At present, not a single sphere of social life can do without forecasts as a means of knowing the future. Of particular importance are forecasts of social economic development society, substantiation of the main directions economic policy, anticipation of the consequences of decisions. Socio-economic forecasting is one of the decisive scientific factors in the formation of the strategy and tactics of social development.
The relevance of this topic, both in the conditions of a developed market economy, and the transition economy is determined by the fact that the level of forecasting the processes of social development determines the effectiveness of planning and management of the economy and other areas.
This term paper is to consider the methodology and methods for developing socio-economic forecasts to determine the essence, areas of application and the most effective methods of forecasting. To do this, it is necessary to solve the following tasks: to determine the essence of the methods of socio-economic forecasting and the scope of their application in the course of studying the theoretical and methodological foundations of the forecasting methodology; to characterize the methods of socio-economic forecasting in economic developed countries and identify the features of their application in modern Ukraine.
In the process of writing this term paper, textbooks edited by V.O. Mosin, 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 relationships”, “Problems of Forecasting”, “Russian Economic Journal”, “Problems of Forecasting”, “Russian Economic Journal”, “Economics of Ukraine”, “Bulletin of Moscow State University”.
Socio-economic foresight of the main directions of social development involves the use of special computational and logical techniques that allow you to determine the parameters of the functioning of individual elements productive forces in their relationship and interdependence. Systematized scientifically substantiated 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 methods 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. Aganbegyan, I.V. Bestuzhev-Lada, L. Klein, V. Goldberg. In the works of these scientists, the significance, essence and functions of forecasting, its role and place in the planning system are considered, questions of the methodology and organization of economic forecasting are examined, and features of scientific forecasting are shown. The development of works covering forecasting issues is carried out in the following main areas: deepening the theoretical and applied developments of several groups of methods that meet the requirements of different objects and different types works on forecasting; development and implementation in practice of special methods and procedures for using various methodological techniques in the course of a specific predictive study; search for ways and methods of algorithmization of forecasting methods and their implementation 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 object of forecasting, 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, at present there are more than 20 forecasting methods, but the number of basic ones is much less (15-20). Many of these methods are rather individual techniques and procedures that take into account the nuances of the forecasting 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.
The existing sources present various classification principles of 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 is general principle the action of forecasting methods, the third - a method of obtaining forecast information. On fig. 1.1 the classification scheme of forecasting methods is presented.
As the diagram shown 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 forecasting object. In this case, expert estimates are used. At the same time, individual and collective expert assessments are distinguished.
The composition of individual expert assessments includes: the “interview” method, in which direct contact is made between an expert and a specialist according to the “question-answer” scheme; an analytical method, in which a logical analysis of any predictable situation is carried out, analytical memorandums are compiled; a method of writing a script, which is based on determining the logic of a process or phenomenon in time under various conditions.
The methods of collective expert assessments include the method of "commissions", "collective generation of ideas" ("brainstorming"), the "Delphi" method, 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. To the second - structural, network and matrix modeling.
The considered classes of intuitive and formalized methods are similar in composition to expert and factographic methods. Factographic methods are based on actually available information about the object of forecasting and its past development, expert methods are based on information obtained from the assessments of expert experts.
The class of expert forecasting methods includes the method of heuristic forecasting (heuristics is a science that studies productively creative thinking). This is an analytical method, the essence of which is to build and then truncate the "search tree" of expert evaluation using some kind of heuristic. With this method, specialized processing of predictive expert assessments obtained by 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 the principles of classification, which include: sufficient coverage of forecasting methods, unity of the classification feature 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 supplementing with new methods) .
In most classification schemes, forecasting methods are divided into three main classes: extrapolation methods, expert assessments, and modeling methods. With such a division, extrapolation methods are opposed as an independent class of modeling methods.
On the one hand, the construction of models aims to reveal the pattern of development of the object or process under study in some retrospective area. And if the model is built correctly and adequately reflects the connections and properties of a real object, it can serve as a basis for extrapolation, i.e., for transferring some conclusions about the behavior of the model to the object. This is the prediction of the object's behavior by extrapolating the 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 historical region of observations according to the dependences between them in the historical region. Thus, the use of extrapolation in forecasting always involves the use of some models. Therefore, any simulation is the basis for extrapolation.
Constructive classification makes it possible to visualize the 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 on the basis of "information basis of the method" are divided into three classes: factual, combined and expert.
Tagiev M.Kh.
Forms and methods of regulation of socio-economic development of regions: current practice and development prospects
In modern economic conditions, there is a fairly wide classification of forms and methods state regulation socio-economic development of regions.
Considering control systems regional structures, it is necessary to pay attention to the management of the socio-economic development of the regions. As you know, socio-economic development includes the following components:
Growth of production, incomes and, as a result, an increase in the welfare of the population;
Significant shifts in the social, institutional, administrative structures of society;
Changes in public consciousness;
Changes in traditions and habits;
Raising 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 needed.
As is known, under a planned economy, the complex of methods for managing the development of Russian regions was limited mainly to administrative methods, i.e. administrative instructions actually carried out the redistribution of resources between the regions, as a result of which a relatively uniform level of resources was achieved.
But in the transition to market relations, naturally, such a set of methods is not entirely suitable for solving such problems. In a vast arsenal modern instruments state regulation of the region's economy can be identified a number of forms and methods. 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 setting of exorbitantly high prices.
Tax and credit forms of regulation are the use of taxes and credits in order to influence the national output. changing tax rates, government benefits affect the contraction or expansion of production, on investment decisions. By varying the terms of lending, the state affects the decrease or increase in production volumes. By selling securities, it reduces bank reserves, while increasing
stagger interest rates and, consequently, production is reduced, and vice versa. By buying securities, the state increases bank reserves, while interest rates fall and production expands.
The subvention form of regulation involves the provision of state subsidies and tax incentives individual industries, enterprises (mainly such industries as agriculture, mining, shipbuilding, transport).
Among the methods of state regulation can be distinguished: administrative and legal regulation, direct and indirect regulation.
Administrative methods include a variety of measures for rationalization and quotas, licensing and quotas, control over prices, incomes, exchange rates, discount percentage, 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 industrial infrastructure, stimulating the inflow of private investment, providing a number of tax and credit benefits, selective subsidies for enterprises that provide minimum employment, supplementing transfers, etc. But the main direction, the main path is the self-development of regions on based on the use of their own socio-economic potential.
Direct regulation implies the management of development through budgetary policy, direct financing, investment in certain regions or industries to curb the decline or increase the pace of development. This is one of the methods of address 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 federal budget railways, highways, scientific, educational and medical centers, etc. The state should also finance projects that have a strong positive impact on employment growth, increase tax base, 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" financing principle). Federal address investment program, included in the structure of the federal budget for 2003, contains hundreds of candy objects and provides for the allocation of 23.8 billion rubles for investments, including production complexes- 7.0 billion rubles, for the social complex - 16.8 billion rubles.
The state should provide selective support to existing enterprises in the form of subsidies for their products. First of all, this
applies to businesses public sector. From the point of view of regional economic policy, it is important where such enterprises are located, in what regional situation. Financial support is especially appropriate when it prevents the larger economic and social costs in 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 the load production capacity, employment and income in different regions, realizing certain tasks of regional economic policy. In the context of an economic downturn, it is especially important to provide orders to city-forming enterprises in order to reduce unemployment and other negative socio-economic consequences. The placement of government orders can stimulate economic recovery in the respective regions and cities.
Organizational, legal, informational support of the regions in special areas of activity. The most important is this kind of support for the regions in those types of activities where the capabilities and competence of regional authorities are limited or insufficient. First of all, it is foreign economic activity. The state should assist the regions in establishing contacts with foreign trade partners and foreign investors, in obtaining international credits and loans, in distributing regional securities on the world financial markets, and in including them 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 Russian Federation; it also acts as a guarantor of the return of loans and the completion of projects.
The above measures taken by the state in modern conditions are mostly direct. 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 areas of activity that affect the course of development, is sharply increasing. regional economy in Russia.
Based on the foregoing, we can say that there is a set of general methods and forms of regulation of the development of regions, by 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 in the territory, between 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 expediency, and be formed on the territory not spontaneously, as is currently the case, but strictly in accordance with their compatibility and consistency. For each type of area tre-
We are trying to substantiate economically compatible sets of economic regulators and benefits, highlighting in them a block dedicated to supporting certain types of entrepreneurial activity.
The mechanism of 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 areas of its regional economic and social policy.
In modern domestic and foreign economic literature, there are four blocks of territorially oriented economic regulators that have an impact on the real process of regional development: social, economic, environmental and interethnic.
In the social sphere, these are:
A mechanism for facilitating the employment of demobilized military personnel, migrants, refugees from neighboring countries and regions of military conflicts, persons leaving the Far North and equivalent areas;
Formation social funds national revival of small peoples and ethnic groups;
Allocation of financial assistance to poor categories of the population from the fund of social support of the population in specific regions;
Change of regional coefficients to wages in problem regions.
AT economic sphere:
For old industrial areas:
Exemption from taxation of part of the profits allocated for the technical re-equipment and reconstruction of enterprises, the conversion of military production and R&D;
Introduction of a preferential system of depreciation;
Subsidizing the costs of retraining workers released as a result of the rationalization of production, re-profiling of enterprises and declaring some of them bankrupt;
Providing tax incentives and insurance guarantees to foreign investors contributing to major structural and technological changes;
Allocation of concessional 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 (depressive) regions:
Allocation of state domestic and foreign investments and subventions within the framework of federal and regional programs;
Use of funds from special budgetary and extrabudgetary regional funds;
Use of preferential regional norms of tax deductions (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 regions:
Reduction or cancellation of customs duties, export-import control over goods entering the zone and re-exported from it (in free trade transit zones);
Introduction of a preferential trade and customs regime, preferential financing and taxation, stimulation of foreign investment in the production sector (in export industrial zones);
Provision of tax, registration benefits and information services for domestic and foreign firms, a special insurance regime and banking operations, preferential taxation for certain types of income and special conditions lending (in banking and insurance zones);
Support for innovative firms through insurance of commercial loans, promotion of domestic developments to the foreign market by lowering the taxation of profits, indexation of depreciation and other measures to influence economic situation(in technological zones);
For regions in an extreme situation:
Granting the right to enterprises to freely sell a certain share of products (oil, gas, gold, diamonds) on the world market;
Increase in the share of foreign exchange earnings left in the regions (Dagestan, Kabardino-Balkaria, etc.);
Use of special regional funds and federal programs regional development;
Political risk guarantee mechanism in the form of collateral in unstable areas;
Sanctions against districts that have stopped transferring funds to the republican budget of the Russian Federation (stopping financing of all federal spending on the territory, stopping customs clearance of all foreign trade cargo, revoking previously issued quotas and licenses for the export of strategic raw materials, stopping the issuance of centralized loans) will have a negative impact on economic activity in the regions.
In the environmental field:
The introduction of territorially differentiated payments for the use of land in urban and countryside, resort areas;
Implementation state program land monitoring, the creation of a multi-level forecast system for the elimination of negative environmental processes (fi-
funding from the federal budget and funds from the collection of land fees);
Granting the pre-emptive right to conclude contracts and obtain licenses for the use of renewable natural resources tribal communities, families of individual representatives of the small peoples of the North in their places of traditional residence;
Creation special regime living in areas of ecological disaster;
Introduction of preferential conditions for the privatization of environmental facilities;
In the field of national and interethnic relations:
Provision of concessional lending and the possibility of acquiring housing for "repressed peoples" and migrants due to interethnic conflicts;
Reduction of interest rates for loans aimed at enhancing the development of farms, employment of migrants, refugees from areas of military conflicts, neighboring countries and those who suffered during the period of repression;
Assistance free privatization objects and territories of traditional forms of economic management of small peoples.
The above system of territorially oriented methods of regulating the economic development of the country's regions 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 particular region, a thorough multifaceted study and identification of its features is necessary.
In addition to the above methods, in modern conditions, the increasing popularity and applicability in the domestic economic practice receive program-targeted methods of state regulation of territorial development.
The use of program-target 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.
The solution of 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 the 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 public authorities in solving one or another important task of its regulation.
Thus, the above set of methods and forms of regulation of the socio-economic development of the region includes a large number of specific activities and ways to solve certain problems in the process of management
development of the region. At present, in our opinion, it is necessary to study all the factors influencing the efficiency of using each of them in order to create and develop an effective mechanism for regulating regional development.
Alikberli M.M., Gadzhiev M.M., Naurkhanov Kh.Ya.
The Place and Role of Investments in the Simplest Models of Economic Growth
Efficient development industrial complex involves a systematic increase in the technical and technological level of the enterprise, as a result of the requirements generated by both the internal environment and the external one. Striving for leadership, enterprises introduce new technologies and equipment, improve the 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 streamlined mechanism for financing capital investments. Development financial market significantly expands and diversifies sources of funds: along with domestic investment, 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 the technical and economic potential lead to increased efficiency capital investments. But, the higher the return on invested capital, the greater the ability of enterprises to radically re-equip, intensify processes and, as a result, achieve diversification goals.
Any business can be imagined as an interconnected system of movement financial resources caused by managerial decisions. It follows from this that since entrepreneurial activity is based on the advance of capital by investing and reinvesting it at all stages of the life cycle of an enterprise, insofar as the efficiency of enterprises is associated with the management, evaluation and analysis of the effectiveness of investments.
The construction of most models of economic growth is based on the allocation of economic environment individual factors and determining the degree of their influence on the results of the functioning of the economy. Despite the generalization and simplification of economic models, they make it possible to determine the main trends in the dynamics of economic development, highlight the key factors influencing these dynamics, and also assess the nature of the impact of these factors.
It seems appropriate to consider the main models of economic growth.
Forecasting, on the one hand, precedes planning, and on the other hand, it is widely used in the process of drawing up and implementing plans.
The forecasting process can be divided into three main stages:
research, analysis of an object, process; establishing the main trends, patterns of its development; selection of the most appropriate forecasting methods;
substantiation of predictive decisions - the development of alternative scenarios for the development of events, the adoption of organizational decisions;
assessment of the probable course of economic events, tracking the forecast object, adjusting forecast decisions.
Each stage of forecasting is characterized by its goals, objectives and methods. At the same time, the methods of economic and social forecasting should be understood as a set of techniques and ways of thinking that allow, based on the analysis of retrospective data, external and internal relations of the object of forecasting, as well as their measurements within the framework of the phenomenon or process under consideration, to derive judgments of a certain reliability regarding the future development of the object.
Currently, according to various estimates, there are over 160 different forecasting methods. However, in practice, only about 15-20 are used as the main ones. The classification of forecasting methods is shown in Fig.1.
According to the degree of formalization, 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 forecasting object. In this case, expert estimates are used. At the same time, they distinguish individual and collective expert assessments.
The composition of individual expert assessments includes: the "interview" method, the analytical method, the script writing method and the idea generation method. The interview method is based on that with it the direct contact of the expert with the specialist is carried out according to the "question - answer" scheme. The analytical method carries out a logical analysis of any predictable situation, analytical reports are compiled. The scenario writing method is based on determining the logic of a process or phenomenon in time under various conditions.
The methods of collective expert assessments include the method of "commissions", "collective generation of ideas" ("brainstorming"), the "Delphi" method. matrix method. This group of methods is based on 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.
Rice. 1. Classification of forecasting methods
The class of expert forecasting methods makes extensive use of heuristic forecasting methods (heuristics is a science that studies productive, creative thinking). The essence of such methods lies in the construction and subsequent truncation of the "search tree" of expert evaluation using some kind of heuristic. With this method, specialized processing of predictive expert assessments obtained by a systematic survey of highly qualified specialists is carried out. It is used to develop forecasts for objects whose development analysis either completely or partially cannot be formalized.
The group of formalized methods includes two subgroups: extrapolation and modeling. The first subgroup includes methods: least squares, exponential smoothing, moving averages. To the second - structural, economic-mathematical, statistical, matrix and simulation modeling.
Methods of predictive extrapolation.
Extrapolation techniques are one of the most common and most comical resources and accumulated potential.
planning methods.
The essence of planning should be considered from two sides - subjective and objective. The activity of the subject of planning is strongly reflected in the quality side of the plan, its indicators. The objective side involves the maximum consideration of the totality of factors of objective economic laws, that is, planning cannot arise (or be canceled) at the will of individual people, since it represents a recognized objective necessity.
balance method
The most important planning method is balance method. Balance is an equation of equality, balance of two sides. Usually the balance has the form of a table, consisting of two equal sets.
All private economic balance sheets are divided into three groups: material, cost and labor.
Material balances serve to establish material material proportions at the level of an enterprise, municipality, region, country. Such balances are developed in appropriate physical units.
Cost balances include economic indicators in monetary terms. Consolidated territorial balance of financial resources, the budget of the territory, the balance of cash income and expenditures of the population - try it on! value balances.
Labor balances reflect the availability and distribution of labor force, labor resources.
The essence of the balance method is the development of planned balances that allow linking the values of the planned indicative and available own and attracted resources, determine the need for resources to achieve the required level of socio-economic development.
Program-target method.
Program target the method is used to develop targeted programs. It is based on the choice of a realistically set goal for the operation of an object and the development of several options for interconnected economic and social development programs for it.
This method involves a variety of goals: scientific, technical, organizational and economic. environmental, etc. In the planning process itself, all these goals intersect. are in certain relationships and relationships. As a result, it becomes necessary to compare the prepared programs taking into account different goals, i.e. hold a contest of goals.
In the development of the program, an integrated approach is used, which is conditioned. on the one hand, the principle of continuity, and on the other hand, its foundation in the future on a system of economic and mathematical models. In turn, the developed planning systems should be based on the principle of stage-by-stage modeling, which involves the use of the results of solving problems of the previous stage at the next stages. At the same time, difficulties arise with the definition of the primary and secondary stages. Sometimes. after solving such problems, it is necessary to check for methodological unity, i.e. analysis of the results of decisions from particular to general and from general to particular. In this way. the program-target method has two approaches: target and complex.
The target approach determines the development of hierarchically interconnected development goals, the allocation of leading goals and subgoals, the determination of the priority of goals and their implementation in time.
A complex approach involves linking technical, technological, organizational and other factors. Programs are an indispensable document of long-term and medium-term socio-economic policy, an important tool for regulating and managing the socio-economic development of the state, region, municipality.
Normative method
Normative the method is based on the regulatory framework for planning, which includes a set of norms and standards.
The norm is a scientifically substantiated measure of the limiting value of a technical and economic indicator. The following norms are distinguished: costs of material resources, natural attrition, costs of labor and wages, personal consumption, etc.
Unlike the rules under regulations understand the regulated, generalized values of the cost of working time, material and monetary resources. They are established analytically or by calculation on enlarged meters (for example, per unit of production).
In planning social development norms for the provision of housing per person, standards for the provision of education, health care, trade, consumer services, standards for the development of the road network, etc. are used.
Calculation-constructive and economic-mathematical methods
At the core variant, or design and construction, method lies in the development of various options for technical and economic coefficients, material and monetary costs. balance linking industries and elements of production.
As in forecasting, expert methods, extrapolation methods, the entire system of economic and mathematical methods and mathematical theories, methods and models of optimal planning are increasingly being used in program planning.
It should be noted that the advantage of optimal planning is quite well proven. At the same time, the used economic and mathematical models cannot yet capture social and psychological reactions. To a certain extent, this is possible only in multivariant productions. But for plans calculated using conventional methods, such a problem cannot be posed at all. These aspects of planning in both cases can be provided by the experience and knowledge of specialists.
We can talk about the advantages of optimal planning when exactly the same initial and normative information is taken, since imperfect information can lead to significant errors.
Specific methods of economic forecasting are classified according to the following criteria:
According to the degree of formalization, i.e. the study of any content area of knowledge in the form of a formal system associated with the strengthening of the role of formal logic and the use of mathematical methods of scientific research, methods of economic forecasting 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 forecasting object. In this case, expert estimates are used. At the same time, individual and collective expert assessments are distinguished, which are united by a common principle of action.
The composition of individual expert assessments includes: the “interview” method, the analytical method, the method of writing scenarios, building a “tree of goals”. When distinguishing between these methods, the third feature of the classification method is used - a method for obtaining predictive information. The methods of collective expert assessments include the methods of "commissions", "collective generation of ideas" (brainstorming), "Delphi", the matrix method, etc.
The group of formalized methods includes two subgroups: extrapolation and modeling. The first subgroup includes methods of least squares, exponential smoothing, moving averages, etc. The second subgroup includes methods of mathematical modeling, regression and correlation analysis, etc.
In addition, normative and balance methods are widely used in the process of economic forecasting. A special place in the classification of economic forecasting methods is occupied by combined methods that combine various methods. For example, collective expert judgments and modeling methods or statistical methods and survey of experts.
Intuitive forecasting methods:
Methods of individual expert assessments.
Interview Method allows for direct contact between an expert and a specialist according to the “question-answer” scheme, during which the forecaster, in accordance with a pre-developed program, puts questions to the expert regarding the prospects for the development of the predicted object.
Analytical method allows you to carry out a logical analysis of any predictable situation and present it in the form of an analytical note. It involves the independent work of an expert on the analysis of trends, assessment of the state and development paths of the predicted object.
Script writing method is based on determining the logic of the development of a process or phenomenon in time under various conditions. The main purpose of the scenario is to determine the general goal of the development of the predicted object, phenomenon and the formulation of criteria for evaluating the upper levels of the “goal tree”. A scenario is a picture showing a consistent detailed solution of a problem, identification of possible obstacles, detection of serious shortcomings in order to resolve the issue of a possible termination of the work begun or the completion of ongoing work on the predicted object.
Target tree method used in the analysis of systems, objects, processes, in which several structural or hierarchical levels can be distinguished. The "tree of goals" is built by sequentially highlighting smaller and smaller components at lower levels.
The branching point is called a vertex. At least two branches must emanate from each vertex, and the number of these branches is not limited from above, that is, there can be three, five or more of them at the upper level.
In building a “goal tree”, three conditions must be noted:
branches emanating from one vertex must form a closed set;
branches coming from the same vertex must be mutually exclusive, that is, there should not be a partial coincidence of objects represented by two different branches coming from the same vertex;
The “goal tree” used in normative forecasting should be considered as a set of goals and sub-goals.
Methods of collective expert assessments.
Method of "commissions" consists in determining the consistency of the opinions of experts on the promising directions for the development of the object of forecasting, previously formulated by individual specialists. This means that the development of this object cannot be determined by other methods. The content of this method is as follows:
the creation of working groups to ensure the preparation and conduct of the survey, the processing of materials and the analysis of the results of the expert assessment;
clarification of the main directions of development of the object, determination of the general goal, sub-goals and means to achieve them;
development of questions for experts, ensuring unambiguous understanding of certain issues by experts, as well as the independence of their judgments;
appointment of a group of experts to develop a forecast;
conducting a survey and processing materials;
determining the final score of the survey, which is displayed either as an average judgment, or as an arithmetic mean, or as a weighted average of the score.
Delphi method consists in organizing a systematic collection of expert assessments, their mathematical and statistical processing and consistent adjustment by experts of their assessments based on the results of each processing cycle. Its main features are: anonymity of experts; multi-round procedure for questioning experts through their questioning; providing experts with information, including its exchange between experts, after each round of the survey, while maintaining the anonymity of the assessments; substantiation of the experts' answers at the request of the organizers. The method is designed to obtain relatively reliable information in situations of its acute insufficiency, for example, in problems of long-term scientific and technical complex forecasting.
The method of “collective generation of ideas” it is expedient for determining possible options for the development of the forecasting object and obtaining productive results in a short time by involving all experts in an active creative process. The essence of this method is to mobilize the creative potential of experts during brainstorming and generate ideas with subsequent destruction (destruction, criticism) of these ideas and the formulation of counter-ideas.
Formalized forecasting methods.
These methods are based on mathematical theory, which provides an increase in the reliability and accuracy of forecasts, significantly reduces the time for their implementation, and allows for information processing and evaluation of results.
extrapolation method consists in applying the development trend defined for the base period economic process to the forecast period, it is based on the preservation in the future of the prevailing conditions for the development of the process. When using this method, it is necessary to have information about the stability of the development trends of the object for a period that is 2-3 times longer than the forecast period. Long term trend economic indicators called a trend. Extrapolation sequence:
a clear definition of the problem, hypotheses about the possible development of the predicted object, consideration of factors that stimulate or hinder the development of this object, determine the necessary extrapolation and its allowable range;
selection of a system of parameters, unification of various units of measurement related to each parameter separately;
collection and systematization of data, verification of their homogeneity and comparability;
identification of trends or symptoms of changes in the studied quantities during statistical analysis and direct extrapolation of data.
The extrapolation operation in general form can be represented as a function value definition:
Уi + L = F (Уi L),
where Ui + L - extrapolated level value;
L - lead time;
Ui is the level taken as the extrapolation base.
The extrapolation method gives reliable results for the short term forecasting of certain objects - 5 - 7 years.
When extrapolating, methods are used: least squares and its modifications; exponential smoothing, moving average, etc.
Modeling methods.
Modeling is considered to be a fairly effective means of forecasting.
The word "model" comes from lat. "modulus" (measure, sample).
In science, the term “model” means some conditional image of the object of study, and in forecasting economic or social processes.
constructing a model based on a preliminary study of the object;
highlighting the essential characteristics of the object;
experimental and theoretical analysis of the model;
comparison of simulation results with the actual data of the object;
correction or refinement of the model.
Economic and mathematical modeling is based on the principle of analogy, that is, the possibility of studying an object through the consideration of another object similar to it and more accessible. Such a more accessible object is the economic-mathematical model. It is a system of formalized equations that describe the basic interconnections of the elements that form an economic system or any economic process.
This model makes it possible to bring the process of obtaining and processing initial information to a complete and exhaustive description, as well as to solve the problems under consideration in a fairly wide class of specific cases.
Normative method applied on the basis of the calculation of predictive indicators. Norms and standards are developed in advance on a legislative or departmental basis. Norm is the maximum allowable value. The standard is the ratio of the elements of the production process (a component of the norm).
Norms and standards are divided into resource, economic and social. If necessary, they are concretized and differentiated by individual areas, objects, regions. For example, the following standards are used: social development - per capita consumption, subsistence level, living space, etc.
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Introduction
Forecasting is central to decision-making procedures. Forecasting is a forward-looking idea of reality. It is a kind of human intellectual activity, one of the functions of human consciousness. The main reason why a person engages in forecasting is that there are phenomena whose future he does not know, but this future is important for the decisions he makes now. Therefore, a person strives to mentally penetrate into this future. The future situation is more or less uncertain. And it is natural for a person to strive to reduce the level of this uncertainty.
Forecasting should precede the definition of goals, not only methodologically, but also in the organization of the management process. Science-based forecasting is now extremely important not only on the scale of the entire economy, but also for each enterprise.
Socio-economic foresight of the main directions of social development involves the use of special computational and logical techniques that allow determining the parameters of the functioning of individual elements of the productive forces in their interconnection and interdependence. Systematized scientifically substantiated forecasting of the development of socio-economic processes on the basis of specialized ones is carried out from the 1st floor. 1950s, although some forecasting techniques were known earlier.
In the development of the methodology for forecasting socio-economic processes, the scientific developments of domestic and foreign scientists A.G. Aganbegyan, I.V. Bestuzhev-Lada, L. Klein, V. Goldberg. In the works of these scientists, the significance, essence and functions of forecasting, its role and place in the planning system are considered, questions of the methodology and organization of economic forecasting are examined, and features of scientific forecasting are shown. The development of works covering forecasting issues is carried out in the following main areas: deepening the theoretical and applied development of several groups of methods 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 predictive study; search for ways and methods of algorithmization of forecasting methods and their implementation using computer technology.
The purpose of this work is to study the methods of socio-economic forecasting.
To achieve this goal, it is necessary to solve the following tasks of the work:
1) reveal the concept and essence of methods of socio-economic forecasting;
2) identify the types of methods of socio-economic forecasting;
3) analyze the application of methods of socio-economic forecasting in practice (on the example of the application of one of the methods in a particular study).
The object of research is a set of methods of socio-economic forecasting.
The subject of the study is the process of applying the methods of socio-economic forecasting.
The research methodology was based on the principles of management theory. The work used scientific works in the field of organization theory, enterprise management, information and communication management, and other branches of knowledge.
Structurally, the work consists of an introduction, in which the relevance of the study is substantiated, its purpose and objectives are outlined; two chapters of the main part, divided into paragraphs, in which the above tasks of the work are sequentially solved; conclusion, which summarizes the results of the study and outlines some possible directions for further development of the topic. The work ends with a bibliographic list and an appendix.
Chapter 1. The essence of methods of socio-economic forecasting
A forecast is understood as a scientifically based judgment about the possible states of an object in the future, about alternative ways and terms for achieving them. The process of developing forecasts is called forecasting. Forecasting is a special scientific study of processes, phenomena, as a result of which, from already known information about the past and present of the object under study, they get an idea of its possible future state. Each forecast is developed with the aim of accelerating the development of the organization in the desired direction and avoiding undesirable results. “Forecast as new knowledge includes, on the one hand, knowledge about the properties of objects that actually exist, observed or unobserved during the forecasting period, and on the other hand, knowledge about the properties of objects that do not actually exist during the forecasting period” 1 Basovsky L.E. . Forecasting and planning in the market Uch. settlement - M.: Finance and statistics, 2002. - S. 9. . The forecast creates an ideal image, model, description of probable processes, events. In the scientific literature, there are several approaches to explaining the essence of forecasting. The point of view of I.V. Bestuzhev-Lada, who proceeds from the fact that the forecast does not provide for solving the problems of the future. Its task is different: to promote the scientific substantiation of plans and decisions. Forecasting presumably characterizes a possible set of necessary ways and means of implementing the planned action program Bestuzhev-Lada I.V. Search social forecasting: Perspective problems of society (Experience of systematization). - M.: Delo, 1994. - S. 126. .
Elucidation of the essence of forecasting is inextricably linked, as noted in the literature, with the need to “develop a specifically prognostic system of concepts”, including “the correct definition of the concept of“ forecast ”and delimiting it from such concepts as foresight, prediction, plan, program, project, expectation , assumption, hypothesis” Zhukovsky O.I. Information Technology. - Tomsk: TSU, 2003. - S. 29. .
Forecasting does not have a directive character. In other words, the qualitative difference between a variant forecast and a specific plan is that the forecast provides information to justify the decision and choose planning methods. It indicates the possibility of one or another development path in the future, and the plan expresses the decision on which of the possibilities the society will implement.
The general logical sequence of the most important operations for developing a forecast is reduced to the following main stages: pre-forecast orientation (research program and specification of the task for the forecast); building the initial (basic) model of the predicted object using the methods of system analysis; collection of forecast background data (for example, economic development, social tension in society, people's well-being, etc.); building a series of preliminary search models using search analysis methods; building a series of normative models; assessment of the reliability and accuracy of the forecast; development of recommendations for decision-making; analysis of the prepared forecast.
The purpose of forecasting is to create scientific prerequisites, including scientific analysis of economic development trends; variant prediction of the forthcoming development of social reproduction, taking into account both the prevailing trends and the intended goals; assessment of the possible consequences of the decisions made; substantiation of the directions of socio-economic and scientific and technological development for making management decisions Comprehensive assessment of the effectiveness of measures aimed at accelerating scientific and technological progress: Guidelines and commentary on their application. - M.: Informelectro, 1989. - S. 56. .
The principle of systematic forecasting involves the study of quantitative and qualitative patterns in economic systems, the construction of such a logical chain of research, according to which the process of developing and justifying any decision is based on determining the overall goal of the system and subordinating the activity of all its subsystems to achieve this goal. "Wherein this system considered as part of a larger system, also consisting of a certain number of subsystems. economic dictionary/ Ed. A.N. Azrilyana. - 2nd ed., revised. and additional - M.: In-t new economy, 1997. - S. 816. .
For example, it is required to develop a strategy for the development of a large commercial enterprise. For this, a forecast of the activity of both this enterprise and its competitors is carried out. At the first stage of forecasting the development of the trading network, the available capacities and the existing provision of consumers with retail space are taken into account. Both the currently existing data and the forecast of the number of consumers for the period for which the strategy is required are taken into account. The planned volume of trade, trends in the structure of the city's population and consumer contingents, and the introduction of progressive forms of service are taken into account. Naturally, taking into account such a large number of factors most often leads to the choice of extrapolation volumes of trade for the forecast period.
The process of coordinating the consumer interests of the population and the interests of producers and sellers is organized as a process of forming reference vectors for the development of industries. Let's explain this. With the help of system analysis and one of its practical applications - the normative system of indicators of efficiency and quality economic activity- expert assessments of the ratio of the movement of indicators of the enterprise's activity in terms of growth rates (for a year, for five years) are developed, which makes it possible to streamline (rank) them and interpret the resulting ranking as one of the economic development strategies of the enterprise, in particular, one that could reorient industry in the most favorable direction for consumers.
The construction of a normative system of indicators of quality and efficiency - in other words, a reference vector for the development of an enterprise - is based on current statistics. The normative system of indicators is a qualitatively new procedure for processing known data, since the reference vector of enterprise development reflects, according to the criterion of a variety of products and services of an enterprise in the social sense, the best implementation of enterprise functions.
The assessment of the achievability of the proposed reference vector of enterprise development is carried out according to the indicators of rank correlation of deviations and inversions of the actual order of movement of indicators from the reference indicator. Of course, in order to eliminate the backlog of the enterprise's operating mode from the reference one, i.e. in order to build a reference vector of enterprise development (it must also meet the criteria of diversity, accessibility, significance and acceptability) and thus describe the economic development strategy of an enterprise, it is necessary to repeatedly build an intermediate vector Gaidaenko T.A. Marketing management. Complete MBA course. Principles of management decisions and Russian practice. - M.: Eksmo, 2005. - S. 390. .
The problem of implementing intermediate vectors is primarily related to the practice of forecasting and planning the structure of trade. For example, volumes of food and non-food products and the most important types of these products are planned. If in the planning procedure in without fail Since the volumes of trade associated with the forms of service will also be introduced (for example, the volume of trade for orders), this will cause a different policy for the introduction of retail space, changes in the number of stores and the number of employees in the enterprise. In this case, with the help of intermediate vectors, it will be possible to calculate various combinations of changes in the growth rates of indicators and their relationship with other indicators. Intermediate vectors will become elements of preplanned developments A.I. Koptelov. Methods for improving the sales process // Financial newspaper. - 2008. - No. 51. - S. 11-12. .
The principle of the adequacy of the forecast to objective regularities characterizes not only the process of identifying, but also the assessment of stable trends and relationships in the development of the economy and the creation of a theoretical analogue of real economic processes with their complete and accurate imitation. The implementation of the principle of adequacy involves taking into account the probabilistic, stochastic nature of real processes. This means the need to assess both the prevailing deviations and those that may occur, as well as the prevailing trends; determination of the possible area of their divergence, i.e. assessment of the probability of realization of the identified trend.
The principle of alternative forecasting is associated with the possibility of developing an enterprise and its individual links along different trajectories, with different relationships and structural relationships. In the transition from imitation of existing processes and trends to foreseeing their future development, it becomes necessary to build alternatives, i.e. determining one of two or more possible, and often opposite, mutually exclusive ways of developing the economy.
The main functions of forecasting are: scientific analysis of economic, social, scientific and technical processes and trends; study of objective links between socio-economic phenomena in the development of the economy under specific conditions in a certain period; assessment of the forecasting object; identification of objective alternatives for economic and social development; accumulation of scientific material for a reasonable choice of certain solutions Svetunkov S.G. Quantitative methods for forecasting the evolutionary components of economic dynamics. - Ulyanovsk: Publishing house of UlGU, 1999. - S. 21. . Let's take a look at some of the features in more detail.
Scientific analysis is carried out in three stages, or stages: retrospection, diagnosis, prospection. Retrospection is understood as the stage of forecasting, at which the history of the development of the object of forecasting is studied in order to obtain its systematic description. At the stage of retrospection, there is a collection, storage and processing of information, sources necessary for forecasting, optimization of both the composition of sources and methods for measuring and providing retrospective information, clarification and final formation of the structure and composition of the characteristics of the forecasting object Vasilyeva O. The role of information management systems in activities campaigns // Financial newspaper. Regional release. - 2008. - No. 35. - S. 5-7. . Diagnosis -- the stage of forecasting, which examines a systematic description of the object of forecasting in order to identify trends in its development and the choice of models and methods of forecasting. At the stage of diagnosis, the analysis of the forecasting object, which underlies the forecasting model, is carried out. This analysis ends not only with the development of a forecasting model, but also with the choice of an adequate forecasting method. Prospection is the stage of forecasting, at which, according to the diagnosis, forecasts are developed for the development of the object of forecasting in the future, the reliability, accuracy or validity of the forecast is assessed (verification), as well as the realization of the goal of the forecast by combining specific forecasts based on the principles of forecasting (synthesis). At the stage of prospecting, the missing information about the forecasting object is revealed, the previously received is specified, adjustments are made to the model of the predicted object in accordance with the newly received information Savitskaya G.V. Analysis of the economic activity of the enterprise: Proc. allowance. - M.: INFRA-M, 2007. - S. 89. .
The study of objective relationships of socio-economic phenomena is carried out in the process of developing a mechanism for the use of economic laws, which are a reflection of the essential cause-and-effect relationships of phenomena, expressing their recurrence under certain conditions. At the same time, when forecasting, it is necessary to take into account the uncertainty due to the probabilistic effect of economic laws, the incompleteness of their knowledge, the presence of a subjective factor in making planned decisions, imperfection and insufficient reliability of information.
The assessment of the forecasting object is based on a combination of the aspects of determinism and uncertainty. Determinism is a philosophical concept that recognizes the objective regularity and causality of all phenomena of nature and society. To determine means to determine, to determine. With absolute determinism, the possibility of an alternative choice of solutions disappears. With absolute uncertainty, a concrete representation of the future is impossible. Therefore, in the absence of one of the aspects, forecasting loses its meaning Orlov A.I. Theory of decision making. Textbook. - M.: Exam, 2006. - S. 102-103. .
The implementation of forecasting functions allows you to determine the general and specific approaches that make up its scientific basis. The following general scientific approaches are used in forecasting: historical and complex. The historical approach is to consider each phenomenon and process in the relationship of its historical forms. In the process of forecasting, one should proceed from the fact that state of the art the object under study is a natural result of its previous development, and the future is a natural result of its development in the past and present. An integrated approach involves consideration of the object of study in its connection and dependence with other processes and phenomena. Within its framework, genetic (research, search) and normative (target) approaches are singled out as specific.
With the normative approach, the goal is to determine the ways and timing of achieving the possible state of the object of forecasting in the future. Possible ways of changing the trend due to the intensification of production, changes in its structure, the dynamics of economic indicators, labor productivity, etc. are investigated and predicted. Both of these approaches are interconnected, mutually complement each other and, as a rule, are used in combination, providing a comprehensive study of the predicted phenomenon or process Management: Textbook / Ed. V.V. Tomilova. - M.: Yurayt-Izdat, 2003. - S. 123. .
The role of forecasting in the management of a country, industry, region, enterprise is obvious. We need to take into account STEP factors (social, technological, economic, political), factors of the competitive environment and scientific and technological progress; forecasting the expenses and incomes of enterprises and society as a whole (in accordance with life cycle products - in time and in 11 stages international standard ISO 9004 Korolev D.V. The role of the ISO 9001:2000 standard in improving business performance modern organization// Lawyer. - 2005. - No. 12. - S. 23-24.). Problems of implementation and practical use Mathematical methods of econometric forecasting are associated primarily with the lack of a sufficiently extensive experience of such studies in our country, since for decades planning has been given priority over forecasting Gavrilets Yu.N. Socio-economic planning: Systems and models. - M.: Economics, 1974. - S. 21-22. .
So, forecasting is the preparation of a forecast for the development, formation, distribution of something (for example, science, industry, process, relationships, etc.) based on the study of carefully selected data. In the problem of forecasting, two aspects are distinguished: epistemological, which implies a description of possible or desirable prospects, states, solutions to problems of the future, and managerial, which involves the use of information about the future when making decisions.
1.2 Methods of socio-economic forecasting: concept and system
As is generally accepted since the days of the founder of scientific management, Henri Fayol, forecasting and planning are the basis of a manager's work. Maytal S. Economics for managers: ten important tools for managers. Per. from English. - M.: Delo, 1996. - S. 55. . The essence of econometric forecasting is the description and analysis of future development, in contrast to planning, in which the future movement is set in a directive way. For example, the forecaster's conclusion may be that in an hour we can walk no more than 5 km from point A, and the planner's indication that in an hour we need to be at point B. It is clear that if the distance between A and B no more than 5 km, then the plan is real (feasible), and if more than 10 km, it cannot be implemented under the given conditions. It is necessary either to abandon the unrealistic plan, or to switch to other conditions for its implementation, for example, to move not on foot, but by car. The considered example demonstrates the possibilities and limitations of forecasting methods. Namely, these methods can be successfully applied under the condition of some stability in the development of the situation and fail with abrupt changes.
The method of science is understood as a set of techniques, means, principles and rules by which the student comprehends the subject, acquires new knowledge. The method is an approach to the studied phenomena, objects and processes, a systematic way of scientific knowledge and the establishment of truth. As the English historian and sociologist G. Buckle noted, "in all the higher branches of knowledge, the greatest difficulty is not the discovery of facts, but the discovery of the correct method according to which laws and facts can be established" Cited. by: Krivich M., Olgin O. Masterskie nauki. - M.: Institute of State and Law of the Academy of Sciences of the USSR, 1988. - P. 45. .
The doctrine of the methods themselves, their classification and effective application, the theoretical substantiation of the methods used in science for cognizing the surrounding reality is usually called methodology. The term "methodology" is composed of two Greek words: "method" (the path to something) and "logos" (science, teaching). Thus, literally, "methodology" is the doctrine of the methods of cognition. The term "methodology" denotes a system of all those methods that are applied by a given science.
If the concept of an object is connected with the question of what phenomena are studied by science, then the concept of a method is how exactly they are studied. There is a very strong connection between the subject and the method. The method is predetermined by the characteristics of the subject.
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 object of forecasting, 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 200 forecasting methods Arzhenovsky S.V. Methods of socio-economic forecasting. Tutorial. - M.: Dashkov i K, Science-Spectrum, 2008. - S. 23-24. , however, the number of basic ones is much less (15-20) Materials of the site www.e-staff.ru. . Many of these methods are rather individual techniques and procedures that take into account the nuances of the forecasting 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.
The existing sources present various classification principles of forecasting methods Orlov A.I. Econometrics. Textbook. - M.: Publishing house "Exam", 2002. - S. 88-89; Pisareva O.M. Methods for forecasting the development of socio-economic systems. - M.: Higher School, 2007. - S. 122-123; Applied Forecasting national economy: textbook / ed. V.V. Ivantera, I.A. Budanova, A.G. Korovkina, V.S. Sutyagin. - M.: Publishing house "Economist", 2007. - S. 289-290; Savinov G.V., Svetunkov S.G. Complex variables in economic analysis and modeling // Proceedings of the St. Petersburg State University of Economics and Finance. - 2006. - No. 4. - S. 22-23. . 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 the operation of forecasting methods, the third is the method of obtaining forecast information. On fig. 1 in the appendix to this paper presents a classification scheme of forecasting methods.
As the diagram shown in Fig. 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 forecasting object. In this case, expert estimates are used. At the same time, individual and collective expert assessments are distinguished. Sidelnikov Yu.V. Theory and organization of expert forecasting. - M.: IMEMO AN SSSR, 1990. - S. 12. .
The composition of individual expert assessments includes: the "interview" method, in which the direct contact of the expert with the specialist is carried out according to the "question - answer" scheme; an analytical method, in which a logical analysis of any predictable situation is carried out, analytical memorandums are compiled; a method of writing a script, which is based on determining the logic of a process or phenomenon in time under various conditions.
The methods of collective expert assessments include the method of "commissions", "collective generation of ideas" ("brainstorming"), the "Delphi" method, 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. To the second - structural, network and matrix modeling The theory of function of a complex variable in economic and mathematical modeling. Materials of the All-Russian Scientific Seminar. December 19, 2005 / Ed. prof. S.G. Svetunkova. - St. Petersburg: Publishing house of St. Petersburg State University of Economics, 2006. - S. 199. .
The considered classes of intuitive and formalized methods are similar in composition to expert and factographic methods. Factographic methods are based on actually available information about the object of forecasting and its past development, expert methods are based on information obtained from the assessments of expert experts.
The class of expert forecasting methods includes the method of heuristic forecasting (heuristics is a science that studies productively creative thinking). This is an analytical method, the essence of which is to build and then truncate the "search tree" of expert evaluation using some kind of heuristic. With this method, specialized processing of predictive expert assessments obtained by 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.
Constructive classification (the second classification feature) allows you to visualize the set of forecasting methods in the form of a hierarchical tree and characterize each level with its own classification feature (Fig. 2 in the appendix to this work).
At the first level, all methods on the basis of "information basis of the method" are divided into three classes: factual, combined and expert.
Factual ones are based on factual information about the object of forecasting and its past development. Expert methods use information that is delivered by expert experts in the process of systematized procedures for identifying and summarizing their opinions. In turn, the classes of expert and factographic methods are divided into subclasses according to the methods of information processing. Combined combine the named types of information.
Expert methods are divided into two subclasses. Direct expert assessments are based on the principle of obtaining and processing an independent generalized opinion of a group of experts (or one of them) in the absence of influence on the opinion of each expert of the opinion of another expert and the entire group. Expert assessments with feedback in one form or another implement the principle of feedback based on the impact on the assessment of the expert group (one expert) by the opinions received earlier from this group (or from one of the experts).
The class of factographic methods combines the following three subclasses: analogy methods, forward methods, 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 as an analogue for an object use objects of a different physical nature, other areas of science and technology, having a mathematical description of the development process, coinciding with the object of forecasting.
Leading 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 that use the construction of time series based on various types of such information, analysis and forecasting on this basis of the development of the corresponding object (for example, the envelope method). Advanced methods can also include methods for researching and evaluating 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 the forecasting object, combined according to the principle of identifying the mathematical patterns contained in it for changing the characteristics of this object in order to obtain predictive models Dubrova T.A. Statistical methods of forecasting in economics. - M.: Moscow International Institute of Econometrics, Informatics, Finance and Law, 2003. - P. 9-10. .
The complexity of choosing the most effective method of socio-economic forecasting lies in determining, with respect to the classification of methods for forecasting the characteristics of each method, 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 methods of socio-economic forecasting.
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, 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 task or its fragment; decision and issuance of quantitative or qualitative characteristics(assessment, result of the decision); processing the results of the decision - received from experts - assessments.
One of the varieties of the method of expert assessments is the method of collective generation of ideas (“brainstorming”), which makes it possible to determine possible options for the development of the forecasting object in a short period of time. Methods of "brainstorming" can be classified according to the presence or absence of feedback between the leader and participants in the "brainstorming" in the process of solving some problem situation. The current situation required the development of a method of "brainstorming" - a destructive related assessment (DRO), capable of qualitatively and quickly assessing options, without limiting their number. The essence of this method lies in the actualization of the creative potential of specialists during the "brainstorming" of a problem situation, which first realizes the generation of ideas and the subsequent destruction (destruction, criticism) of these ideas with the formation of counter-ideas. The method of collective generation of ideas has been tested in practice and allows finding a group solution when determining possible options for the development of the forecasting object, excluding the path of compromises, when a consensus 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 the statistical processing of the opinions of expert experts and achieve a more or less agreed 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 serves to determine and evaluate the likelihood of certain events. The Delphi method is based on the following principle: in inexact sciences, expert opinions and subjective judgments must necessarily replace the exact laws of causality reflected by the natural sciences. The Delphi method allows you to generalize the opinions of individual experts into an agreed group opinion. It has all the shortcomings of forecasts built on the basis of 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 the usual methods of group interaction of experts: a) anonymity of experts; b) using the results of the previous round of the survey; C) statistical characteristic of the group response.
Anonymity lies in the fact that during the procedure of expert evaluation of the predicted phenomenon, the object, the participants of the expert group are unknown to each other. At the same time, the interaction of group members when filling out questionnaires is completely eliminated. As a result of this statement, the author of the answer can change his mind without publicly announcing it.
The statistical characterization of the 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 applied. The future event is presented as a huge set of connected and passing into each other paths of development. With the introduction of cross-correlation, the value of each event due to the introduced certain relationships will change either positively or negatively, thereby adjusting the probabilities of the events under consideration. For the purpose of the future correspondence of the model to 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 shifts is very complex, since in real life the magnitude of the correlation is very difficult to measure, the correlations are fuzzy and vary widely depending on the achievement under consideration.
And, finally, the third classification feature is the method of obtaining information. As can be seen from fig. 1 (see Appendix), on this basis, forecasting methods are divided into: interviews, analytical, scenario building, idea generation, etc.
The “interview” method allows for direct contact between an expert and a specialist according to the “question-answer” scheme, during which the forecaster, in accordance with a pre-developed program, puts questions to the expert regarding the prospects for the development of the predicted object.
The analytical method allows you to carry out a logical analysis of any predictable situation and present it in the form of an analytical note. It involves the independent work of an expert on the analysis of trends, assessment of the state and development paths of the predicted object.
The idea generation method has already been discussed in sufficient detail above.
A specific forecasting method is a scenario forecast - this is a kind of method for describing a logically sequential process, an event based on the current situation. Scenarios are described taking into account time estimates. The main purpose of the scenario is to determine the general goal of the development of the predicted object, phenomenon and formulate criteria for evaluating the upper levels of the “goal tree”. Scenarios are usually developed on the basis of preliminary forecast data and source materials on the development of the forecast object. The source materials should include technical and economic characteristics and indicators of the main processes of the production and scientific base for solving the set goal. A scenario is a picture showing a consistent detailed solution of a problem, identification of possible obstacles, detection of serious shortcomings in order to predetermine the issue of a possible termination of the work begun or the completion of ongoing work on the predicted object. The scenario according to which a forecast of the development of an object or processes should be made should contain issues of development not only of science and technology, but also of the economy, foreign and domestic policy. Therefore, scenarios should be developed by highly qualified specialists of the corresponding 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 should be subjected to careful analysis.
In the studied literature Economic strategy firms / Proc. allowance ed. A.P. Gradov. - St. Petersburg: Publishing House of JSC "SPb Orchestra", 2008. - S. 456-457. a significant number of classification schemes according to forecasting methods are presented. Only a few of them have been discussed above. The main error of such schemes is a violation of the principles of classification, which include: sufficient coverage of forecasting methods, unity of the classification feature 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 supplementing with new methods) .
In general, we can conclude that in the process of systematic scientifically based forecasting of the development of socio-economic processes, the development of a forecasting methodology took place, as a set of methods, techniques and ways of thinking, which, based on the analysis of retrospective data, exogenous and endogenous relationships of the forecasting object, and also their measurements within the framework of the phenomenon or process under consideration to derive judgments of a certain reliability regarding its future development.
Chapter 2
2.1 Features of the extrapolation method
The simplest methods for recovering the dependencies used for predicting are based on a given time series, i.e. a function defined at a finite number of points on the time axis. In this case, the time series is often considered within the framework of a probabilistic model, other factors (independent variables) are introduced, in addition to time, for example, volume money supply(unit M2) Sorokina E.M. Organization flow analysis // Economic analysis: theory and practice. - 2004. - No. 17. - P. 6. . The time series can be multidimensional, i.e. the number of responses (dependent variables) may be more than one. The main tasks to be solved are interpolation and extrapolation.
The essence of predictive extrapolation methods is to study the dynamics of changes in the socio-economic phenomenon in the pre-forecast period and transfer the found pattern to a certain period of the future. Extrapolation sequence:
A clear definition of the problem, putting forward hypotheses about the possible development of the predicted object, considering factors that stimulate or hinder the development of this object, determining the necessary extrapolation and its permissible range;
The choice of a system of parameters, the unification of various units of measurement related to each parameter separately;
Collection and systematization of data, verification of their homogeneity and comparability;
Identification of trends or symptoms of changes in the studied quantities in the course of statistical analysis and direct extrapolation of data.
An obligatory condition for applying the 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 reasonableness of the choice of extrapolation limits and the stability of the correspondence of "measuring instruments" in relation to the essence of the phenomenon under consideration. It should be noted that complex objects, as a rule, cannot be characterized by a single parameter.
The extrapolation operation in general view can be thought of as defining the values of a function. The simplest forecasting method is considered to be an approach that forms a forecast estimate from the level actually achieved using the average increase or growth rate. In accordance with it, the forecast is k steps forward at a point in time.
where d is the average absolute increase
This method has certain advantages, including the insignificant complexity of the computational algorithm, universal design schemes.
In addition to these advantages, it has several significant disadvantages.
First, all actual observations are the result of regularity and chance, therefore, it is wrong to rely on the last observation.
Secondly, there is no way to assess the legitimacy of using the average increase in each specific case.
Thirdly, this approach does not allow one to form an interval in which the predicted value falls. In this regard, the extrapolation method does not give accurate results for a long-term forecast, because this method proceeds from 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 correct 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.
When extrapolating, methods are used: least squares and its modifications; exponential smoothing, moving average, etc. The least squares method is most often used with several factors (2-5) Svetunkov S.G. Fundamentals of the theory of econometrics of complex variables. - St. Petersburg: Publishing house of St. Petersburg State University of Economics, 2008. - S. 56-57. . The method of least modules and other extrapolation methods are less commonly used, although their statistical properties are often better.
So, the extrapolation method consists in applying the development trend of the economic process determined for the base period to the forecast period, it is based on the preservation of the prevailing conditions for the development of the process in the future. When using this method, it is necessary to have information about the stability of the development trends of the object for a period that is 2-3 times longer than the forecast period.
2.2 Application of the extrapolation method on the example of predicting the level of crime
Suppose there is a time series of crime rates k for a particular region from 2002 to 2008, shown in the figure. The task is to determine the pattern of change in this series. Novichkov V. Features of complex forecasting in the field of combating crime // Criminal Law. - 2003. - No. 2. - S. 67. .
For the convenience of registration of the calculation, it is proposed to enter all the obtained values in the table. one.
Table 1. Calculation algorithm
Here n is the number of members of the series;
T - calendar year;
t - the value of the real time scale, which is calculated by the formula t \u003d T n - T 0, for our example T 0 \u003d 2002;
X - the value of the conditional time scale, which is calculated by the formula X = t - (n + 1) / 2; k f - the actual expression of the state of the indicator;
k p - calculated state of the indicator (trend);
e i - the difference between the actual state and the calculated, which is calculated by the formula e i = k f - k p; e is the deviation value.
Let us assume that the considered values of the indicator “fluctuate” around a certain straight line, the analytical expression of which has the form:
k p \u003d a + b t (1),
where k p is the calculated state of the indicator k; a, b - unknown trend indicators (constant values for a particular trend); t is the value of the time indicator.
The task is to determine the unknown values a and b in expression (1) from the available values of the index k f for seven years. To simplify the determination of the values a and b, the time report has been moved to the middle of the billing period, that is, we will replace the real time scale t with the conventional time scale X. Then
Substituting taken from the table. 1 value values
into formulas (2) and (3), we obtain the values of the parameters a and b, i.e. parameters of a straight line expressing the trend of the series: a = 6 and b = 0.5. The found expressions a and b will be included in expression (1) and we will obtain the trend equation: k p = 6 + 0.5X. Of course, it is more familiar and convenient to use a real time scale, so let's replace the X argument with the t argument. For our case, X \u003d t - 4. We have k p \u003d 6 + 0.5 (t - 4) \u003d 6 + 0.5t - 2 \u003d 4 + 0.5t. Since for our example t \u003d T n - 2002, we finally get k p \u003d 4 + 0.5 (T n - 2002).
The obtained model of k p change, however, has one drawback: using it as a forecasting tool, we obtain average values around which the actual values of the (real) indicator k will fluctuate. Therefore, it is necessary to know the confidence interval in which, with varying degrees of probability, the values of the predicted indicators k will be located.
The first step in calculating confidence intervals is to determine the value of the standard deviation over time.
The standard deviation is determined by the formula
where e i is the difference between the actual and calculated value of k,
e i \u003d k f - k p.
For our example
The next step to determine the confidence interval is to determine the value of the deviation e, which is determined by the formula
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