

In this regard, the basis for economic forecasting in developed countries is the formation of demand (personal consumption, government spending, capital investment and exports), on the one hand, and the supply of goods and services, on the other.

Consequently, forecasting economic processes is carried out within three methods of calculating GNP: by end use, by income generation and using the production method.

When calculating GNP by expenses, the expenses of all economic agents using GNP are summed up. Total expenses can be broken down into several components.

Personal consumption expenditures of households include expenditures on durable goods and current consumption, as well as on services.

Gross investment is the sum of net investment and depreciation and consists of investments in fixed assets, construction and inventories.

Government purchases of goods and services represent part of government expenditures that are included in the state budget. This group does not include transfer payments, since they are not related to the movement of goods and services.

Net exports of goods and services abroad are calculated as the difference between exports and imports. Differences between the components of GNP are based primarily on differences between the types of economic agents making the expenditures, rather than on differences in the goods and services purchased. Data on the structure of GNP by type of expenditure are shown in Fig. 2.2.

When calculating GNP by income, all types of factor income are summed up, as well as depreciation charges and net indirect taxes on business. The following types of factor income are usually distinguished as part of GNP: compensation for the labor of employees, income of owners, rental income, corporate profits and net interest.

In the theory and practice of forecasting economic growth, economic and mathematical modeling is widely used. The most common production function models based on the theory of production factors. In these models, the volume of GNP is presented as a function depending on the number of production factors used and the marginal productivity of each of them. Marginal factor productivity refers to the amount of increase in output obtained from each unit of increase in a given factor of production. Marginal productivity is calculated by relating the increase in output to the increase in a given production factor.

The simplest among the models of production functions is linear, in which the volume of production is presented as a sum of functions; linear, in which the volume of production is presented as the sum of the products of production factors and their marginal productivity. To take into account the influence of scientific and technological progress as an additional source of economic growth, the rate of scientific and technical progress is added to this amount. Thus, the simple derivative function looks like:

Where D1, D2, D3 are the shares of labor, capital and natural resources in the total product;

T, K, P – growth rates of labor, capital and natural resources;

A – rate of scientific and technological progress;

Y is the growth rate of the total product.

In 1928, the American economist P. Douglas and mathematician I. Cobb proposed a power-form production function, which takes into account the influence of only two factors - labor and capital costs and the rate of scientific and technological progress. This model looks like:

Where e is a power coefficient depending on the marginal productivity of the factor;

A – proportionality coefficient;

T – labor costs;

K – fixed assets in value terms.

The simplified Cobb-Douglas production function did not require taking into account the costs of natural resources, which was associated with significant difficulties, which led to its widespread use in forecasting practice.

In 1990, a forecast of socio-economic development of the United States for 1992-1997, developed by UN experts, was published. In this case, to predict the main macroeconomic indicator - the volume of GNP - the Cobb-Douglas production function was used, the initial parameters of which are shown in Table 2.1.

Initial data for forecasting the volume of US GNP

Table 2.1

	Working-age population, million people.	Share of unemployed, %	Cost of fixed production assets, million dollars.

Application of the production function to the initial data allows us to determine the value of GNP for the period 1992-1997. In 1997, specialists from the University of Michigan compared the results of the UN forecast in the annual forecast of the University of Michigan, as well as with the actual values ​​of GNP for the period under study (Table 2.2).

Forecasts of economic growth in the United States in 1992-1997.

Table 2.2

	Factual data		University of Michigan Forecast			UN forecast
	GNP, billion dollars	Growth, %	GNP, billion dollars	Growth, %	Deviation from fact, %	GNP, billion dollars	Growth, %	Deviation from fact, %

Obviously, the pessimistic version of the University of Michigan forecast was more accurate, since the deviation of the forecast indicators from the actual data did not exceed 0.22%. The GNP forecast developed by the UN was more optimistic, but the rate of economic growth in the United States in 1992-1997. were less significant, which led to an increase in deviations of predicted values ​​from actual ones - up to 2.57%.

It should be noted that despite the deviations of the forecast values ​​from the actual ones, in both forecasts there is a tendency towards steady growth, which reaches its maximum value in 1994, followed by a decrease in the rate of economic growth (Fig. 2.3).

As evidenced by the data presented in table. 2.2 and in Fig. 2.3, in the period 1992-1997. The longest dynamic economic development continued. The economic growth rate increased to 3.5% in 1994.

In 1995, economic growth in the United States slowed, and slowed more than predicted in both versions of the forecast (to 2%), but the following year it picked up the pace again. In general, in 1996, the growth of US GNP was 2.7%, which exceeded the forecast data. In 1997, actual growth increased to 2.8%. Slowdown in the rate of economic recovery in the United States in 1995-1997. was united, first of all, by weakening domestic consumer demand for durable goods, which led to a reduction in investment in inventories. The decline in external demand in Western Europe caused a drop in US export growth by almost 4 times.

Based on the forecast values ​​of US GNP for 1992-1997, obtained as a result of forecast research at the University of Michigan, and extrapolation modeling of the structure of GNP by end use, the nominal sizes of GNP components are predicted (Table 2.3).

Consequently, in the period 1992-1997. an increase in the share of private and public consumption was predicted, with a reduction in gross investment and net exports. It should be noted that during the period of significant economic recovery (1993-1994), a reduction in the absolute and relative values ​​of government consumption and an increase in net exports were expected to a minimum level. During this period, an increase in the volume and share of gross investment was predicted.

Forecast values ​​of US GNP components in 1992-1997.

Table 2.3

	GNP value, billion dollars	Components of GNP
		Private consumption		Government consumption		Gross Investment		Net exports
			Billion Doll.		Billion Doll.		Billion Doll.		Billion Doll.

A comparison of actual and forecast indicators of economic growth in the United States allows us to conclude that the economic recovery is developing in a fairly balanced manner and this trend can be expected to continue until the end of the decade (2000).

Thus, the experience of state regulation of a market economy indicates that it should be based on systematic scientific forecasting, which allows, on the basis of the information received about the past and present state of the economy, to suggest alternative ways of its development in the coming period. Forecasting the development of a market economy is based primarily on the Keynesian concept, which provides for the influence of the state on macroeconomic indicators. In this regard, economic forecasting in the United States, as in other developed countries, is based on the formation of demand (personal consumption, government spending, capital investment and exports) and supply (production of goods and services, as well as construction), which corresponds to the macroeconomic model of GNP circulation .

Possibilities of using the experience of applying socio-economic forecasting methods in modern Ukraine

Creating the prerequisites for stopping the decline in production volumes with their subsequent increase at the present stage of Ukraine’s development comes to the forefront among the tasks of economic policy. Without overcoming the decline in production and transferring the economy to a growth trajectory, it is not possible to solve a single socio-economic problem of Ukrainian society. This circumstance, as well as the introduction of a national currency and a decisive course towards achieving financial and general economic stability in the state, lead to increased requirements for the quality of macroeconomic forecasting.

Taking this into account, on April 2, 1998, the National Bank, the Ministry of Economy, the Institute of Economic Forecasting of the National Academy of Sciences of Ukraine, and the National Institute for Strategic Studies in Ukraine organized and held a scientific and practical conference “Economy of Ukraine in 1998-2000,” in which representatives also participated Verkhovna Rada of Ukraine.

The conference presented the methodology and forecasts used by various scientific institutions in Ukraine to develop forecasts for socio-economic development. The main methods of socio-economic forecasting were recognized as methods of economic-mathematical modeling and expert assessments.

One of the most important problems arising in the process of forecasting macroeconomic indicators was recognized as the problem of forecasting revenues to the State budget. The existence of different forms of ownership and management methods, the lack of effective production management make the standard method of calculating revenues, which was widely used during the times of planned economic management, unsuitable for use.

In a transition economy, the most important factor determining production volumes, and, consequently, the forecast of GDP, is effective demand. A significant component of this demand—public consumption expenditures (state security, health care, education)—is financed from the state budget. A large share of expenses falls on the budgetary sector. Thus, an accurate forecast of GDP is not possible without taking into account the volume and structure of budget expenditures. But budget revenues using this method can only be calculated based on the GDP forecast.

Another disadvantage of statistical methods is that they cannot sufficiently take into account the influence of non-economic factors, such as, for example, costs caused by the aggravation of the socio-political situation in a transition economy.

All this requires the creation of new approaches that would be based on modern quantitative research methods - system analysis and mathematical modeling. The multivariate development of events caused by the action of unpredictable factors is taken into account through scenario forecasting. The development by experts of scenarios for the influence of such factors precedes the implementation of forecasts for each of the scenarios, which makes it possible to take into account the greatest number of aspects of the modeled process. The use of scenario forecasting methods can be considered using the example of developing a draft state budget for 1998. Since the results of budget implementation significantly depend on the overall macroeconomic situation, which is influenced by difficult-to-predict factors, it is effective to use the following scenarios:

Scenario one (“optimistic”). Provides for a reduction in the cost of imports (in dollar terms) by 8-10% per year, a 30% reduction in total production costs, tight monetary and credit policies, as well as a reduction in lending rates by 5-6%.

According to experts, this set of conditions is the most favorable for achieving financial stabilization. Along with this, tough financial policies will certainly entail an additional decrease in the solvency of consumers, therefore, according to this scenario, a decline in production of 7-9% per year is expected.

Scenario two (“realistic”). Provides for the continuation of inflation trends, an increase in import prices to 5% per year, and the preservation of existing basic lending rates. The expected decline in production should not exceed 6% per year.

Scenario three (“moderately pessimistic”). It differs from the previous ones in the assumption of a twice as high rate of depreciation of the national currency and, as a consequence, an increase in the effect of external factors that also intensify inflationary processes in society. The expected decline in production is 6% per year.

The purpose of further research is to forecast revenues to the consolidated budget and determine the most important areas of expenditure. To do this, within the framework of the macroeconomic scenarios outlined above, the following sub-scenarios are considered:

Scenario one - A. Includes all the proposals of the first scenario, and also provides that the performance indicators of producers (product sales volume, profit, profitability) are calculated in accordance with the production volumes indicated in the forecasts of the Ministry of Economy. Covering the budget deficit from emission sources cannot exceed 30%. In fact, this scenario is a set of conditions under which the draft budget is calculated.

Scenario one – B. It differs from the previous one in that the performance indicators of producers are calculated on the basis of estimates of the volumes of effective demand, exports and imports obtained using a modeling system, taking into account the projected financial situation of consumers and producers.

Scenario two - A. Includes all the proposals of the second scenario, and the indicators are calculated similarly to the first scenario - A.

Scenario two - B. Includes all the proposals of the second scenario, and the indicators are calculated similarly to the first scenario - B.

The third scenario - A. Includes all the proposals of the third scenario, and the indicators are calculated similarly to the first scenario - B.

Then forecasts of revenues and main expenses are analyzed, and a scenario is selected according to which the macroeconomic situation could develop most realistically and effectively.

In conditions of economic decline in production volumes and instability of the economic situation in modern Ukraine, there is an increasing use of methods of expert assessments and calculations in forecasting socio-economic phenomena and processes. The use of these methods can be observed when forecasting the development of volumes of effective demand and final consumption.

The development of forecast options for the development of final consumption begins with an analysis of the coefficients of satisfaction of the population's needs, which are determined by relating the levels of consumption of various types of products for different periods, first to real ones, and then to rational ones. The inverse indices of demand for various types of products are also used in the analysis.

During the analysis process, these indices for various types of products are ranked by their value (starting from the lowest to the highest), and then grouped at a certain interval into 5-10 groups (highest, highest, increased, above average, average, below average , small) (see table 3.1)

By dividing the previously obtained indices of real, separately recommended and rational needs into these groups, one can obtain three sets of information for a meaningful analysis of the dynamics, quantitative dependencies, trends and patterns of proportionality development for the reporting years.

Basic quantitative characteristics and intervals of groups of different proportions

Table 3.1

	Need satisfaction rate	Needs index	Degree of proportionality
			Highest
			Increased
			Above average
			Below average

The coefficients of satisfaction of needs and indices of needs discussed above contain a comparison of objective indicators of production levels with the needs and effective demand of the population, based on subjective and expert ideas.

Further development of forecast options for consumption indicators is carried out by comparing two or three methods based on a hypothetical approach and studying the development of consumption of main types of products for the reporting period. Forecast options are developed for the future - both by extending the series for the reporting period according to the average annual established rates, and according to dynamism indices.

Complex and mostly spontaneous processes of transition to a market economy, commodity shortages and inflation are making great changes in the modern socio-economic situation. Due to the unpredictability of economic processes during the transition period, priority is given to short-term forecasting. The main task is to determine current trends in the development of market conditions, monitor the actual implementation of annual plans and make appropriate adjustments for the future.

The existing statistical base in Ukraine does not meet the requirements for information and statistical support for short-term forecasts. Thus, indicators necessary for short-term forecasting, such as the normal level of unemployment, wages, working hours, as well as other elements of the information base important for the development of short-term forecasts, are still not calculated monthly.

Short-term forecasting of macroeconomic indicators uses methods of extrapolation of economic dynamics and trends. The short-term forecast is based on forecast calculations of the nominal and real values ​​of GDP, as well as the level of inflation as a whole for the period and on an assessment of trends in changes in the market economy. For example, the forecast dynamics of real GDP for 1997: according to the minimum option - in the range from 3.6 to 2.7%, and according to the moderate option - from 0.1 to 1.4%. The forecast of volumes and dynamics of GDP for 1997 is carried out on the basis of actual data for 1994-1996, as well as for the first 3 months of 1997, on monthly volumes of GDP, consumer and wholesale price index.

The forecast was made taking into account trends for the analyzed period, taking into account the limitation that in 1997 no economic decisions will be made that will significantly affect the dynamics of macroeconomic indicators.

After this, a relationship is determined that is sufficient for use in a forecast, in which the correlation coefficients between the data are quite significant. This situation was observed when comparing the dynamics of the coefficients of monthly growth of nominal GDP (compared to the previous period from the beginning of the year) in 1995-1997. (see Fig. 3.1).

From Figure 3.1 it is clear that the relationship between the indicators turned out to be almost linear, which made it possible to use the coefficients of monthly growth of nominal GDP for the forecast.

In the process of developing a short-term forecast, the features of various economic systems were taken into account. In a closed economy, total income increases in accordance with the amount of increase in spending, and in an open economy, the increase in income is lower because part of the increase in income “leaves the economy” through imports.

Fig 3.1
Wholesale and consumer price indices in April December 1997 were estimated using the method of expert assessments. Based on them, the deflator of consumer and wholesale prices was calculated using formula (8):

Where D is the deflator of wholesale and consumer prices;

I – consumer price index for the corresponding period;

P – wholesale price index for the corresponding period.

Based on the above methodology based on 1997 data, a forecast was made for the nominal and real value of GDP for 1998, which included two options: moderate (without taking into account the expected increase in prices, in which case the inflation index in 1998 would be 8%, and the wholesale index prices – 5%)); minimal (taking into account the administrative increase in tariffs for communication services and gas for the population by 15.8%).

The dynamics of deviations in this model characterizes changes in general trends in relation to inflation rates, as well as growth in the physical volume of goods produced and services provided. An expert assessment of inflation rates is accompanied by monitoring state external and internal debts, the dynamics of interest rates for loans, and the state budget deficit.

The results of the GDP forecast in Ukraine for the second half of the year, calculated on the basis of the presented model, are shown in table. 3.2

Forecast of nominal and real GDP of Ukraine

in the second half of 1998

Table 3.2

	Nominal GDP, million UAH.	Real GDP, %
Minimum option	Moderate option
September

The data presented in table. 3.2 indicate that in the case of the minimum option, the growth of nominal GDP occurs due to an increase in the inflation rate, which leads to the fact that real GDP begins to decline to -2.7% in December. In the moderate version, the growth of nominal GDP is explained by an increase in production volumes and a stable level of inflation, which allows real GDP to grow from 0.2% in July to 1.4% in December.

Thus, for forecasting and modeling socio-economic processes in Ukraine in the context of the transition to a market economy, statistical models that are based on existing trends in changes in macroeconomic indicators are most applicable. Forecasting models can be both long-term and short-term. Due to the high degree of economic policy uncertainty in Ukraine, priority is given to short-term forecasts. The disadvantage of short-term forecasts is that they use only monetary variables - such as price indices, money velocity, budget deficit, external direct investment. Variables that focus on summarizing the creation of real added value can only be effectively used in long-term forecasting.

Conclusion

Based on the research conducted on the topic “methods of socio-economic forecasting”, the following conclusions must be drawn:

In the process of systematized scientifically based forecasting of the development of socio-economic processes, the development of forecasting methodology took place, as a set of methods, techniques and ways of thinking, allowing, based on the analysis of retrospective data, exogenous and endogenous connections of the forecast object, as well as their measurements within the framework of the phenomenon or process under consideration, to deduce judgments of some certainty regarding its future development.

The study of various classification schemes of forecasting methods allows us to identify factual, expert and combined methods as the main classes, the specialization of which is determined by the specifics of goals and objectives, the quantity and quality of initial information, and the forecast lead time.

Thus, the optics of state regulation of a market economy indicate that it should be based on systematic scientific forecasting, which allows, on the basis of the information received about the past and present state of the economy, to suggest alternative ways of its development in the coming period. The market economy is based primarily on the Keynesian concept, which provides for the influence of the state on macroeconomic indicators. In this regard, economic forecasting in the United States, as in other developed countries, is based on the formation of demand (personal consumption, government spending, capital investment and exports) and supply (production of goods and services, as well as construction), which corresponds to the macroeconomic model of GNP circulation .

It should be noted that the processes of reforming the economic system in modern Ukraine caused a change in priorities in the methodology of socio-economic forecasting. Thus, the lack of directive management made the normative method, which was widely used in a planned economy, unsuitable for forecasting. The economic decline in production and the instability of the economic situation in Ukraine determine the priority importance of short-term forecasting of socio-economic processes using economic and mathematical models and expert assessments.

Bibliography

Agapova T. Modern economic theory: methodological basis and models // Russian Economic Journal. – 1995. - No. 10.

Bogacheva O. USA: the sixth year of stable economic recovery // World Economy and International Relations. – 1998. - No. 8.

Vlasyuk A. Stabilization of the Ukrainian economy // Economy of Ukraine. – 1995. - No. 12.

Gorelov S. Mathematical methods in forecasting. – M.: Progress, 1993.

Deniskin V. Fundamentals of social forecasting in the food industry. – M.: Kolos, 1993.

Dudkin V. Indicative planning is a mechanism for coordinating the activities of state and non-state subjects of management // Russian Economic Journal. – 1998. - No. 6.

Krivov V. Legislative determination of the content of economic decisions // Economist. – 1997. - No. 12.

Course in Economic Theory / Ed. A.S. Sidorovich. – M.: Moscow State University Textbooks, 1997.

Leskova N. Forecast of the development of the world economy // Bulletin of foreign commercial information. – 1995. - No. 145.

Fundamentals of economic and social forecasting / Edited by Mosin N. - M.: Higher School, 1985.

Panasyuk B., Sergienko I. Forecasting the development of the Ukrainian economy // Economy of Ukraine. – 1996. - No. 1.

Panasyuk B., Smenkovsky A. On some methodological approaches to short-term forecasting of macroeconomic indicators // Economy of Ukraine. – 1998. - No. 10.

Saati M.A. Modeling of complex systems. – M.: Nauka, 1993.

Sokolov N. GDP dynamics in the main groups of countries // Forecasting problems. – 1998. - No. 1.

Sutyagin V. On the relationship between scientific forecasts and state programs of socio-economic development // Problems of forecasting. – 1998. - No. 1.

Tsygichko V. Fundamentals of systems forecasting. – M.: Finance and Statistics, 1986.

Chernikov D. Macroeconomic theory // Russian Economic Journal. – 1995. - No. 9.

Yurchenko A. Modeling the socio-economic development of society // Bulletin of Moscow State University: Economics. – 1993. - No. 2.

Annex 1

Flow curve model in an open economy

Forecasting methodology – a set of working techniques that form the forecasting technology used by forecast developers.

Along with the methods given earlier, other methods are used in forecasting.

Forecasts of the country's economic development are developed in at least three time horizons: long-term - for seven to ten years, medium-term - for a period of three to five years, short-term - up to one year.

Long term forecast serves as the basis for developing a concept for the country's socio-economic development for the long term. To ensure the continuity of the ongoing economic policy, long-term forecast data are used in the development of medium-term forecasts, concepts and programs for the country's socio-economic development. Data from long-term and medium-term forecast calculations, as well as concepts of socio-economic development, are published in the open press.

Medium-term forecast socio-economic development of the country is developed for a period of three to five years with annual data adjustments. It serves as the basis for developing a concept for economic development in the medium term.

Short term forecast socio-economic development is developed annually and is the basis for drawing up the draft state budget.

The above documents are an integral part of the package submitted by the Government of the Russian Federation to the Federal Assembly. This package includes:

Results of the country's socio-economic development over the past period of the current year;

Forecast of socio-economic development for the coming year;

Project of consolidated financial balance on the territory of Russia;

A list of the main socio-economic problems (tasks) of development, the solution of which will be addressed by the policy of the Government of the Russian Federation;

List of federal target programs planned for financing in the coming year from the Federal Budget;

List and volume of supplies of products for government needs according to an enlarged range;

Data on the development of the public sector of the economy.

Along with this, the Government of the Russian Federation presents draft laws that it considers necessary to adopt to implement the intended tasks.

Forecasting methods vary depending on the level (macroeconomic forecast, sectoral, regional, etc.) and the object of forecasting. Methods of demographic forecasting, scientific and technical forecasting or natural resource forecasting have their own specifics.

Scientists estimate that there are over 150 different forecasting methods. No more than 15 methods are used as the main ones in practice. Let us consider forecasting methods in general, without noting their specifics in each area of ​​forecasting.

The basis of the forecasting methodology is: conducting an analytical study; database preparation; database quality; studying and combining information into a whole. The future becomes predictable in many respects if the current situation, factors and trends contributing to its change in the future are correctly and fully taken into account. Without these prerequisites, forecasting turns into probabilistic fortune telling.

The set of forecasting methods can be grouped according to various criteria: degree of formalization; general principle of operation; method of obtaining and processing information; directions and purpose of forecasting; the procedure for obtaining the parameters of a predictive model, etc. For example, according to the principle of processing information about an object, one can distinguish: statistical methods, methods of analogies.

Statistical methods combine methods for processing quantitative information on the principle of identifying mathematical relationships between the characteristics of an object in order to obtain predictive models.

The most common grouping of forecasting methods according to the degree of formalization, according to which all methods can be divided into intuitive and formalized. Let's look at these methods in more detail.

Intuitive (expert) forecasting methods.

Intuitive (expert) forecasting methods are used mainly in the following cases:

The forecasting object does not lend itself to mathematical description or formalization;

There is no sufficiently representative statistical sample that allows us to draw a conclusion;

It is impossible to take into account the influence of many factors due to the significant complexity of the forecast object;

Extreme situations have arisen when quick decisions are required.

Expert assessment methods

At interview method there is direct contact between the expert and the specialist, when analytical method A logical analysis of any predicted situation is carried out, and reports are compiled.

Sample survey method makes it possible to obtain extensive and timely information about the standard of living of various population groups. The results of sample surveys serve as the basis for characterizing various socio-economic processes, differentiating the population by income level, and identifying different types of regions. Using the method of sample surveys, re-employment of the population, the level of actual unemployment, etc. are determined.

Widely used in expert forecasting survey method. It is difficult to formulate survey questions - they can be either closed answer options or open (with unregulated answers). A representative sample is taken from the questionnaires, which allows, after processing them, to draw conclusions on the problem under study. It is also difficult to form a workable group of experts.

At script writing method the logic of a process or phenomenon over time under various conditions is determined. A scenario is a description of a possible sequence of events connecting the present and the future. The purpose of the scenario is to determine the strategic direction of events. Typically, a scenario is developed for strategic planning. For an objective forecast, it is necessary to have several scenarios for the development of events (optimistic, pessimistic and average). The middle scenario is the most likely or expected. The main advantages of the methods are the possibility of maximum use of the individual abilities of experts and the insignificance of psychological pressure.

Methods of collective expert assessments have the following varieties: the commission method, the Delphi method, the collective idea generation method “brainstorming”, the goal tree method, etc. The goal tree method allows you to break down the main forecasting task into subtasks (subgoals) and create a system of connections “weighted” according to expert assessments.

Formal forecasting methods

The main formalized methods include extrapolation methods and mathematical modeling methods.

Extrapolation consists in studying the stable trends in economic development that have developed in the past and present and transferring them to the future. In forecasting, extrapolation is used in the study of time series and is the finding of function values ​​outside the domain of its definition using information about the “behavior” of this function at some points belonging to the domain of its definition.

Mathematical modeling methods

Economic and mathematical modeling consists in constructing a model, meaning a measure, a sample. An economic model is a conventional image of the object of study of the socio-economic process. It is some similarity (adequacy) of the object under study. Economic and mathematical modeling allows you to simulate real economic processes. Modeling allows you to quantitatively reflect the relationship of a number of factors.

It is difficult to strictly classify economic and mathematical models used in forecasting; it is only possible, with a certain convention, to distinguish several groups:

Models of econometric type associated with the processing of statistical information of a retrospective nature;

Factorial economic and mathematical models.

They allow you to predict a particular economic value (dependent variable) based on the expected change in one or more factors (independent variables).

Factor models can describe the influence of one or a number of factors on the predicted value. Single-factor and multifactor models are used in forecasting.

A specific example of a multifactor model can be a model of production functions that reflect the dependence of the level of production (dependent variables) on the costs of various production resources (independent variables). The relationship between various types of resources and output volumes is expressed by equations. A multifactor model (production functions) can be built for an enterprise, industry, or national economy.

A developed form of economic and mathematical modeling is structural models, among which the leading place is occupied by the interindustry balance model. Another example is the consumption structure model.

Optimization (optimal) models represent a system of equations, equalities and inequalities, which, in addition to restrictions (conditions), also include a special kind of equation called a functional or optimality criterion. Using this criterion, a solution is found that is the best according to some indicator.

The optimality criterion quantitatively expresses the maximum measure of the economic effect of the decision made. This could be, for example, maximum profit, minimum labor costs, time to achieve a goal, etc.

Logic modeling methods are used primarily for a qualitative description of the development of the predicted object. They proceed from the general laws of economic development and have the goal of highlighting the most important long-term development problems and the main ways and sequence of their achievement.

The methods discussed make up only a small part of them. As a rule, a combination of methods is used in forecasting; for example, expert methods can rely on extrapolation.

From the above classification it is clear that a significant part of the methods is unformalized and is heuristic in nature.

In forecasting, two methodological approaches to economic objects are possible: genetic and teleological.

Genetic approach is based on an analysis of the previous development of the projected object, reflects stable growth trends, and on this basis conclusions are drawn regarding the state of the projected object in the future.

The genetic approach is implemented through a system of economic and mathematical models of econometric type. Models are built on the results of processing statistical information related to the past, as well as on estimates of individual variables and their parameters, which can be obtained by expert means and included in econometric models.

Teleological approach, it is also called normative (target) approach, reflects another aspect of the predicted processes, their controlled nature, dependence on the set development goals. The goal can be fixed through some normative state (for example, the level of goal achievement) and in the form of a desired trajectory of transition from the current state to the normative one. For example, the transition in consumption from a subsistence level to a rational consumer budget, a wealth budget, etc.

Genetic and regulatory approaches complement each other. If a goal is put forward that is in no way connected with the current patterns, then the ways to achieve it in the future cannot be outlined, which means that the forecast loses any scientific justification. If foresight reflects only established trends, then the possibility of assessing and controlling socio-economic processes to achieve given goals disappears.

10. Antimonopoly regulation

The system of antimonopoly regulation in the Russian Federation.

The system of state regulation of the economy, which has been formed in all industrialized countries, as a mandatory element provides for the creation of favorable conditions for the development of a competitive environment in the market of goods and services. Antimonopoly regulation is the most important component of state economic policy in all countries with developed market economies.

Antimonopoly regulation is a targeted government activity carried out on the basis and within the limits permitted by current legislation to establish and implement rules for conducting economic activity in commodity markets in order to protect fair competition and ensure the efficiency of market relations.

The development of antimonopoly regulation is very important for the development of the Russian economy, where the degree of market monopolization is higher than in states with a historically established market economy. The Russian economy inherited from the Soviet economy a high level of concentration of production in many sectors of the economy. In Russia, natural monopolies operating in the basic sectors of the economy - electric power and transport - also have great market power. Thus, RAO UES of Russia controls 98% of electricity consumers, RAO GAZPROM controls 94% of the domestic gas market, and the Ministry of Railways controls 77% of freight turnover.

Antimonopoly regulation, combined with support for domestic entrepreneurship and the organization of consumer protection, serve as one of the essential conditions for the successful socio-economic development of Russia.

Methods of antimonopoly regulation

Modern competition is regulated. The main task of regulating competition is to prevent firms from monopolizing the market.

Let's consider the main methods of antimonopoly regulation.

Ø Administrative (legislative) regulation. The main instrument of state antimonopoly policy is the state legal mechanism - antimonopoly legislation and the system of legislative, executive and judicial authorities. With the help of antimonopoly laws, the state carries out legal and administrative regulation of the activities of monopolies, creating conditions for the reproduction of competition.

Administrative (legislative) regulation of competition is based on countering unfair competition and monopolization of the economy by issuing legislative acts and monitoring their compliance by the state.

Ø Regulation of market access and control of market concentration. When determining a monopoly situation, product markets are usually identified that are difficult for new competitors to access. These are savings on large scales of production and sales (enterprises that have mastered large series of production and created distribution networks have cost advantages); patent-protected technological monopoly; control over raw materials and, in general, vertical integration of enterprises; the need to invest large capital to access the market, i.e. financial barriers; sustainable consumer choice (customers prefer the products of a particular company, and in order to compete with it, large advertising costs are needed). In many countries, the public administration responsible for enforcing antitrust laws constantly monitors markets that are difficult to access and calculates and publishes market concentration indices. Of course, quantitative indicators of concentration are rather conditional, since the connection between the size structure of the market (industry) and the behavior of enterprises - their prices, output, profitability - is not always direct. However, in some countries, laws set market share thresholds that determine supplier dominance. Each country has its own meanings.

Market concentration indices are used to regulate mergers of enterprises, regardless of how the mergers are carried out (through the purchase of shares, by mutual agreement or by transfer of management rights). Business mergers eliminate competition more severely than price and distribution agreements. At the same time, a merger is a way to realize economies of scale, which in principle cannot be prohibited, since the economic effect of large-scale production may be objectively necessary. However, it is believed that if, in the course of evolution, a company increases its capacity and gains positions in the market, then it undergoes strict market selection, but during a merger such selection does not occur.

Ø Methods of normative-orienting influence. Along with legislative antimonopoly regulation, in countries with market economies, methods of regulatory guidance are also used. These include:

Government orders;

Interest;

Government subsidies.

Using these levers, the state has the opportunity to influence the intensity of competition in different sectors and market segments.

The main feature of normatively oriented competition regulation is the stimulation of entrepreneurial activity of firms. For this purpose, competitive conditions are practiced in the state contract system, tax incentives and subsidies are applied for the development of priority areas of production, which are of particular importance for supporting new firms. Newly created companies are provided not only with financial and material support, but also with information and advisory assistance.

Carrying out normative-guiding regulation of business relations, the Government acts, first of all, as an instrument of state support for business, promoting the development of a market economy through increased competition.

Ø Antimonopoly control. To prevent and suppress monopolistic activities, the State Register of the Russian Federation of associations and monopolistic enterprises operating in commodity markets is maintained, which began to take shape in Russia in 1992. It includes business entities whose share exceeds 35% in the relevant market and which violate antimonopoly legislation. The level of monopolization in the planned economy was very high. During the process of denationalization it decreased. However, in recent years the number of monopoly enterprises in Russia has increased significantly.

Basic methods of regulating natural monopolies.

In almost all countries there are groups of industries exempted from antitrust laws. These are the so-called direct regulation industries, in which the state specifically establishes and protects the dominant position of producers, regardless of the form of ownership. They are also known as natural monopolies.

Natural monopoly is an enterprise or organization that produces products, the satisfaction of demand for which, due to the technological features of production, is effective in the absence of competition.

We are talking about those types of activities in which, due to technological and other conditions, there can be no competition. These are industries organized on the principle of a large-scale network economy with expensive equipment (such an economy cannot be duplicated on its territory); industries where the volume of demand is determined by technology (for example, the capacity of communication cables, the number of air frequencies); industries in which only large-scale production has low costs, and the products are used by almost everyone, and consumers should be protected from discrimination and from monopoly high prices. These are public sectors, which include electricity, gas, water supply, as well as railway, air and municipal transport, communications, radio broadcasting and television. Access to these industries is regulated by permits from the relevant administration, which is guided by the balance of supply and demand in a given area (in transport - along routes), so that the demand in the area (route) is fully covered and not too much exceeded.

This creates a territorial monopoly of the supplier, who must be large enough to provide economies of scale. Businesses in these industries cannot close (even temporarily) without permission from the government administration and are required to serve all customers without discrimination. They are charged with submitting capital investment plans for the development and capital repair of equipment to the executive authorities, as well as cost calculations for monopoly products, balance sheet valuation of property and financial statements, i.e. information that in other industries constitutes a trade secret of enterprises.

Tariffs for products (services) of this group of industries are regulated by the state, and in cases of sharp increases in costs (for example, when fuel prices for power plants increase), the state subsidizes tariffs from the budget.

The formation of Russian practice of regulating natural monopolies is generally in line with foreign experience.

The cardinal way to establish direct control over a natural monopoly is state ownership. Therefore, some sectors of natural monopolies served as priority targets for nationalization.

In other sectors of natural monopolies, non-state companies operate.

The main methods of regulation are: price regulation, i.e. direct determination of prices (tariffs) or setting their maximum level; identification of consumers for mandatory service and establishment of a minimum level of their provision in accordance with Russian legislation. Regulatory authorities are also charged with monitoring various types of activities of natural monopoly entities, including transactions for the acquisition of property rights, large investment projects, and the sale and rental of property.

State regulation of prices (tariffs) of natural monopoly industries includes regulation of tariffs for both electrical and thermal energy. Currently, serious changes are taking place in the system of tariff regulation of natural monopolies in Russia. The creation of a single tariff body, the reduction of cross-subsidies, and the transition to a targeted system of social benefits were proclaimed. At the same time, the state does not have a comprehensive long-term concept of price regulation of natural monopolies.

The concept of reform of natural monopolies from the point of view of price regulation should provide, first of all, for the introduction of new, interconnected tariffs on their products. To do this, it is necessary to substantiate the general model of the tariff system, adequate for the transitional conditions of the Russian economy.

The price regulation model should be based on such general principles of tariff regulation in natural monopoly industries as the principle of fair prices and the principle of indexing tariffs in accordance with rising price levels.

Improving price regulation of natural monopolies has a strong impact not only on the natural monopoly sector itself, but also on the economy as a whole. It is important to note that in Russia such regulation is not consistent with other methods of state regulation of natural monopolies. Decisions regarding prices for the services of natural monopolies are often the result of opportunistic political decisions that do not have sufficient economic justification.

A more promising and effective direction in the field of regulation of natural monopolies is their restructuring. Restructuring of natural monopoly industries involves creating conditions for the introduction of elements of competition in these industries, eliminating barriers to entry and entry into monopolized markets for other economic entities.

This method of regulation can be effective not only for individual monopolists, but, what is especially important, for the state as a whole, since it allows making transparent financial flows within various intermediary firms that divert financial flows bypassing both the company itself and the budget.

The influence of natural monopolies on the Russian economy .

Their influence can be both positive and negative.

Russia has not avoided the negative impact of industries - natural monopolies in market conditions - on production and the standard of living of the population.

With the general decline in production in Russia, the demand for products and services of natural monopoly industries, with the exception of communications industries, has been constantly declining. These industries are extremely capital intensive, with a significant portion of their costs being fixed. As a result, the share of fixed costs in the unit price of production increased. In addition, until recently, natural monopoly entities financed investments largely from internal sources (investment and stabilization funds formed from costs and profits), which determined the excessive burden on tariffs.

In almost all industries, cross-subsidization of some consumer groups at the expense of others remained. Low tariffs for the population and budgetary organizations were subsidized by industrial and commercial consumers. For example, in railway transport, losses on passenger transportation are covered by freight tariffs.

The rapid and significant increase in prices in the electric power industry, gas industry, communications and railway transport has necessitated raising the question of the validity of costs (wages, social benefits, investment activities) and the correspondence of the quality of products and services offered to the price level. In the industries of natural monopolies, wages exceeded the average for the economy and their workers enjoyed greater social benefits compared to other industries.

Considering the cost-generating nature of these industries, it is obvious that the rise in prices for the products they produce was a powerful factor in macroeconomic inflation, which is characterized by economists as cost-push inflation.

However, it cannot be stated unequivocally that industries that are natural monopolies have ensured their prosperity at the expense of the rest of the economy during the years of transition to the market. Price discrimination and catastrophic non-payments hit their own source the hardest.